Urban vegetation mapping using sub-pixel analysis and expert system rules: A critical approach

Since the traditional hard classifier can label each pixel only with one class, urban vegetation (e.g. trees) can only be recorded as either present or absent. The sub-pixel analysis that can provide the relative abundance of surface materials within a pixel may be a potential solution to effectivel...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of remote sensing Vol. 27; no. 13; pp. 2645 - 2665
Main Author Myint, S. W.
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 10.07.2006
Taylor and Francis
Subjects
Animal, plant and microbial ecology
Applied geophysics
Biological and medical sciences
Earth sciences
Earth, ocean, space
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Internal geophysics
Teledetection and vegetation maps
expert systems
data
Vegetation index
urban environment
Riparian vegetation
Classifier
trees
agriculture
solution
Gramineae
Limitation
rank
Wild plant
Procedure
Ecological abundance
Threshold
Reference
Plantae
urban areas
analysis
Vegetation map
correlation
Vegetation type
angiosperms
materials
Monocotyledoneae
Checklist
Spermatophyta
Pixel
Online AccessGet full text

Cover

More Information
Summary:Since the traditional hard classifier can label each pixel only with one class, urban vegetation (e.g. trees) can only be recorded as either present or absent. The sub-pixel analysis that can provide the relative abundance of surface materials within a pixel may be a potential solution to effectively identifying urban vegetation distribution. This study examines the effectiveness of a sub-pixel classifier with the use of expert system rules to estimate varying distributions of different vegetation types in urban areas. The Spearman's rank order correlation between the vegetation output and reference data for wild grass, man-made grass, riparian vegetation, tree, and agriculture were 0.791, 0.869, 0.628, 0.743, and 0.840 respectively. Results from this study demonstrated that the expert system rule using NDVI threshold procedure is reliable and the sub-pixel processor picked the signatures relatively well. This study reports a checklist of the sources of limitation in the application of sub-pixel approaches.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0143-1161
1366-5901
DOI:10.1080/01431160500534630