Full Text

Turn on search term navigation

© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

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.

Details

Title
Characterization and Mapping of the Potential Area of Oil Palm Using Multi-Criteria Decision Analysis in a Geographic Information Systems Environment
Author
Kamireddy Manorama 1 ; Obi Reddy, G P 2 ; Suresh, K 1 ; Ray, S S 3 ; Behera, S K 4 ; Kumar, Nirmal 2 ; Mathur, R K 5 

 ICAR-Indian Institute of Oil Palm Research, Pedavegi 534450, Andhra Pradesh, India 
 ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur 440033, Maharashtra, India 
 ISRO-Mahalanobis National Crop Forecasting Centre, New Delhi 110012, India 
 ICAR-Indian Institute of Soil Science, Bhopal 462038, Madhya Pradesh, India 
 Institute of Oil Seeds Research, Hyderabad 500300, Telangana State, India 
First page
986
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
20770472
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3084713709
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.