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Coupling geographic information system integrated fuzzy logic-analytical hierarchy process with global and machine learning based sensitivity analysis for agricultural suitability mapping

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Listed:
  • Talukdar, Swapan
  • Naikoo, Mohd Waseem
  • Mallick, Javed
  • Praveen, Bushra
  • Shahfahad,
  • Sharma, Pritee
  • Islam, Abu Reza Md. Towfiqul
  • Pal, Swades
  • Rahman, Atiqur

Abstract

India's increasing population growth and unsystematic land cover transformation have led to land degradation and a decline in agricultural production. To achieve optimum advantage from the land, proper exploitation of its resources is necessary. Remote sensing, advanced fuzzy logic, and multi-criteria decision-making like analytical hierarchy process (AHP) integrated agricultural land suitability analysis (ALAS) may facilitate identifying and formulating effective agricultural management strategies required for smart agriculture.

Suggested Citation

  • Talukdar, Swapan & Naikoo, Mohd Waseem & Mallick, Javed & Praveen, Bushra & Shahfahad, & Sharma, Pritee & Islam, Abu Reza Md. Towfiqul & Pal, Swades & Rahman, Atiqur, 2022. "Coupling geographic information system integrated fuzzy logic-analytical hierarchy process with global and machine learning based sensitivity analysis for agricultural suitability mapping," Agricultural Systems, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:agisys:v:196:y:2022:i:c:s0308521x21002961
    DOI: 10.1016/j.agsy.2021.103343
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    1. Showmitra Kumar Sarkar & Saifullah Bin Ansar & Khondaker Mohammed Mohiuddin Ekram & Mehedi Hasan Khan & Swapan Talukdar & Mohd Waseem Naikoo & Abu Reza Towfiqul Islam & Atiqur Rahman & Amir Mosavi, 2022. "Developing Robust Flood Susceptibility Model with Small Numbers of Parameters in Highly Fertile Regions of Northwest Bangladesh for Sustainable Flood and Agriculture Management," Sustainability, MDPI, vol. 14(7), pages 1-23, March.

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