Sentinel 1A SAR Backscattering Signature of Maize and Cotton Crops

Abstract

Crop discrimination is a key issue for agricultural monitoring using remote sensing techniques. Synthetic Aperture Radar (SAR) data are advantageous for crop monitoring and classification because of their all-weather imaging capabilities. The multi-temporal Sentinel 1A SAR data was acquired from 08th August, 2015 to 23rd January, 2016 at 12 days interval covering the extent of Perambalur district of Tamil Nadu. Both the Vertical - Vertical (VV) and Vertical-Horizontal (VH) polarized data are compared. The ground truth data collection was performed for cotton and maize during the vegetative, flowering and harvesting stages. The temporal backscattering coefficient (σ0 ) for cotton and maize are extracted using the training datasets. The mean backscattering values for cotton during the entire cropping period ranges from -10.58 dB to -6.28 dB and -20.59 dB to -14.53 dB for VV and VH polarized data respectively, and for maize it ranges from -11.08 dB to -7.07 dB and -19.85 dB to -14.14 dB for VV and VH polarized data respectively.

Mango Area Mapping Using Very High-Resolution Satellite Data in Major Blocks of Krishnagiri District, Tamil Nadu, India

“…Sabthapathy et al [13] used Sentinel-2A data for estimation of Mango and Cashew area for few districts of Tamil Nadu and estimated that 39313.01ha for entire Krishnagiri district. Similar to this, [14] Comparison between spatially estimated area and statistical data Sentinel-1A VH polarized SAR data based acreage estimation of maize and cotton produced higher accuracy using maximumlikelihood classification [15]. Mansaray et al [16] mapped rice fields in Shanghai, China, from Sentinel-1A and Landsat 8 data using maximumlikelihood classification, producing overall accuracy of 85 per cent with a kappa score of 0.81…”