Agroforestry Area Mapping using Medium Resolution Satellite Data and Object-based Image Analysis

Background: The current view of agroforestry is not as a collection of technologies, but of trees included in agricultural landscapes. India’s sub-national climate change action plans acknowledge agroforestry’s potential for climate change adaptation and mitigation. Understanding the extent and distribution of trees on agricultural land, at the landscape level, including the numbers and characteristics of farmers and farming communities within those landscapes, can help to assess the importance and role of agroforestry both to the climate change mitigation as well as to overall global agricultural production. With this perspective of agroforestry, site specific studies are required to delineate different agroforestry systems and estimation of exact area under agroforestry. Methods: In this study, the area under agroforestry was estimated by using remote sensing and GIS techniques with medium resolution satellite (Sentinel 2A and 2B) data in e-Cognition developer software (10.0 version) through multi-resolution segmentation and object-based image analysis (OBIA). Result: The agroforestry area was estimated in erstwhile Khammam district of Telangana, India, which is 30,038 ha covering 1.87% of the total district geographical area (16,02,900 ha) with an overall accuracy of 81.5%. The major agroforestry systems observed in erstwhile Khammam district were Eucalyptus, Subabul, Malabar Neem, Teak, Sandalwood and Red Sanders. Agroforestry gained momentum after adopting the National Agroforestry Policy (NAP) in 2014, which aimed to organize the sector and reform any legislative barriers. This area estimation is useful to policy makers as there is only rough estimates of agroforestry area unlike agricultural area.