Rowlinson, LCSummerton, MAhmed, F2007-03-262007-06-072007-03-262007-06-071999-10Rowlinson, LC, Summerton, M and Ahmed, F. 1999. Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones. Water SA, vol. 25(4), pp 497-5000378-4738http://hdl.handle.net/10204/2076http://hdl.handle.net/10204/2076It has been estimated that South Africa will reach the limits of its usable freshwater resources during the first half of the next century if current trends in water use are not reversed. Removing alien vegetation, responsible for the uptake of large amounts of water from riparian zones, is one of the methods of maximising water supply in South Africa. Remote sensing is a cost- and time-effective technique for identifying alien vegetation in riparian zones and remote sensing data can be incorporated into a geographic information system (GIS) which can be used as a tool for the management of riparian zones. In this paper, vegetation identification and classification techniques by using aerial videography, aerial photography and satellite imagery, are assessed in terms of accuracy and cost for a small subcatchment in the KwaZulu-Natal midlands. This was achieved by incorporating the data obtained from aerial videography, aerial photography and ground mapping into a GIS. Accuracies of the different techniques were then examined. Data obtained from satellite imagery were assessed independently using digital image decoding procedures. The costs of each technique were also determined and, together with the accuracy results, used to make recommendations for the most effective manner of identifying alien vegetation in riparian zones. The accuracy results obtained in this study indicate that using manual techniques to identify riparian vegetation from 1:10 000 black: and white aerial photographs yield the most accurate and cost-effective results. The least cost-effective data sources were found to be 1:10 000 colour aerial photographs and digital aerial photographs and the least accurate data sources were aerial videography and Landsat thematic mapper (TM) satellite imagery.41022 bytesapplication/pdfenCopyright: 1999 Water Research CommissionAlien vegetationRiparian zonesVegetation identificationRemote sensingCatchmentsVegetation classification techniquesWater resourcesArticleRowlinson, L., Summerton, M., & Ahmed, F. (1999). Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones. http://hdl.handle.net/10204/2076Rowlinson, LC, M Summerton, and F Ahmed "Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones." (1999) http://hdl.handle.net/10204/2076Rowlinson L, Summerton M, Ahmed F. Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones. 1999; http://hdl.handle.net/10204/2076.TY - Article AU - Rowlinson, LC AU - Summerton, M AU - Ahmed, F AB - It has been estimated that South Africa will reach the limits of its usable freshwater resources during the first half of the next century if current trends in water use are not reversed. Removing alien vegetation, responsible for the uptake of large amounts of water from riparian zones, is one of the methods of maximising water supply in South Africa. Remote sensing is a cost- and time-effective technique for identifying alien vegetation in riparian zones and remote sensing data can be incorporated into a geographic information system (GIS) which can be used as a tool for the management of riparian zones. In this paper, vegetation identification and classification techniques by using aerial videography, aerial photography and satellite imagery, are assessed in terms of accuracy and cost for a small subcatchment in the KwaZulu-Natal midlands. This was achieved by incorporating the data obtained from aerial videography, aerial photography and ground mapping into a GIS. Accuracies of the different techniques were then examined. Data obtained from satellite imagery were assessed independently using digital image decoding procedures. The costs of each technique were also determined and, together with the accuracy results, used to make recommendations for the most effective manner of identifying alien vegetation in riparian zones. The accuracy results obtained in this study indicate that using manual techniques to identify riparian vegetation from 1:10 000 black: and white aerial photographs yield the most accurate and cost-effective results. The least cost-effective data sources were found to be 1:10 000 colour aerial photographs and digital aerial photographs and the least accurate data sources were aerial videography and Landsat thematic mapper (TM) satellite imagery. DA - 1999-10 DB - ResearchSpace DP - CSIR KW - Alien vegetation KW - Riparian zones KW - Vegetation identification KW - Remote sensing KW - Catchments KW - Vegetation classification techniques KW - Water resources LK - https://researchspace.csir.co.za PY - 1999 SM - 0378-4738 T1 - Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones TI - Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones UR - http://hdl.handle.net/10204/2076 ER -