Land suitability modeling for newly reclaimed area using GIS-based multi-criteria decision analysis

Area of Science:

• Agricultural Science
• Environmental Science
• Geographic Information Systems (GIS)

Background:

• Sustainable development hinges on appropriate land-use planning.
• Conventional methods for evaluating land suitability in newly reclaimed areas often yield contradictory results.
• Accurate land suitability assessment is crucial for optimizing agricultural productivity, especially for staple crops like wheat.

Purpose of the Study:

• To develop and validate a novel spatial model for assessing land suitability for wheat cultivation.
• To overcome limitations and contradictions associated with conventional land suitability evaluation methods.
• To enhance the accuracy and reliability of land suitability assessments in newly reclaimed agricultural lands.

Main Methods:

• Development of a spatial model integrating modeling techniques with geographic information systems-based multi-criteria decision analysis (GIS-MCDA).
• Application of two approaches: the proposed GIS-MCDA model and the conventional parametric (square root) method.
• Validation of the proposed model by comparing its estimated wheat yield with actual yield data using correlation coefficients.

Main Results:

• The proposed GIS-MCDA model classified 20.5% of the study area as highly suitable and 61.5% as moderately suitable for wheat.
• In contrast, the square root method classified 75.0% of the area as not suitable.
• The proposed model demonstrated a strong correlation (r = 0.95) with actual wheat yield, significantly outperforming the square root method (r = 0.46).

Conclusions:

• The integrated GIS-MCDA spatial model provides a more accurate and reliable method for assessing land suitability for wheat in newly reclaimed areas.
• The proposed model effectively addresses the contradictions found in conventional land evaluation techniques.
• This approach offers a flexible and effective tool for improving land-use planning and sustainable agricultural development.