Change Detection Study of Abuja Municipal Area Council Abuja, Federal Capital Territory Nigeria Between 2002 And 2023

Izuegbu Ogochukwu Uju, Dalhatu Umaru Sangari and Sunday Yusuf Kpalo
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Izuegbu Ogochukwu Uju: Office of the Surveyor General of the Federation (OSGoF), Headquarters Abuja-FCT, Nigeria
Dalhatu Umaru Sangari: Department of Geography, Nasarawa State University, Keffi, Nigeria
Sunday Yusuf Kpalo: Department of Geography, Nasarawa State University, Keffi, Nigeria

International Journal of Research and Innovation in Social Science, 2025, vol. 9, issue 3, 4969-4979

Abstract: Change detection is the process of identifying differences in the state of a feature or phenomenon by observing it at different times (Singh, 1989). In the course of urban development, changes have significantly occurred in the study area. This study was conducted in order to determine the land use and land cover changes (as well as the type of changes and their direction) occurring in the use of land in the Abuja Municipal Area Council, Abuja Federal Capital Territory for the period 2002-2023. Remote Sensing (RS) and Geographic Information System (GIS) techniques were used for the detailed derivation of the land use and land cover classes and the changes that occurred between them. Landsat satellite imageries; Enhanced Thematic mapper plus (ETM+) of 2002 and Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) of 2023 were used to carry out supervised image classification using maximum likelihood algorithm in Erdas Imagine software environment. The Imagery used covered a span of 21 years. The classification results were used to carry out the change detection analysis using change detection work flow algorithm in ENVI 5.0 software environment. The results shows that the area where no changed occurred accounted for 27.031% of total area changes of the Land Use Land Cover classes, from built-up area to vegetation accounted 0.05%, from built-up area to bare land accounted for 0.56 %, from waterbody area to built-up area accounted for 0.03 %, from vegetation area to built-up area accounted for 28.3%, from vegetation area to bare land area accounted for 3.67 %, from bare land area to built-up area accounted for 38.93% and the area of change from bare land area to vegetation accounted for 1.39%. Change Detection Studies are crucial for understanding environmental changes and making informed decisions, successful planning and urban management.

Date: 2025
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