National-scale soybean mapping and area estimation in the United States using medium resolution satellite imagery and field survey

详细信息    查看全文

• 作者：Xiao-Peng Song^a ; ^{xpsong@umd.edu} ; Peter V. Potapov^a ; Alexander Krylov^a ; LeeAnn King^a ; Carlos M. Di Bella^b ; ^c ; ^d ; Amy Hudson^a ; Ahmad Khan^a ; Bernard Adusei^a ; Stephen V. Stehman^e ; Matthew C. Hansen^a
• 关键词：Agriculture ; Cropland ; Sample ; Remote sensing ; Landsat ; Image time-series ; Classification ; Decision tree
• 刊名：Remote Sensing of Environment
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：190
• 期：Complete
• 页码：383-395
• 全文大小：3576 K
• 卷排序：190

文摘

A new method for national-scale crop-specific area estimation and wall-to-wall mapping. Field-based stratified sample soybean area estimate 1–2% different from USDA estimates. Soybean map calibrated to match sample estimated area had 84% overall accuracy. Methodology suitable for operational use for other regions and crops.