Modeling the Rice Land Suitability Using GIS and Multi-Criteria Decision Analysis Approach in Sindh, Pakistan


 Suitability map, Factor, Constraint, AHP, Pair-Wise Comparison Matrix, Principal Eigen vector, MCE, Weighted Linear Combination, Overlay, Area, Production, ArcGIS, Erdas Imagine, Idrisi Selva.

How to Cite

Anila Naz, & Haroon Rasheed. (2017). Modeling the Rice Land Suitability Using GIS and Multi-Criteria Decision Analysis Approach in Sindh, Pakistan. Journal of Basic & Applied Sciences, 13, 26–33.


The objective of this research was to evaluate rice land suitability in Sindh, Pakistan, by designing GIS-based Multi-Criteria Decision Analysis (MCDA) spatial model to aggregate interdisciplinary aspects including factors of soil physical and chemical properties, ground water quality, soil pH, agro-ecological zones, canal command area and temperature. A constraint map of water bodies was also utilized in this model. On the basis of these parameters,standardized raster maps were created, and then Pair-Wise Comparison Matrix (PWCM) of Analytical Hierarchy Process (AHP) was developed to calculate significant weights by means of Principal Eigen vector by Saaty’s method, with accepted Consistency Ratio (CR) of 0.10. Furthermore, Multi-Criteria Evaluation (MCE) employing Weighted Linear Combination (WLC) aggregated all the suitability maps to yield rice land suitability map. Final output map of this work demonstrated 30.2% increase in area suitable for rice cultivation with an increased production of 14,716,592.17 tonnes as compared to existing rice practices in Sindh. This increase in the area and production of the potential land shows the capability of our novel model and offers an opportunity to improve cultivation by providing the much required information at local level that could benefit farmers, vision scientists and decision makers to select appropriate cropping site and agricultural planning making the best use of available data.


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Copyright (c) 2017 Anila Naz , Haroon Rasheed