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Using Classified Landsat Thematic Mapper Data for Stratification in a Statewide Forest InventoryAuthor(s): Mark H. Hansen; Daniel G. Wendt
Source: Proceedings of the First Annual Forest Inventory and Analysis Symposium. p. 20-27. (2000)
Publication Series: Scientific Journal (JRNL)
Station: North Central Research Station
PDF: Download Publication (1.44 MB)
DescriptionThe 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM} data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone. Estimates based on twophase sampling for stratification were made at the county level. This procedure differed from methods used in previous inventories where stratification was based on the stereoscopic examination of aerial photo plots. Changes in plot design, sampling intensity, and population parameters between 1986 and 1999 make it impossible to attribute differences in sampling errors entirely to this change in methods. The stratified sample estimates based on TM data provided good estimates and greatly reduced costs by eliminating the need for thousands of aerial photos and manual interpretation of several hundred thousand photo plots.
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CitationHansen, Mark H.; Wendt, Daniel G. 2000. Using Classified Landsat Thematic Mapper Data for Stratification in a Statewide Forest Inventory. Proceedings of the First Annual Forest Inventory and Analysis Symposium. p. 20-27. (2000)
Keywordsplot design, buffer zone, Landsat Thematic Mapper, stratification, Nation Gap Analysis Program
- Using classified Landsat Thematic Mapper data for stratification in a statewide forest inventory
- Stratifying FIA Ground Plots Using A 3-Year Old MRLC Forest Cover Map and Current TM Derived Variables Selected By "Decision Tree" Classification
- Comparing Forest/Nonforest Classifications of Landsat TM Imagery for Stratifying FIA Estimates of Forest Land Area
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