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ARS Home » Research » Publications at this Location » Publication #111600
Title: HYDROLOGICAL INFORMATION FROM TEMPERATURE AND REMOTE SENSING MEASUREMENTS

Author
item ZEHRFUHS, DIANE - UNIV OF S. CAROLINA
item LAKSHIMI, VENKAT - UNIV OF S. CAROLINA
item Jackson, Thomas

Submitted to: Sring Meeting American Geographical Union Washington DC
Publication Type: Abstract Only
Publication Acceptance Date: 4/12/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary: None.

Technical Abstract: Regional and global estimation of soil moisture requires the use of space-based sensors. Satellite data allows analysis on a variety of temporal and spatial scales. Field measurements of temperature and soil moisture were performed for the time period July 8-20, 1999, in the Little Washita Watershed, Chickasha, Oklahoma. In-situ observations of soil moisture are required for calibration and validation of model and other aircraft-based remotely sensed estimates. Initial results from this study have shown that surface temperature measurements taken with handheld InfraRed thermometers (IRT) and gravimetric soil moisture in the 0-2.5cm depth interval are related to each other based on surface, soil, and vegetation characteristics. A high correlation between the surface layer temperature and soil moisture will allow us to use satellite surface temperature data for making soil moisture interpretations. Specifically, we ecan use AVHRR and/or TOVS data for regional moisture estimates. The surfac temperature collected during this experiment will be compared to estimates from TOVS, AVHRR, and GOES satellite sensors. Surface temperature was observed in a 400m x 400m field at various spatial grid spacing such as 50m, 10m, and 1m over a 15-day time period in order to quantify the changes in spatially distributed behavior of surface temperature during a drydown period and to see the spatial resolution of the remote sensing devices used during this study. The correlation of temperature with soil moisture, as well as with other meteorological data, is vital for future efforts involving these parameters at regional scales using remote sensing techniques.