Accurate prediction of bird species richness patterns in an urban environment using Landsat-derived NDVI and spectral unmixing

Bino, G., Levin, N., Darawshi, S., Van Der Hal, N., Reich-Solomon, A. and Kark, S. (2008) Accurate prediction of bird species richness patterns in an urban environment using Landsat-derived NDVI and spectral unmixing. International Journal of Remote Sensing, 29 13: 3675-3700. doi:10.1080/01431160701772534


Author Bino, G.
Levin, N.
Darawshi, S.
Van Der Hal, N.
Reich-Solomon, A.
Kark, S.
Title Accurate prediction of bird species richness patterns in an urban environment using Landsat-derived NDVI and spectral unmixing
Journal name International Journal of Remote Sensing   Check publisher's open access policy
ISSN 0143-1161
1366-5901
Publication date 2008-01-01
Year available 2008
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1080/01431160701772534
Open Access Status Not yet assessed
Volume 29
Issue 13
Start page 3675
End page 3700
Total pages 26
Place of publication Abingdon, Oxfordshire, United Kingdom
Publisher Taylor and Francis
Language eng
Subject 1903 Computers in Earth Sciences
Abstract Urban landscapes are expanding rapidly and are reshaping the distribution of many animal and plant species. With these changes, the need to understand and to include urban biodiversity patterns in research and management programmes is becoming vital. Recent studies have shown that remote sensing tools can be useful in studies examining biodiversity patterns in natural landscapes. The present study aimed to explore whether remote sensing tools can be applied in biodiversity research in an urban landscape. More specifically, the study examined whether the Landsat-derived Normalized Difference Vegetation Index (NDVI) and linear spectral unmixing of urban land cover can predict bird richness in the city of Jerusalem. Bird richness was sampled in 40 1-ha sites over a range of urban environments in 329 surveys. NDVI and the per cent cover of built-up area were strongly and negatively correlated with each other, and were both very successful in explaining the number of bird species in the study sites. Mean NDVI in each site was positively correlated with the site bird species richness. A hump-shaped relationship between NDVI and species richness was observed (when calculated over increasing spatial scales), with a maximum value (Pearson's R=0.87, p0.001, n=40) at a scale of 15ha. We suggest that remote sensing approaches may provide planners and conservation biologists with an efficient and cost-effective method to study and estimate biodiversity across urban environments that range between densely built-up areas, residential neighbourhoods, urban parks and the peri-urban environment.
Formatted abstract
Urban landscapes are expanding rapidly and are reshaping the distribution of many animal and plant species. With these changes, the need to understand and to include urban biodiversity patterns in research and management programmes is becoming vital. Recent studies have shown that remote sensing tools can be useful in studies examining biodiversity patterns in natural landscapes. The present study aimed to explore whether remote sensing tools can be applied in biodiversity research in an urban landscape. More specifically, the study examined whether the Landsat‐derived Normalized Difference Vegetation Index (NDVI) and linear spectral unmixing of urban land cover can predict bird richness in the city of Jerusalem. Bird richness was sampled in 40 1‐ha sites over a range of urban environments in 329 surveys. NDVI and the per cent cover of built‐up area were strongly and negatively correlated with each other, and were both very successful in explaining the number of bird species in the study sites. Mean NDVI in each site was positively correlated with the site bird species richness. A hump‐shaped relationship between NDVI and species richness was observed (when calculated over increasing spatial scales), with a maximum value (Pearson's R = 0.87, p<0.001, n = 40) at a scale of 15 ha. We suggest that remote sensing approaches may provide planners and conservation biologists with an efficient and cost‐effective method to study and estimate biodiversity across urban environments that range between densely built‐up areas, residential neighbourhoods, urban parks and the peri‐urban environment. 
Keyword Agricultural Landscapes
Ecological Applications
Assessing Biodiversity
Biotic Homogenization
Community Composition
Vegetation Indexes
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: School of Geography, Planning and Environmental Management Publications
School of Biological Sciences Publications
 
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