Implications of land use and land cover change in Mampong municipality, Ghana

ABSTRACT

Understanding and managing land use and land cover (LULC) changes are crucial for addressing environmental challenges, promoting efficient utilization of natural resources, sustainability of environmental and ecological systems for the well-being of both present and future generations. This study was conducted to map the geo-physical features of Mampong municipality to assess the extent of LULC dynamism using Landsat 7 TOA (top-of-atmosphere) image of 2006 and Landsat 8 TOA (top-of-atmosphere) images of 2013 and 2020. Supervised random forest machine learning classification algorithm was applied to classify and examine the dynamics of land use changes in the study area. Markov chain simulation was adopted to examine the magnitude of transition of land cover changes. The results of the study revealed a substantial change in land cover uses in the study area over the period (2006–2020). The trend analysis in area percentage changes indicated that natural forest and deciduous forest land had reduced drastically mainly for the purpose of agriculture production and build-ups for human settlement as revealed by the negative change or reduction in typical biodiversity hotspot reservations: natural forest (−22.71%), deciduous forest (−26.74%) and water bodies (−32.11%) with a positive change in components such as built-up area (29.11%), barren land (4.96) and agriculture (37.91) in the study area. The study, however, revealed serious trend in water bodies extinction within the municipality as indicated by the dynamic change analysis results, suggesting that 7.86 km² area that was originally under water pathways have been converted for human settlement and 0.76 km² of agriculture lands are exposed to erosion (barren land). A Markov chain simulation prediction of the transition for the year 2032 revealed a positive probability increasing rate in urban and surface build-up and agriculture at a rate of 2.33% and 1.69%, respectively, with substantive reduction in natural biodiversity resources in future given the present scenario. Given the dynamics of LULC changes, we recommend that major stakeholders including environmental protection agency, forest guides, Ghana water company and municipal assembly authorities should develop feasibility holistic preventive measures that seek to ensure effective and efficient utilization of resources and promote the livelihood of individuals who depend on these resources for survival.

KEYWORDS:

• Remote sensing data
• Markov chain simulation
• land use change and land cover changes
• supervised random forest algorithm

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

All the authors contributed by conceiving, designing the research, analyzing the data, and critically reviewed and approved the final version of the manuscript.

Data availability statement

Data used for this work is a public data that was downloaded from GEE. Landsat 5 TM⁺ image period of 2006 and Landsat 8 TOA (top-of-atmosphere) satellite image for the period 2013–2020. Code for data extraction was obtained through the link https://code.earthengine.google.com/. R-codes for data collection, processing and analysis are available on request.