The use of Landsat ETM imagery as a suitable data capture source for alien acacia species for the WFW programme - Cobbing, Benedict Louis (Rhodes University, Faculty of Science, Department of Geography, 2007)
Geographic Information System technology today allows for the rapid analysis of vast amounts of spatial and non-spatial data. The power of a GIS can only be effected with the rapid collection of accurate input data. This is particularly true in the case of the South African National Working for Water (WFW) Programme where large volumes of spatial data on alien vegetation infestations are captured throughout the country. Alien vegetation clearing contracts cannot be generated, for WFW, without this data, so that the accurate capture of such data is crucial to the success of the programme. Mapping Invasive Alien Plant (IAP) data within WFW is a perennial problem (Coetzee, pers com, 2002), because not enough mapping is being done to meet the annual requirements of the programme in the various provinces. This is re-iterated by Richardson, 2004, who states that there is a shortage of accurate data on IAP abundance in South Africa. Therefore there is a need to investigate alternate methods of data capture; such as remote sensing, whilst working within the existing WFW data capture standards. The aim of this research was to investigate the use of Landsat ETM imagery as a data capture source for mapping alien vegetation for the WFW Programme in terms of their approved mapping methods, for both automated and manual classification techniques. The automated and manual classification results were compared to control data captured by differential Global Positioning Systems (DGPS). The research tested the various methods of data capture using Landsat ETM images over a range of study sites of varying complexity: a simple grassland area, a medium complexity grassy fynbos site and a complicated indigenous forest site. An important component of the research was to develop a mapping (classification) Ranking System based upon variables identified by WFW as fundamental in data capture decision making: spatial and positional accuracy, time constraints and cost constraints for three typical alien invaded areas. The mapping Ranking System compared the results of the various mapping methods for each factor for the study sites against each other. This provided an indication of which mapping method is the most efficient or suitable for a particular area.
Keywords: Geographic information systems; Global Positioning System; Landsat satellites; Agriculture -- Remote sensing; Geography -- Remote sensing