Research on Land Use and Land Cover (LULC) dynamics, and an understanding of the drivers responsible for these changes, are very crucial for modelling future LULC changes and the formulation of sustainable and robust land-management strategies and policy decisions. This study adopted a mixed method consisting of remote sensing and Geographic Information System (GIS)-based analysis, focus-group discussions, key informant interviews, and semi-structured interviews covering 586 households to assess LULC dynamics and associated LULC change drivers across the Dedza district, a central region of Malawi. GIS-based analysis of remotely sensed data revealed that barren land and built-up areas extensively increased at the expense of agricultural and forest land between 1991 and 2015. Analysis of the household-survey results revealed that the perceptions of respondents tended to validate the observed patterns during the remotely sensed data-analysis phase of the research, with 57.3% (n = 586) of the respondents reporting a decline in agricultural land use, and 87.4% (n = 586) observing a decline in forest areas in the district. Furthermore, firewood collection, charcoal production, population growth, and poverty were identified as the key drivers of these observed LULC changes in the study area. Undoubtedly, education has emerged as a significant factor influencing respondents’ perceptions of these drivers of LULC changes. However, unsustainable LULC changes observed in this study have negative implications on rural livelihoods and natural-resource management. Owing to the critical role that LULC dynamics play to rural livelihoods and the ecosystem, this study recommends further research to establish the consequences of these changes. The present study and future research will support decision makers and planners in the design of tenable and coherent land-management strategies.

This paper investigates the multivariate relationships between the soil and vegetation characteristics of plant communities of forest, fallow and cocoa for two reasons. The first is to bringing out the interactions among a set of independent variables and pinpoint the relative importance of each of these variables on a dependent variable be it a soil or a vegetation element. The second is to illustrate the changes that occur to the soil-vegetation properties as the tropical rainforest is cultivated to cocoa and field crops. The processes of choosing the study sites followed a random selection of sample points under three land use types: forest, fallow and cocoa (Theobroma cacao). A total of 300 sample points were selected under each of fallow and cocoa and 260 were selected under the forest. From each sample point soil samples were collected to a depth of 45 cm (i.e. 0-15 cm; 15-45 cm) placed into well-labelled polythene bags and taken to the laboratory for analysis. The results for the forest shows that the canonical variate of the vegetation variables account for 31% of the variance extracted by the soil factors, while the soil variables also account for 31% of the variance extracted by the vegetation variables while the result of the canonical correlation for fallow soil and vegetation extracted for the first and second canonical variates are 0.91 and 0.61 respectively. The result for the canonical correlation coefficients for cocoa for the first and second canonical variates is 0.68 and 0.51 respectively. The study concluded that while simple relationships were observed among soil and vegetation properties in the forest and fallow, complex relationships were recognised in the cocoa plant community.

Cocoa-producing landscapes in southwestern Nigeria are undergoing dramatic changes due to artisanal and small-scale mining (ASM), but there is insufficient knowledge regarding the spatial and temporal aspects of vegetation degradation associated with mining activities. This paper examines land use and vegetation cover changes over the period of 2015 to 2025 in the Ife South Local Government Area of Osun State, Nigeria based on multi-temporal Landsat-8 and Sentinel-2 satellite imagery. It employed supervised support vector machine classification to identify land-cover features, in addition to NDVI, SAVI, and NDRE indices in the assessment of vegetative change. Post classification comparison technique was then used to determine the extent of land-use changes associated with mining activities. The study shows a significant transformation of landscapes in the study region, for example, the open forest cover decreased from 85.62 km² in 2015 to 23.87 km² in 2025, accounting for 72.1% of decline. The barren mining lands increased from 13.37 to 21.46 km², which is about 60.5% of increase. The vegetation indices indicated the decreasing values of vegetation conditions over time: NDVI max value dropped from 0.40 to 0.379, while NDVI minimum: 0.077 and -0.023 correspondingly. The changes in the vegetation index values testify to the gradual transformation of vegetated lands into the lands degraded by mining activity. The paper emphasizes the need for using a combination of satellite imagery techniques and vegetation indices in the studies of mining deteriorated landscapes. The authors conclude that further development of systematic geological monitoring, improvement in environmental regulations, and reclamation after mining would be beneficial for agricultural lands.