Knauer, Kim and Klein, Doris and Allsopp, Nicky and Baumhauer, Roland and Dech, Stefan (2011) Monitoring ecosystem health of Fynbos remnant vegetation in the City of Cape Town using remote sensing. In: SOUTH AFRICAN JOURNAL OF BOTANY, 77, p. 572. South African Association of Botanists – Annual Meeting, 2011-01-17 - 2011-01-19, Grahamstown, Südafrika. doi: 10.1016/j.sajb.2011.03.003.
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Official URL: http://www.sciencedirect.com/science/article/pii/S0254629911000160
Abstract
Sand Fynbos in and around the City of Cape Town has been reduced to fragments by urbanisation and agriculture. Further threats include exotic plant species. Invasive Port Jackson (Acacia saligna) is a major threat and grasses, both indigenous and alien, appear to be an alternative state on some Sand Fynbos sites. This study investigates if remote sensing can provide indicators for the rapid detection of vegetation state of remaining vegetation fragments. Productivity of the vegetation in response to rainfall is determined with the Enhanced Vegetation Index (EVI) at sites within or adjacent to the City of Cape Town which are of conservation interest. Terra MODIS EVI data with a spatial resolution of 250 m and precipitation data from 19 rainfall stations for the period 2000 – 2008 are analysed. In January 2010, fieldwork was undertaken to investigate the state and composition of the local vegetation. EVI data are correlated with the rainfall data. Within the scope of a flexible correlation, different lags of the reaction are analysed. Residual trends (RESTREND), the difference be- tween observed EVI and the one predicted by precipitation, are calculated. EVI response of Fynbos to rainfall is considerably lower than that of grasses or A. saligna, and grass response is highly seasonal. A. saligna has a higher EVI than Fynbos vegetation and shows a higher rain-use efficiency. With the specific characteristics of these indicators and the spectral signature of A. saligna, i.e. its unique reflectance over the course of the year, its distribution can be estimated. Remote sensing shows promise as a suitable instrument to assess the state of lowland fynbos fragments.
| Item URL in elib: | https://elib.dlr.de/105366/ | ||||||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||||||||||
| Title: | Monitoring ecosystem health of Fynbos remnant vegetation in the City of Cape Town using remote sensing | ||||||||||||||||||||||||
| Authors: |
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| Date: | January 2011 | ||||||||||||||||||||||||
| Journal or Publication Title: | SOUTH AFRICAN JOURNAL OF BOTANY | ||||||||||||||||||||||||
| Refereed publication: | No | ||||||||||||||||||||||||
| Open Access: | No | ||||||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||||||
| In SCOPUS: | No | ||||||||||||||||||||||||
| In ISI Web of Science: | Yes | ||||||||||||||||||||||||
| Volume: | 77 | ||||||||||||||||||||||||
| DOI: | 10.1016/j.sajb.2011.03.003 | ||||||||||||||||||||||||
| Page Range: | p. 572 | ||||||||||||||||||||||||
| Status: | Published | ||||||||||||||||||||||||
| Keywords: | Remote Sensing, Fynbos, Ecosystem Health, RESTREND | ||||||||||||||||||||||||
| Event Title: | South African Association of Botanists – Annual Meeting | ||||||||||||||||||||||||
| Event Location: | Grahamstown, Südafrika | ||||||||||||||||||||||||
| Event Type: | national Conference | ||||||||||||||||||||||||
| Event Start Date: | 17 January 2011 | ||||||||||||||||||||||||
| Event End Date: | 19 January 2011 | ||||||||||||||||||||||||
| Organizer: | Rhodes University | ||||||||||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||||||||||
| HGF - Program Themes: | Earth Observation | ||||||||||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||
| DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||||||
| DLR - Research theme (Project): | R - Geoscientific remote sensing and GIS methods | ||||||||||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||||||||||
| Institutes and Institutions: | German Remote Sensing Data Center | ||||||||||||||||||||||||
| Deposited By: | Knauer, Kim | ||||||||||||||||||||||||
| Deposited On: | 06 Sep 2016 13:16 | ||||||||||||||||||||||||
| Last Modified: | 24 Apr 2024 20:10 |
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