Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/29537
Title: Determination of Land Suitability for Oil Palm with Multi-dimension Decision Support Using Analytic Network Process (ANP) in Southern Thailand
Authors: Arunplod C.
Witayangkurn A.
Kongtong D.
Keywords: ANP
GIS
MCDM
Multi-dimension criteria
Oil palm
Issue Date: 2023
Publisher: Springer Science and Business Media Deutschland GmbH
Abstract: Oil palm is one of the most important economic crops in Thailand. It contributes to the product in variety like petrol, cosmetics, consumer products, etc. The main problem for plantation oil palm plantation is improper land for plantation. Therefore, it results in fluctuations in reduction of quality and production quantity. The main objective of this study is to assess the land suitability for oil palm using multi-dimension criteria in Surat Thani and Krabi provinces, in Southern Thailand, through the analytic network process (ANP) integrated with geographic information system (GIS). The study was carried out with 28 layers grouped into six main criteria: topography, climate, physical soil, chemical soil, disaster events, and socioeconomic factors. All 28 criteria layers are weighted based on expert opinions according to the ANP method. The ANP disclosed that the rainfall is the most affecting criteria for oil palm plantation; the highest weight score is 0.112. Results from this study reveal two climate conditions: (1) land suitability for oil palm plantation based on 1-year climate data, a very highly suitable class is 273.6 km2 (1.5%), and (2) oil palm suitability based on 5-year accumulated data, a very highly suitable class is 388.9 km2 (2.2%). The suitable difference areas are affected by the variable rainfall and dry season conditions relating to the climate change situation at the local scale. Finally, this study developed an effective decision tool for local farmers to manage their plantations with multi-dimensions to sustain the quality and quantity of oil palm yield. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144008668&doi=10.1007%2f978-3-031-16217-6_17&partnerID=40&md5=994620ca61ab86d416c939875808b8f2
https://ir.swu.ac.th/jspui/handle/123456789/29537
Appears in Collections:Scopus 2023

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