Geospatial-Based Land Grading System Development for Enhanced Property Valuation: A Case Study of Adama City, Ethiopia

Abstract

The integration of Geographic Information Systems (GIS) into land grading and property valuation processes has gained increasing attention in recent years, driven by advancements in technology and a growing recognition of the importance of spatial data in decision-making. This study aims the integration of geospatial-based land grading systems into property valuation processes in Adama City, Ethiopia. As the city experiences rapid urbanization, accurate property valuation has become crucial for effective urban planning, real estate development, and policymaking. Traditional property valuation methods in Adama have often lacked standardized and data-driven approaches, leading to inconsistencies and inefficiencies. This research employs AHP based Geographic Information Systems (GIS) and remote sensing technologies to develop a land grading system that incorporates the data such as topography, soil quality, infrastructure accessibility, and land use patterns. By analyzing geospatial data, the study creates a grading system that classifies land into categories as "first/G1/," "second/G2/," "third/G3/," "fourth/G4/," and fifith/G5/ grades based on factors influencing land quality and value. The study employs statistical and spatial analysis to assess the relationship between land grades and property prices, demonstrating how geospatial data can enhance valuation accuracy. The results indicate that the overlay analysis of these parameters revealed that G1 grade covers approximately 1,052,807.11 square meters, G2 covers 24,041,834.56 square meters, G3 encompasses 76,736,869.52 square meters, G4 spans 132,334,640.94 square meters, and G5 totals 9,686,237.43 square meters. The findings provide recommendations for integrating this system into land valuation practices in Adama City and other rapidly urbanizing regions of Ethiopia, offering a scalable framework for enhancing land management and urban development strategies.