Browsing by Author "Munch, Zahn"

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    Assessment of GIS-interpolation techniques for groundwater evaluation : a case study of the Sandveld, Western Cape, South Africa
    (Stellenbosch : University of Stellenbosch, 2004-12) Munch, Zahn; Zietsman, H. L.; University of Stellenbosch. Faculty of Science. Dept. of Earth Sciences.
    ENGLISH ABSTRACT: The Sandveld, a potato growing area of the Western Cape is subject to significant groundwater abstraction for both municipal and agriculture purposes. The climate is arid and sensitive and important ecosystems in the area are showing varying degrees of impact. Management measures are needed to ensure ongoing sustainable development of the area. In this study, different interpolation techniques were evaluated to calculate values for unsampled variables rainfall and groundwater elevation. Local deterministic techniques as well as geostatistical techniques were used. It was found that geostatistical techniques, especially with collateral information, such as topography, provided a more accurate result. For environmental studies of this nature, Kriging is recommended as interpolation technique. The underlying data will determine the selection of the particular type of Kriging. Data was extracted from a customized relational database, geoMon, used for data capture, retrieval, processing and reporting. Ease of data extraction facilitated analysis. The interpolated grids were applied in two scenarios: Recharge calculations and quantification as well as a new classification approach according to Resource Directed Measures (RDM). Management classes were defined based on GIS-derived data.
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    Characterizing degradation gradients through land cover change analysis in rural Eastern Cape, South Africa
    (MDPI, 2017) Munch, Zahn; Okoye, Perpetua I.; Gibson, Lesley; Mantel, Sukhmani; Palmer, Anthony
    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.
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    Geohydrological conceptualization from a remotely sensed simplified water balance in the sandveld, South Africa
    (Institute of Electrical and Electronics Engineers, 2012) Munch, Zahn; Gibson, Lesley
    ENGLISH SUMMARY : The Sandveld (Western Cape, South Africa), located on the Cape West Coast, is characterized by low rainfall and minimal river flows, however despite this limitation, significant aquifer systems are found [1]. The groundwater in the region supports extensive agriculture and supplies towns with water for domestic use. The use of remote sensing can influence the way in which groundwater resources can be managed despite the fact that it is a subsurface resource and therefore cannot be directly measured by remote sensing techniques. The G30F catchment in the Northern Sandveld is reported to be experiencing water stress due to increasing abstraction for domestic water supply and agriculture, particularly potato crops. As suggested by Brunner et al [2], we propose the use of the simplified water balance determined from remote sensing data to estimate recharge and discharge zones within the catchment. Furthermore, we propose that this method is a useful aid in the geohydrological conceptualization of this particular water system. Of particular interest is the use of the recently released MOD16 evapotranspiration (ET) data product together with a precipitation data product, highlighting the ease with which studies of this nature can now be executed.
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    Measuring and modelling evapotranspiration in a South African grassland : comparison of two improved Penman-Monteith formulations
    (South African Water Research Commission, 2018) Gwate, Onalenna; Mantel, Sukhmani K.; Palmer, Anthony R.; Gibson, Lesley; Munch, Zahn
    Accurately measuring evapotranspiration (ET) is important in the context of global atmospheric changes and for use with climate models. Direct ET measurement is costly to apply widely and local calibration and validation of ET models developed elsewhere improves confidence in ET derived from such models. This study sought to compare the performance of the Penman-Monteith-Leuning (PML) and Penman-Monteith-Palmer (PMP) ET models, over mesic grasslands in two study sites in South Africa. The study used routine meteorological data from a scientific-grade automatic weather station (AWS) to apply the PML and PMP models. The PML model was calibrated at one site and validated in both sites. On the other hand, the PMP model does not require calibration and hence it was validated in both sites. The models were validated using ET derived from a large aperture scintillometer (LAS). The PML model performed well at both sites with root mean square error (RMSE) within 20% of the mean daily observed ET (R2 of 0.83 to 0.91). Routine meteorological data were able to reproduce fluxes calculated using micrometeorological techniques and this increased the confidence in the use of data from sparsely distributed AWSs to derive reasonable ET values. The PML model was better able to simulate observed ET compared to the PMP model, since the former models both transpiration and soil evaporation (ES), while the latter only models transpiration. Hence, the PMP model systematically underestimated ET in a context where the leaf area index (LAI) was < 2.5. Model predictions in the grasslands could be improved by incorporating the ES component in the PMP model while the PML model could be improved by careful choice of the number of days to be used in the determination of the fraction of ES.
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    Monitoring effects of land cover change on biophysical drivers in rangelands using albedo
    (MDPI, 2019) Munch, Zahn; Gibson, Lesley; Palmer, Anthony
    This paper explores the relationship between land cover change and albedo, recognized as a regulating ecosystems service. Trends and relationships between land cover change and surface albedo were quantified to characterise catchment water and carbon fluxes, through respectively evapotranspiration (ET) and net primary production (NPP). Moderate resolution imaging spectroradiometer (MODIS) and Landsat satellite data were used to describe trends at catchment and land cover change trajectory level. Peak season albedo was computed to reduce seasonal effects. Different trends were found depending on catchment land management practices, and satellite data used. Although not statistically significant, albedo, NPP, ET and normalised difference vegetation index (NDVI) were all correlated with rainfall. In both catchments, NPP, ET and NDVI showed a weak negative trend, while albedo showed a weak positive trend. Modelled land cover change was used to calculate future carbon storage and water use, with a decrease in catchment carbon storage and water use computed. Grassland, a dominant dormant land cover class, was targeted for land cover change by woody encroachment and afforestation, causing a decrease in albedo, while urbanisation and cultivation caused an increase in albedo. Land cover map error of fragmented transition classes and the mixed pixel effect, affected results, suggesting use of higher-resolution imagery for NPP and ET and albedo as a proxy for land cover.
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    Multi-temporal remote sensing land-cover change detection for biodiversity assessment in the Berg River catchment
    (CONSAS, 2013) Stuckenberg, Tristan; Munch, Zahn; Van Niekerk, Adriaan
    Due to the intimate relationship that exists between land cover and biodiversity it is possible to draw inferences on the current state of the biodiversity of an area, assess the likely future pressures and plan accordingly based on an analysis of land-cover change. As a means of assessing the state of biodiversity in the Cape Floristic Region, two land-cover maps (1986/7 and 2007) were developed and demonstrated for the Berg River catchment in the Western Cape province of South Africa using multispectral Landsat Thematic Mapper (TM) data. The land-cover maps were produced to an accuracy of 85% using an object-orientated nearest neighbour supervised classification. The existing vegetation types of South Africa data set were superimposed on the newly classified remnants of natural vegetation to model changes in biodiversity. It was found that the area occupied by natural vegetation increased by more than 14%, suggesting an increase in biodiversity from 1986/7 to 2007. Considerable variation between vegetation types was, however, recorded. The land cover mapping, change analysis and biodiversity modelling methods employed by this study show that land-cover change analysis provides an ideal platform from which to initiate more intensive analyses of biodiversity change and conservation. Some limitations to the use of Landsat imagery for biodiversity monitoring are discussed.
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    Remote sensing evapotranspiration (SEBS) evaluation using water balance
    (Water Research Commission, 2011-06) Gibson, Lesley; Munch, Zahn; Carstens, Marilie; Conrad, Julian
    ENGLISH SUMMARY : This report follows on from WRC Report 1690/1/09 (Gibson et al., 2009) entitled "Remote sensing as a tool for resource assessment towards the determination of the legal compliance of surface and groundwater use" which showed that due to many uncertainties and limitations with both the input data and methodology, it was not possible to determine the actual water consumption of individual farms or compliance to legislation. In this project, the aim was to address the uncertainties and limitations in WRC Report 1690/1/09 and thereby determine the efficacy or inefficiency of the method to highlight water-stressed catchments.
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    Spatial variation in school performance, a local analysis of socio-economic factors in Cape Town
    (CONSAS Conference, 2014) Naidoo, Arulsivanathan Ganas Varadappa; Van Eeden, Amanda; Munch, Zahn
    Poor pass rates of matric learners at secondary schools in South Africa has been a concern for quite some time. Despite large government spending on education, research has shown that the South African schooling system is struggling to convert resources to student performances and failing to promote social equity. The poor performance by South African students prompts further investigation into the factors contributing to educational outputs. The focus of this case study in Cape Town is twofold, firstly to determine if there are any spatial patterns among the matric pass rates of secondary schools and secondly to determine if there are any relationships between the matric pass rate of the school and the socio-economic attributes of the school feeder areas. Key findings of this research suggest that Cape Town schools are clustered in terms of school performance with high performing schools grouped together and many low performing schools also clustered together. There were a few exceptions where within a cluster of low performing schools there was one high performing school and vice versa. Outcomes of the research into spatially varying relationships point to selected socio-economic factors of the community, particularly parent and household characteristics, influencing the learner’s school performance.
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    Towards land change management using ecosystem dynamics and land cover change in rural Eastern Cape
    (Stellenbosch : Stellenbosch University, 2019-12) Munch, Zahn; Van Niekerk, Adriaan; Stelllenbosch University. Faculty of Arts and Social Sciences. Dept. of Geography & Environmental Studies.
    ENGLISH ABSTRACT: Land cover change, triggered by natural and anthropogenic land use change, affects ecosystem services provided by grasslands. Woody encroachment into the grasslands is a threat to function and productivity of rangelands, and threaten rural livelihoods, intensified by rising CO2 levels associated with climate change. Processes of change can only effectively be identified after spatial land transition has been revealed and patterns of change quantified. Accurately quantifying the rates and extent of land cover change is the first step in relating underlying land use processes and the environmental effects thereof to land cover change trajectories involving grassland transformation. The study aims to demonstrate how land cover change, in particular woody encroachment influences landscape functions provided by grasslands in the Eastern Cape. The study seeks to determine how accurately land cover transformation can be quantified and modelled using existing datasets that may contain map error and raises the question how the error pattern can affect modelling of future evapotranspiration and carbon storage. A further question is how the drivers of change vary between regions under different land tenure, i.e. dualistic or commercial systems. Systematic land cover change analysis and future land change modelling were used to characterise land cover change trajectories and flows in the landscape. Flows were described using (1) an indicator-based approach, and (2) intensity analysis and change budget. Hypothetical map error was determined for observed and modelled land cover maps. Overall change was partitioned into quantity, exchange and shift disagreement and intensity. The change budget was computed both at catchment and local level. Map error was further investigated using a local geographically weighted method. Local geographically weighted correspondence matrices were constructed to determine spatially explicit probabilities of change and error at catchment level and per land cover class. By consulting the overall allocation difference maps, hotspots of change and probable error were identified for further investigation. Trends in remote sensing-derived biophysical variables were analysed to determine how land cover change would affect the surface energy budget and the carbon cycle, as proxies for water use and rangeland productivity. Primary drivers of landscape modification comprised rangeland degradation, woody encroachment, urbanisation, increased dryland cultivation and commercial afforestation, with the latter concentrated in the commercial catchment. Though grassland persistence still dominated land cover in the landscape, catchments under dualistic land tenure experienced steeper declines in the grassland area. Woody encroachment was also found predominantly in these catchments. Overall accuracy for the input land cover maps were reported as >80%, equating to theoretical land cover change accuracy of 67–72%. Landscape change varied between 18% and 42%, with 19% estimated from direct overlay of land cover maps with 30 m resolution pixels. By applying a multi-resolution aggregation technique, the study showed that lower resolution input data would identify less change in the landscape, mainly because the allocation error diminishes at lower resolutions. For higher change accuracies and reliability, the accuracy of input land cover maps would have to be increased. Hypothetical map error in observed land cover change maps were found to be higher in catchments under dualistic tenure for gaining transitions, whereas losing transitions showed higher error in catchments practicing commercial farming. The hypothetical error accounted for almost 50% of the reported change. The modelled land cover change showed higher allocation disagreement, suggesting that the land change model was not very reliable, particularly for the commercial catchment. Analysis of remotely sensed data products such as albedo, net primary production and evapotranspiration, in combination with land cover change data has led to better understanding of the landscape of the catchments. Though grasslands are predicted to decrease in favour of woody invasive plant species and cultivated land, this study predicted a decrease of 12% and 6% respectively in net carbon storage and water use by vegetation. Information from multiple sources, in both quality and type, were integrated to better understand rangeland productivity degradation and to compare the impact of climate versus land management in the different catchments. Quantifying changes in biophysical parameters can assist scientists and managers in addressing global challenges.
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    Using remote sensing in support of environmental management : a framework for selecting products, algorithms and methods
    (Elsevier, 2016-08) De Klerk, Helen Margaret; Gilbertson, Jason; Luck-Vogel, Melanie; Kemp, Jaco; Munch, Zahn
    Traditionally, to map environmental features using remote sensing, practitioners will use training data to develop models on various satellite data sets using a number of classification approaches and use test data to select a single ‘best performer’ from which the final map is made. We use a combination of an omission/commission plot to evaluate various results and compile a probability map based on consistently strong performing models across a range of standard accuracy measures. We suggest that this easy-to-use approach can be applied in any study using remote sensing to map natural features for management action. We demonstrate this approach using optical remote sensing products of different spatial and spectral resolution to map the endemic and threatened flora of quartz patches in the Knersvlakte, South Africa. Quartz patches can be mapped using either SPOT 5 (used due to its relatively fine spatial resolution) or Landsat8 imagery (used because it is freely accessible and has higher spectral resolution). Of the variety of classification algorithms available, we tested maximum likelihood and support vector machine, and applied these to raw spectral data, the first three PCA summaries of the data, and the standard normalised difference vegetation index.We found that there is no ‘one size fits all’ solution to the choice of a ‘best fit’ model (i.e. combination of classification algorithm or data sets), which is in agreement with the literature that classifier performance will vary with data properties.We feel this lends support to our suggestion that rather than the identification of a ‘single best’ model and a map based on this result alone, a probability map based on the range of consistently top performing models provides a rigorous solution to environmental mapping.