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Assessment of the application of copper stress vegetation index on Hyperion image in Dexing Copper Mine, China

Authors :
Chengye Zhang
Tianyuan Zhang
Huazhong Ren
Qiming Qin
Jun Li
Ziyi Huang
Yuanheng Sun
Source :
Journal of Applied Remote Sensing. 13:1
Publication Year :
2019
Publisher :
SPIE-Intl Soc Optical Eng, 2019.

Abstract

We are the first to apply the copper stress vegetation index (CSVI) on a remotely sensed image and the purpose is to verify the effectiveness of CSVI at the satellite-image scale. The study area was located at the Dexing Copper Mine, Jiangxi Province, China. First, the data preprocessing for the Hyperion image was conducted, including bands removal, radiometric calibration, and atmospheric correction. Second, the regions with high vegetation cover were extracted based on endmembers extraction and spectral unmixing. The CSVI was calculated on the high-vegetation-cover regions. Third, the samples of soil and leaves were collected from the study area and the copper contents in the samples were measured for the assessment. The results showed that the high values of the CSVI were near the functional regions for copper mining and the polluted rivers. What is more, there was a significant positive correlation between the CSVI calculated from the Hyperion image and the copper content in soil/leaves. We demonstrate that CSVI is applicable for monitoring the copper stress on vegetation using satellite hyperspectral images. In addition, we provide a complete example for the application of CSVI at the satellite-image scale for the first time, which is helpful for the community in remote sensing of copper-stressed vegetation.

Details

ISSN :
19313195
Volume :
13
Database :
OpenAIRE
Journal :
Journal of Applied Remote Sensing
Accession number :
edsair.doi...........885819dae5e696adc1ce7da1c3b39446
Full Text :
https://doi.org/10.1117/1.jrs.13.014511