DocumentCode
576407
Title
Object based data fusion of landform and ancillary data for upscaling soil-landscape mapping in the western Australian pastoral rangelands
Author
Wilson, D. ; Corner, R. ; Schut, T.
Author_Institution
Dept. of Spatial Sci., Curtin Univ., Bentley, WA, Australia
fYear
2012
fDate
22-27 July 2012
Firstpage
7569
Lastpage
7572
Abstract
We have investigated methods to derive landform and vegetation data from a Digital Elevation Model and remote sensing, using classification and segmentation. These data are required to upscale existing regional level landsystem mapping to a higher spatial and thematic resolution (subsystems). In turn the land subsystem data will be used to support rangeland condition mapping in a large area of leasehold rangeland. The derived landform and vegetation classes have been tested against available landsystem mapping derived by conventional methods and have shown promising relationships. These classifications need to be further revised prior to their use in either an object based or probabilistic classifier.
Keywords
data assimilation; digital elevation models; geomorphology; geophysics computing; pattern classification; probability; remote sensing; vegetation; DEM; ancillary data; data classification; data segmentation; digital elevation model; land subsystem data; landform data; object based classifier; object based data fusion; probabilistic classifier; rangeland condition mapping; regional level landsystem mapping; remote sensing; soil landscape map upscaling; vegetation data; western Australian pastoral rangelands; Australia; Digital elevation models; Earth; Remote sensing; Satellites; Soil; Vegetation mapping; Digital Elevation Models; Geographic Information Systems; Land surface; Remote Sensing;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6351910
Filename
6351910
Link To Document