Water hyacinth (Eichhornia crassipes) is one of the most aggressive and lethal free-floating aquatic weed that degrades and chokes freshwater ecosystems and threatens aquatic life. Early detection and up-to-date information regarding its distribution is, therefore, crucial in understanding its spatial configuration and propagation rate. The present study, thus, sought to map the seasonal dynamics of invasive water hyacinth, in Greater Letaba river system in Limpopo Province, South Africa, using Sentinel-2 data and Linear Discriminant Analysis (LDA). Classification test results showed that seasonal water hyacinth distribution patterns can be accurately detected and mapped, using Sentinel-2 data with high accuracies. Water hyacinth was mapped with an overall accuracy of 80.79% during the wet season, and 79.04% during the dry season, with kappa coefficients of 0.76 and 0.724, respectively, using combined vegetation indices and spectral bands. The use of spectral bands (wet: 79.48% and dry: 75.98%) and vegetation indices (wet: 76.42% and dry: 74.42%) as independent dataset yielded slighter lower accuracies when compared to the use of the combined dataset. Further, areal coverage results showed that approximately 63.82% and 28.34% of the river system was infested with water hyacinth during wet and dry seasons, respectively. Findings of this study underscore the importance of new generation sensors in detecting and mapping the seasonal distribution of water hyacinth in river systems. Overall such findings provide a baseline or provide a framework for developing invasive aquatic species management and eradication strategies.

Wetlands are highly productive systems that act as habitats for a variety of fauna and flora. Despite their ecohydrological relevance, wetland systems are severely under threat from global environmental changes and anthropogenic activities. This results in the disturbance of plant species composition, spatial distribution, productivity, diversity, and their ability to offer goods and services in wetlands. However, wetland degradation varies considerably from place to place with severe degradation in developing countries, especially in sub-Saharan Africa. The lack of monitoring and assessment in this region has led to a lack of consolidated statistics on the rate of wetland loss. For example, a lack of up-to-date and reliable spatial explicit information further complicates the management of wetland ecosystems. To monitor and understand wetland degradation, there is a need for the use of remote sensing for accurate estimation and precise mapping of present and historic information. Similarly, there is a need to develop robust methodologies to precisely assess and monitor wetland degradation, hydrological cycle and healthy over space and time. This work thereof, provides a comprehensive overview of remote sensing applications in monitoring and mapping the wetland ecosystem. It also highlights the strength and challenges associated with the use of satellite data for purposes of wetland monitoring. Spatial explicit and periodical information offered by satellite remote sensing will add value to the understanding of wetlands, their transition process, and transformation. This will aid in policy development and decision-making, as well as in implementing sustainable measures for wetland conservation.

Early detection and mapping of the spatio-temporal distribution of invasive water hyacinth (Eichhornia crassipes) in inland hydrological systems are vital for a number of water resource management-related reasons. Field surveys and current climate change projections (associated with longer dry spells, and shortened rain seasons) have shown that climate change and the rapid spread of aquatic invasive species are increasingly affecting inland surface water availability in semi-arid regions of Southern Africa. It is upon this premise that accurate, reliable, and timely information on the spatio-temporal distribution and configuration of water hyacinth is required in tracing their evolution and propagation in affected areas as well as in potential vulnerable areas. This work, therefore, attempts to test two robust push-broom multispectral sensors: Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) in identifying, detecting, and mapping the spatial distribution and configuration of invasive water hyacinth in a river system. The results of the study show that water hyacinth in small reservoirs can be mapped with an overall accuracy of 68.44% and 77.56% using Landsat 8 and Sentinel-2 data, respectively. The results further demonstrated the blue, red, red edge (RE) 1, short-wavelength infrared (SWIR)-1, and SWIR-2 of both satellite data sets as the critical and outstanding spectral regions in detecting and mapping water hyacinth from other land-cover types. Overall, the study highlights the unexploited prospects of the new noncommercial multispectral sensors in monitoring invasive species infestation from inland surface waterbodies in semi-arid regions (i.e. smaller reservoirs).

Identification of groundwater potential zones (GWPZ) is as equally important as determining the most effective groundwater mapping models for efficient production of reliable GWPZ maps. In this study, relative frequency ratio (RF) with predictor value and analytic hierarchy process (AHP) models, including two RF-AHP hybrid models (HM-A and HM-B) were applied and compared to evaluate their effectiveness and accuracy in groundwater potential mapping. For HM-A model, RF was used to rank the subclasses of groundwater controlling parameter and AHP provided the weight of that parameter. For HM-B, it was vice versa. Eight parameters (slope, geomorphology, lithology, lineament density, drainage density, soil, rainfall and LULC) were considered for this assessment. The RF, AHP, HM-A and HM-B show the AUC value of 72.47%, 60.55%, 71.96% and 49.85%, respectively. The models based on RF-derived ranks show better accuracies (>70%), thus suggesting that ranks have more influence in the performance of models than weights.

The study explored the impact of Land Use and Land Cover (LULC) change dynamics in relation to the condition and status of an unprotected wetland located in the arid-tropical parts of the Limpopo Province, South Africa. The long-term Landsat archival data series was used to map and quantify the impacts of LULC change on the wetland over a period of 36 years (1983-2019). A multi-source satellite image analysis was performed, using the Support Vector Machine (SVM) algorithm and advanced spatially- explicit geographic information system tools. Landsat data series covering the entire study area was used to assess, map and monitor LULC change that occurred over-time. Post-classification maps for the Maungani wetland area were analysed to provide a quantitative assessment and a detailed overview of the rate of change. The generated wetland detection maps for four temporal phases (i.e. 1983-1992, 1992-2001, 2002-2010) were analysed. This study found that the spatial extent of the wetland area declined severely during the period under study with 728 300 ha. The findings of this work provide critical insights and baseline information about the state of unprotected wetlands in the rural parts. This information is useful for the development of tailor-made wetland management strategies and a possible rehabilitation framework for unprotected wetland ecosystems.

Illegal disposal of solid waste is a significant issue in many parts of the world, particularly in urban areas. Because of unprecedented urbanization, these areas are crowded, putting pressure on the already inadequate municipal services such as waste management. As municipalities fail to provide adequate and effective waste management services, the expansion and proliferation of informal settlements contribute to the problem of illegal dumping. Apartheid spatial planning produced environmentally unsustainable cities characterized by glaring disparities in municipal resource allocation, disturbingly inefficient transportation systems, and widespread urban insecurity. Therefore, this study examines how the expansion of informal settlement at an unprecedented rate contributes to illegal dumping post-apartheid by conducting a systematic review. Using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, a literature search from 1994 to 2023 was conducted in the field of waste management. The review focuses on three key aspects: (1) factors that contribute to illegal dumping in townships; (2) waste management laws during apartheid and post apartheid; and (3) waste collection system in townships and spatial planning. South Africa’s inequality is a major contributor to environmental degradation. The situation was exacerbated by efforts to prevent urban migration and forcefully remove black people from cities; apartheid ideology justified the dormitory-like nature of urban townships. In the South African context, the literature reveals that there is a research gap in the application of technologies and effective waste management plans to keep up with the growing number of informal settlements. Furthermore, despite progressive environmental policies, implementation has been ineffective. This study offers valuable evidence on the spatial and temporal dynamics of informal settlements, addressing both the location and time aspects. A robust government-led Community Participation in Solid Waste Management program is required immediately.