DocumentCode
2131585
Title
Remotely sensed vegetation cover in the Land Data Assimilation Systems project
Author
Cosgrove, Brian A. ; Houser, Paul R.
Author_Institution
SAIC Gen. Sci. Corp., Greenbelt, MD, USA
Volume
5
fYear
2001
fDate
2001
Firstpage
2079
Abstract
Over the past decade, remotely sensed vegetation datasets have become increasing detailed and accurate. We examine the impact of such data sets on LDAS land surface modeling through several experiments utilizing the Mosaic LSM. Simulations were conducted using 1 degree ISLSCP data and 1 kilometer EROS data over Oklahoma, and results were compared to soil moisture and soil temperature information available from the Oklahoma Mesonet network of instruments
Keywords
geophysical signal processing; geophysical techniques; hydrological techniques; vegetation mapping; ISLSCP; LDAS; Land Data Assimilation Systems; Mosaic LSM; Oklahoma; USA; United States; geophysical measurement technique; hydrology; land surface modeling; remote sensing; soil moisture; soil temperature; vegetation cover; vegetation mapping; Agriculture; Data assimilation; Land surface; Land surface temperature; Linear discriminant analysis; NASA; Predictive models; Soil moisture; Tiles; Vegetation mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location
Sydney, NSW
Print_ISBN
0-7803-7031-7
Type
conf
DOI
10.1109/IGARSS.2001.977909
Filename
977909
Link To Document