Abstract
Trees are an integral part of the sustainable farming practices that can withstand extreme weather events, pest risks, and optimize land and water productivity to achieve food, fuel, fodder and nutritional security while safeguarding the environmental flows. This study was undertaken to analyze the landscape potential for the South Asian region in the geospatial domain utilizing the FAO’s land suitability criteria. The key datasets were derived from satellite remote sensing at a global and regional scale for land, soil, climate, and topography and were used to model the agroforestry suitability across South Asia. Furthermore, the agroforestry suitability categories and tree cover dominance were investigated with respect to the total geographical area, agriculture land cover and with climate variables to understand the present and future trends. The comprehensive analysis revealed that 69% of the total geographical area retains 55% and greater suitability for agroforestry. The analysis revealed that nearly 73.4% of the landscape is absent (0%) of tree cover, 7.1%, shows 1–10% and 19.5% area having more than 10% tree cover. The tree dominance/hotspot analyses in the agriculture land were found notably high in the multiple farming components such as home gardens. The single crop of irrigated and rain-fed croplands showed high land suitability towards agroforestry. Such land can be utilized to enhance the tree cover that suits locally as per the farmer's need based on a community-driven participatory approach to bring the sustainability and resilience in degraded landscapes (FAO in Agroforestry for landscape restoration, 2017). The future climate data analysis showed a significant change in the distribution of temperature and precipitation that will influence future farming practices in South Asia. The agroforestry suitability and tree cover mapping results/analysis will assist crucially the agroforestry policymakers/planners in the various South Asian countries to implement and extend it to the new area. The analysis clearly shows that the advent of big data, remote sensing and GIS provide insights into the agroforestry interventions and scaling which further helps in building resilient landscapes for sustainable agri-food systems, livelihoods, safeguarding the environmental security and supporting some of the important sustainable development goals (SDGs).
Highlights
The United Nations has set 17 Sustainable Development Goals (SDGs) to be achieved over the one and a halfdecade for the betterment of society while maintaining the landscape potentiality
Agroforestry got adequate focus in the world due to the global effort in the research and development. They addressed the issues in an integrated approach of the most crucial land-management goals and highlighted that one billion of agriculture land retain more than 10% tree cover, still several categories of land use/land cover globally have the capacity and can be utilized under various agroforestry practices (Nair and Garrity 2012)
The northwest parts of the South Asian region are mostly having less than 25% agroforestry suitability categories due to low soil fertility, low precipitation and dry environment
Summary
The United Nations has set 17 Sustainable Development Goals (SDGs) to be achieved over the one and a halfdecade for the betterment of society while maintaining the landscape potentiality. The agroforestry directly or indirectly can contribute significantly to some of the most challenging goals such as SDG 1 for ending poverty, SDG 2 for mitigating hunger/ achieve food security/improved nutrition/promote sustainable agriculture, SDG 3 for healthy lives and promote wellbeing, SDG 5 for women and girls’ empowerment, SDG 6 to SDG 7 for clean water and affordable clean energy, SDG 13 for mitigating the climate change and its impacts, SDG 15 for sustainable forestry and restoration of degraded land and lt biodiversity loss (Mbow et al 2014; Waldron et al 2017; Montagnini and Metzel 2017) Such goals can be achieved on the existing land-use systems with appropriate strategies by orienting higher levels of integration of financial and human resources, policy/institutional space within the existing frameworks and when modeled from national/global to local development planning (Noordwijk et al 2018). We have investigated a few layers using GIS complex Query to understand the multidimensional relationship among them
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: KN - Journal of Cartography and Geographic Information
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
