Characterization and Mapping of the Potential Area of Oil Palm Using Multi-Criteria Decision Analysis in a Geographic Information Systems Environment

Kamireddy Manorama (), G. P. Obi Reddy, K. Suresh, S. S. Ray, S. K. Behera, Nirmal Kumar and R. K. Mathur
Additional contact information
Kamireddy Manorama: ICAR-Indian Institute of Oil Palm Research, Pedavegi 534450, Andhra Pradesh, India
G. P. Obi Reddy: ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur 440033, Maharashtra, India
K. Suresh: ICAR-Indian Institute of Oil Palm Research, Pedavegi 534450, Andhra Pradesh, India
S. S. Ray: ISRO-Mahalanobis National Crop Forecasting Centre, New Delhi 110012, India
S. K. Behera: ICAR-Indian Institute of Soil Science, Bhopal 462038, Madhya Pradesh, India
Nirmal Kumar: ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur 440033, Maharashtra, India
R. K. Mathur: Institute of Oil Seeds Research, Hyderabad 500300, Telangana State, India

Agriculture, 2024, vol. 14, issue 7, 1-18

Abstract: This study presents a GIS-based Multi-Criteria Decision Analysis (MCDA) spatial model to assess land suitability for oil palm (OP) cultivation in rainfed conditions. Initially, twelve parameters, viz., rainfall, number of rainy days, mean temperature, RH, ground water level, soil pH, salinity, soil depth, surface texture, stoniness, slope, and drainage, were selected for assessing OP suitability in one of the states (Kerala). However, subsequent ground verification revealed significant discrepancies, which prompted refining the model by focusing on key parameters with greater accuracy and relevance. Accordingly, only five the most critical parameters affecting OP cultivation under rainfed conditions were selected through the rank sum method, and weights were assigned ac-cording to their significance. This study was aimed at creating a comprehensive tool for informed decision making in agricultural planning. District-level spatial data from reliable sources were utilized for Multi-Criteria Decision Analysis. Thematic rasters, representing key factors influencing land suitability, were created in a GIS. Utilizing MCDA techniques, a digital suitability map was generated in ArcGIS 10.3, delineating three distinct classes over an extensive area of 10.5 million hectares. Further, with an aim to focus on actual locations that can be readily planted with oil palm, the suitable locations identified were restricted to eight selected land use/land cover (LULC) classes. This strategic limitation aimed to facilitate the expansion of OP cultivation exclusively to areas deemed most suitable based on the identified criteria. The validation of this developed model involved comparing the suitability map generated with the performance of existing oil palm plantations across diverse locations. The reasonable similarity between the model’s predictions and real-world plantation outcomes validated the effectiveness of this MCDA spatial model. This model not only helps identify suitable locations for rainfed oil palm cultivation but also serves as a valuable tool for strategic decision making in agricultural land use planning.

Keywords: GIS-based; multic-criteria decision analysis (MCDA); thematic rasters; land use/land cover (LULC) classes; validation (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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