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Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones

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dc.contributor.author Rowlinson, LC en_US
dc.contributor.author Summerton, M en_US
dc.contributor.author Ahmed, F en_US
dc.date.accessioned 2007-03-26T13:54:39Z en_US
dc.date.accessioned 2007-06-07T10:09:15Z
dc.date.available 2007-03-26T13:54:39Z en_US
dc.date.available 2007-06-07T10:09:15Z
dc.date.copyright en_US
dc.date.issued 1999-10 en_US
dc.identifier.citation Rowlinson, 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 497-500 en_US
dc.identifier.issn 0378-4738 en_US
dc.identifier.uri http://hdl.handle.net/10204/2076 en_US
dc.identifier.uri http://hdl.handle.net/10204/2076
dc.description.abstract 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. en_US
dc.format.extent 41022 bytes en_US
dc.format.mimetype application/pdf en_US
dc.language.iso en en_US
dc.publisher Water Research Commission en_US
dc.rights Copyright: 1999 Water Research Commission en_US
dc.source en_US
dc.subject Alien vegetation en_US
dc.subject Riparian zones en_US
dc.subject Vegetation identification en_US
dc.subject Remote sensing en_US
dc.subject Catchments en_US
dc.subject Vegetation classification techniques en_US
dc.subject Water resources en_US
dc.title Comparison of remote sensing data sources and techniques for identifying and classifying alien invasive vegetation in riparian zones en_US
dc.type Article en_US
dc.identifier.apacitation Rowlinson, 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/10204/2076 en_ZA
dc.identifier.chicagocitation Rowlinson, 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/10204/2076 en_ZA
dc.identifier.vancouvercitation Rowlinson 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. en_ZA
dc.identifier.ris 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 - en_ZA


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