Mapping GIS-based agroforestry land potentiality in Sunamganj, Bangladesh

Rapid climate change has increasingly disrupted agricultural systems and livelihoods in vulnerable regions like the Haor areas of northeastern Bangladesh. This study aims to assess the land suitability for agroforestry in the Sunamganj district, a region frequently impacted by flash floods. Agroforestry offers multifaceted benefits, including improved food security, income diversification, ecosystem services, and alignment with Sustainable Development Goals (SDGs). Using GIS and remote sensing technologies, a multi-criteria analysis (MCA) was followed, prioritizing climatic (annual temperature and rainfall), topographical (slope, elevation), soil (general type, texture, reaction, nutrient status, inundation type), and ecological parameters (LULC and NDVI). The study integrated 30m resolution Landsat OLI imagery, ASTER DEM, WorldClim climate data, and national soil and land use datasets. Results show that 34% of the land in Sunamganj is highly suitable (clustered in uplands), 53% is moderately suitable, and 13% is least suitable (adjacent to rivers) for agroforestry development. The district exhibits optimal climatic conditions, soil, and ecological factors contributing to a sustainable land use system in the Haor area. However, low elevation zones and flood-prone areas constrain agroforestry expansion. This research presents the importance of site-specific planning in enhancing agroforestry adoption. This is the first GIS-based agroforestry suitability mapping in Sunamganj or the Haor region. The framework used in the study could be useful for policymakers, practitioners, and local stakeholders aiming to build resilient, sustainable agroecosystems in Bangladesh's flood-prone Haor region.