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 |
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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 -
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en_ZA |