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Article

Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study

by 1,2,3, 1,2,*, 1,2, 1,2 and 3,4
1
International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
2
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
3
Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
4
Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(7), 807; https://doi.org/10.3390/rs11070807
Received: 6 March 2019 / Revised: 1 April 2019 / Accepted: 2 April 2019 / Published: 3 April 2019
(This article belongs to the Special Issue Applications of Spectroscopy in Agriculture and Vegetation Research)
Crop residue left in the field after harvest helps to protect against water and wind erosion, increase soil organic matter, and improve soil quality, so a proper estimate of the quantity of crop residue is crucial to optimize tillage and for research into environmental effects. Although remote-sensing-based techniques to estimate crop residue cover (CRC) have proven to be good tools for determining CRC, their application is limited by variations in the moisture of crop residue and soil. In this study, we propose a crop residue angle index (CRAI) to estimate the CRC for four distinct soils with varying soil moisture (SM) content and crop residue moisture (CRM). The current study uses laboratory-based tests ((i) a dry dataset (air-dried soils and crop residues, n = 392); (ii) a wet dataset (wet soils and crop residues, n = 822); (iii) a saturated dataset (saturated soils and crop residues, n = 402); and (iv) all datasets (n = 1616)), which allows us to analysis the soil and crop residue hyperspectral response to varying SM/CRM. The CRAI combines two features that reflect the moisture content in soil and crop residue. The first is the different reflectance of soil and crop residue as a function of moisture in the near-infrared band (833 nm) and short-wave near-infrared band (1670 nm), and the second is different reflectance of soils and crop residues to lignin, cellulose, and moisture in the bands at 2101, 2031, and 2201 nm. The effects of moisture and soil type on the proposed CRAI and selected traditional spectral indices ((i) hyperspectral cellulose absorption index; (ii) hyperspectral shortwave infrared normalized difference residue index; and (iii) selected broad-band spectral indices) were compared by using a laboratory-based dataset. The results show that the SM/CRM significantly affects the broad-band spectral indices and all other spectral indices investigated are less correlated with CRC when using all datasets than when using only the dry, wet, or saturated dataset. Laboratory study suggests that the CRAI is promising for estimating CRC with the four soils and with varying SM/CRM. However, because the CRAI was only validated by a laboratory-based dataset, additional field testing is thus required to verify the use of satellite hyperspectral remote-sensing images for different crops and ecological areas. View Full-Text
Keywords: crop residue cover; crop residue moisture; soil moisture; angle index; remote sensing crop residue cover; crop residue moisture; soil moisture; angle index; remote sensing
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MDPI and ACS Style

Yue, J.; Tian, Q.; Dong, X.; Xu, K.; Zhou, C. Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study. Remote Sens. 2019, 11, 807. https://doi.org/10.3390/rs11070807

AMA Style

Yue J, Tian Q, Dong X, Xu K, Zhou C. Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study. Remote Sensing. 2019; 11(7):807. https://doi.org/10.3390/rs11070807

Chicago/Turabian Style

Yue, Jibo; Tian, Qingjiu; Dong, Xinyu; Xu, Kaijian; Zhou, Chengquan. 2019. "Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study" Remote Sens. 11, no. 7: 807. https://doi.org/10.3390/rs11070807

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