Agroforestry area mapping using medium resolution satellite data and object-based image analysis

Abstract

Agroforestry is gaining increased attention within global policy processes and has been promoted as a strategy for working towards better food security, climate change adaptation and mitigation and livelihood resilience. With this gaining importance of agroforestry, site-specific studies are required to delineate different agroforestry systems and estimate the exact area under agroforestry. In this study remote sensing and GIS techniques were used for the estimation of area under agroforestry using medium-resolution satellite (sentinel 2A and 2B) data. Agroforestry area classification and estimation were done in e-Cognition developer software (10.0 version) through multiresolution segmentation and object-based image analysis (OBIA). The agroforestry area estimated in the erstwhile Warangal district was 3753 ha with an overall accuracy of 86% and a kappa coefficient of 0.84. The major agroforestry systems observed in the erstwhile Warangal district were eucalyptus, subabul, malabar neem, teak, sandalwood and red sanders.