Mapping Land Suitability for Sugarcane Crop with Fuzzy AHP and Multi-Criteria Evaluation

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P. Pipatsitee
S. Ninsawat
N.K. Triapthti
M. Shanmugam
J. Som-ard

Abstract

Mapping land suitability is crucial for identifying appropriate land use for site selection and land-use planning. However, climate changes exacerbate water shortages and droughts, significantly affecting land suitability and resulting in crop yield losses. Therefore, it is important to consider drought conditions in land suitability evaluations by incorporating evapotranspiration to reflect the water balance and mitigate the climate change impacts. This study aimed to map the sugarcane land suitability in Northeastern Thailand using Global Navigation Satellite System-based Precipitable Water Vapor (GNSS-PWV), fuzzy AHP and multi-criteria evaluation. Six significant criteria were selected for sugarcane land suitability mapping: the ETDI as drought index, slope, soil texture, distance from the river, distance from the road and distance from the sugar mill. Land suitability for sugarcane cultivation was evaluated by integrating the fuzzy AHP and multiple criteria evaluation. The results indicated that ETDI and distance from river were the most influential factors, with average weights of 0.66 and 0.34, respectively. Suitable areas for sugarcane were mostly found in the moderately suitable class (S2; 49.6%), followed by the marginally suitable class (S3; 36.0%) and the highly suitable class (S1; 11.2%). Actual sugarcane cultivation areas were mainly distributed in the S3 class (49.0%), followed by 43.2% in the S2 class and 6.7% in the S1 class. The S2 class areas could be enhanced to the S1 class by implementing irrigation systems and establishing small ponds to reduce the risk of drought, potentially expanding S1 class areas by 2.7 times and increasing yields by approximately 1.1 tons/ha. Potential areas within the S1 class were 6,519 km2 with Nakhon Ratchasima province having the greatest potential areas (35%). Further research on a larger scale, covering the entire country, is necessary to improve the accuracy of the land suitability map in addressing the challenges posed by global climate change

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How to Cite
Pipatsitee, P., Ninsawat, S., Triapthti, N., Shanmugam, M., & Som-ard, J. (2024). Mapping Land Suitability for Sugarcane Crop with Fuzzy AHP and Multi-Criteria Evaluation. International Journal of Geoinformatics, 21(1), 56–71. https://doi.org/10.52939/ijg.v21i1.3793
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