dc.contributor.author |
Lück-Vogel, Melanie
|
|
dc.contributor.author |
Mbolambi, C
|
|
dc.contributor.author |
Adams, J
|
|
dc.contributor.author |
Rautenbach, K
|
|
dc.date.accessioned |
2017-07-28T09:36:35Z |
|
dc.date.available |
2017-07-28T09:36:35Z |
|
dc.date.issued |
2015-04 |
|
dc.identifier.citation |
Lück-Vogel, M., Mbolambi, C., Adams, J. et al. 2015. Mapping coastal & estuarine vegetation using VHR satellite imagery in St Lucia. International CoastGIS Symposium Proceedings, Cape Town, 22 April 2015 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10204/9402
|
|
dc.description |
International CoastGIS Symposium Proceedings, Cape Town, 22 April 2015 |
en_US |
dc.description.abstract |
The iSimangaliso Wetland Park in which the St Lucia estuary is embedded hosts the largest estuarine system in Africa (155 000 Ha). Remote sensing mapping of the composition of the otherwise largely inaccessible estuarine vegetation provides a baseline for understanding and managing of estuarine environments. Within the presented project, we compared ecosystem and land cover classifications for the Greater St Lucia region derived from very high resolution (VHR) multispectral imagery from the RapidEye, WorldView-2 and SPOT-6 sensors with and without the additional use of LiDAR derived topographic data. As ground reference, a GIS-derived wetland classification based on site visits and aerial photos have been used. Results show that accuracies increase with higher spatial resolution, of both, the multispectral as well as the Li-DAR derived topographic data. |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.ispartofseries |
Worklist;19149 |
|
dc.subject |
St Lucia |
en_US |
dc.subject |
Vegetation mapping |
en_US |
dc.subject |
Remote sensing |
en_US |
dc.subject |
LIDAR |
en_US |
dc.title |
Mapping coastal & estuarine vegetation using VHR satellite imagery in St Lucia |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Lück-Vogel, M., Mbolambi, C., Adams, J., & Rautenbach, K. (2015). Mapping coastal & estuarine vegetation using VHR satellite imagery in St Lucia. http://hdl.handle.net/10204/9402 |
en_ZA |
dc.identifier.chicagocitation |
Lück-Vogel, Melanie, C Mbolambi, J Adams, and K Rautenbach. "Mapping coastal & estuarine vegetation using VHR satellite imagery in St Lucia." (2015): http://hdl.handle.net/10204/9402 |
en_ZA |
dc.identifier.vancouvercitation |
Lück-Vogel M, Mbolambi C, Adams J, Rautenbach K, Mapping coastal & estuarine vegetation using VHR satellite imagery in St Lucia; 2015. http://hdl.handle.net/10204/9402 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Lück-Vogel, Melanie
AU - Mbolambi, C
AU - Adams, J
AU - Rautenbach, K
AB - The iSimangaliso Wetland Park in which the St Lucia estuary is embedded hosts the largest estuarine system in Africa (155 000 Ha). Remote sensing mapping of the composition of the otherwise largely inaccessible estuarine vegetation provides a baseline for understanding and managing of estuarine environments. Within the presented project, we compared ecosystem and land cover classifications for the Greater St Lucia region derived from very high resolution (VHR) multispectral imagery from the RapidEye, WorldView-2 and SPOT-6 sensors with and without the additional use of LiDAR derived topographic data. As ground reference, a GIS-derived wetland classification based on site visits and aerial photos have been used. Results show that accuracies increase with higher spatial resolution, of both, the multispectral as well as the Li-DAR derived topographic data.
DA - 2015-04
DB - ResearchSpace
DP - CSIR
KW - St Lucia
KW - Vegetation mapping
KW - Remote sensing
KW - LIDAR
LK - https://researchspace.csir.co.za
PY - 2015
T1 - Mapping coastal & estuarine vegetation using VHR satellite imagery in St Lucia
TI - Mapping coastal & estuarine vegetation using VHR satellite imagery in St Lucia
UR - http://hdl.handle.net/10204/9402
ER -
|
en_ZA |