Geo-space monitoring technology and gis based predictive modeling of land use/land cover dynamics

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Research Paper 19/06/2026
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Geo-space monitoring technology and gis based predictive modeling of land use/land cover dynamics

E. Ahuchaogu Udo*, U. Duru Uchenna, E. Njoku Richard, G. Ogbonna Chukwuemeka, C. Okoboji Anthony, E. F. Onyeagoro
J. Biodiv. & Environ. Sci. 28(6), 202-213, June 2026.
Copyright Statement: Copyright 2026; The Author(s).
License: CC BY-NC 4.0

Abstract

Adequate geographic information of natural resources is required for environmental management and sustenance. Therefore, the aim of this study is to investigate the trend of land use/land cover dynamics in Owerri North and predict future trend for planning by integrating data captured using space monitoring technology with geographic information system (GIS). Data used include Landsat satellite imagery of five (5) epochs. The dataset has been pre-processed and enhanced using ERDAS Imagine and exported to ArcGIS10.5 window. Progressively, a training file was created which assisted in clustering the dataset into four feature classes. Evaluation of classification accuracy was made using confusion matrix before change detection analysis. Least square regression analysis was utilized to develop predictive models which were used to predict future trend of the feature classes that showed significant spatial variation between the epochs. Result revealed that between 1980 and 2020, water bodies and sparse vegetation spaces increased and decreased respectively by 3.95% and 5.42% while thick vegetation and built-up areas decreased and increased respectively by 26.86% and 28.31% and is the major causes of environmental degradations in the study area. This study predicted that beyond 2070 thick vegetation may be in extinction due to urban expansion, and this is of grave consequences to environmental sustainability.

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