The integration of digital technologies into agroforestry offers transformative potential for sustainable tree-based farming. Digital agroforestry leverages tools such as Geographic Information Systems (GIS), unmanned aerial vehicles (UAVs or drones) and computer-based decision support systems (DSS) to enhance planning, monitoring and management of tree-crop-livestock systems. GIS allows spatial mapping of soil, climate and land-use variables to identify suitable sites and optimize farm design. UAVs provide ultra-high-resolution aerial data (centimetre-scale) for tree inventory, species identification and stress detection. Data from sensors and remote sensing feeds into DSS that integrate ecological, socio-economic and field data to generate context-specific recommendations. Together, these technologies enable precision agroforestry: for example, mapping 90% of croplands in Odisha, India, as suitable for bund plantations or intercropping
and detecting irrigation needs in olive orchards via drone-based NDVI in Tunisia
. Digital agroforestry supports climate resilience by improving resource efficiency (e.g. targeted irrigation/fertilization
) and enhancing ecosystem services (carbon sequestration, erosion control). However, adoption faces challenges: high upfront costs, data management, connectivity gaps and user training needs
. To realize its promise, policies must promote infrastructure (e.g. rural IoT, broadband), capacity building and interoperable platforms. Future research should focus on AI-driven analytics (digital farm “twins”
), integration of upcoming satellite missions (GEDI, NISAR) and participatory DSS design. This review synthesizes global and Indian case studies and technical foundations, showing how GIS, drones and DSS collectively advance agroforestry. It highlights both opportunities (precision management, sustainability gains) and challenges (infrastructure, data) for implementing climate-smart, tree-based farming.
