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U.S. GEOLOGICAL SURVEY
Scientific Investigations Report 2007–5050
Version 1.1, April 2010

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Appendix A. Landsat Analysis Methods

The imagery classification was based on two levels of resolution: (1) a generalized nonirrigated level that consisted of four Anderson Level I/II classes: ice and snow, evergreen forest, water, and shrub lands that represented a combination of bare soil, rock, sagebrush and other nonirrigated vegetation (Anderson and others, 1976); and (2) irrigated lands clustered into five vegetative classes based on their spectral similarity and potential crop water needs. These classes were labeled alfalfa and irrigated grasses, small grains, onions-garlic, potatoes-corn, and strawberries. Although it would have been desirable, identification of individual crop types proved to be impossible because of the lack of unique spectral signatures (Paul Seevers, EROS Data Center, written commun., 2000). The use of three satellite images from different times during the growing season increased the probability that certain crop-types could be distinguished based on the development of their spectral signatures. To aid in the classification of the imagery, field work was conducted to map directly crop types in areas totaling about 17,000 acres. A variety of representative land-cover types were observed, including native trees, pasture and most of the agricultural crops. Most data were collected in mid-July. Data on crop type and height, percentage of crop cover, sprinkler type, and other parameters also were collected.

The three images were processed in succession. The May 21, 2000, scene (from Landsat 5) showed full canopy cover of the perennial crops such as alfalfa, irrigated grasses, and any winter wheat that may have been planted the previous fall. The timing of the scene put it before any annual row crops had enough growth to show a vegetative signature. Areas with vigorous growth in the May scene served to mask over the same areas in the August scene. This step reduced the amount of data in the August scene that required analysis. The irrigation district boundaries were used to segregate irrigated areas outside of the Klamath Project. The August 1 scene (from Landsat 7) revealed the full canopy of the annual row crops planted during the spring. The September 18 scene (also from Landsat 7) was used to show any crops that might have a vigorous vegetative signature beyond the harvest dates of the small grains.

A review was performed on the results of the final land-cover classification by creating an error matrix to evaluate how well the classification of the imagery matched what was actually mapped on the ground. The review looked at how accurately the classification identified specific crop-types and how accurately the classification did with respect to all irrigated crop-classes. To do this, the new land-cover map created from the classified Landsat imagery was converted to a polygon dataset, with each polygon being 30 meters, the resolution of the original imagery. Each polygon contained a code for crop class determined by the classification process. The ground reference boundaries were then used to clip out the same areas in the classified land cover. The clipped land-cover polygons were then evaluated by crop class against the ground reference. For example, if a ground reference area was identified as alfalfa, then the same area was compared in the land cover. The results of the review showed that large-acreage crops such as alfalfa had a correct classification ratio of about 64 percent. However, if all irrigated crop classes were included then the accuracy of identifying irrigated lands within that area increased to about 73 percent. For crops grown on smaller fields, the accuracy of the classification to identify specific crop class decreased to a range of 20 to 30 percent. If all irrigated lands were included then the accuracy increased to the 50 to 70 percent range. Sugar beet fields for example, were correctly classified 34 percent of the time, but if all irrigated lands for the same area were included then the accuracy increased to 62 percent. All mint and strawberry fields were located during the ground truth and were included in the final classification.

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