Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

Phinn, S. R., Stanford, M., Scarth, P. F., Shyy, T. and Murray, A. (2002) Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques. International Journal of Remote Sensing, 23 20: 4131-4153. doi:10.1080/01431160110114998


Author Phinn, S. R.
Stanford, M.
Scarth, P. F.
Shyy, T.
Murray, A.
Title Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques
Journal name International Journal of Remote Sensing   Check publisher's open access policy
ISSN 0143-1161
1366-5901
Publication date 2002-01-01
Sub-type Article (original research)
DOI 10.1080/01431160110114998
Volume 23
Issue 20
Start page 4131
End page 4153
Total pages 23
Place of publication London
Publisher Taylor and Francis
Language eng
Subject C1
291003 Photogrammetry and Remote Sensing
779905 Integrated (ecosystem) assessment and management
090905 Photogrammetry and Remote Sensing
Abstract The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.
Keyword Remote Sensing
Imaging Science & Photographic Technology
Remotely-sensed Imagery
Land-cover
Census-data
Spot Hrv
Classification
Integration
Area
Information
Morphology
Patterns
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
School of Architecture Publications
 
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Created: Wed, 15 Aug 2007, 03:43:26 EST