A new vegetation index derived from the pattern decomposition method applied to Landsat‐7/ETM+ images in Mongolia

Muramatsu, Keiichi; Xiong, Yan; Nakayama, Sayaka; Ochiai, F.; Daigo, M.; Hirata, Masahiro; Oishi, Kazato; Bolortsetseg, B.; Oyunbaatar, Dambaravjaa; Kaihotsu, Ichirow

doi:10.1080/01431160601024200

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…Xiao et al [45] developed NDII as the land surface water index based on the SPOT-4 satellite image and used it to estimate water stress coefficient. Muramatsu et al [46] constructed a new index and applied it to Landsat satellite images for land-cover classification. Sentinel-2 satellite remote sensing images have a wide application in distinguishing different crop types, monitoring plant stress, and retrieving biophysical parameters, such as LAI, leaf Chl content, and leaf water content (Cw) [47,48,49,50,51,52].…”

Section: Introductionmentioning

confidence: 99%

Developing a New Spectral Index for Detecting Cadmium-Induced Stress in Rice on a Regional Scale

Liu

et al. 2019

IJERPH

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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.

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