Application of remote sensing data in property valuation: case study: Kampala

Abstract

Traditional property valuation techniques, typically dependent on physical site inspections, encounter difficulties including accessibility constraints, safety hazards, and time inefficiencies, resulting in possible errors and delays. Although RS data holds significant promise for providing high-resolution, objective, and current property insights remotely, its utilization in the property valuation sector remains insufficiently investigated. This study investigated the application of Remote Sensing data in property value, specifically identifying several methods for integrating it and establishing the best practices for its implementation. The research utilized a cross-sectional survey methodology. Data was gathered from valuation and real estate specialists in Uganda through semi-structured interviews; high-resolution satellite data for 2019 and 2025 was also acquired from the Kampala Capital City Authority. The findings indicated that Remote Sensing data serves a supportive yet progressively significant role in contemporary property appraisal. It is typically utilized to augment fieldcollected data and can serve for change detection, attribute extraction, and as visualization tools in valuation reports. The results indicate that best practices include ensuring data accuracy, precision, and correctness; safeguarding confidentiality and privacy; employing ethical and transparent data usage; maintaining integrity in data sourcing and referencing; and carrying out rigorous data verification and ground truthing as essential. The study advocated for additional research into the error margin linked to remote sensing data measurements, a comprehensive assessment of user requirements for institutions engaged in remote sensing data acquisition and distribution, and an analysis of the integration of remote sensing technology into current survey regulations pertaining to property valuation in Uganda. This corresponds with the growing need for effective valuation techniques in rapidly urbanizing areas and endorses a transition towards data-driven, remote, and automated methodologies.