TY - JOUR
T1 - A bottom-up approach to vegetation mapping of the Lake Tahoe Basin using hyperspatial image analysis
AU - Greenberg, Jonathan A.
AU - Dobrowski, Solomon Z.
AU - Ramirez, Carlos M.
AU - Tull, Jahatel L.
AU - Ustin, Susan L.
PY - 2006/5
Y1 - 2006/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33744929348&partnerID=8YFLogxK
U2 - 10.14358/PERS.72.5.581
DO - 10.14358/PERS.72.5.581
M3 - Article
AN - SCOPUS:33744929348
SN - 0099-1112
VL - 72
SP - 581
EP - 589
JO - Photogrammetric Engineering and Remote Sensing
JF - Photogrammetric Engineering and Remote Sensing
IS - 5
ER -