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Two hyperspectral indices for detecting cadmium and lead contamination from arice canopy spectrum

Bibliographic Data

ID21647591
AuthorsShuangyin Zhang (0000-0002-4660-3996, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing Wuhan University Luoyu Rd. 129 Wuhan 430079 PR China), Fei Teng (0000-0003-0371-1142, Wuhan University, corresponding author), Teng Fei (0000-0002-3415-1654, School of Resource and Environmental Sciences Wuhan University Luoyu Rd. 129 Wuhan 430079 PR China), Xiang You (0009-0005-1506-8838, School of Resource and Environmental Sciences Wuhan University Luoyu Rd. 129 Wuhan 430079 PR China), Yinkang Wan (School of Resource and Environmental Sciences Wuhan University Luoyu Rd. 129 Wuhan 430079 PR China), Yunjiang Wang (School of Resource and Environmental Sciences Wuhan University Luoyu Rd. 129 Wuhan 430079 PR China), Meng Bian (0000-0002-2889-3192, School of Remote Sensing and Information Engineering Wuhan University Luoyu Rd. 129 Wuhan 430079 PR China, corresponding author)
Year2021
Volume32
Issue1
Pages66-78
Publication date2021-01-15
Open AccessYes
TypeARTICLE
VenueLand Degradation and Development (JOURNAL)
Journal identifiersISSN: 1085-3278 • E-ISSN: 1099-145X
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ldr.3721
OpenAlexW3043170964
LanguageEN
References cited55

Neither Cadmium (Cd) nor lead (Pb) is necessary for crop growth, and they both cause severe soil pollution in many countries. A cross‐stress experiment was designed to investigate the feasibility of diagnosing the type and the level of Cd–Pb cross‐stress by observing rice canopy hyperspectral images. Two‐way analysis of variance and random forest algorithm were employed to select the sensitive indices for Cd–Pb cross‐stress diagnosing. Following the exploration of bandwidth expansion from 1 to 20 nm, the final sensitive indices were proposed. We proposed two indices for distinguishing the two heavy metals named: the cadmium stress vegetation index (CSVI) and the lead stress vegetation index (LSVI). The diagnostic accuracies of CSVI distinguishing the four different Cd‐stressed levels (0, 2, 5, 8 mg L −1 ) reached 0.85, 0.92, 0.96, and 0.92, respectively, while the precision for four Pb‐stressed levels (0, 50, 100, 500 mg L −1 ) based on the LSVI were 0.92, 0.94, 0.96, and 0.96, respectively. The two indices are CSVI = [( R 772 + R 773 + R 774 + ... + R 789 ) ‐ ( R 754 + R 755 + R 756 + ... + R 771 )]/18, LSVI = [( R 711 + R 712 + R 713 + ... + R 718 ) – ( R 703 + R 704 + R 705 + ... + R 710 )]/8, located in near‐infrared ranges with 18 and 8 nm bandwidth, respectively. Therefore, it was feasible to diagnose the type and the level of Cd–Pb cross‐stress by examining the hyperspectral dataset of the rice canopy. Finally, the experiment compared the diagnostic ability of the proposed indices with the typical spectral indices for the physiological characterization of rice. The results showed that the proposed indices had state‐of‐the‐art distinguishing accuracies

Biology · Botany · Cadmium · Canopy · Hyperspectral imaging · Remote sensing · Chemistry · Environmental Science · Remote Sensing in Agriculture · Remote-Sensing Image Classification · Spectroscopy and Chemometric Analyses · Environmental Chemistry · Geology

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