Soil moisture measurement from remotely sensed images

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Soil moisture measurement from remotely sensed images

Objective

Field collected values of soil moisture from Theta probes are being used to calibrate transformations of Landsat Thematic mapper (TM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), Hyperion and airborne-collected hyperspectral images to create soil moisture values directly from the image radiances.

History

Originally funded by Land Remote Sensing (LRS) as a 3-year project.

Accomplishments

We continue to have a robust collaboration with many distinguished scientists at the U.S. Department of Agriculture (USDA), the Institute for Technology Development (ITD), the University of Georgia, and the University of Missouri - Rolla. We employed a Ph.D. student from the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL); this employee completed extensive field work associated with the goals of the project. In addition to satellite remote sensors, we have deployed a leading-edge airborne hyperspectal sensor and collected some unique datasets. Preliminary analyses show good correlations of measured soil moisture with a few specific bands in the infrared.

Results and outputs

The reported results of our technical approaches from various preliminary stages has resulted in a poster presented at the USGS Land Remote Sensing Science Fair, Reston, VA. In addition, we are preparing a paper for submission as a U. S. Geological Survey Open-File Report and a paper for submission to the journal Geosciences and Remote Sensing.

Current status (2007)

We have an extensive database of images from ASTER, TM, ALI, Hyperion, and airborne hyperspectral (collected under contract in fiscal year 2005 and fiscal year 2006) data over the test site in the Little River, Georgia, watershed. These images have been preprocessed including rectification to ground control, conversion of pixel values to reflectance and radiance, and generation of tasseled-cap transformations. Acquisition of an additional airborne hyperspectral image is now under contract.

Planned future work

In collaboration with our partners, the soil moisture values for the point samples from the theta probes are being scaled to pixel size (30 x 30 m) areas with in-field measurements of climate conditions, vegetation, soil and air moisture, and spectral reflectances, during airborne hyperspectral flights. These pixel area measurements will be compared to image reflectances and interpolated to a regional assessment of soil moisture. Through image transformations (including tasseled-cap and modified wetness calculations) and statistical analyses, such as canonical analysis and correlation, we hope to establish a capability to predict soil moisture values from image radiances. In association with USDA, ITD, NESPAL, and UGA, we will complete this project in fiscal year 2007.

Overview of the research projects

Although each project has its own specific objectives, approaches, context, and outcomes, certain concepts are common to them all. A short summary of these concepts is discussed below.

Geospatial data

The data for the long-term study of the Delaware River Basin primarily relies on the historical topographic maps the USGS published throughout the twentieth century. The primary challenges for building data bases from these sources include data categorization, its integration with other environmental or social data, and problems of resolving data captured at different scales. More specific discussion of these topics is available in a paper on methods for using historical USGS maps for environmental research. Where possible, the data files from these studies can be obtained via the Internet or by contacting the USGS contact person listed below. A graphic index of the quadrangle outlines (by latitude and longitude coordinates) and names together with the map edition timelines is available to assist the identification and selection of data files. Some supplementary data, described under the heading of the specific project, are also available.

Geospatial technologies for the study of temporal change

The data used in analyses of change with time require the support of logical concepts in space-time continuity in their methods of use. We are examining recent research on temporal change data models for the organization of disparate data sources with time for their effectiveness in representing structure of land-surface change the way we understand it.

Spatial analysis and modeling

Methods of spatial analysis test geographic data for statistically significant patterns, though the added variable of location causes these tests to differ from normal statistics. Besides widely accepted methods such as Regression and Dimensional Analysis, tests are applied to geographical point-pattern, network/path, and regional/shape structures. Some of the most important of these are spatial autocorrelation, accessibility and interaction, matrix analysis, and methods applied to spatially continuous data. Significant findings of spatial analysis lend their mathematical formalizations to statistical/mathematical modeling. The mathematical tests that are applied to organized empirical data are used for either explanatory or predictive (projection) purposes, but some modeling objectives also can be achieved through the topological manipulation of the map-like layers of geographical information systems (GIS).