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Proceedings Paper

Evaluate rice phenological differences under heavy metal stress using NDVI time-series by blending MODIS and Landsat data
Author(s): Ping Wang; Fang Huang; Songhe Kang; Ling Zhao; Ning Sun; Yang Han
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Paper Abstract

Monitoring heavy metal stress on rice is of great significance for food security. In this paper, we used NDVI time series during the whole growing period of rice to identifying the rice growing differences under varied heavy metal stress. Here the NDVI time series were with high spatial-temporal resolution and obtained by blending MODIS and Landsat NDVI data. We extracted two kinds of features: Max NDVI value and time-integrated NDVI and use Fisher discrimination to explore the rice phonological differences under mild and severe stress levels. Results indicates that under severe stress the values of the metrics for presenting rice phonological differences in the experimental areas of heavy metal stress were smaller than the ones under mild stress. This means using the phenology differences can help to monitoring the heavy metal contamination.

Paper Details

Date Published: 23 October 2018
PDF: 8 pages
Proc. SPIE 10780, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VII, 107800B (23 October 2018); doi: 10.1117/12.2324399
Show Author Affiliations
Ping Wang, Northeast Normal Univ. (China)
Fang Huang, Northeast Normal Univ. (China)
Songhe Kang, Northeast Normal Univ. (China)
Ling Zhao, Jilin Agricultural Univ. (China)
Ning Sun, Northeast Normal Univ. (China)
Yang Han, Northeast Normal Univ. (China)


Published in SPIE Proceedings Vol. 10780:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VII
Allen M. Larar; Makoto Suzuki; Jianyu Wang, Editor(s)

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