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USGS2009

Ground and surface temperature variability for remote sensing of soil moisture in a heterogeneous landscape

At the Little River Watershed (LRW) heterogeneous landscape near Tifton Georgia US an in situ network of stations operated by the US Department of Agriculture-Agriculture Research Service-Southeast Watershed Research Lab (USDA-ARS-SEWRL) was established in 2003 for the long term study of climatic and soil biophysical processes. To develop an accurate interpolation of the in situ readings that can be used to produce distributed representations of soil moisture (SM) and energy balances at the landscape scale for remote sensing studies, we studied (1) the temporal and spatial variations of ground temperature (GT) and infra red temperature (IRT) within 30 by 30 m plots around selected network stations; (2) the relationship between the readings from the eight 30 by 30 m plots and the point reading of the network stations for the variables SM, GT and IRT; and (3) the spatial and temporal variation of GT and IRT within agriculture landuses: grass, orchard, peanuts, cotton and bare soil in the surrounding landscape. The results showed high correlations between the station readings and the adjacent 30 by 30 m plot average value for SM; high seasonal independent variation in the GT and IRT behavior among the eight 30 by 30 m plots; and site specific, in-field homogeneity in each 30 by 30 m plot. We found statistical differences in the GT and IRT between the different landuses as well as high correlations between GT and IRT regardless of the landuse. Greater standard deviations for IRT than for GT (in the range of 2-4) were found within the 30 by 30 m, suggesting that when a single point reading for this variable is selected for the validation of either remote sensing data or water-energy models, errors may occur. The results confirmed that in this landscape homogeneous 30 by 30 m plots can be used as landscape spatial units for soil moisture and ground temperature studies. Under this landscape conditions small plots can account for local expressions of environmental processes, decreasing the errors and uncertainties in remote sensing estimates caused by landscape heterogeneity.

Journal of Hydrology↗

USGS2008

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Journal of Hydrology↗