Browsing by Author "Harmse, Christiaan Johannes"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Earth observation methods for sustainable Karoo Rangeland Management
    (Stellenbosch : Stellenbosch University, 2023-12) Harmse, Christiaan Johannes; Van Niekerk, Adriaan; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies.
    ENGLISH ABSTRACT: Rangelands, which comprise 25% of the earth's land surface, are under severe pressure due to the increasing global environmental problem of rangeland degradation. Ecological rangeland studies aim to determine the condition and productivity of rangelands and the severity of their degradation. In situ assessments are considered the most accurate way of monitoring rangeland degradation, but they are expensive and time-consuming, particularly when carried out over large areas. The Nama-Karoo biome in Southern Africa is primarily used for sheep and goat farming and is at risk of being overgrazed. Rangeland monitoring aims to determine whether grazing management strategies meet the goals of sustainable resource utilisation. Three experiments involving the combination of Earth observation technologies for rangeland monitoring were carried out in this research. First, a hypothesis that sheep graze more selectively under low stocking rates – potentially resulting in localised overgrazing – was tested. Livestock tracking, in situ observations, and Sentinel-2 imagery were used to make rangeland-scale observations of sheep grazing behaviour and vegetation conditions in the Nama-Karoo. The results showed that livestock congregates along drainage lines with deeper soil depth. There was a clear difference in the use of grazing areas among different stocking density classes. The conclusion was that spatial analyses of remotely sensed data can provide a landscape-scale overview of livestock movement patterns; and that high-resolution normalised difference vegetation index (NDVI) data can be used as a grazing management tool to determine the spatial variability of productive areas across the semiarid Upper Karoo rangelands and identify preferred grazing areas. Monitoring animal weight gain is expensive and often involves rounding up animals over large areas and long distances, leading to stress-related health problems and weight loss in animals. The second experiment evaluated remotely sensed vegetation indices for modelling sheep weight gain in semi-arid rangelands. The experiment also analysed the grazing behaviours in relation to time and location by using Sentinel-2 imagery and sheep movement data obtained from global positioning system (GPS) collar receivers. The results show that the average daily distance covered by sheep remained consistent throughout the year. The study successfully demonstrated the predictive capability of the NDVI in determining changes in the weight of sheep. The third experiment evaluated the effectiveness of multispectral (MS) and hyperspectral (HS) remotely sensed, unmanned aerial vehicle-(UAV)-based data and machine learning (random forest) methods to differentiate between 15 dominant Nama-Karoo plant species to aid ecological impact surveys. The results show that MS imagery was unsuitable as classification accuracies were generally low (37.5%). However, higher classification accuracies (>70.0%) were achieved when HS imagery was employed. Using in situ spectroscopic data collected with a fieldspectroradiometer, 12 key wavelengths were identified for discriminating among the dominant Karoo plant species with accuracies exceeding 90%. Reducing the dimensionality of the in situ spectroscopic dataset to the 12 key bands increased classification accuracies from 84.8% (all bands) to 91.7% (12 bands). Although classification accuracies were comparatively lower (76%) when HS remotely sensed imagery was used (instead of the in situ spectroscopic data), the results indicate that HS remote sensing imaging has the capability to effectively map indicator plant species in the Karoo region. The techniques developed in this research can be used to carry out satellite and UAV-based ecological assessments over large and inaccessible areas, assisting in managing the extensive Karoo rangelands more sustainably.