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		<title>USGS Publications Warehouse</title>
		<link>https://pubs.usgs.gov</link>
		<description>New publications of the USGS.</description>
		<language>en-us</language>
		<lastBuildDate>Fri, 1 May 2026 05:49:26 +0000</lastBuildDate>
		<webmaster>https://pubs.usgs.gov/feedback</webmaster>
		<pubDate>Fri, 1 May 2026 05:49:26 +0000</pubDate>
		<item>
			<title>Geologic map of the Emmons Lake volcanic center, Alaska</title>
			<author>Miller, Thomas; Waythomas, Christopher; Mangan, Margaret; Trusdell, Frank; Calvert, Andrew</author>
			<link>https://pubs.usgs.gov/publication/sim3519</link>
			<description>&lt;h1&gt;Introduction&amp;nbsp;&lt;/h1&gt;&lt;p&gt;The Emmons Lake volcanic center is a spatially clustered group of stratovolcanoes and calderas in the southwestern part of the Alaska Peninsula, Alaska. The volcanic center is characterized by several ice- and snow-clad stratovolcanoes located within and along the margins of a nested-caldera complex that includes Emmons Lake. A shieldlike ancestral edifice (ancestral Mount Emmons) is truncated by the caldera complex and forms a broad volcanic platform around the center. The main stratovolcanoes of the Emmons Lake volcanic center are Pavlof Sister, Pavlof Volcano, Little Pavlof, Double Crater, Mount Hague, and Mount Emmons. Several small unnamed cinder cones and vents also are located within Emmons Lake volcanic center and on the east flank of Pavlof Volcano. Many of these cones and vents have been the source of the young lava flows that mantle the floor of the caldera. Pavlof Volcano, in the northeastern part of the Emmons Lake volcanic center, is one of the most historically (that is, the past about 300 years) active volcanoes in Alaska, and eruptions from Pavlof Volcano pose the greatest hazards to the region.&lt;/p&gt;&lt;p&gt;Volcanic rocks of the Emmons Lake volcanic center overlie continental and marine sedimentary rocks of chiefly Late Jurassic to early Tertiary age. The oldest rocks in the area are those of the Naknek Formation, consisting of volcaniclastic sandstone, siltstone, and conglomerate of Late Jurassic age. The southern part of the area includes rocks of the Belkofski Formation, a thick sequence of volcaniclastic sandstone, siltstone, and conglomerate of middle Tertiary age. Lava flows, volcanic breccia, and fluvial volcaniclastic rocks of late Miocene age, which unconformably overlie the Belkofski Formation south of the Emmons Lake volcanic center, are primarily exposed on the islands just south of the Alaska Peninsula.&lt;/p&gt;&lt;p&gt;The Emmons Lake volcanic center was affected multiple times by glaciation associated with the glacier expansion that characterized the Quaternary. Glaciation has played a key role in shaping the present-day landscape, and much of the eruptive history of the Emmons Lake volcanic center has involved interactions with glacier ice. Thus, a brief review of the Quaternary glacial history of the area is provided to establish the physical context for Emmons Lake volcanic center eruptive activity.&lt;/p&gt;</description>
			<pubDate>Thu, 2 Apr 2026 14:28:05</pubDate>
			<category>Scientific Investigations Map</category>
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			<title>A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping</title>
			<author>Fleckenstein, Rylie; Wellington, Danika; Jin, Suming; Tollerud, Heather; Brown, Jesslyn; Dewitz, Jon; Pastick, Neal; Barber, Christopher; O'Brien, Austin; Spanier, Mark</author>
			<link>https://pubs.usgs.gov/publication/70274250</link>
			<description>&lt;div id=&quot;sp0075&quot; class=&quot;u-margin-s-bottom&quot;&gt;Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD.&lt;/div&gt;&lt;div class=&quot;u-margin-s-bottom&quot;&gt;&lt;br data-mce-bogus=&quot;1&quot;&gt;&lt;/div&gt;&lt;div id=&quot;sp0080&quot; class=&quot;u-margin-s-bottom&quot;&gt;LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics.&lt;/div&gt;&lt;div class=&quot;u-margin-s-bottom&quot;&gt;&lt;br data-mce-bogus=&quot;1&quot;&gt;&lt;/div&gt;&lt;div id=&quot;sp0085&quot; class=&quot;u-margin-s-bottom&quot;&gt;Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved&lt;span&gt; 72.1 ± 1.60%&lt;/span&gt;&lt;span class=&quot;math&quot;&gt;&lt;span id=&quot;MathJax-Element-1-Frame&quot; class=&quot;MathJax_SVG&quot; data-mathml=&quot;&amp;lt;math xmlns=&amp;quot;http://www.w3.org/1998/Math/MathML&amp;quot;&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;72.1&amp;lt;/mn&amp;gt;&amp;lt;mo linebreak=&amp;quot;goodbreak&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;&amp;amp;#xB1;&amp;lt;/mo&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;1.60&amp;lt;/mn&amp;gt;&amp;lt;mi mathvariant=&amp;quot;normal&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;%&amp;lt;/mi&amp;gt;&amp;lt;/math&amp;gt;&quot;&gt;&lt;/span&gt;&lt;/span&gt;&lt;span&gt;&amp;nbsp;&lt;/span&gt;overall agreement, compared to&lt;span&gt; 71.1 ± 1.7%&lt;/span&gt;&lt;span class=&quot;math&quot;&gt;&lt;span id=&quot;MathJax-Element-2-Frame&quot; class=&quot;MathJax_SVG&quot; data-mathml=&quot;&amp;lt;math xmlns=&amp;quot;http://www.w3.org/1998/Math/MathML&amp;quot;&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;71.1&amp;lt;/mn&amp;gt;&amp;lt;mo linebreak=&amp;quot;goodbreak&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;&amp;amp;#xB1;&amp;lt;/mo&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;1.7&amp;lt;/mn&amp;gt;&amp;lt;mi mathvariant=&amp;quot;normal&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;%&amp;lt;/mi&amp;gt;&amp;lt;/math&amp;gt;&quot;&gt;&lt;/span&gt;&lt;/span&gt;&lt;span&gt;&amp;nbsp;&lt;/span&gt;agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved&lt;span&gt; 83.4 ±&lt;/span&gt;&lt;span class=&quot;math&quot;&gt;&lt;span id=&quot;MathJax-Element-3-Frame&quot; class=&quot;MathJax_SVG&quot; data-mathml=&quot;&amp;lt;math xmlns=&amp;quot;http://www.w3.org/1998/Math/MathML&amp;quot;&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;83.4&amp;lt;/mn&amp;gt;&amp;lt;mo linebreak=&amp;quot;goodbreak&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;&amp;amp;#xB1;&amp;lt;/mo&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;1.22&amp;lt;/mn&amp;gt;&amp;lt;mi mathvariant=&amp;quot;normal&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;%&amp;lt;/mi&amp;gt;&amp;lt;/math&amp;gt;&quot;&gt;&lt;/span&gt;&lt;/span&gt;&lt;span&gt; 1.22% &lt;/span&gt;agreement, compared to 84.6&lt;span&gt; ±&lt;/span&gt;&lt;span class=&quot;math&quot;&gt;&lt;span id=&quot;MathJax-Element-4-Frame&quot; class=&quot;MathJax_SVG&quot; data-mathml=&quot;&amp;lt;math xmlns=&amp;quot;http://www.w3.org/1998/Math/MathML&amp;quot;&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;84.6&amp;lt;/mn&amp;gt;&amp;lt;mo linebreak=&amp;quot;goodbreak&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;&amp;amp;#xB1;&amp;lt;/mo&amp;gt;&amp;lt;mn is=&amp;quot;true&amp;quot;&amp;gt;1.11&amp;lt;/mn&amp;gt;&amp;lt;mi mathvariant=&amp;quot;normal&amp;quot; is=&amp;quot;true&amp;quot;&amp;gt;%&amp;lt;/mi&amp;gt;&amp;lt;/math&amp;gt;&quot;&gt;&lt;/span&gt;&lt;/span&gt;&lt;span&gt; 1.11% &lt;/span&gt;agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.&lt;/div&gt;</description>
			<pubDate>Thu, 19 Mar 2026 19:31:01</pubDate>
			<category>Remote Sensing of Environment</category>
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			<title>Forecasting volcanic activity in Germany—A multi-criteria approach</title>
			<author>Bartels, A.; Rummel, L.H.; May, Franz</author>
			<link>https://pubs.usgs.gov/publication/pp1890C</link>
			<description>&lt;p&gt;Igneous activity, including shallow intrusions and volcanism, has the potential to disrupt underground critical infrastructure. Notably, future underground infrastructure projects like high-level radioactive waste repositories must be sited in areas of extremely low disruption probability by igneous activity. In Germany, according to the Repository Site Selection Act of 2017 (Standortauswahlgesetz, or StandAG), areas in which Quaternary volcanism is either present or future volcanic activity is expected within the next 1 million years (m.y.) must be excluded from the site selection process. Although the locations of regions with Quaternary volcanism are reasonably well known in Germany, forecasting potential igneous activity at intraplate volcanic fields is challenging, as many processes and their interactions control the spatial distribution of volcanic centers. Here, a semi-quantitative, multi-criteria approach is proposed for a regional evaluation of the relative potential of future igneous activity in Germany. A variety of geoscientific indicators are used, including seismic anomalies in Earth’s mantle, gravity data, tectonic activity, sutures, ground motion, earthquakes, mantle degassing centers, and geochronological data of volcanic rocks. The indicators describe the sequence of processes from potential melt generation in Earth’s mantle, through ascent and accumulation of melt within the lithosphere, to eruption at Earth’s surface. In total, 15 out of 30 proposed geoscientific indicators are selected and quantified using 20 total assigned parameters. Defined threshold values are used to spatially delimit relevant parameter properties to focus on areas with higher potential of future magmatic activity. To consider uncertainties of parameters and their underlying processes, which are usually more spatially extensive below ground, buffer zones are defined in which values of relevance decrease with increasing distance from the initial lateral shape of a parameter. Normalized parameters are combined into an index, whose spatial value distribution is used to differentiate the relative potential of future igneous activity (within the next 1 m.y.). The sensitivity of the results is shown by varying the weighting factors for the relevant parameters in country-wide index maps. Thereby, profiles illustrate the distribution of the resulting index values and respective index fractions of various parameters. Different index maps for the relative potential of future igneous activity are presented and can be used for hazard assessments.&lt;/p&gt;</description>
			<pubDate>Tue, 3 Mar 2026 14:52:29</pubDate>
			<category>Professional Paper</category>
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