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GIS-based land suitability mapping for rubber cultivation in Seremban, Malaysia


Ahmed, Goma Bedawi and Mohamed Shariff, Abdul Rashid and Idrees, Mohammed Oludare and Balasundram, Siva Kumar and Abdullah, Ahmad Fikri (2017) GIS-based land suitability mapping for rubber cultivation in Seremban, Malaysia. International Journal of Applied Engineering Research, 12 (20). 9420 - 9433. ISSN 0973-4562; ESSN: 1087-1090

Abstract / Synopsis

Land suitability evaluation (LSE) is a valuable tool for land use planning in major countries of the world, including Malaysia. Previous LSE studies focused mostly on the use of biophysical and ecological datasets for the design of equally important socio–economic variables. This study presents sub national level estimation of suitable agricultural lands for Rubber crops in Seremban, Malaysia, combining physical, biophysical and ecological variables. The objective of the study was to provide an up–to-date GIS-based agricultural land suitability evaluation (ALSE) for determining suitable agricultural land for Rubber crops in the study area. Biophysical and ecological factors that influence agricultural land use were assembled and the weights of their respective contributions were assessed using analytic hierarchical process. For Rubber cultivation, Lenggeng, Pantai and Setul are the most suitable; while Ampangan, Seremban, Rasah, and Rantau are moderately suitable. Since Seremban, Labu, and Pantai are not suitable for growing rubber. The total suitable land for rubber cultivation in Seremban district is 35575 hectares distributed among the classes as: 16048 hectares is highly suitable, 15399 hectares moderately suitable and 4128 hectares is marginally suitable. These values represent 45%, 43% and 12% respectively Quantitative assessment of the model’s detection accuracy reveals to what extent it is sensitive to suitable and non-suitable land with sensitivity and specificity values of 84.14% and 76% respectively and overall accuracy (area under the ROC curve) of 0.80 (80%) with p-value of <0.0001 at 95% confidence interval.

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Additional Metadata

Item Type: Article
Publisher: Research India Publications
Keywords: Multi criteria; Analytical hierarchy proses; GIS; Rubber
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 11 Mar 2019 11:53
Last Modified: 11 Mar 2019 11:53
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