A Sensitive Band to Optimize Winter Wheat Crop Residue Cover Estimation by Eliminating Moisture Effect

Yamei Wang, Shuhe Zhao, Wenting Cai, Joon Heo and Fanchen Peng
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Yamei Wang: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Shuhe Zhao: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Wenting Cai: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Joon Heo: Department of Civil and Environmental Engineering, Yonsei University, Seoul 100-744, Korea
Fanchen Peng: School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

Sustainability, 2019, vol. 11, issue 11, 1-18

Abstract: Crop residues can retain soil moisture and increase soil organic matter. Crop residue cover is also a hot issue in agricultural remote sensing. Crop residue cover can be estimated linearly with cellulose absorption index (CAI), while moisture of crop residues and soil would reduce the accuracy of crop residue cover estimation. Crop residue and soil were used as materials to carry out the laboratory experiment to reveal the impact of moisture on crop residue cover estimation and eliminate said impact. This paper discovered a sensitive band, R 2005 , which can invert water content of materials to eliminate moisture effect and improve estimation accuracy of crop residue cover. In terms of inverting water content, compared with two ratio water indices proposed in 2016 ( R 1.6 / R 1.5 , R 1.6 / R 2.0 ), using R 2005 can increase R 2 from 0.828 to 0.935 and decline root-mean-square error (RMSE) from 0.12 to 0.07. At the point of results validation, R 2 is 0.958 and RMSE is 0.06, indicating R 2005 has a high accuracy. Another advantage of R 2005 is that it is more suitable to promote to actual production because of simple and efficient band calculation.

Keywords: winter wheat; crop residue cover; cellulose absorption index (CAI); R 2005 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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