Bottom-up Approach to Vegetation Mapping of the Lake Tahoe Basin Using Hyperspatial Image Analysis

Increasing demands on the accuracy and thematic resolution of vegetation community maps from remote sensing imagery has created a need for novel image analysis techniques. We present a case study for vegetation mapping of the Lake Tahoe Basin which fulfills many of the requirements of the Federal Ge...

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Bibliographic Details
Published in:Photogrammetric engineering and remote sensing 2006-05, Vol.72 (5), p.581-589
Main Authors: Greenberg, Jonathan A, Dobrowski, Solomon Z, Ramirez, Carlos M, Tuil, Jahalel L, Ustin, Susan L
Format: Article
Language:English
Subjects:
Animal, plant and microbial ecology
Applied geophysics
Biological and medical sciences
digital images
Earth sciences
Earth, ocean, space
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
hyperspectral imagery
image analysis
Internal geophysics
lakes
spatial data
Teledetection and vegetation maps
thematic maps
vegetation cover
vegetation types
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Summary:Increasing demands on the accuracy and thematic resolution of vegetation community maps from remote sensing imagery has created a need for novel image analysis techniques. We present a case study for vegetation mapping of the Lake Tahoe Basin which fulfills many of the requirements of the Federal Geographic Data Committee base-level mapping (FGDC, 1997) by using hyperspatial Ikonos imagery analyzed with a fusion of pixel-based species classification, automated image segmentation techniques to define vegetation patch boundaries, and vegetation community classification using querying of the species classification raster based on existing and novel rulesets. This technique led to accurate FGDC physiognomic classes. Floristic classes such as dominance type remain somewhat problematic due to inaccurate species classification results. Vegetation, tree and shrub cover estimates (FGDC required attributes) were determined accurately. We discuss strategies and challenges to vegetation community mapping in the context of standards currently being advanced for thematic attributes and accuracy requirements.
ISSN:0099-1112
2374-8079
DOI:10.14358/PERS.72.5.581