Integrated GIS and AHP techniques for land suitability assessment of cotton crop in Perambalur District, South India

Subbarayan Sathiyamurthi (), Subbarayan Saravanan (), Ramanarayan Sankriti (), Manjunath Aluru (), Sankaralingam Sivaranjani () and Ravi Srivel ()
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Subbarayan Sathiyamurthi: Faculty of Agriculture, Annamalai University
Subbarayan Saravanan: National Institute of Technology
Ramanarayan Sankriti: National Institute of Technology
Manjunath Aluru: MVSR Engineering College
Sankaralingam Sivaranjani: Bharathidasan University
Ravi Srivel: Adhiparasakthi Engineering College

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 1, No 24, 267-278

Abstract: Abstract The paper under consideration addresses a combined holistic approach to analyze the process of agricultural land suitability using the structured combination consisting of multicriteria decision analysis technique together with geographical information systems (GIS) methods. Identifying suitable cropland is one of the challenging problems is to improve agricultural land management for efficient use of land resources. Integrating analytical hierarchy process alongside GIS provides additional pliable and precise decisions into the decision-making bodies, that are focused on the evaluation of the effective factors. The connected bio-physical variables related to soil and topographical parameters have been taken into consideration for suitability analysis. The specific objective in this study is to prepare a suitability map concerning cotton (Gossypium hirsutum L.) cultivability with a basis on physico-climatic related factors that are considered suitable for production along with identification of the potential areas for expansion and optimization of the production in the Perambalur district of Tamilnadu. The analysis revealed that in the study area, 19.768% (345.2463 km2) of total cropland is highly suitable, 30% (524 km2), 16.7% (292 km2) of the total area were moderately, marginally suitable areas respectively and 9.39% (164 km2) was under not suitable areas.

Keywords: AHP; Cotton crop; Geographic information system; Land suitability analysis; MCDA (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-022-01705-2

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