Fodder crop estimation using Sentinel-2A/B satellite data for West Bengal, India

Abstract

Mapping, monitoring and estimation of fodder crop area can support farmers, policy makers to make right decisions in various conditions to improve the livestock productivity. The freely available high-resolution Sentinel-2 MSI data has increased the application of precision agriculture for a broader range. This study investigated the capabilities of Sentinel-2A/B MSI satellite data to identify and discriminate the fodder crops from other crops and estimate the area utilized for fodder cultivation in five districts of West Bengal during 2019–20 in rabi season (October to March). Multi-date NDVI based spectral profiles were generated from satellite imagery to ascertain the time of sowing which plays an important role to differentiate fodder crops from other crops. Image classification has been done through the ISODATA clustering technique. A field survey has been carried out in the study area and a total of 610 GT points were collected from different locations of fodder crops using handheld GPS and smartphone-based applications to validate the classification of crops. Accuracy assessment has also been performed between four classes (Fodder crops, Other crops, Forest and Waterbody) which is 81.61% for fodder crops, and 88.97% overall accuracy was observed in classification. The area under fodder cultivation was 0.68% of the total agricultural area, which has been estimated to the tune of 6.78 per thousand hectares. This study can be implemented for fodder crop identification and cultivation management plan to improve the livestock productivity by supply of fodder throughout the year.