article · Geocarto International
Predictive modelling using the CA-Markov model in Terrset software examines land use and land cover dynamics for 2038 and 2054 in the Vea catchment, Ghana. The analysis reveals an ongoing expansion of cropland, projected to increase from 181 square kilometres in 2038 to 183 square kilometres in 2054. This agricultural growth occurs primarily at the expense of natural habitats, with grassland projected to decrease from 51 to 50 square kilometres and mixed vegetation or forest projected to decline from 73 to 71 square kilometres. Driven predominantly by population growth and agricultural expansion, identified through the Relative Importance Index, these rising anthropogenic land uses are projected to diminish irrigation water availability and threaten landscape sustainability. The findings deliver critical baseline projections to guide responsible land planning, water governance, and resource management across the catchment area.
Expanding agriculture driven by population growth reduces natural vegetation cover and directly threatens regional water supplies. Understanding projected land use shifts helps planners and communities balance food production with water conservation. This foresight is critical for ensuring reliable irrigation access, avoiding resource depletion, and maintaining ecological stability in vulnerable river basins.
This work demonstrates early-stage predictive modelling that can inform environmental monitoring systems, spatial planning tools, and water allocation programmes. The primary users are regional water managers, agricultural planning authorities, and environmental governance bodies balancing land and water resources. The research remains at an applied modelling stage, providing predictive datasets rather than a direct commercial product, but it offers a functional basis for catchment-scale decision-support tools.
AI-generated from the published abstract. Always read the original work before citing.
Assessment and prediction of land use/land cover change using spatiotemporal data are of great importance for better environmental monitoring, land use planning, and management. Therefore, the objective of this study is to predict LULC change and its driving factors and impact on water availability for irrigation in the Vea catchment, Ghana. CA-Markov model was used to predict land-use changes in 2038 and 2054. Terrset geospatial monitoring and modeling system software was used to run the model. The Relative Importance Index was used to identify major drivers of the LULC change. The results showed an increase in cropland from 181 km2 in 2038 to 183 km2 in 2054 at the expense of grassland and mixed vegetation/forest, which are expected to decrease from 51-50 km2 and 73-71 km2, respectively. Population growth and agricultural expansion are among the leading drivers of LULC change in the Vea catchment. The CA-Markov model shows a continued increase in anthropogenic land uses, negatively affecting irrigation water availability and landscape sustainability. These results provide a foundation for sustainable land use governance through responsible planning and management of land and water resources by considering trade-offs between LULC change and water availability for irrigation in the Vea catchment.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1080/10106049.2023.2243093
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
