Characterising Historic Land Use and Land Cover Change
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CHARACTERISING HISTORIC LAND USE AND LAND COVER CHANGE USING LANDSAT EARTH OBSERVATION DATA IN THE WATERBERG BIOSPHERE RESERVE By Tsedzuluso Dylan Mundalamo (0711253K) A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science (Geographical Information Systems and Remote Sensing) at the School of Geography, Archaeology & Environmental Studies Supervisor: Dr Elhadi Adam Co Supervisor: Dr Darragh Woodford Johannesburg, 2019 DECLARATION I, Tsedzuluso Dylan Mundalamo, declare that this research report is my own unaided work. It is submitted for the Degree of Master of Science in Geographical Information Systems and Remote Sensing at the University of the Witwatersrand, Johannesburg. It has not been submitted before for any degree or examination at any other University. Signature ………………………………………………. Date……27/05/2019………………………....… i ABSTRACT Information about Land use and land cover (LULC) is important for making a better decision, planning, and management of human activities and natural resources in protected, conserved and unprotected areas such as river catchment area and biosphere reserve. The study was conducted in the Waterberg region to characterize and compare historical landscape modification within the Waterberg Biosphere Reserve (WBR) and the surrounding river catchments, both prior to and after its promulgation with United Nation Education Scientific and Cultural Organization’s Man and Biosphere Programme in 2001. The research objectives of this study were to map the LULC classes from 1984 to 2016 in successive five years interval using the Landsat 4-5, 7 and 8 images, quantify LULC changes within and outside the WBR (River catchment areas) and lastly, quantify the impact of the WBR on urban and agriculture. Information about LULC was derived using Support Vector Machine (SVM) algorithm with 140 reference data for each LULC class (70% as training data and the remaining 30% as validation data). The Normalized Difference Vegetation Index (NDVI) and statistical testing (paired t-test) were computed and performed, respectively. The overall accuracies range from 80.29% to 90.12%, User’s accuracies (50.65 to 100%), producer’s accuracies (45.24% to 100% and kappa indices (0.78 to 0.81) Landscape has insignificantly modified over the analysis period (P >0.05) on both sides of the study whilst the NDVI shows significant change (P<0.05). Cultivated land decreased on both sides of the WBR as land covered by this LULC type was 8.41% (Inside) and 7.52% (Outside) in 1984 and decreased to 4.04% and 4.90% inside and outside the WBR respectively, in 2016. Built up area increased outside the WBR as it was 1.04% in 1984 and 1.59% in 2016. However, built up area decreased from 0.79% in 1984 to 0.69% in 2016 outside the WBR. Mines occur outside the periphery of the WBR and increased from 0.04 %( 1984) to 0.13% (2016). Waterbody also increased from 0.10% inside and 0.01% outside the WBR in 1984 to 0.13% and 0.04% respectively, in 2016. The area is experienced rapid urban and mine growth which raise concern on the quality of water, aquatic species and ecosystem functionality as the WBR did not halt these developments within the region as it holds the potential coalfields to supply coal for fossil energy generation. The conversion of cropland to game farming caused revegetation which could influence the ecological functioning of both aquatic and terrestrial ecosystems. Proper planning and management of both human activities and natural resources are recommended to conserve the biodiversity while promoting local community involvement in sustainable development structures. ii DEDICATIONS In lovely memory of my mother and grandmother: Ms Mashudu Ratshitaka and Mrs Mukatshelwa Singo. The dedication also goes to my siblings: Vhutshilo Mundalamo, Masha Mundalamo, and Seani Mundalamo. iii ACKNOWLEDGEMENTS Praises go to the almighty God for his guidance and protection during my entire study at the University of the Witwatersrand. I would like to express my appreciation to my supervisors: Dr Elhadi Adam and Dr Darragh Woodford for their guidance and supervision they offered throughout this research project. I would like to thank my siblings for their social and financial support. Without you, this research project would be impossible Special thanks go to Dr Fhatuwani James Mundalamo for his encouragement during this project. I would like to extend my appreciation to the School of Geography, Archaeology and Environmental Studies Staff for sharing their knowledge with me and also giving me an opportunity to do a Master of Science iv LIST OF FIGURES Figure 1: Locality Map (Source: DWS and DEA) ................................................................................... 7 Figure 2: Methodology Flow Diagram .................................................................................................. 10 Figure 3: LULC map of WBR in 1984, 1990, 1996, 2001, 2006, 2011 and 2016 .................................... 18 Figure 4: LULC coverage (%) for 1984, 1990, 1996, 2001, 2006, 2011,and 201 .................................... 20 Figure 5: NDVI maps for the year 1984, 1990, 1996, 2001, 2006, 2011 and 2016 .................................. 23 Figure 6: NDVI trend from 1984 to 2016 .............................................................................................. 24 Figure 7: LULC coverage (%) inside and outside WBR for 1984, 1990, 1996, 2001, 2006, 2011 and 2016 ............................................................................................................................................................ 28 Figure 8: NDVI comparison between inside and outside the WBR......................................................... 29 v LIST OF TABLES Table 1: Satellite/sensor properties ......................................................................................................... 9 Table 2: LULC classes ......................................................................................................................... 12 Table 3: Reference datasets for the LULC............................................................................................. 12 Table 4: LULC coverage of the study area for the years 1984,1990,1996,2001,2011 and 2016 ............... 21 Table 5: NDVI values from 1984 to 2016 ............................................................................................. 24 Table 6: LULC coverage within and outside the WBR from 1984 to 2016 ............................................. 26 Table 7: The confusion matrix for the 1984 classified image ................................................................. 29 Table 8: The confusion matrix for the 1990 classified image ................................................................. 30 Table 9: The confusion matrix for the 1996 classified image ................................................................. 30 Table 10: The confusion matrix for the 2001 classified image ............................................................... 31 Table 11: The confusion matrix for the 2006 classified image ............................................................... 31 Table 12: The confusion matrix for the 2011 classified image ............................................................... 32 Table 13: The confusion matrix for the 2016 classified image ............................................................... 32 Table 14: LULC changes within and outside WBR from 1984 to 2016 .................................................. 35 Table 15: NDVI Changes and Statistical testing .................................................................................... 36 vi ABBREVIATIONS AND ACRONYMS ANN Artificial Neural Networks ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer AVHRR Advanced Very High-Resolution Radiometer BIC Bushveld Igneous Complex BR Biosphere Reserve DEA Department of Environmental Affairs DEAT Department of Environmental Affairs and Tourism DRDLR Department of Rural Development and Land Reform DMR Department of Mineral Resources DWS Department of Water and Sanitation ENVI Environment for Visualising Images ETM+ Enhanced Thematic Mapper Plus FLAASH Fast Line of Sight Atmospheric Analysis of Hyperspectral Cubes GCP Ground Control Points GDP Gross Domestic Product GIS Geographic Information Systems GPS Global Positioning System K2C Kruger to Canyon LULC Land use and land cover MAB Man and Biosphere MODIS Moderate Resolution Imaging Spectroradiometer MSS Multi-spectral scanner NGI National Geospatial Information OLI Operational Land Imager PCA Principal Component Analysis RDP Reconstruction and Development Programme RMSE Root Mean Square Error RS Remote Sensing SANLC South African National Land Cover SPOT Satellite Pour l’Observation de la Terre SVM Support Vector Machine TIRS Thermal Infrared Sensor vii TM Thematic Mapper UNESCO United Nations Education, Scientific and Cultural Organization USGS United States Geological Survey UTM Universal Transverse Mercator VBR Vhembe Biosphere Reserve WGS World Geodetic System WBR Waterberg Biosphere Reserve viii Contents DECLARATION .................................................................................................................................... i ABSTRACT .......................................................................................................................................... ii DEDICATIONS ..................................................................................................................................