Land use/cover change modelling and land degradation assessment in the Keiskamma catchment using remote sensing and GIS

Land degradation in most communal parts of the Keiskamma catchment has reached alarming proportions. The Keiskamma catchment is particularly predisposed to severe land degradation associated with soil erosion, thicket degradation and deteriorating riparian vegetation. There is a close coupling between land use/cover dynamics and degradation trends witnessed in the catchment. Soil erosion is prevalent in most of the communal areas in the catchment. The principal aim of this study was to investigate land use/cover trends, model the spatial patterns of soil loss and predict future land use/cover scenarios as a means of assessing land degradation in the Keiskamma catchment. Multi-temporal Landsat satellite imagery from 1972 to 2006 was used for land use/cover change analyses using object-oriented post-classification comparison. Fragmentation analysis was performed by computing and analyzing landscape metrics in the riparian and adjacent hillslope areas to determine the land cover structural changes that have occurred since 1972. The landscape function analysis was used to validate the current rangeland conditions in the communal areas and the former commercial farms. The current condition of the riparian zones and proximal hillslopes was assessed using the Rapid Appraisal of Riparian Condition and future land use/cover scenarios were simulated using the Markovcellular automata model. Spatial patterns of soil loss in the Keiskamma catchment were determined using the Sediment Assessment Tool for Effective Erosion Control (SATEEC), which is a GIS based RUSLE model that integrates sediment delivery ratios. Object oriented classification was used to map soil erosion surfaces and valley infill in ephemeral stream channels as a means of demonstrating the major sediment transfer processes operating in the Keiskamma catchment. The Mahalanobis distance method was used to compute the topographic thresholds for gully erosion. To understand the effect of soil characteristics in severe forms of erosion, laboratory analyses were undertaken to determine the physico-chemical soil properties. iv The temporal land use/cover analysis done using the post-classification change detection indicated that intact vegetation has undergone a significant decline from 1972 to 2006. The temporal changes within the intermediate years are characterized by cyclic transitions of decline and recovery of intact vegetation. An overall decline in intact vegetation cover, an increase in degraded vegetation and bare eroded soil was noted. Fragmentation analyses done in the communal villages of the central Keiskamma catchment indicated increasing vegetation fragmentation manifested by an increase in smaller and less connected vegetation patches, and a subsequent increase of bare and degraded soil patches which are much bigger and more connected. The Landscape Organisation Index revealed very low vegetation connectivity in the communal rangelands that have weak local traditional institutions. Fragmentation analyses in the riparian and proximal hillslopes revealed evidence of increasing vegetation fragmentation from 1972 to 2006. The Markov Cellular Automata simulation predicted a decline in intact vegetation and an increase in bare and degraded soil in 2019. The Keiskamma catchment was noted as experiencing high rates of soil loss that are above provincial and national averages. The classification of erosion features and valley infill showcased the vegetation enrichment in the ephemeral streams which is occurring at the expense of high soil losses from severe gully erosion on the hillslopes. This in turn has led to an inversion of grazing patterns within the catchment, such that grazing is now concentrated within the ephemeral stream channels. Soil chemical analyses revealed a high sodium content and low soluble salt concentration, which promote soil dispersion, piping and gully erosion. The presence of high amounts of illite-smectite in the catchment also accounts for the highly dispersive nature of the soil even at low SAR values. Significant amounts of swelling 2:1 silicate clays such as smectites cause cracking and contribute to the development of piping and gullying in the catchment. Given the worsening degradation trends in the communal areas, a systematic re-allocation of state land in sections of the catchment that belonged to the former commercial farms is recommended to alleviate anthropogenic pressure. Strengthening local institutions that effectively monitor and manage natural resources will be required in order to maintain v optimum flow regimes in rivers and curb thicket degradation. Measures to curb environmental degradation in the Keiskamma catchment should encompass suitable ecological interventions that are sensitive to the socio-economic challenges facing the people in communal areas

Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape

This study validated SNAP-derived LAI from Sentinel-2 and its consistency with existing global LAI products. The validation and intercomparison experiments were performed on two processing levels, i.e., Top-of-Atmosphere and Bottom-of-Atmosphere reflectances and two spatial resolutions, i.e., 10 m, and 20 m. These were chosen to determine their effect on retrieved LAI accuracy and consistency. The results showed moderate R2, i.e., ~0.6 to ~0.7 between SNAPderived LAI and in-situ LAI, but with high errors, i.e., RMSE, BIAS, and MAE >2 m2 m–2 with marked differences between processing levels and insignificant differences between spatial resolutions. In contrast, inter-comparison of SNAP-derived LAI with MODIS and Proba-V LAI products revealed moderate to high consistencies, i. e., R2 of ~0.55 and ~0.8 respectively, and RMSE of ~0.5 m2 m–2 and ~0.6 m2 m–2, respectively. The results in this study have implications for future use of SNAP-derived LAI from Sentinel-2 in agricultural landscapes, suggesting its global applicability that is essential for large-scale agricultural monitoring. However, enormous errors in characterizing field-level LAI variability indicate that SNAP-derived LAI is not suitable for precision farming. In fact, from the study, the need for further improvement of LAI retrieval arises, especially to support farm-level agricultural management decisions

Testing the ability of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) to map hydrothermal alteration zones : a case study of the Haib Porphyry Copper-Molybdenum Deposit, Namibia

Thesis (MSc)--Stellenbosch University, 2005.ENGLISH ABSTRACT: The availability of multispectral data from the satellite-borne ASTER (Advanced Space borne Thermal Emission Reflection Radiometer) sensor with 14 spectral bands, launched on 18 December 1999, ushers in a new dimension in large-scale mineral exploration. The ASTER bands are strategically positioned to map distinctive absorptive features for mapping alteration mineralogy, which has increased the potential to map hydrothermal alteration zones as compared to the conventional Landsat TM satellite and aerial photographs. This research tests the ability of ASTER to map hydrothermal alteration zones by applying various image enhancement techniques and comparing them. The study area is the Haib copper prospect in Namibia. The Crosta technique, standard colour composites, spectral band ratioing, the software defoliant technique, log residuals and spectral linear unmixing were applied and compared against results from the previous detailed geophysical and geochemical exploration. The results from all the techniques corresponded with published geological maps from previous work and indicated ASTER's ability to detect alteration zonations. Comparison of the methods applied showed that choice of technique is usually dependent of the level of detail which one seeks to achieve. Standard colour composite and log residuals are more useful for a generalized overview of the alteration mineralogy, whilst uniquely defining mineral end members is achieved by application of the Crosta technique, ratioing and spectral linear unmixing. Application of the software defoliant techniques involved ratioing results, which are affected by spectral interferences from other minerals. The presence of a highly fractured system has been established by application of Sobel filtering. A spatial association of the extracted fracture system with alteration areas suggest mineralization at the Haib is fracture controlled. The results support the presence of argillicphyllic and prophylitic alteration zones on a regional scale, a scenario which can be equated to the Lowell-Guilbert model. The potassic-phyllic zone boundary could not be spectrally detected which also supports previous studies which suggest the potassic zone is nondefinitive and is over-printed by the phyllic zone. The results demonstrate that ASTER is an effective tool to map hydrothermal alteration systems in arid areas.AFRIKAANSE OPSOMMING: Multispektrale data van die ASTER (' Advanced Space Borne Thermal Emmission Reflection Radiometer') sensors bestaande uit 14 spektrale bande, afkomstig van 'n satelliet gelanseer op 18 Desember 1999 lui 'n nuwe era in vir grootskaalse minerale eksplorasie. Die ASTER bande is strategies sodanig op die spektrum geposisioneer om onderskeidende absorberende verskynsels van veranderde mineralisasie te identifiseer. Hierdie data het die potensiaal verhoog om hidrotermale veranderingstelsels meer suksesvol te karteer as met konvensionele Landsat TM beelde en lugfotos. Hierdie navorsing toets die vermoeëns van ASTER om hidrotermale veranderingstelsels te karteer deur 'n wye reeks beeldverrykings tegnieke toe te pas en te vergelyk. Die studiegebied IS die Haib koperafsetting in Namibië. Die Crosta tegniek, standaard kleursamestellings ('colour composites'), ratio-tegnieke, plantegroeistroping ('software defoiliant'), log residuele ('log residual '), en spektrale lineêre ontmenging ('spectral linear unmixing') is toegepas en die resultate met vorige gedetailleerde geofisiese en geo-chemiese veldopnames te vergelyk. Die verkreë resultate van al die verskillende tegnieke het grootliks met gepubliseerde geologiese kaarte van die gebied ooreengestem en bevestig dat ASTER data geskik is om sulke mineralogies veranderde gebiede te karteer. Vergelykings tussen die tegnieke het getoon dat die keuse van tegniek bepaal word deur die vlak en tipe detail wat verlang word. Standaard kleursamestellings en die log residuele tegnieke lewer goeie resultate om veralgemeende oorsigte van mineralogies veranderde sones te verskaf, terwyl die Crosta-, ratio- en spektrale lineêre ontmengingstegnieke meer suksesvol is om spesifieke minerale te identifiseer. Die plantegroei stropingtegniek is nodig in gevalle waar spektrale ratios deur plantegroeiresponse geaffekeer word. Die aanwesigheid van 'n intensief gefraktuurde sisteem is bepaal deur 'n Sobel filter toe te pas. Ruimtelike assosiasies tussen die voorkoms van die gefraktuurde sone met en die minealogies gewysigde sones dui aan dat mineralogiese wysiging in die Haib gebied deur frakturering beheer is. Die resultate steun die aanwesigheid van argillities-fillitiese enpropolities gewysigde sones op 'n streekskaal, 'n scenario wat deur die Lowell-Guilbertmodel voorgehou word. Die grense van die kalium-fillitiese sone kon nie spektraal waargeneem word nie. Dit steun ook vorige studies wat suggereer dat die kaliumsone nieafbakenbaar is en waarskynlik deur die fillitiese sone oorlê word. Die resultate bevestig onomwonde dat ASTER data benut kan word om hidrotermaal veranderde sones in semiariede gebiede effektief te karteer

The Role of African Emerging Space Agencies in Earth Observation Capacity Building for Facilitating the Implementation and Monitoring of the African Development Agenda: The Case of African Earth Observation Program

AU-Agenda 2063 was adopted at the 24th Ordinary Session of the African Heads of State and Government in 2015 as the blueprint for the future development of the continent. Built upon the continent’s past experiences, challenges, and successes, AU-Agenda 2063 comprehensively describes the strategic path for Africa’s future development in the next 50 years. Thus, the monitoring of its implementation in various African states is critical for ensuring sustainable development and track progress. However, the higher cost of collecting data for accurately and reliably monitoring the implementation of Agenda 2063 may hinder the progress towards achieving these goals. Satellite Earth observation provides ample data, and thus has provided opportunities for the development of novel products and services with the potential to support implementation, monitoring and reporting for AU-Agenda 2063 development imperatives. However, it has been limitedly exploited in Africa, as evidenced by lower research outputs and investments. This calls for increased capacity building in the use of available EO data and products for various users including decision makers to advance national, regional and continental priorities. The use of such data products is often hampered by the capability to understand the products and thus their value for addressing socio-economic challenges. This paper discusses the potential of Earth observation capacity building for supporting the implementation, monitoring of, and reporting towards achieving AU-Agenda 2063 development imperatives. Specifically, this paper identifies existing capacity building resources, including the role of open and free Earth observation data, open-source software, and product dissemination platforms that can be leveraged for supporting national development, service delivery and the achievement of AU-Agenda 2063 targets. Furthermore, the paper recognizes the importance of bilateral and multilateral partnerships in leveraging existing know-how, technology and other resources for advancing strategic goals of African emerging space agencies and promoting sustainable development, with examples from South African National Space Agency (SANSA). Then, the challenges and opportunities for capacity building and the wide adoption of EO in Africa are discussed in the context of AU-Agenda 2063. The paper thus concludes that EO capacity building is essential to address the skills and data gaps and increase the use of EO-based solutions for decision making in various sectors, critical for achieving AU-A2063

Mapping and Assessment of Housing Informality Using Object-Based Image Analysis: A Review

Research on the detection of informal settlements has increased in the past three decades owing to the availability of high- to very-high-spatial-resolution satellite imagery. The achievement of development goals, such as the Sustainable Development Goals, requires access to up-to-date information on informal settlements. This review provides an overview of studies that used object-based image analysis (OBIA) techniques to detect informal settlements using remotely sensed data. This paper focuses on three main aspects: image processing steps followed when detecting informal settlements using OBIA; informal settlement indicators and image-based proxies used to detect informal settlements; and a review of studies that extracted and analyzed informal settlement land use objects. The success of OBIA in detecting informal settlements depends on the understanding and selection of informal settlement indicators and image-based proxies used during image classification. To meet the local ontology of informal settlements, the transfer of OBIA mapping techniques requires the fine-tuning of the rulesets. Machine learning OBIA techniques using image proxies derived from multiple sensors increase the opportunities for detecting informal settlements on the city or national level

A Comparative Assessment of Annual Solar Irradiance Trends between Mpumalanga and Northern Cape Province in South Africa Using PVGIS

South Africa has committed to reducing its greenhouse emissions by sixty-five percent by 2030 in their National Integrated Energy Plan (NEIP). The lack of investment and development for renewable energy sources put the country on an uncertain trajectory in fulfilling its 2030 energy commitments. At the same time, the country has been labeled as a region with one of the highest solar energy potentials. Provinces such as Mpumalanga and Northern Cape are on opposite ends of the matter, with Northern Cape is one of the leading provinces for renewal energy, while the Mpumalanga province remains the host to eighty-five per cent of the country’s coal plants. Solar energy is an abundant renewable energy source and can be assessed using Geographic Information Systems (GIS) techniques. In this paper, the geostatistical technique, Kriging, is employed to predict, estimate, and compare the regional distribution, potential, and variability of annual optimum solar energy (irradiance) between the Mpumalanga Province and Northern Cape Province. Spot-based radiation data are available for solar energy analyses from the GIS Web-based tool Photovoltaic Geographical Information Systems (PVGIS). Kriging was used to estimate the spatial variability of solar energy at an average error of 1.98505% for the Northern Cape Province and 2.32625% for the Mpumalanga Province. It was identified that the Northern Cape receives the highest annual optimum irradiation and has a low overall spatial variation in irradiation over its provincial area. Mpumalanga receives lesser amounts of irradiation but has high overall spatial variation over its provincial area. Most of Northern Cape’s central to northwestern regions have the highest annual optimum irradiation ranging from 2583 kWh/m2 to 2638 kWh/m2, while Mpumalanga’s highest regions of annual irradiation occur primarily on its western and northwestern parts and ranges in highs of 2345 kWh/m2 to 2583 kWh/m2

Assessing the Impacts of COVID-19 on SO₂, NO₂, and CO Trends in Durban Using TROPOMI, AIRS, OMI, and MERRA-2 Data

This research report investigated the impacts of the COVID-19 lockdown restrictions on CO, SO2, and NO2 trends in Durban from 2019 to 2021. The COVID-19 lockdown restrictions proved to decrease greenhouse gas (GHG) emissions globally; however, the decrease in GHG emissions was for a short period only. Space-borne technology has been used by researchers to understand the spatial and temporal trends of GHGs. This study used Sentinel-5P to map the spatial distribution of CO, SO2, and NO2. Use was also made of the Atmospheric Infrared Sounder (AIRS), Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), and the Ozone Monitoring Instrument (OMI) to understand the temporal trends of CO, SO2, and NO2, respectively. To validate the results of this study, we used the Sequential Mann–Kendall (SQMK) test. This study indicated that there were no significant changes in all the investigated gases. Therefore, this study failed to reject the null hypothesis of the SQMK test that there was no significant trend for all investigated gasses. Increasing trends were observed for CO, SO2, and NO2 trends during winter months throughout the study period, whereas a decreasing trend was observed in all investigated gases during the spring months. This shows that meteorological factors play a significant role in the accumulation of air pollutants in the atmosphere. Most importantly, this study has noted that there was an inverse relationship between the trends of all investigated gases and the COVID-19 lockdown restrictions

An Application of Machine-Learning Model for Analyzing the Impact of Land-Use Change on Surface Water Resources in Gauteng Province, South Africa

The change in land-use diversity is attributed to the anthropogenic factors sustaining life. The surface water bodies and other crucial natural resources in the study area are being depleted at an alarming rate. This study explored the implications of the changing land-use diversity on surface water resources by using a random forest (RF) classifier machine-learning algorithm and remote-sensing models in Gauteng Province, South Africa. Landsat datasets from 1993 to 2022 were used and processed in the Google Earth Engine (GEE) platform, using the RF classifier. The results indicate nine land-use diversity classes having increased and decreased tendencies, with high F-score values ranging from 72.3% to 100%. In GP, the spatial coverage of BL has shrunk by 100.4 km2 every year over the past three decades. Similarly, BuA exhibits an annual decreasing rate of 42.4 km2 due to the effect of dense vegetation coverage within the same land use type. Meanwhile, water bodies, marine quarries, arable lands, grasslands, shrublands, dense forests, and wetlands were expanded annually by 1.3, 2.3, 2.9, 5.6, 11.2, 29.6, and 89.5 km2, respectively. The surface water content level of the study area has been poor throughout the study years. The MNDWI and NDWI values have a stronger Pearson correlation at a radius of 5 km (r = 0.60, p = 0.000, n = 87,260) than at 10 and 15 km. This research is essential to improve current land-use planning and surface water management techniques to reduce the environmental impacts of land-use change

Investigation of Informal Settlement Indicators in a Densely Populated Area Using Very High Spatial Resolution Satellite Imagery

Automation of informal settlements detection using satellite imagery remains a challenging task in urban remote sensing. This is due to the fact that informal settlements vary in shape, size and spatial arrangement from one region to the other in some cases within a city. This paper investigated the methodology to detect informal settlements in a densely populated township by assessing informal settlement indicators observed from very high spatial resolution satellite imagery. We assessed twelve informal settlement indicators to determine the most effective indicators to distinguish between informal and informal classes. These indicators included the spectral indices first and second-order statistical measurements. In addition to the commonly used informal settlement indicators, we assessed the effectiveness of built-up area and iron cover. The GLCM textural measures performed poorly in separating informal and formal settlements compared to first-order statistics measurement and spectral indices. The built-up area index, coastal blue index and the first-order statistics mean measurements produced higher separability distance of informal and formal settlements. The iron index performed better in separating the two settlement types than the commonly used GLCM measure and NDVI. The proposed ruleset that uses the three features with the highest separability distance achieved producer and user accuracies of informal settlements of 95% and 82%, respectively. The results of this study will contribute towards developing methodologies to automatically detect informal settlements

Assessment of Spatial Patterns of Backyard Shacks Using Landscape Metrics

Urban informality in developing economies like South Africa takes two forms: freestanding shacks are built in informal settlements, and backyard shacks are built in the yard of a formal house. The latter is evident in established townships around South African cities. In contrast to freestanding shacks, the number of backyard shacks has increased significantly in recent years. The study assessed the spatial patterns of backyard shacks in a formal settlement containing low-cost government houses (LCHs) using Unmanned Aerial Vehicle (UAV) products and landscape metrics. The backyard shacks were mapped using Object-Based Image Analysis (OBIA), which uses height information, vegetation index, and radiometric values. We assessed the effectiveness of rule-based and Random Forest (RF) OBIA techniques in detecting formal and informal structures. Informal structures were further classified as backyard shacks using spatial analysis. The spatial patterns of backyard shacks were assessed using eight shapes, aggregation, and landscape metrics. The analysis of the shape metrics shows that the backyard shacks are primarily square, as confirmed by a higher shape index value and a lower fractional dimension index value. The contiguity index of backyard shack patches is 0.6. The values of the shape metrics of backyard shacks were almost the same as those of formal and informal dwelling structures. The values of the assessed aggregation metrics of backyard shacks were more distinct from formal and informal structures compared with the shape metrics. The aggregation metrics show that the backyard shacks are less connected, less dense, and more isolated from each other compared with formal and freestanding shacks. The Shannon’s Diversity Index and Simpson’s Evenness Index values of informal settlements and formal areas with backyard shacks are almost the same. The results achieved in this study can be used to understand and manage informality in formal settlements