{"pageNumber":"12","pageRowStart":"275","pageSize":"25","recordCount":1869,"records":[{"id":70221757,"text":"70221757 - 2021 - Tracking rates of postfire conifer regeneration vs. deciduous vegetation recovery across the western United States","interactions":[],"lastModifiedDate":"2021-07-01T12:24:30.74617","indexId":"70221757","displayToPublicDate":"2020-10-16T07:23:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Tracking rates of postfire conifer regeneration vs. deciduous vegetation recovery across the western United States","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Postfire shifts in vegetation composition will have broad ecological impacts. However, information characterizing postfire recovery patterns and their drivers are lacking over large spatial extents. In this analysis, we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of postfire, dual-season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field-measured patterns of re-vegetation, and (3) identify seasonally specific drivers of postfire rates of NDVI recovery. Rates of postfire NDVI recovery were calculated for both the GS and SCS for more than 12,500 burned points across the western United States. Points were partitioned into faster and slower rates of NDVI recovery using thresholds derived from field plot data (<i>n</i>&nbsp;=&nbsp;230) and their associated rates of NDVI recovery. We found plots with conifer saplings had significantly higher SCS NDVI recovery rates relative to plots without conifer saplings, while plots with ≥50% grass/forbs/shrubs cover had significantly higher GS NDVI recovery rates relative to plots with &lt;50%. GS rates of NDVI recovery were best predicted by burn severity and anomalies in postfire maximum temperature. SCS NDVI recovery rates were best explained by aridity and growing degree days. This study is the most extensive effort, to date, to track postfire forest recovery across the western United States. Isolating patterns and drivers of evergreen recovery from deciduous recovery will enable improved characterization of forest ecological condition across large spatial scales.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2237","usgsCitation":"Vanderhoof, M.K., Hawbaker, T., Ku, A.M., Merriam, K., Berryman, E., and Cattau, M., 2021, Tracking rates of postfire conifer regeneration vs. deciduous vegetation recovery across the western United States: Ecological Applications, v. 31, no. 2, e02237, 20 p., https://doi.org/10.1002/eap.2237.","productDescription":"e02237, 20 p.","ipdsId":"IP-114863","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":454378,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2237","text":"Publisher Index Page"},{"id":436652,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TD78FW","text":"USGS data release","linkHelpText":"Data release for tracking rates of post-fire conifer regeneration distinct from deciduous vegetation recovery across the western U.S."},{"id":386915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -126.21093749999999,\n              30.29701788337205\n            ],\n            [\n              -100.37109375,\n              30.29701788337205\n            ],\n            [\n              -100.37109375,\n              49.55372551347579\n            ],\n            [\n              -126.21093749999999,\n              49.55372551347579\n            ],\n            [\n              -126.21093749999999,\n              30.29701788337205\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":818635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":818636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ku, Andrea Ming 0000-0003-1341-5988","orcid":"https://orcid.org/0000-0003-1341-5988","contributorId":260741,"corporation":false,"usgs":true,"family":"Ku","given":"Andrea","email":"","middleInitial":"Ming","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":818637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merriam, Kyle","contributorId":260742,"corporation":false,"usgs":false,"family":"Merriam","given":"Kyle","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":818638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berryman, Erin","contributorId":260744,"corporation":false,"usgs":false,"family":"Berryman","given":"Erin","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":818639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cattau, Megan","contributorId":260748,"corporation":false,"usgs":false,"family":"Cattau","given":"Megan","affiliations":[{"id":52668,"text":"Boise State","active":true,"usgs":false}],"preferred":false,"id":818640,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70218235,"text":"70218235 - 2021 - Landsat 9 mission update and status","interactions":[],"lastModifiedDate":"2021-04-19T14:30:19.391207","indexId":"70218235","displayToPublicDate":"2020-08-28T09:22:29","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat 9 mission update and status","docAbstract":"<p><span>Landsat 9 is currently undergoing testing at the integrated observatory level in preparation for launch from Vandenberg Air Force Base in 2021. Landsat 9 will replace Landsat 7 in orbit, 8 days out of phase with Landsat 8. Landsat 9 is largely a copy of Landsat 8 in terms of instrumentation, with an Operational Land Imager (OLI), model #2 and a Thermal Infrared Sensor (TIRS), model #2. The TIRS-2 is more significantly changed from TIRS with increased redundancy, as well as changes to the telescope baffling to improve stray light control and a revised scene select mirror encoder mechanism. Data quality of the Landsat 9 instruments is comparable to, or better than the Landsat 8 ones, with an increase to 14 bits of data transmitted and more detailed pre-launch characterization for OLI-2, and with more detailed characterization of the TIRS-2 pre-launch, in addition to the improved stray light control. The performance of the two instruments is summarized and compared to that of the Landsat 8 instruments.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings volume 11501, Earth observing systems XXV","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","doi":"10.1117/12.2569748","usgsCitation":"Markham, B., Jenstrom, D., Pszcolka, S., Dulski, V., Hair, J., Joel McCorkel, Kvaran, G., Thome, K., Montanaro, M., Pedelty, J., Anderson, C., Choate, M., Barsi, J., Kaita, E., and Miller, J., 2021, Landsat 9 mission update and status, <i>in</i> Proceedings volume 11501, Earth observing systems XXV, 115010O, 7 p., https://doi.org/10.1117/12.2569748.","productDescription":"115010O, 7 p.","ipdsId":"IP-121748","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":385191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Markham, Brian","contributorId":251770,"corporation":false,"usgs":false,"family":"Markham","given":"Brian","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenstrom, Del","contributorId":251771,"corporation":false,"usgs":false,"family":"Jenstrom","given":"Del","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pszcolka, Steven","contributorId":251772,"corporation":false,"usgs":false,"family":"Pszcolka","given":"Steven","email":"","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dulski, Vicki","contributorId":251773,"corporation":false,"usgs":false,"family":"Dulski","given":"Vicki","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hair, Jason","contributorId":251774,"corporation":false,"usgs":false,"family":"Hair","given":"Jason","email":"","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Joel McCorkel","contributorId":251775,"corporation":false,"usgs":false,"family":"Joel McCorkel","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810564,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kvaran, Geir","contributorId":251776,"corporation":false,"usgs":false,"family":"Kvaran","given":"Geir","email":"","affiliations":[{"id":50396,"text":"Ball Aerospace","active":true,"usgs":false}],"preferred":false,"id":810565,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thome, Kurtis","contributorId":251777,"corporation":false,"usgs":false,"family":"Thome","given":"Kurtis","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810566,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Montanaro, Matthew","contributorId":251778,"corporation":false,"usgs":false,"family":"Montanaro","given":"Matthew","affiliations":[{"id":32390,"text":"Rochester Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":810567,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pedelty, Jeffery","contributorId":251779,"corporation":false,"usgs":false,"family":"Pedelty","given":"Jeffery","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":810568,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":810569,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":251780,"corporation":false,"usgs":true,"family":"Choate","given":"Michael J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":810570,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Barsi, Julia","contributorId":251781,"corporation":false,"usgs":false,"family":"Barsi","given":"Julia","email":"","affiliations":[{"id":50397,"text":"SSAI","active":true,"usgs":false}],"preferred":false,"id":810571,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kaita, Ed","contributorId":251782,"corporation":false,"usgs":false,"family":"Kaita","given":"Ed","email":"","affiliations":[{"id":50397,"text":"SSAI","active":true,"usgs":false}],"preferred":false,"id":810572,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Miller, Jeffery","contributorId":251783,"corporation":false,"usgs":false,"family":"Miller","given":"Jeffery","email":"","affiliations":[{"id":50397,"text":"SSAI","active":true,"usgs":false}],"preferred":false,"id":810573,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70218225,"text":"70218225 - 2021 - Estimating inundation of small waterbodies with sub-pixel analysis of Landsat imagery: Long-term trends in surface water area and evaluation of common drought indices","interactions":[],"lastModifiedDate":"2021-03-19T20:54:21.790299","indexId":"70218225","displayToPublicDate":"2020-07-10T12:29:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Estimating inundation of small waterbodies with sub-pixel analysis of Landsat imagery: Long-term trends in surface water area and evaluation of common drought indices","docAbstract":"<p><span>Small waterbodies are numerically dominant in many landscapes and provide several important ecosystem services, but automated measurement of waterbodies smaller than a standard Landsat pixel (0.09&nbsp;ha) remains challenging. To further evaluate sub‐Landsat pixel techniques for estimating inundation extent of small waterbodies (basin area: 0.06–1.79&nbsp;ha), we used a partial spectral unmixing method with matched filtering applied to September 1985–2018 Landsat 5 and eight imagery from southern Arizona, USA. We estimated trends in modeled surface water area each September and evaluated the ability of several common drought indices to explain variation in mean water area. Our methods accurately classified waterbodies as dry or inundated (Landsat 5: 91.3%; Landsat 8: 98.9%) and modeled and digitized surface water areas were strongly correlated (</span><i>R</i><sup>2</sup><span>&nbsp;=&nbsp;0.70–0.92; bias&nbsp;=&nbsp;−0.024 to −0.015&nbsp;ha). Estimated surface water area was best explained by the 3‐month seasonal standardized precipitation index (SPI03; July‒September). We found a wide range of estimated relationships between drought indices (e.g. SPI vs. Palmer Drought Severity Index) and estimated water area, even for different durations of the same drought index (e.g. SPI01 vs. SPI12). Mean waterbody surface area decreased by ~14% from September 1985 to September 2018, which matches declines in local annual precipitation and regional trends of reduced inundation extent of larger waterbodies. These results emphasize the importance of understanding local systems when relying on drought indices to infer variation in past or future surface water dynamics. Several challenges remain before widespread application of sub‐pixel methods is feasible, but our results provide further evidence that partial spectral unmixing with matched filtering provides reliable measures of inundation extent of small waterbodies.</span></p>","language":"English","publisher":"Zoological Society of London (Wiley)","doi":"10.1002/rse2.172","usgsCitation":"Sall, I., Jarchow, C., Sigafus, B.H., Eby, L., Forzley, M.J., and Hossack, B., 2021, Estimating inundation of small waterbodies with sub-pixel analysis of Landsat imagery: Long-term trends in surface water area and evaluation of common drought indices: Remote Sensing in Ecology and Conservation, v. 7, no. 1, p. 109-124, https://doi.org/10.1002/rse2.172.","productDescription":"16 p.","startPage":"109","endPage":"124","ipdsId":"IP-114730","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454519,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.172","text":"Publisher Index Page"},{"id":383382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona","otherGeospatial":"San Rafael Valley and neighboring areas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.89599609375,\n              31.283245492650792\n            ],\n            [\n              -110.2313232421875,\n              31.283245492650792\n            ],\n            [\n              -110.2313232421875,\n              31.991771310172094\n            ],\n            [\n              -110.89599609375,\n              31.991771310172094\n            ],\n            [\n              -110.89599609375,\n              31.283245492650792\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Sall, Ibrahima 0000-0002-7526-636X","orcid":"https://orcid.org/0000-0002-7526-636X","contributorId":251750,"corporation":false,"usgs":false,"family":"Sall","given":"Ibrahima","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":810490,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":810491,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sigafus, Brent H. 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":4534,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":810492,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eby, Lisa A","contributorId":251751,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":810493,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forzley, Michael James 0000-0001-5307-8459","orcid":"https://orcid.org/0000-0001-5307-8459","contributorId":251752,"corporation":false,"usgs":true,"family":"Forzley","given":"Michael","email":"","middleInitial":"James","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":810494,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":810495,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70210111,"text":"70210111 - 2021 - Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida","interactions":[],"lastModifiedDate":"2021-02-17T22:21:56.760044","indexId":"70210111","displayToPublicDate":"2020-04-06T11:01:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida","docAbstract":"<p><span>Studies integrating mangrove&nbsp;</span><i>in-situ</i><span>&nbsp;observations and remote sensing analysis for specific sites often lack precise estimates of carbon stocks over time frames that include disturbance events. This study quantifies change in mangrove area from 1985 to 2018 with Landsat time series analysis, estimates above and belowground stored carbon using field data, and evaluates aboveground carbon stock changes after the 2004 Category 4, Hurricane Charley, in J.N. “Ding” Darling National Wildlife Refuge. Two allometric equation methods yielding similar results were used to estimate aboveground carbon content in three mangrove species found in the refuge. Aboveground carbon contained 67 (SE&nbsp;=&nbsp;2) MgC ha</span><sup>−1</sup><span>&nbsp;with a total refuge estimate of 74,504 MgC in 2018. Sediment contained 259 (SE&nbsp;=&nbsp;28) MgC ha</span><sup>−1</sup><span>&nbsp;for a total of 288,008 MgC in the refuge. The initial reduction in mangrove area caused by Hurricane Charley was between 0.6% and 5.3%, equivalent to between 427 MgC and 3,599 MgC under three different scenarios of carbon loss. As a result of the hurricane, approximately 61&nbsp;ha of mangroves were disturbed, of which 24&nbsp;ha had recovered by 2018, with 37&nbsp;ha (~3% of the pre-hurricane mangrove area) still not recovered 14 years after the event. The 37&nbsp;ha of mangroves that have not recovered are located in a tidally restricted area of the refuge. A longer recovery time in this area will likely result in a greater loss of carbon storage than in the rest of the refuge.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2020.106750","usgsCitation":"Peneva-Reed, E.I., Krauss, K., Bullock, E.L., Zhu, Z., Woltz, V., Drexler, J.Z., Conrad, J.R., and Stehman, S.V., 2021, Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida: Estuarine, Coastal and Shelf Science, v. 248, 106750, 13 p., https://doi.org/10.1016/j.ecss.2020.106750.","productDescription":"106750, 13 p.","ipdsId":"IP-111057","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":374829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"J.N. “Ding” Darling National Wildlife Refuge, Sanibel Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.16949462890624,\n              26.434609799691536\n            ],\n            [\n              -82.0513916015625,\n              26.434609799691536\n            ],\n            [\n              -82.0513916015625,\n              26.49577131935652\n            ],\n            [\n              -82.16949462890624,\n              26.49577131935652\n            ],\n            [\n              -82.16949462890624,\n              26.434609799691536\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"248","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peneva-Reed, Elitsa I. 0000-0002-4570-4701","orcid":"https://orcid.org/0000-0002-4570-4701","contributorId":202809,"corporation":false,"usgs":true,"family":"Peneva-Reed","given":"Elitsa","email":"","middleInitial":"I.","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":789169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bullock, Eric L. 0000-0003-3279-6771","orcid":"https://orcid.org/0000-0003-3279-6771","contributorId":224710,"corporation":false,"usgs":false,"family":"Bullock","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":40922,"text":"Department of Earth & Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":789171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"preferred":true,"id":789172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woltz, Victoria 0000-0001-7843-6486","orcid":"https://orcid.org/0000-0001-7843-6486","contributorId":223011,"corporation":false,"usgs":true,"family":"Woltz","given":"Victoria","email":"","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":789174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, Jeremy R.","contributorId":149347,"corporation":false,"usgs":false,"family":"Conrad","given":"Jeremy","email":"","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":789175,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stehman, Stephen V. 0000-0001-5234-2027","orcid":"https://orcid.org/0000-0001-5234-2027","contributorId":216812,"corporation":false,"usgs":false,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[{"id":39524,"text":"College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":789176,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70229515,"text":"70229515 - 2020 - Landsat surface reflectance validation site selection","interactions":[],"lastModifiedDate":"2022-03-11T15:35:55.452537","indexId":"70229515","displayToPublicDate":"2021-02-17T09:31:32","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat surface reflectance validation site selection","docAbstract":"<p><span>An investigation was conducted to determine optimal locations within the continental United States for insitu measurements to validate the U.S. Landsat Analysis Ready Data (ARD) Surface Reflectance product. Site assessment involved analysis of aerosol optical depth, precipitable water vapor, land cover, cloud cover, and elevation models. Nineteen sites were selected for further month-by-month ranking to identify those sites most likely to capture simple or complex atmosphere.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"IGARSS 2020 - 2020 IEEE international geoscience and remote sensing symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"IEEE","doi":"10.1109/IGARSS39084.2020.9323374","usgsCitation":"Maddox, E.M., and Zavesky, L.D., 2020, Landsat surface reflectance validation site selection, <i>in</i> IGARSS 2020 - 2020 IEEE international geoscience and remote sensing symposium, p. 6133-6136, https://doi.org/10.1109/IGARSS39084.2020.9323374.","productDescription":"4 p.","startPage":"6133","endPage":"6136","ipdsId":"IP-115451","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":397023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maddox, Emily M. 0000-0001-5649-1193","orcid":"https://orcid.org/0000-0001-5649-1193","contributorId":288315,"corporation":false,"usgs":true,"family":"Maddox","given":"Emily","email":"","middleInitial":"M.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":837721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zavesky, Landon Douglas 0000-0003-1109-8149","orcid":"https://orcid.org/0000-0003-1109-8149","contributorId":288316,"corporation":false,"usgs":true,"family":"Zavesky","given":"Landon","email":"","middleInitial":"Douglas","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":837722,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216822,"text":"ofr20201131 - 2020 - Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana","interactions":[],"lastModifiedDate":"2021-01-28T01:20:54.786589","indexId":"ofr20201131","displayToPublicDate":"2021-01-27T15:30:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1131","displayTitle":"Mapping <i>Phragmites australis</i> Live Fractional Cover in the Lower Mississippi River Delta, Louisiana","title":"Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana","docAbstract":"<p>In response to a co-occurring non-native scale infestation and <i>Phragmites australis</i> dieback in southeast Louisiana, normalized difference vegetation index (NDVI) satellite mapping was implemented to track <i>P. australis</i> condition in the lower Mississippi River Delta. While the NDVI mapping successfully documented relative condition changes, identification of cause required a quantitative-biophysical metric directly related to <i>P. australis</i> marsh live vegetation proportion. During this study, a satellite mapping tool that quantified <i>P. australis</i> live fraction cover (LFC) magnitude was designed and implemented. The key to development of the quantitative LFC mapping was the field to satellite calibration design. The calibration of <i>P. australis</i> marsh LFC to optical satellite image data combined field and near-in-time satellite data collections in the fall of 2018 and summer of 2019. Basing the field-NDVI to field-LFC calibrations and the satellite-NDVI to field-NDVI calibrations on combined pre-senescence and peak-growth period data offers nearly year-round LFC mapping. The utility of the developed <i>P. australis</i> marsh LFC mapping tool was demonstrated by the creation of a yearly suite of Mississippi River Delta LFC status and change maps extending from 2009 to 2019. <i>P. australis</i> marsh LFC mapping relies on Sentinel-2 for current to future mapping and relies on Landsat for historical mapping.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201131","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Rangoonwala, A., Howard, R.J., and Ramsey, E.W., III, 2020, Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana (ver. 1.1, January 2021): U.S. Geological Survey Open-File Report 2020–1131, 24 p., https://doi.org/10.3133/ofr20201131.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-119555","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":381145,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ASPB4E","text":"USGS data release","description":"USGS Data Release","linkHelpText":"<i>Phragmites australis</i> live fractional cover yearly map from 2009 to 2019 of the lower Mississippi River Delta using Landsat and Sentinel-2 satellite data"},{"id":381143,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1131/coverthb2.jpg"},{"id":381144,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1131/ofr20201131.pdf","text":"Report","size":"6.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1131"},{"id":382663,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1131/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020–1131 version history"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.54544067382812,\n              28.930045059458923\n            ],\n            [\n              -89.000244140625,\n              28.930045059458923\n            ],\n            [\n              -89.000244140625,\n              29.40371231103247\n            ],\n            [\n              -89.54544067382812,\n              29.40371231103247\n            ],\n            [\n              -89.54544067382812,\n              28.930045059458923\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: December 14, 2020; Version 1.1: January 27, 2021","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc\" href=\"https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc\">Wetland and Aquatic Research Center</a><br>U.S. Geological Survey<br>700 Cajundome Blvd.<br>Lafayette, Louisiana 70506  </p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Area</li><li>Methods</li><li>Results</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-12-14","revisedDate":"2021-01-27","noUsgsAuthors":false,"publicationDate":"2020-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rangoonwala, Amina 0000-0002-0556-0598","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":212060,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Rebecca J. 0000-0001-7264-4364 howardr@usgs.gov","orcid":"https://orcid.org/0000-0001-7264-4364","contributorId":2429,"corporation":false,"usgs":true,"family":"Howard","given":"Rebecca","email":"howardr@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey III, Elijah W. 0000-0002-4518-5796","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":214746,"corporation":false,"usgs":true,"family":"Ramsey III","given":"Elijah W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806430,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217862,"text":"70217862 - 2020 - New operational national satellite burned area product","interactions":[],"lastModifiedDate":"2021-06-14T19:38:42.992542","indexId":"70217862","displayToPublicDate":"2020-12-31T07:50:52","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"New operational national satellite burned area product","docAbstract":"Introduction\nLack of consistent spatial and temporal fire information with relevant spatial resolution hinders land management and broad-scale assessments of fire activity, especially in the eastern United States and the Great Plains where fi re is important ecologically and culturally. Remote sensing can be used to monitor fi re activity, augment existing fi re data, and fill information gaps. In particular, Landsat offers one of the most complete time series of remote sensing data sets as the Landsat satellites with spectral bands useful for mapping fi res and burn severity have been operational since 1984. Furthermore, Landsat satellite imagery collect data at a resolution useful for on-the-ground comparisons and management decisions.\n\nMethods\nA gradient-boosting regression model algorithm was used to predict burn probabilities (BP), indicating the likelihood that a pixel had burned in a fire. Then the algorithm translated the burn probability images to burn classification (BC) images using thresholding and region growing. Burned areas smaller than 5 acres were removed to reduce noise. The BP and BC products were generated for Landsat scenes collected from 1984 to present with <= 80% cloud cover and are available for download from USGSs EarthExplorer website (www.earthexplorer. usgs.gov).\n\nAnnual summaries were also produced from the scene-level BC and BP products. These include: 1) the maximum burn probability value from all scenes in a year, (2) the burn classification count, or the number of times a pixel was classified as burned in a year, (3) the burn date, or the day of year of the first Landsat scene a pixel was classified as burned, and (4) a burn classification which removes burned areas still visible from previous years with a filter.\n\nResults\nThe Landsat Burned Area Products identified 183% more burned area than the Monitoring Trends in Burn Severity and 56% more burned area than the MODIS MCD64A1.006 products2. From 1984 through 2018, annual burned area mapped by the Landsat Burned Area Products averaged 30,000 km2, ranged between 14,000 km2 in 1991 and 46,500 km2 in 2012, and increased over time at a rate of 356 km2/year. \n\nThe Landsat Burned Area products consistently map burned areas 5 acres or larger over time while capturing unburned islands within fi res. Such characteristics are critical for understanding long-term impacts of fi res on human and natural systems. The products are being routinely produced as new Landsat data are collected and demonstrate the utility remote sensing offers for monitoring landscape change.","language":"English","publisher":"Great Plains Fire Science Exchange","usgsCitation":"Hawbaker, T., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.G., Picotte, J.J., Takacs, J., Falgout, J.T., and Dwyer, J., 2020, New operational national satellite burned area product, 2 p.","productDescription":"2 p.","ipdsId":"IP-122391","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":383093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383081,"type":{"id":15,"text":"Index 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1.0: December 21, 2020; Version 1.1: December 12, 2022","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a>&nbsp;<br>U.S. Geological Survey&nbsp;<br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Land Change and Permafrost Accounting</li><li>Coastlines and Fisheries</li><li>Wildfire and Disaster Response</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-12-21","revisedDate":"2022-12-12","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":147999,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":807117,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70216967,"text":"fs20203066 - 2020 - Maine and Landsat","interactions":[],"lastModifiedDate":"2026-02-04T20:22:00.663948","indexId":"fs20203066","displayToPublicDate":"2020-12-21T17:11:26","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3066","displayTitle":"Maine and Landsat","title":"Maine and Landsat","docAbstract":"<p>Maine is a place of rocky coastlines, of rich maritime history symbolized by lighthouses dotting the ocean bluffs, and of wondrous nature areas like the granite and spruce islands of Acadia National Park. But Maine is a place of changes, too. Climate variability has brought the state heavier and more frequent rainstorms. Summers are hotter and drier. With sea levels rising, severe storms increasingly cause floods that damage property and infrastructure. 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 \"}}]}","edition":"Version 1.0: December 21, 2020; Version 1.1: July 1, 2022; Version 1.2: May 16, 2023","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a>&nbsp;<br>U.S. Geological Survey&nbsp;<br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Forest Health and Changes</li><li>Fishing and Farms</li><li>Coastlines and Wetlands</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-12-21","revisedDate":"2023-05-16","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":210377,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":807116,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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 \"}}]}","edition":"Version 1.0: December 21, 2020; Version 1.1: October 17, 2022; Version 1.2: November 26, 2024","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a>&nbsp;<br>U.S. Geological Survey&nbsp;<br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Smart Urban Development</li><li>Water-Quality Monitoring</li><li>Precision Agriculture</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-12-21","revisedDate":"2024-11-26","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128215,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":807087,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70224299,"text":"70224299 - 2020 - Analyzing vegetation change in a sagebrush ecosystem using long-term field observations and Landsat imagery in Wyoming","interactions":[],"lastModifiedDate":"2021-09-21T13:32:48.181241","indexId":"70224299","displayToPublicDate":"2020-12-09T08:29:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Analyzing vegetation change in a sagebrush ecosystem using long-term field observations and Landsat imagery in Wyoming","docAbstract":"<p><span>The importance of monitoring shrublands to detect and understand changes through time is increasingly recognized as critical to management. This research focuses on ecological change observed over 10&nbsp;yr of field observation at 126 plots and over 35&nbsp;yr of the Landsat archive in a shrubland ecosystem. Field data consisting of the fractional cover of shrubs, sagebrush, herbs, litter, and bare ground components were collected to be directly comparable to Landsat time-series predictions at an ecoregion level. We used these data to test three hypotheses. First, that precipitation and temperature govern changes in the proportions of shrubland components on an interannual time scale. Second, that longer-term component change is related to climate change. Finally, that change intensity varies by shrubland communities clustered by biophysical conditions. We found that the field observations and Landsat times-series predictions generally responded similarly to interannual variation in weather, chiefly driven by precipitation. Landsat times-series data provided a reasonable means of scaling up the findings of the field observations to a larger temporal and spatial window. The results of the analysis indicate that shrubland component change intensity significantly varies by biophysical clusters, and indicate a significant increase in the cover of shrubs and sagebrush in long-term monitoring plots between 2008 and 2017 and in the Landsat time-series data across the Wyoming Basin study area from 1985 to 2017 and from 2008 to 2017. Our results indicate that the Landsat time series can be used to answer critical questions regarding the influence of climate change and the suitability of management practices in shrubland ecosystems.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3311","usgsCitation":"Shi, H., Homer, C., Rigge, M.B., Postma, K., and Xian, G.Z., 2020, Analyzing vegetation change in a sagebrush ecosystem using long-term field observations and Landsat imagery in Wyoming: Ecosphere, v. 11, no. 12, e03311, 20 p., https://doi.org/10.1002/ecs2.3311.","productDescription":"e03311, 20 p.","ipdsId":"IP-113232","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":454690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3311","text":"Publisher Index Page"},{"id":389545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.972900390625,\n              40.95501133048621\n            ],\n            [\n              -108.48999023437499,\n              40.95501133048621\n            ],\n            [\n              -108.48999023437499,\n              42.601619944327965\n            ],\n            [\n              -110.972900390625,\n              42.601619944327965\n            ],\n            [\n              -110.972900390625,\n              40.95501133048621\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":823501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin 0000-0003-4755-8135","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":238918,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":823502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":823503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Postma, Kory 0000-0001-8058-498X","orcid":"https://orcid.org/0000-0001-8058-498X","contributorId":265826,"corporation":false,"usgs":true,"family":"Postma","given":"Kory","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":823504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xian, George Z. 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":238919,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":823505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221756,"text":"70221756 - 2020 - Development of a standard database of reference sites for validating global burned area products","interactions":[],"lastModifiedDate":"2021-07-01T12:30:08.258764","indexId":"70221756","displayToPublicDate":"2020-12-08T07:28:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8948,"text":"Earth System Science Data journal","active":true,"publicationSubtype":{"id":10}},"title":"Development of a standard database of reference sites for validating global burned area products","docAbstract":"<p>Over the past 2&nbsp;decades, several global burned area products have been produced and released to the public. However, the accuracy assessment of such products largely depends on the availability of reliable reference data that currently do not exist on a global scale or whose production require a high level of dedication of project resources. The important lack of reference data for the validation of burned area products is addressed in this paper. We provide the Burned Area Reference Database (BARD), the first publicly available database created by compiling existing reference BA (burned area) datasets from different international projects. BARD contains a total of 2661 reference files derived from Landsat and Sentinel-2 imagery. All those files have been checked for internal quality and are freely provided by the authors. To ensure database consistency, all files were transformed to a common format and were properly documented by following metadata standards. The goal of generating this database was to give BA algorithm developers and product testers reference information that would help them to develop or validate new BA products. BARD is freely available at https://doi.org/10.21950/BBQQU7 (Franquesa et al., 2020).</p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-12-3229-2020","usgsCitation":"Franquesa, M., Vanderhoof, M.K., Stavrakoudis, D., Gitas, I., Roteta, E., Padilla, M., and Chuvieco, E., 2020, Development of a standard database of reference sites for validating global burned area products: Earth System Science Data journal, v. 12, no. 4, p. 3229-3246, https://doi.org/10.5194/essd-12-3229-2020.","productDescription":"18 p.","startPage":"3229","endPage":"3246","ipdsId":"IP-116811","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":454694,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-12-3229-2020","text":"Publisher Index Page"},{"id":386917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Franquesa, Magi","contributorId":260737,"corporation":false,"usgs":false,"family":"Franquesa","given":"Magi","email":"","affiliations":[{"id":52663,"text":"Universidad de Alcalá","active":true,"usgs":false}],"preferred":false,"id":818628,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":818629,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stavrakoudis, Dimitris","contributorId":260738,"corporation":false,"usgs":false,"family":"Stavrakoudis","given":"Dimitris","email":"","affiliations":[{"id":52665,"text":"Aristotle University of Thessaloniki","active":true,"usgs":false}],"preferred":false,"id":818630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gitas, Ioannis","contributorId":260739,"corporation":false,"usgs":false,"family":"Gitas","given":"Ioannis","email":"","affiliations":[{"id":52665,"text":"Aristotle University of Thessaloniki","active":true,"usgs":false}],"preferred":false,"id":818631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roteta, Ekhi","contributorId":260740,"corporation":false,"usgs":false,"family":"Roteta","given":"Ekhi","email":"","affiliations":[{"id":52667,"text":"University of the Basque Country","active":true,"usgs":false}],"preferred":false,"id":818632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Padilla, Marc","contributorId":213986,"corporation":false,"usgs":false,"family":"Padilla","given":"Marc","email":"","affiliations":[{"id":38955,"text":"Centre for Landscape & Climate Research, Leicester Institute for Space and Earth Observation, School of Geography, University of Leicester, Leicester LE1 7RH, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":818633,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chuvieco, Emilio","contributorId":213978,"corporation":false,"usgs":false,"family":"Chuvieco","given":"Emilio","email":"","affiliations":[{"id":38949,"text":"Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Universidad de Alcalá. Calle Colegios 2, Alcalá de Henares, 28801, Spain","active":true,"usgs":false}],"preferred":false,"id":818634,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70216777,"text":"70216777 - 2020 - The new Landsat Collection-2 Digital Elevation Model","interactions":[],"lastModifiedDate":"2020-12-07T16:01:13.585843","indexId":"70216777","displayToPublicDate":"2020-11-28T09:57:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The new Landsat Collection-2 Digital Elevation Model","docAbstract":"<p><span>The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset (NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from the Collection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 m was measured. By using theses improved vertical values in a line of sight algorithm, horizontal improvements were noted in some of the most mountainous regions over multiple 30-m Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs12233909","usgsCitation":"Franks, S., Storey, J., and Rengarajan, R., 2020, The new Landsat Collection-2 Digital Elevation Model: Remote Sensing, v. 12, no. 23, 3909, 24 p., https://doi.org/10.3390/rs12233909.","productDescription":"3909, 24 p.","ipdsId":"IP-123106","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":454735,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12233909","text":"Publisher Index Page"},{"id":381037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"23","noUsgsAuthors":false,"publicationDate":"2020-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Franks, Shannon 0000-0003-1335-5401","orcid":"https://orcid.org/0000-0003-1335-5401","contributorId":245457,"corporation":false,"usgs":false,"family":"Franks","given":"Shannon","email":"","affiliations":[{"id":49197,"text":"KBR, Contractor to NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":806216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storey, James C. 0000-0002-6664-7232","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":242015,"corporation":false,"usgs":false,"family":"Storey","given":"James C.","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":806217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":806218,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70248052,"text":"70248052 - 2020 - Using remote sensing products to predict recovery of vegetation across space and time following energy development","interactions":[],"lastModifiedDate":"2024-05-16T15:37:39.154563","indexId":"70248052","displayToPublicDate":"2020-11-12T09:16:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Using remote sensing products to predict recovery of vegetation across space and time following energy development","docAbstract":"<p><span>Using localized studies to understand how ecosystems recover can create uncertainty in recovery predictions across landscapes. Large archives of remote sensing data offer opportunities for quantifying the spatial and temporal factors influencing recovery at broad scales and predicting recovery. For example, energy production is a widespread and expanding land use among many semi-arid ecosystems of the Western United States dominated by sagebrush (</span><i>Artemisia</i><span>&nbsp;spp.), a keystone species providing a variety of ecological services. With remotely-sensed (Landsat) estimates of vegetation cover collected every 2–5 years from southwestern Wyoming, USA, over nearly three decades (1985–2015), we modeled changes in sagebrush cover on 375 former oil and gas well pads in response to weather and site-level conditions. We then used modeled relationships to predict recovery time across the landscape as an indicator of resilience for vegetation after well pad disturbances, where faster recovery indicates a greater capacity to recover when similarly disturbed. We found the rate of change in sagebrush cover generally increased with moisture and temperature, particularly at higher elevations. Rate of change in sagebrush cover also increased and decreased with greater percent sand and larger well pads, respectively. We predicted 21% of the landscape would recover to pre-disturbance conditions within 60 years, whereas other areas may require &gt;100 years for recovery. These predictions and maps could inform future restoration efforts as they reflect resilience. This approach also is applicable to other disturbance types (e.g., fires and vegetation removal treatments) across landscapes, which can further improve conservation efforts by characterizing past conditions and monitoring trends in subsequent years.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.105872","usgsCitation":"Monroe, A., Aldridge, C.L., O’Donnell, M.S., Manier, D., Homer, C., and Anderson, P.J., 2020, Using remote sensing products to predict recovery of vegetation across space and time following energy development: Ecological Indicators, v. 110, 105872, 15 p.; 2 Data Releases, https://doi.org/10.1016/j.ecolind.2019.105872.","productDescription":"105872, 15 p.; 2 Data Releases","ipdsId":"IP-101503","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454840,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2019.105872","text":"Publisher Index Page"},{"id":436724,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XV8GH7","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA (ver. 2.0, January 2021)"},{"id":436723,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XV8GH7","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA (ver. 2.0, January 2021)"},{"id":436722,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQ5INM","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA"},{"id":436721,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQ5INM","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA"},{"id":420410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.03921100550399,\n              42.92284600849075\n            ],\n            [\n              -111.03921100550399,\n              41.03307775348375\n            ],\n            [\n              -106.02701021455793,\n              41.03307775348375\n            ],\n            [\n              -106.02701021455793,\n              42.92284600849075\n            ],\n            [\n              -111.03921100550399,\n              42.92284600849075\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"110","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":881652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manier, Daniel 0000-0002-1105-1327","orcid":"https://orcid.org/0000-0002-1105-1327","contributorId":244206,"corporation":false,"usgs":true,"family":"Manier","given":"Daniel","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Homer, Collin 0000-0003-4755-8135","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":238918,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":881655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881656,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70228467,"text":"70228467 - 2020 - Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment","interactions":[],"lastModifiedDate":"2022-02-14T12:04:27.764111","indexId":"70228467","displayToPublicDate":"2020-10-28T11:13:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment","docAbstract":"<p><span>Biologists and policy-makers have the difficult task of allocating limited resources to habitat conservation and management for endangered species in the face of changing environmental conditions. Satellite remote sensing can inform conservation because it is an efficient means to obtain environmental data over broad spatial and temporal extents. Yet, the challenges of accessing, processing, and analyzing remote sensing data hinder wider application of these techniques in conservation planning. We used Landsat data and hierarchical statistical models to link satellite-derived habitat measurements with abundance of endangered Yuma Ridgway's rails (</span><i>Rallus obsoletus yumanensis</i><span>) within the Lower Colorado River Basin and Salton Sink, USA. We addressed many of the challenges facing the application of remote sensing techniques by using the web-based, freely-available Google Earth Engine to process Landsat datasets, apply habitat models, and generate maps to predict habitat suitability at a fine spatial grain (30&nbsp;m) across the range of the species. These maps are shareable, interactive, and easy to update annually as habitat conditions change using a Google Earth Engine App we developed. Thus, we provide a framework for building habitat suitability models and maps to help target adaptive habitat management over broad extents for sensitive species, enabling biologists to improve conservation and restoration efforts regularly as conditions change in highly variable ecosystems. We demonstrate this approach for Yuma Ridgway's rails, but our methods for merging hierarchical statistical models with open-source mapping software to describe spatial-temporal heterogeneity in habitat quality are applicable to any species, and are especially helpful to species inhabiting highly variable ecosystems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108734","usgsCitation":"Harrity, E.J., Stevens, B., and Conway, C.J., 2020, Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment: Biological Conservation, v. 250, 108734,10 p., https://doi.org/10.1016/j.biocon.2020.108734.","productDescription":"108734,10 p.","ipdsId":"IP-116214","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Nevada","otherGeospatial":"Colorado River Basin, Salton Sink","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.840087890625,\n              32.52828936482526\n            ],\n            [\n              -114.796142578125,\n              32.44024912337551\n            ],\n            [\n              -114.08752441406249,\n              32.697177359290635\n            ],\n            [\n              -114.246826171875,\n              33.55055114384406\n            ],\n            [\n              -114.29077148437499,\n              33.8247936182649\n            ],\n            [\n              -113.873291015625,\n              34.31621838080741\n            ],\n            [\n              -114.356689453125,\n              34.88593094075317\n            ],\n            [\n              -114.63134765625001,\n              34.858890491257796\n            ],\n            [\n              -115.916748046875,\n              33.128351191631566\n            ],\n            [\n              -114.840087890625,\n              32.52828936482526\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"250","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harrity, Eamon J.","contributorId":275852,"corporation":false,"usgs":false,"family":"Harrity","given":"Eamon","email":"","middleInitial":"J.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Bryan S.","contributorId":275853,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan S.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70216544,"text":"70216544 - 2020 - Climate sensitivity of water use by riparian woodlands at landscape scales","interactions":[],"lastModifiedDate":"2020-12-14T16:56:03.212697","indexId":"70216544","displayToPublicDate":"2020-10-15T10:46:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Climate sensitivity of water use by riparian woodlands at landscape scales","docAbstract":"<p><span>Semi‐arid riparian woodlands face threats from increasing extractive water demand and climate change in dryland landscapes worldwide. Improved landscape‐scale understanding of riparian woodland water use (evapotranspiration, ET) and its sensitivity to climate variables is needed to strategically manage water resources, as well as to create successful ecosystem conservation and restoration plans for potential climate futures. In this work, we assess the spatial and temporal variability of Cottonwood (</span><i>Populus fremontii</i><span>)‐Willow (</span><i>Salix gooddingii</i><span>) riparian gallery woodland ET and its relationships to vegetation structure and climate variables for 80 km of the San Pedro River corridor in southeastern Arizona, USA, between 2014 and 2019. We use a novel combination of publicly available remote sensing, climate and hydrological datasets: cloud‐based Landsat thermal remote sensing data products for ET (Google Earth Engine EEFlux), Landsat multispectral imagery and field data‐based calibrations to vegetation structure (leaf‐area index, LAI), and open‐source climate and hydrological data. We show that at landscape scales, daily ET rates (6–10 mm day</span><sup>−1</sup><span>) and growing season ET totals (400–1,400 mm) matched rates of published field data, and modelled reach‐scale average LAI (0.80–1.70) matched lower ranges of published field data. Over 6 years, the spatial variability of total growing season ET (CV = 0.18) exceeded that of temporal variability (CV = 0.10), indicating the importance of reach‐scale vegetation and hydrological conditions for controlling ET dynamics. Responses of ET to climate differed between perennial and intermittent‐flow stream reaches. At perennial‐flow reaches, ET correlated significantly with temperature, whilst at intermittent‐flow sites ET correlated significantly with rainfall and stream discharge. Amongst reaches studied in detail, we found positive but differing logarithmic relationships between LAI and ET. By documenting patterns of high spatial variability of ET at basin scales, these results underscore the importance of accurately accounting for differences in woodland vegetation structure and hydrological conditions for assessing water‐use requirements. Results also suggest that the climate sensitivity of ET may be used as a remote indicator of subsurface water resources relative to vegetation demand, and an indicator for informing conservation management priorities.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13942","usgsCitation":"Mayes, M., Caylor, K.K., Singer, M.B., Stella, J., Roberts, D., and Nagler, P.L., 2020, Climate sensitivity of water use by riparian woodlands at landscape scales: Hydrological Processes, v. 34, no. 25, p. 4884-4903, https://doi.org/10.1002/hyp.13942.","productDescription":"10 p.","startPage":"4884","endPage":"4903","ipdsId":"IP-120214","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455038,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orca.cardiff.ac.uk/id/eprint/135647/","text":"External Repository"},{"id":380788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"San Pedro River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.58563232421875,\n              31.3348710339506\n            ],\n            [\n              -109.79461669921875,\n              31.3348710339506\n            ],\n            [\n              -109.79461669921875,\n              32.15468722002481\n            ],\n            [\n              -110.58563232421875,\n              32.15468722002481\n            ],\n            [\n              -110.58563232421875,\n              31.3348710339506\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"25","noUsgsAuthors":false,"publicationDate":"2020-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Mayes, Marc","contributorId":245241,"corporation":false,"usgs":false,"family":"Mayes","given":"Marc","email":"","affiliations":[],"preferred":false,"id":805665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caylor, Kelly K.","contributorId":245242,"corporation":false,"usgs":false,"family":"Caylor","given":"Kelly","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":805666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singer, Michael B.","contributorId":168369,"corporation":false,"usgs":false,"family":"Singer","given":"Michael","email":"","middleInitial":"B.","affiliations":[{"id":25268,"text":"University of St Andrews, UK","active":true,"usgs":false}],"preferred":false,"id":805667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stella, John C","contributorId":149423,"corporation":false,"usgs":false,"family":"Stella","given":"John C","affiliations":[{"id":17732,"text":"Professor, Dept of Forest & Natural Resources Mgmt, SUNY at ESF","active":true,"usgs":false}],"preferred":false,"id":805668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Dar","contributorId":13721,"corporation":false,"usgs":true,"family":"Roberts","given":"Dar","affiliations":[],"preferred":false,"id":805669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70215379,"text":"70215379 - 2020 - Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data","interactions":[],"lastModifiedDate":"2020-10-16T11:48:29.969933","indexId":"70215379","displayToPublicDate":"2020-10-09T06:45:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Across Alaska’s Kenai Peninsula, disturbance events have removed large areas of forest over the last half century. Simultaneously, succession and landscape evolution have facilitated forest regrowth and expansion. Detecting forest loss within known pulse disturbance events is often straightforward given that reduction in tree cover is a readily detectable and measurable land-cover change. Land-cover change is more difficult to quantify when disturbance events are unknown, remote, or environmental response is slow in relation to human observation. While disturbance events and related land-cover change are relatively instant, assessing patterns of post-disturbance succession requires long term monitoring. Here, we describe a method for classifying land cover and quantifying land-cover change over time, using Landsat legacy imagery for three historical eras on the western Kenai Peninsula: 1973–2002, 2002–2017, and 1973–2017. Scenes from numerous Landsat sensors, including summer and winter seasons, were acquired between 1973 and 2017 and used to classify vegetation cover using a random forest classifier. Land-cover type was summarized by era and combined to produce a dataset capturing spatially explicit land-cover change at a moderate 30-m resolution. Our results document large-scale forest loss across the study area that can be attributed to known disturbance events including beetle kill and wildfire. Despite numerous and extensive disturbances resulting in forest loss, we estimate that the study area has experienced net forest gain over the duration of our study period due to reforestation within large fire events that predate this study. Transition between forest and graminoid non-forest land cover including wetlands and herbaceous uplands is the most common land-cover change—representing recruitment of a graminoid dominated understory following forest loss and the return of forest canopy given sufficient time post-disturbance.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/land9100382","usgsCitation":"Baughman, C., Loehman, R.A., Magness, D.R., Saperstein, L., and Sherriff, R., 2020, Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data: Land, v. 9, no. 10, 382, 22 p., https://doi.org/10.3390/land9100382.","productDescription":"382, 22 p.","ipdsId":"IP-116240","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":455092,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land9100382","text":"Publisher Index Page"},{"id":436759,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92BGHW1","text":"USGS data release","linkHelpText":"Land Cover Estimates for the Kenai Peninsula Lowlands; 1973, 2002, and 2017"},{"id":379452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -153.10546875,\n              59.0405546167585\n            ],\n            [\n              -147.48046875,\n              59.0405546167585\n            ],\n            [\n              -147.48046875,\n              61.52269494598361\n            ],\n            [\n              -153.10546875,\n              61.52269494598361\n            ],\n            [\n              -153.10546875,\n              59.0405546167585\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":801904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":801905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magness, Dawn R.","contributorId":243262,"corporation":false,"usgs":false,"family":"Magness","given":"Dawn","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":801907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saperstein, Lisa","contributorId":218974,"corporation":false,"usgs":false,"family":"Saperstein","given":"Lisa","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":801906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherriff, Rosemary L.","contributorId":243263,"corporation":false,"usgs":false,"family":"Sherriff","given":"Rosemary L.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":801908,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215189,"text":"70215189 - 2020 - A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data","interactions":[],"lastModifiedDate":"2020-10-29T15:15:46.334579","indexId":"70215189","displayToPublicDate":"2020-10-07T07:27:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Evapotranspiration (ET) is needed in a range of applications in hydrology, climatology, ecology, and agriculture. Remote sensing-based estimation is the only viable and economical method for ET estimation over large areas. The current Landsat satellites provide images every 16&nbsp;days limiting the ability to capture biophysical changes affecting ET. Thus, we explored the potential integration of Landsat 8 and Sentinel-2 data for estimating ET using a surface energy balance model. The results indicate the proposed Landsat-Sentinel data fusion approach substantially reduced relative errors from 48% to 10% on area-wide and from 49% to 17% on pixel-wide compared to linear interpolation between two Landsat images. The proposed approach had a better agreement with expected actual ET maps across high-vegetation conditions than in low-vegetation conditions. The finer temporal resolution and better accuracy of ET maps based on Landsat-Sentinel integration is of great importance in managing limited water resources.</p></div></div>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02626667.2020.1817461","usgsCitation":"Singh, R., Khand, K.B., Kagone, S., Schauer, M., Senay, G., and Wu, Z., 2020, A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data: Hydrological Sciences Journal, v. 65, no. 14, p. 2508-2519, https://doi.org/10.1080/02626667.2020.1817461.","productDescription":"12 p.","startPage":"2508","endPage":"2519","ipdsId":"IP-113350","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02626667.2020.1817461","text":"Publisher Index Page"},{"id":379288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California","otherGeospatial":"Palo Verde Irrigation District","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.9444580078125,\n              32.9764120829052\n            ],\n            [\n              -114.3402099609375,\n              32.9764120829052\n            ],\n            [\n              -114.3402099609375,\n              33.911454454267606\n            ],\n            [\n              -114.9444580078125,\n              33.911454454267606\n            ],\n            [\n              -114.9444580078125,\n              32.9764120829052\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"65","issue":"14","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Ramesh 0000-0002-8164-3483","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":210983,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khand, Kul Bikram 0000-0002-1593-1508","orcid":"https://orcid.org/0000-0002-1593-1508","contributorId":242921,"corporation":false,"usgs":true,"family":"Khand","given":"Kul","email":"","middleInitial":"Bikram","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kagone, Stefanie 0000-0002-2979-4655","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":216913,"corporation":false,"usgs":true,"family":"Kagone","given":"Stefanie","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":216909,"corporation":false,"usgs":true,"family":"Schauer","given":"Matthew","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":801110,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":801111,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70214661,"text":"70214661 - 2020 - Harmonizing the Landsat ground reference with the Sentinel-2 Global Reference Image using space-based bundle adjustment","interactions":[],"lastModifiedDate":"2020-10-01T17:18:27.914365","indexId":"70214661","displayToPublicDate":"2020-09-24T12:14:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7131,"text":"MDPI Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Harmonizing the Landsat ground reference with the Sentinel-2 Global Reference Image using space-based bundle adjustment","docAbstract":"There is an ever-increasing need to use accurate and consistent geometric ground reference in the processing of remotely sensed data products as it reduces the burden on the end-users to account for the differences between the data products from different missions. In this regard, United States Geological Survey (USGS) initiated an effort to harmonize the Landsat ground reference with the Sentinel-2 Global Reference Image (GRI) to improve the co-registration between the data products of the two global medium-resolution missions. In this paper, we have discussed the process, results, and the improvements expected from this harmonization of two ground references using space-triangulation based bundle adjustment techniques. The ground coordinates of the Landsat reference library, consisting of 5 million Ground Control Points (GCPs) were adjusted in a series of four simultaneous bundle block adjustments using thousands of Landsat-8 (L8) scenes anchored with more than 300,000 control points extracted from the GRI dataset. The net adjustments to each of the four blocks, namely, Australia, Americas, Eurasia, and Islands, varied anywhere from 1 m to 13 m, depending on the accuracy of the GCPs in these blocks. The use of the GRI dataset in our bundle adjustment not only improved the absolute accuracy of the Landsat ground reference but\nwill also improve the co-registration between Sentinel-2 and Landsat terrain corrected products, as the European Space Agency plans to process the Sentinel-2 products using the GRI dataset. Independent validation of the Landsat products processed using harmonized GCPs with the GRI dataset indicated a global mis-registration error of less than 8 m Circular Error Probable at 90 % (CE90), an improvement from 25 meters prior to harmonization. The improvements to the Landsat products using the harmonized GCPs will be available to the public as part of Landsat Collection-2 processing by the end of 2020.","language":"English","publisher":"MDPI","doi":"10.3390/rs12193132","usgsCitation":"Rengarajan, R., Storey, J., and Choate, M.J., 2020, Harmonizing the Landsat ground reference with the Sentinel-2 Global Reference Image using space-based bundle adjustment: MDPI Remote Sensing, v. 12, no. 19, 3132, 26 p., https://doi.org/10.3390/rs12193132.","productDescription":"3132, 26 p.","ipdsId":"IP-121294","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455232,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12193132","text":"Publisher Index Page"},{"id":378962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"19","noUsgsAuthors":false,"publicationDate":"2020-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":800346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storey, James C. 0000-0002-6664-7232","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":242015,"corporation":false,"usgs":false,"family":"Storey","given":"James C.","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":800347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":800348,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70214486,"text":"70214486 - 2020 - Ecohydrological responses to surface flow across borders: Two decades of changes in vegetation greenness and water use in the riparian corridor of the Colorado River Delta","interactions":[],"lastModifiedDate":"2025-12-11T22:12:21.683482","indexId":"70214486","displayToPublicDate":"2020-09-19T08:49:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Ecohydrological responses to surface flow across borders: Two decades of changes in vegetation greenness and water use in the riparian corridor of the Colorado River Delta","docAbstract":"<p>Hydrological and bioclimatic processes that lead to drought may stress plants and wildlife, restructure plant community type and architecture, increase monotypic stands and bare soils, facilitate the invasion of non‐native plant species and accelerate soil erosion. Our study focuses on the impact of a paucity of Colorado River surface flows from the United States (U.S.) to Mexico. We measured change in riparian plant greenness and water use over the past two decades using remotely sensed measurements of vegetation index (VI), evapotranspiration (ET), and a new annualized Phenology Assessment Metric (PAM) for ET. We measure these long‐term (2000‐2019) metrics and their short‐term (2014‐2019) response to an environmental, pulse flow in 2014, as prescribed under Minute 319 of the 1944 Water Treaty between the two nations. In subsequent years, small directed flows were provided to restoration areas under Minute 323. We use 250 m MODIS and 30 m Landsat imagery to evaluate three vegetation indices (NDVI, EVI, EVI2). We select EVI2 to parameterize an optical‐based ET algorithm and test the relationship between ET from Landsat and MODIS by regression approaches. Our analyses show significant decreases in VIs and ET for both the 20‐year and post‐pulse 5‐year periods. Over the last 20 years, EVI<span>&nbsp;</span><sub>Landsat</sub><span>&nbsp;</span>declined 34% (30% by EVI<sub>MODIS</sub>) and ET<sub>Landsat‐EVI</sub><span>&nbsp;</span>declined 38% (27% by ET<sub>MODIS‐EVI</sub>), overall ca. 1.61 mmd<sup>‐1</sup><span>&nbsp;</span>or 476 mmyr<sup>‐1</sup><span>&nbsp;</span>drop in ET. Over the 5 years since the 2014 pulse flow, EVI<span>&nbsp;</span><sub>Landsat</sub><span>&nbsp;</span>declined 20% (13% by EVI<sub>MODIS</sub>) and ET<sub>Landsat‐EVI</sub><span>&nbsp;</span>declined 23% (4% by ET<sub>MODIS‐EVI</sub>) with a 0.77 mmd<sup>‐1</sup><span>&nbsp;</span>or a 209 mmyr<sup>‐1</sup><span>&nbsp;</span>5‐year drop in ET. Data and change maps show the pulse flow contributed enough water to slow the rate of loss, but only for the very short‐term (1‐2 years). These findings are critically important as they suggest further deterioration of biodiversity, wildlife habitat and key ecosystem services due to anthropogenic diversions of water in the U.S. and Mexico and from land clearing, fires, and plant‐related drought which affect hydrological processes.</p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13911","usgsCitation":"Nagler, P.L., Barreto-Muñoz, A., Chavoshi Borujeni, S., Jarchow, C., Gómez‐Sapiens, M., Nouri, H., Herrmann, S.M., and Didan, K., 2020, Ecohydrological responses to surface flow across borders: Two decades of changes in vegetation greenness and water use in the riparian corridor of the Colorado River Delta: Hydrological Processes, v. 34, no. 25, p. 4851-4883, https://doi.org/10.1002/hyp.13911.","productDescription":"33 p.; Data Release","startPage":"4851","endPage":"4883","ipdsId":"IP-117414","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":378804,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":436784,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PGDJ1","text":"USGS data release","linkHelpText":"Colorado River Delta Project: A compilation of vegetation indices, phenology assessment metrics, estimates of evapotranspiration and change maps for seven reaches of the delta's 150 km region, for nearly the last two decades"}],"country":"Mexico, United States","otherGeospatial":"Colorado River delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.15869140624999,\n              31.606609719226917\n            ],\n            [\n              -114.521484375,\n              31.606609719226917\n            ],\n            [\n              -114.521484375,\n              32.76880048488168\n            ],\n            [\n              -115.15869140624999,\n              32.76880048488168\n            ],\n            [\n              -115.15869140624999,\n              31.606609719226917\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"25","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":799708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barreto-Muñoz, Armando","contributorId":239891,"corporation":false,"usgs":false,"family":"Barreto-Muñoz","given":"Armando","affiliations":[{"id":48028,"text":"University of Arizona, Biosystems Engineering, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":799709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chavoshi Borujeni, Sattar","contributorId":241612,"corporation":false,"usgs":false,"family":"Chavoshi Borujeni","given":"Sattar","email":"","affiliations":[{"id":48363,"text":"Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Centre, AREEO, Isfahan, Iran","active":true,"usgs":false}],"preferred":false,"id":799710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":799711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gómez‐Sapiens, Marth M.","contributorId":241615,"corporation":false,"usgs":false,"family":"Gómez‐Sapiens","given":"Marth M.","affiliations":[],"preferred":false,"id":799732,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nouri, Hamideh","contributorId":178847,"corporation":false,"usgs":false,"family":"Nouri","given":"Hamideh","affiliations":[],"preferred":false,"id":799733,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herrmann, Stefanie M. 0000-0002-4069-2019","orcid":"https://orcid.org/0000-0002-4069-2019","contributorId":20234,"corporation":false,"usgs":true,"family":"Herrmann","given":"Stefanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":799734,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":799735,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70214084,"text":"70214084 - 2020 - Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes","interactions":[],"lastModifiedDate":"2020-09-22T15:23:40.116445","indexId":"70214084","displayToPublicDate":"2020-09-18T10:16:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes","docAbstract":"<p><span>In terrestrial and marine ecosystems, remote sensing has been used to estimate gross primary productivity (GPP) for decades, but few applications exist for shallow freshwater ecosystems.Here we show field-based GPP correlates with satellite and airborne lake color across a range of optically and limnologically diverse lakes in interior Alaska. A strong relationship between&nbsp;</span><i>in situ</i><span>&nbsp;GPP derived from stable oxygen isotopes (δ</span><sup>18</sup><span>O) and space-based lake color from satellites (e.g. Landsat-8, Sentinel-2 and CubeSats) and airborne imagery (AVIRIS-NG) demonstrates the potential power of this technique for improving spatial and temporal monitoring of lake GPP when coupled with additional field validation measurements across different systems. In shallow waters clear enough for sunlight to reach lake bottoms, both submerged vegetation (macrophytes and algae) and phytoplankton likely contribute to GPP. The stable isotopes and remotely sensed shallow lake color used here integrate both components. These results demonstrate the utility of lake color as a feasible means for mapping lake GPP from remote sensing. This novel methodology estimates GPP from remote sensing in shallow lakes by combining field measurements of oxygen isotopes with airborne, satellite and CubeSat imagery. This use of lake color for providing insight into ecological processes of shallow lakes is recommended, especially for remote arctic and boreal landscapes.</span></p>","language":"English","publisher":"ioP Science","doi":"10.1088/1748-9326/aba46f","usgsCitation":"Kuhn, C.D., Bogard, M.J., Johnston, S.E., John, A., Vermote, E., Spencer, R., Dornblaser, M.M., Wickland, K.P., Striegl, R.G., and Butman, D., 2020, Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes: Environmental Research Letters, v. 10, no. 15, 105001, 13 p., https://doi.org/10.1088/1748-9326/aba46f.","productDescription":"105001, 13 p.","ipdsId":"IP-113821","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":455274,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aba46f","text":"Publisher Index Page"},{"id":378668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -148.68347167968747,\n              65.80727906299441\n            ],\n            [\n              -144.0802001953125,\n              65.80727906299441\n            ],\n            [\n              -144.0802001953125,\n              66.59631225137328\n            ],\n            [\n              -148.68347167968747,\n              66.59631225137328\n            ],\n            [\n              -148.68347167968747,\n              65.80727906299441\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"15","noUsgsAuthors":false,"publicationDate":"2020-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Kuhn, Catherine D. 0000-0002-9220-630X","orcid":"https://orcid.org/0000-0002-9220-630X","contributorId":213255,"corporation":false,"usgs":false,"family":"Kuhn","given":"Catherine","email":"","middleInitial":"D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":799398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bogard, Matthew J. 0000-0001-9491-0328","orcid":"https://orcid.org/0000-0001-9491-0328","contributorId":213254,"corporation":false,"usgs":false,"family":"Bogard","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":799399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnston, Sarah Ellen","contributorId":213256,"corporation":false,"usgs":false,"family":"Johnston","given":"Sarah","email":"","middleInitial":"Ellen","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":799400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"John, Aji","contributorId":241042,"corporation":false,"usgs":false,"family":"John","given":"Aji","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":799401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vermote, Eric","contributorId":198856,"corporation":false,"usgs":false,"family":"Vermote","given":"Eric","email":"","affiliations":[],"preferred":false,"id":799402,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Rob 0000-0003-0860-4717","orcid":"https://orcid.org/0000-0003-0860-4717","contributorId":241050,"corporation":false,"usgs":false,"family":"Spencer","given":"Rob","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":799403,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dornblaser, Mark M. 0000-0002-6298-3757 mmdornbl@usgs.gov","orcid":"https://orcid.org/0000-0002-6298-3757","contributorId":1636,"corporation":false,"usgs":true,"family":"Dornblaser","given":"Mark","email":"mmdornbl@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":799404,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wickland, Kimberly P. 0000-0002-6400-0590 kpwick@usgs.gov","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":1835,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","email":"kpwick@usgs.gov","middleInitial":"P.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":799405,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":799406,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Butman, David","contributorId":224754,"corporation":false,"usgs":false,"family":"Butman","given":"David","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":799407,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70214657,"text":"70214657 - 2020 - Landsat Collection 2 geometric calibration updates","interactions":[],"lastModifiedDate":"2020-10-02T11:59:42.820426","indexId":"70214657","displayToPublicDate":"2020-09-17T12:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat Collection 2 geometric calibration updates","docAbstract":"<p><span>The U.S. Geological Survey (USGS) changed the management and delivery of Landsat products to the public in its archive through the implementation of Collections. The Collections process ensures consistent data quality through time and across all the Landsat sensors with a few modifications to the metadata. The consistent data products from Collections are more conducive for applications such as time-series analysis, because the data can be used without a need for sensor-specific geometric or radiometric adjustments. The Collections process also allows for calibration improvements from updated reference sources, model trending, and enhanced algorithms that are grouped together and applied at one time, thus limiting the operational impacts to users. The first collection, Collection-1 was released in 2016, and Collection-2 is expected to be released in 2020. This paper addresses the geometric improvements to the Collection -2 dataset. Geometric improvements in Collection-2 include improvements to the geometric accuracy and interoperability of all Landsat products by implementing the Sentinel 2 Global Reference Image (GRI), improved elevation dataset using NASADEM and other sources of Digital Elevation Model (DEM) for terrain correction, improvements to the precision correction process for Enhanced Thematic Mapper Plus (ETM+) and Thematic Mapper (TM) sensors, changes to the Thermal Infrared Sensor (TIRS) to Operational Land Imager (OLI) alignment estimates, thermal band detector alignments and focal plane adjustments for ETM+, and improvements to the ETM+ sensor to attitude control system (ACS).</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings: Earth observing systems XXV","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Earth Observing Systems XXV","conferenceDate":"Aug 24-Sep 4, 2020","language":"English","publisher":"SPIE","doi":"10.1117/12.2570429","usgsCitation":"Rengarajan, R., Choate, M.J., Storey, J.C., Franks, S., and Micijevic, E., 2020, Landsat Collection 2 geometric calibration updates, <i>in</i> Proceedings: Earth observing systems XXV, v. 11501, Aug 24-Sep 4, 2020, 115010N, 11 p., https://doi.org/10.1117/12.2570429.","productDescription":"115010N, 11 p.","ipdsId":"IP-122667","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":378968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11501","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rengarajan, R. 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":56036,"corporation":false,"usgs":true,"family":"Rengarajan","given":"R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":800336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":800337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storey, James C. 0000-0002-6664-7232 storey@usgs.gov","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":5333,"corporation":false,"usgs":true,"family":"Storey","given":"James","email":"storey@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":800436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Franks, Shannon 0000-0003-1335-5401","orcid":"https://orcid.org/0000-0003-1335-5401","contributorId":93362,"corporation":false,"usgs":true,"family":"Franks","given":"Shannon","affiliations":[],"preferred":false,"id":800437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Micijevic, Esad 0000-0002-3828-9239 emicijevic@usgs.gov","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":3075,"corporation":false,"usgs":true,"family":"Micijevic","given":"Esad","email":"emicijevic@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":800438,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70213119,"text":"gip206 - 2020 - 40 years strong—Long-time Geoscience Australia, U.S. Geological Survey (USGS) partnership benefits both agencies and the world","interactions":[],"lastModifiedDate":"2020-09-11T12:22:08.358003","indexId":"gip206","displayToPublicDate":"2020-09-10T13:24:01","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"206","displayTitle":"40 Years Strong—Long-Time Geoscience Australia, U.S. Geological Survey (USGS) Partnership Benefits both Agencies and the World","title":"40 years strong—Long-time Geoscience Australia, U.S. Geological Survey (USGS) partnership benefits both agencies and the world","docAbstract":"<p>In 1979, the Australian Government chose the city of Alice Springs to host a Landsat Ground Station because of its location in central Australia. This location enables satellite coverage of the entire Australian continent. Its antennas have played a key role in supporting international satellite programs over more than 40 years.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip206","usgsCitation":"U.S. Geological Survey, 2020, 40 years strong—Long-time Geoscience Australia, U.S. Geological Survey (USGS) partnership benefits both agencies and the world: U.S. Geological Survey General Information Product 206, 2 p., https://doi.org/10.3133/gip206.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-119082","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":378285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0206/coverthb.jpg"},{"id":378286,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0206/gip206.pdf","text":"Report","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 206"}],"contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/eros\" href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science (EROS) Center</a> <br>U.S. Geological Survey<br>47914 252d Street <br>Sioux Falls, SD 57198</p>","tableOfContents":"<ul><li>When the Partnership Began</li><li>What the Partnership Involves</li><li>Benefits to Australia</li><li>Benefits to USGS</li><li>Serving the Greater Good</li><li>A Partnership Captured in Art</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-09-10","noUsgsAuthors":false,"publicationDate":"2020-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":147999,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":798284,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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