MAPPING CROPLAND EXTENT FROM SYNTHETIC APERTURE RADAR USING THE COEFFICIENT OF VARIATION

被引:0
作者
Sharp, Kaylee G. [1 ]
Pankratz, Hannah G. [2 ]
Bell, Jordan R. [3 ]
Schultz, Lori A. [3 ]
Lucey, Ronan [1 ]
Meyer, Franz J. [4 ]
机构
[1] Univ Alabama Huntsville, Earth Syst Sci Ctr, Huntsville, AL 35899 USA
[2] Marshall Space Flight Ctr, NASA Postdoctoral Program, Huntsville, AL 35808 USA
[3] NASA Marshall Space Flight Ctr, Earth Sci Branch, Huntsville, AL USA
[4] Univ Alaska Fairbanks, Alaska Satellite Facil, Fairbanks, AK USA
来源
IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024 | 2024年
关键词
SAR; agriculture; time series; classification; coefficient of variation;
D O I
10.1109/IGARSS53475.2024.10640557
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Satellite remote sensing time series have frequently been leveraged to track crop phenology changes throughout the growing season worldwide. These time series, primarily derived from optical sensors, can provide insights on changes that occur throughout the growing season compared to previous years. Additionally, time series can help monitor crop yields and overall production and can provide information about what is planted in a specific field. Optical remote sensors rely upon atmospheric and sky conditions, often causing gaps in the time series when images cannot be used because of cloud cover. The increasing availability of observations from synthetic aperture radar (SAR) allows for worldwide and repeat year-round collections. This study uses acquisitions from several different SAR missions (2018-2022) to map cropland extent using the coefficient of variation (CV) method in agricultural regions around the world, focusing predominantly on major global producers of corn, wheat, and rice.
引用
收藏
页码:4946 / 4948
页数:3
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