DocumentCode :
411062
Title :
Modeling and visualizing uncertainty in continuous variables predicted using remotely sensed data
Author :
Dungan, Jennifer L. ; Kao, David L. ; Pang, Alex
Author_Institution :
NASA Ames Res. Center, Moffett Field, CA, USA
Volume :
5
fYear :
2003
fDate :
2003
Firstpage :
3017
Abstract :
The use of remotely sensed images to map continuous biophysical variables, such as those related to terrestrial vegetation amount, sea surface temperature, and many other targets of NASA´s Earth Observing System (EOS), includes variable, parametric, positional, spatial support and structural sources of uncertainty. A complete description of uncertainty will lead to a probability distribution at each location, allowing the exploration of the spatial dimension of uncertainty, that is, where the field is not well quantified. To achieve this purpose, convenient visualization tools are required. We have produced such a tool, called PDFVis, that facilitates the display of probability density functions (pdfs) on a per-grid-cell basis. The density estimate from Monte-Carlo generated realizations is interactively displayed as well as parametric and non-parametric summaries of the pdf field (such as mean, median, quartiles, standard deviation, number of modes, and locations of modes.) Shaded surface renderings of pdfs along a transect can also be projected onto a plane. This tool will become more useful as richer descriptions of spatial uncertainty become available.
Keywords :
Earth; Monte Carlo methods; biophysics; geophysical prospecting; terrestrial atmosphere; vegetation mapping; Earth Observing System; Monte-Carlo methods; NASA; biophysical variables; density functions; exploration; probability density functions; remotely sensed images; sea surface; shaded surface renderings; standard deviation; terrestrial vegetation map; Data visualization; Displays; Earth Observing System; Ocean temperature; Predictive models; Probability distribution; Sea surface; Temperature sensors; Uncertainty; Vegetation mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
Print_ISBN :
0-7803-7929-2
Type :
conf
DOI :
10.1109/IGARSS.2003.1294666
Filename :
1294666
Link To Document :
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