Legume Research - An International Journal

Web of Science
  • Year: 2022
  • Volume: 45
  • Issue: 3

Rabi groundnut area estimation using synthetic aperture radar (SAR) in Thiruvannamalai district of Tamil Nadu

  • Author:
  • S. Thirumeninathan1,, S. Pazhanivelan2, N.S. Sudarmanian2, K.P. Ragunath2, A. Gurusamy3, N. Sritharan4
  • Total Page Count: 8
  • Page Number: 319 to 326

1Department of Agronomy, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

2Department of Remote Sensing and GIS, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

3Dryland Agricultural Research Station, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

4Department of Crop Physiology, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India

*Corresponding Author: S. Thirumeninathan, Department of Agronomy, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India, Email: thirumeni95@gmail.com

Online Published on 14 April, 2022.

Abstract

Groundnut, commonly known as peanut, is a significant oil, food and feed legume crop grown in all seasons in Tamil Nadu, including kharif, rabi and summer and it is cultivated both under irrigated and rainfed conditions in all the seasons at Thiruvannamlai district. One of the most important applications of remote sensing in agriculture is a crop acreage and production estimation (CAPE). The CAPE's main goal is to estimate crop acreage and production of important crops, so that advanced food production, distribution and supply data were achieved.

Multi-temporal Sentinel 1A SAR IW- GRD data with 20 m spatial resolution and 12 days temporal resolution of vertical -horizontal (V-H) polarization were downloaded for the period of 4th October 2020 to 8th January 2021 to have the full coverage during the crop growth period in the study area used for this work. Crop backscattering and multi-temporal features were extracted from MAP scape 5.2 automated pre-processing tool and its classified using supervised maximum likelihood classification for groundnut acreage extraction for Thiruvannamalai district.

The rabi groundnut area of Thiruvannamalai district of Tamil Nadu was estimated using SAR Sentinel-1A data as 32298 ha with a higher accuracy percentage of 87.4 and kappa coefficient of 0.75.

Keywords

Backscattering, Groundnut, MAP Scape, Maximum likelihood classification, Multi-temporal features, QGIS, Sentinel-1A