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Proceedings Paper

Analysis of crop condition during monsoon season using multispectral and polarimetric SAR images
Author(s): Sanjit Maitra
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Paper Abstract

Satellite images are widely used for identification of different types of crops, health monitoring and estimating crop production. This study is to analyze the effect of seasonal monsoon rainfall on different types of crops using multispectral and polarimetric synthetic aperture radar (SAR) images. The study area for this analysis is around Tezpur town located centrally in the north-eastern state of Assam in India. The major crops produced in this area are rice, tea, sugarcane, lychee. Multispectral images from the Indian Space Research Organization’s (ISRO) ResourceSat 2 satellite are used along with dual polarization (HH and HV) SAR images from RISAT 1. The health of the different varieties of crops before and after the monsoon is measured from the multispectral images using modified 2 band Enhanced Vegetation Index (EVI2). The ratio of the cross-polarized to co-polarized back scatter (HV/HH) is used as another metric to track the change in volume scatter from the different types of crops. The change in the vegetation index along with the amount of volume backscatter pre- and post-monsoon gives an idea of the effect of rainfall on the vegetation health along with changes in the structure and leaf density for the different types of crops. The results show that there is an increase in HV/HH and decrease in EVI2 for tea, sugarcane and rice during the season while both EVI2 and HV/HH decreased for lychee. This preliminary study shows how complementary information from multispectral and polarimetric SAR images can be fused with improved vegetation monitoring capability.

Paper Details

Date Published: 10 October 2018
PDF: 9 pages
Proc. SPIE 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, 1078324 (10 October 2018); doi: 10.1117/12.2500154
Show Author Affiliations
Sanjit Maitra, Indian Statistical Institute (India)


Published in SPIE Proceedings Vol. 10783:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XX
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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