Author
Listed:
- Chuanyu Wu
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
- Meiling Liu
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
- Xiangnan Liu
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
- Tiejun Wang
(Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 Enschede, The Netherlands)
- Lingyue Wang
(School of Information Engineering, China University of Geosciences, Beijing 100083, China)
Abstract
In natural farmland ecosystems, cadmium (Cd) pollution in rice has attracted increasing attention because of its high toxicity, relative mobility, and high water solubility. This study aims to develop a spectral index for detecting Cd stress in rice on a regional scale. Three experimental sites are selected in Zhuzhou City, Hunan Province. The hyperspectral data, chlorophyll (Chl) content, leaf area index, average leaf angle, Cd concentration in soil, and Sentinel-2A images from 2017 and 2018 are collected. A new spectral index sensitive to Cd stress in rice is established based on the global sensitivity analysis of the radiative transfer model PROSPECT + SAIL (commonly called PROSAIL) model with the auxiliary of the field-measured data. The heavy metal Cd stress-sensitive spectral index (HCSI) is devised as an indicator of the degree of Cd stress in rice. Results indicate that (1) the HCSI developed based on Chl is a good indicator of rice damage caused by Cd stress, that is, low values of HCSI occur in rice subject to relatively high pollution; (2) compared with common spectral indices, such as red-edge position and red-edge Chl index, HCSI is more sensitive to Chl content with higher Pearson correlation coefficients with respect to Chl content, ranging from 0.85 to 0.95; (3) HCSI is successfully applied in Sentinel-2A images from the two different years of monitoring rice Cd stress on a regional scale. Cd stress levels in rice stabilized, and the largest area percentage of each pollution levels of Cd decreased in the following order: No pollution (i.e., 40%), low pollution (i.e., 35%), and high pollution (i.e., 25%). This study indicates that a combination of simulation data from the PROSAIL model and measured data appears to be a promising method for establishing a sensitivity spectral index to heavy metal stress, which can accurately detect regional Cd stress in crops.
Suggested Citation
Chuanyu Wu & Meiling Liu & Xiangnan Liu & Tiejun Wang & Lingyue Wang, 2019.
"Developing a New Spectral Index for Detecting Cadmium-Induced Stress in Rice on a Regional Scale,"
IJERPH, MDPI, vol. 16(23), pages 1-18, November.
Handle:
RePEc:gam:jijerp:v:16:y:2019:i:23:p:4811-:d:292512
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