Land cover change in marginalised landscapes of South Africa (1984–2014): Insights into the influence of socio-economic and political factors (original) (raw)
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The South African land reform policy under the democratic government (after 1994) was designed to redress the inequality of land ownership aiming to reverse the land ownership injustice that had occurred in the past era as a deliberate act of policy by the colonial and the apartheid government. This study aimed at investigating the effects of the South African land reform policy on land use and land cover change on a land restitution project in Makotopong, Limpopo province, South Africa. To determine land cover dynamics, 1994 and 2007 Landsat images were used. A maximum likelihood classification for each image was computed for identification of land cover variables. Trends in land cover change depict a decline in post-transfer activities with agricultural cropland decreasing from 78.04 ha in 1994 to 20.43 ha in 2007. Inadvertently, land under fallow and shrubs increased by 6% and 30%, respectively. This accelerated decline of agricultural activity is mainly attributable to change of land ownership and management skills from the commercial farmers to the inexperienced land claimants. Results suggest that quantification of the changes in land use and land cover types can be very useful in assessing environmental and social condition of the land reform project. The study recommends that spatial data analysis through remote sensing procedures should form the information base in monitoring and evaluating the land reform projects to ensure productivity and management.
Exploring the significance of land-cover change in South Africa
South African Journal of Science, 2012
Changing land cover is a phenomenon that is growing in magnitude and significance, both globally 1 and in South Africa 2. Changes in land cover include the conversion of natural vegetation to agricultural crops and forest plantations, changes to natural vegetation through bush encroachment and overgrazing, soil erosion, invasion by alien plant species, and accelerating urbanisation. Land-cover changes increasingly relate to climate and atmospheric changes in ways that are currently poorly understood but potentially significant, especially in terms of compromising or enhancing the delivery of vital ecosystem services from rangelands, agricultural croplands, water catchments and conservation areas.
Environmental Monitoring and Assessment
In semi-arid regions, interactions between biophysical and socio-economic variables are complex. Such interactions and their respective variables significantly alter land use and land cover, degrade landscape’s structure, and impede the efficacy of the adopted land management interventions. This scenario is particularly prevalent in communal land tenure system or areas managed by a hybrid of traditional and state led institutions. Hence, this study sought to investigate the impacts of land use and land cover changes (LULCCs) on land degradation (LD) under communal rural districts, and the key drivers of habitat fragmentation in the Greater Sekhukhune District Municipality (GSDM), South Africa. The study used the wet and dry season multi-temporal remotely sensed image data, key-informant interviews, and workshop with tribal council to determine the major drivers of LULCC and LD. Results revealed that mines and quarries, subsistence and commercial cultivation, and thicket/dense bush L...
Geosciences, 2017
Land cover change analysis was performed for three catchments in the rural Eastern Cape, South Africa, for two time steps (2000 and 2014), to characterize landscape conversion trajectories for sustained landscape health. Land cover maps were derived: (1) from existing data (2000); and (2) through object-based image analysis (2014) of Landsat 8 imagery. Land cover change analysis was facilitated using land cover labels developed to identify landscape change trajectories. Land cover labels assigned to each intersection of the land cover maps at the two time steps provide a thematic representation of the spatial distribution of change. While land use patterns are characterized by high persistence (77%), the expansion of urban areas and agriculture has occurred predominantly at the expense of grassland. The persistence and intensification of natural or invaded wooded areas were identified as a degradation gradient within the landscape, which amounted to almost 10% of the study area. The challenge remains to determine significant signals in the landscape that are not artefacts of error in the underlying input data or scale of analysis. Systematic change analysis and accurate uncertainty reporting can potentially address these issues to produce authentic output for further modelling.
Mapping Land-Use/Land-Cover Change in a Critical Biodiversity Area of South Africa
International Journal of Environmental Research and Public Health
Land-use/land-cover (LULC) changes have implications for the long-term outlook of environmental processes, especially in the face of factors such as climate change. These changes can have serious consequences for humans. In this study, remote sensing and geographic information system methods were used to investigate LULC changes in a critical biodiversity area (CBA) in the northern sections of Limpopo Province in South Africa from 1990 to 2018 using data obtained from the South African National Land Cover project. In 1990, the dominant land cover comprised thickets and dense bush, followed by woodland and built-up areas, covering proportions of 40, 24 and 18% of the total land-cover area, respectively. Bare and forest areas were the least dominant classes during this time. In 2018, the dominant land cover was woodland, followed by built-up areas, comprising 71 and 20% of the total area, respectively. Subsistence agriculture is a land-cover class with a relatively higher area compare...
African J. of Economic and Sustainable Development, 2015
Many factors contribute to rapid urban expansion and large-scale land use/land cover (LULC) changes. This paper analyses spatiotemporal patterns of LULC and quantifies landscape structures in the Rustenburg district, South Africa, locus of a platinum mining boom. Using multi-temporal Landsat images from 1973 to 2002, LULC changes are evaluated to derive transition matrices of patterns and rates of change of LULC classes. These matrices are integrated with landscape metrics to assess impacts of LULC changes on landscape fragmentation. Changes in LULC are coincident with expansion of mining; urban and mining categories increase at the expense of cultivated land, woodland and grassland. The landscape becomes highly fragmented with decreases in mean and largest patch size, and increases in patch density. The pre-existing natural land cover, grassland, shows a high degree of fragmentation. To ensure proper landscape planning for resource management, this study has implications for rapidly growing cities and mining regions.
Simple algebraic change detection techniques viz. image difference and image ratio were applied to the South African national land use / cover (NLC) datasets of years 2000 and 2014, prepared in grid format covering the Klerksdorp-Orkney-Stilfontein-Hartebeestfontein (KOSH) region in order to assess land use/land cover changes. Both the 2000 and 2014 NLC datasets were generated from Landsat images using different classification schemes and the code values & attributes of the land cover classes of the two datasets were different/not comparable. In order to make these datasets comparable for change detection, the NLC2000 dataset was examined in ArcView GIS by superimposing it onto the NLC2014 dataset and similarities and differences were identified. For each cover type of the NLC2000 dataset, comparable cover type of the 2014 dataset was identified by making a query to the NLC2000 dataset and after viewing the spatial distributions of selected units in respect of the NLC2014 dataset. Suitable code values of NLC2014 dataset were identified for the NLC2000 dataset and it was later reclassified. The land use / cover change detection study reveals that increase in areas were observed for the cover types: Cultivated common fields (low), Cultivated common fields (med), Mines 2 semi-bare, Wetlands, Urban commercial and Plantations/woodlots mature. The Grassland, Thicket/dense bush, Urban residential (dense trees/bush), Mines 1 bare, and Cultivated common pivots (high) showed a decrease in places. During the 14 years, Grassland had decreased from 2,132.47 km2 (77.35% of the total area) to 1,629.78 km2 (59.11% of the total area) owing to landscape transformation to other land covers (e.g. Cultivated common fields and Urban residential) due to human activities. The percentage increase in areas observed for the Cultivated common fields (low and medium) were 8.21% and 2.96% while the Mines 2 semi-bare, Wetlands, Urban commercial, Plantations/woodlots mature showed increases of 0.67%, 0.32%, 0.28% and 0.23% respectively. The area of Thicket/dense bush decreased from 108.15 km2 to 56.71 km2 (change of 1.87%). Maps of land use/land cover changes and statistics obtained for the changed areas are very useful for identifying various changes occurring in different classes and for monitoring land use dynamics.
2018
Countries around the world are faced with land use and land cover (LULC) change due to various factors such as rapid population growth, increased demand for agricultural productivity, and change in climatic characteristics. Land cover change needs to be addressed through monitoring and management. Automated geographical analysis offers a powerful tool for monitoring and detecting LULC change over time and space. This study was conducted to assess LULC in the northern Keiskamma catchment of the Eastern Cape Province of South Africa. The study specifically aimed to quantify LULC dynamics in the area using Landsat imagery between the years 2000 and 2016. Five images were acquired at an interval of approximately four years. Six land cover classes were generated by classifying the multispectral and normalized difference vegetation indices (NDVIs) of each image using an unsupervised classification technique. Accuracy assessment of the classification based on the latest image was evaluated...
Land
Understanding the patterns and drivers of land use and land cover (LULC) changes is fundamental for rational and specific planning for sustainable land management. Using remote sensing techniques, geographic information systems (GIS) and statistical modeling via multinomial logistic regression, we sought to identify spatial variables that determine LULC change and their extent over time in the protected and communal areas of the Zambezi Region, Namibia. Multi-temporal satellite imagery of the Landsat series was used to map changes over a period of twenty-six years, divided into three stages (1984–1991, 1991–2000 and 2000–2010). Post classification change detection methodologies were used to determine conversions between LULC classes. Additionally, socio-economic characteristics of the area were used to identify drivers of changes. Four spatial drivers of LULC change that we identified included the distance to the nearest road, distance to settlements, population density and fire ret...
Planning Africa 2016, 2016
The Western Cape Province is currently faced with population growth, declining household sizes, increasing household numbers, high levels of migration, urbanization and escalating development pressures. These factors have consequently triggered changes in land use and land cover (LULC) and incited issues such as urban sprawl, marginalization of the poor, limited public access to resources, land degradation and climate change. This paper seeks to understand the most significant drivers of LULC change in the Western Cape Province. Focus is given to the major LULC changes which have occurred in the Province in past 24 years by integrating a desktop study of LULC changes using the 1990 and 2013-2014 South African National LULC datasets; document analysis; and expert opinion in the form of semi-structured interviews with municipal town planners. An adapted Driver-Pressure-State-Impact-Response (DPSIR) Framework is used to analyse and understand LULC changes in the study area. LULC changes are driven by political, economic, technological, demographic, biophysical and cultural factors that must be considered in strategies and policies in future planning to avoid detrimental impacts on the environment whilst maintaining socioeconomic benefits.