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Agroforestry suitability mapping of India: geospatial approach based on FAO guidelines

  • Firoz Ahmad
  • Md Meraj Uddin
  • Laxmi Goparaju
Article

Abstract

Agroforestry system has the enormous capacity to achieve social, economic, and environmental goals by optimizing land productivity. The aim of the present study was to evaluate the land potentiality in India for agroforestry based on FAO land suitability criteria utilizing various land, soil, climate, and topographic themes. This was achieved in GIS Domain by integrating various thematic layers scientifically. The analysis of land potentiality in India for agroforestry suitability reveals 32.8% as highly suitable (S1), 40.4% moderately suitable (S2), 11.7% marginally suitable (S3), and 9.1% not suitable (NS). About 52% of land of India is under the cropland category. In addition, it revealed that the 46% of these cropland areas fall into high agroforestry suitable category “S1,” and provide huge opportunity for harnessing agroforestry practices. Furthermore, agroforestry suitability mapping in broad ecosystem and in different agroecological regions will assist various projects in India at the regional level. Such results will also boost the various objectives of the National Agroforestry Policy (2014, http://www.cafri.res.in/NAF_Policy.pdf) and policymakers of India where they need to extend it. The potential of geospatial technology can be exploited in the field of agroforestry for the benefit of rural poor people/farmers by ensuring food and ecological security, resilience in livelihoods, and can sustain extreme weather events such as droughts and climate change impact. Such type of research can be replicated in India at village level (local level) to state level (regional level) utilizing the significant themes which affect the agroforestry suitability. This will certainly fetch better results on ground and will significantly assist the management programs.

Keywords

Agroforestry FAO GIS Land suitability Harmonized World Soil Database India 

Notes

Acknowledgements

The authors are grateful to the USGS, Food and Agriculture Organization of the United Nations (FAO), and the International Institute for Applied Systems Analysis (IIASA), the WorldClim-Global Climate Data, the European Commission’s science and knowledge service, and DIVA GIS for allowing free downloads of various datasets used in the analysis.

Funding

No funding in any form has been received by any of the authors for the current work.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Vindhyan Ecology and Natural History FoundationMirzapurIndia
  2. 2.University Department of Mathematics, MCARanchi UniversityRanchiIndia

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