Evaluate rice phenological differences under heavy metal stress using NDVI time-series by blending  MODIS and Landsat data

Ping Wang; Fang Huang; Songhe Kang; Ling Zhao; Ning Sun; Yang Han

doi:10.1117/12.2324399

23 October 2018 Evaluate rice phenological differences under heavy metal stress using NDVI time-series by blending MODIS and Landsat data

Ping Wang, Fang Huang, Songhe Kang, Ling Zhao, Ning Sun, Yang Han

Author Affiliations +

Proceedings Volume 10780, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VII; 107800B (2018) https://doi.org/10.1117/12.2324399
Event: SPIE Asia-Pacific Remote Sensing, 2018, Honolulu, Hawaii, United States

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.

Citation Download Citation

Ping Wang, Fang Huang, Songhe Kang, Ling Zhao, Ning Sun, and Yang Han "Evaluate rice phenological differences under heavy metal stress using NDVI time-series by blending MODIS and Landsat data", Proc. SPIE 10780, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VII, 107800B (23 October 2018); https://doi.org/10.1117/12.2324399

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