Estimates of bare ground and vegetation cover from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) short-wave-infrared reflectance imagery

Gill, tony and Phinn, Stuart R. (2008) Estimates of bare ground and vegetation cover from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) short-wave-infrared reflectance imagery. Journal of Applied Remote Sensing, 2 Article 023511: 1-19. doi:10.1117/1.2907748

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Author Gill, tony
Phinn, Stuart R.
Title Estimates of bare ground and vegetation cover from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) short-wave-infrared reflectance imagery
Journal name Journal of Applied Remote Sensing   Check publisher's open access policy
ISSN 1931-3195
Publication date 2008-03-20
Year available 2008
Sub-type Article (original research)
DOI 10.1117/1.2907748
Open Access Status File (Publisher version)
Volume 2
Issue Article 023511
Start page 1
End page 19
Total pages 19
Editor Dr Wei Gao
Place of publication Bellingham, WA, United States
Publisher SPIE - International Society for Optical Engineering
Language eng
Abstract The high level of success of estimating photosynthetic vegetation from multispectral satellite sensors at regional scales has not been repeated for non-photosynthetic vegetation and bare ground. Therefore regional scale estimates of total vegetation from multispectral sensors are largely underestimated with implications for a wide range of agricultural and environmental applications. Recent research using simulated data showed that the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) had the potential to provide reliable estimates of bare ground and total vegetation. This study built on that research and found that estimates of bare ground retrieved from ASTER short-wave infrared imagery using linear spectral unmixing correlated well with field measurements (RMSE < 0.1, r(2) > 0.7). Image endmember libraries required for spectral unmixing were extracted from the image data using a combination of field knowledge and the lignin and cellulose absorption index. The most reliable results were found by applying a sum-constraint to the unmixing models and tying the signatures at wavebands that corresponded to cellulose or clay-hydroxyl absorption features. The results of this research show that ASTER can improve the estimates of total vegetation extracted from satellite imagery for environmental studies at regional scales.
Keyword bare ground
Lignin and Cellulose Absorption (LCA) index
Monte-Carlo Spectral Mixture Analysis (MCSMA)
vegetation cover
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2009 Higher Education Research Data Collection
School of Geography, Planning and Environmental Management Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 11 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 14 times in Scopus Article | Citations
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Created: Fri, 03 Apr 2009, 19:34:04 EST by Helen Smith on behalf of School of Geography, Planning & Env Management