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Satellite-Based GIS Evaluation of Land to Scale Agroforestry Restoration Planning in Afghanistan

Firoz Ahmad (), Nazimur Rahman Talukdar, Laxmi Goparaju and Javed Rizvi
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Firoz Ahmad: Vindhyan Ecology and Natural History Foundation
Nazimur Rahman Talukdar: Assam University
Laxmi Goparaju: Vindhyan Ecology and Natural History Foundation
Javed Rizvi: Center for International Forestry Research (CIFOR)- World Agroforestry (ICRAF)

Biophysical Economics and Resource Quality, 2022, vol. 7, issue 3, 1-14

Abstract: Abstract Agroforestry has gained attention because of its diverse roles ranging from direct economic to sustainable environment. The present study is an attempt to understand the land potentiality of Afghanistan to scale agroforestry restoration planning in the country. The potential agroforestry suitable areas were achieved through the Geographical Information System modeling approach. The study found that 13.2% of the geographical area of the country was under agriculture. Approximately, one-fourth of the total geographical area of the country is useful in various diversified agroforestry formats because of the sound agroforestry suitability percent. The total agriculture landscape (1% to 50%) grid was identified as equivalent to 32 million hectares (49% of total geographical area). About 53% of these lands were found medium to very high suitable for agroforestry purposes and the remaining 47% of the agriculture landscape showed low agroforestry suitable percent. The full-scale implementation of an agroforestry restoration blueprint needs adequate funds and appropriate planning at the country level that will serve many of the SDG goals for socioeconomic-stressed Afghan people which will provide them food and nutrient security, livelihood, and eliminate poverty, enhance biodiversity, and mitigate the impact of climate change.

Keywords: Afghanistan; GIS modeling; Land potentiality; Policy & planning (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s41247-022-00104-2

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Handle: RePEc:spr:bioerq:v:7:y:2022:i:3:d:10.1007_s41247-022-00104-2