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Woodward, R. H.

Publications and source records attributed to Woodward, R. H..

An Automated Method for Navigation Assessment for Earth Survey Sensors Using Island Targets

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalogue of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean colour sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Patt, F. S.↗

Automatic analysis of stereoscopic satellite image pairs for determination of cloud-top height and structure

Results are presented on an automatic stereo analysis of cloud-top heights from nearly simultaneous satellite image pairs from the GOES and NOAA satellites, using a massively parallel processor computer. Comparisons of computer-derived height fields and manually analyzed fields show that the automatic analysis technique shows promise for performing routine stereo analysis in a real-time environment, providing a useful forecasting tool by augmenting observational data sets of severe thunderstorms and hurricanes. Simulations using synthetic stereo data show that it is possible to automatically resolve small-scale features such as 4000-m-diam clouds to about 1500 m in the vertical.

Hasler, A. F.↗

Automatic analysis of stereoscopic GOES/GOES and GOES/NOAA image pairs for measurement of hurricane cloud top height and structure

Results are presented from a baseline study using an synthetic stereo image pair to test the Automatic Stereo Analysis (ASA) technique for reproducing cloud top structure. The ASA analysis, display, and calibration procedures are described. A GEO/LEO (GOES/NOAA AVHRR) image pair from Hurrican Allen in 1980 is used to illustrate the results that can be obtained using the ASA technique. Also, results are presented from applying the ASA technique to a GEO/GEO (GOES/GOES) image pair of Hurricane Gilbert in 1988.

Hasler, A. F.↗

Determining soil moisture from geosynchronous satellite infrared data - A feasibility study

Numerical modelling results are reported from a pilot study investigating the feasibility of developing a technique for daily soil moisture measurement throughout the world, based on GOES infrared data. A detailed one-dimensional boundary layer-surface-soil model was used in order to determine which physical parameters observable from GOES are most sensitive to soil moisture, and which are most effected by seasonal changes, atmospheric effects and vegetation cover. The results of the sensitivity test show that the mid-morning differential of surface temperature with respect to absorbed solar radiation is optimally sensitive to soil moisture. A case study comparing model results with GOES infrared data confirms the sensitivity of this parameter to soil moisture and also confirms the applicability of the model to predicting area-averaged surface temperature changes. Model measurements of soil moisture are expected to be most accurate for dry or marginal agricultural areas where drought is common. Sources of error, including the advection of clouds, are examined and methods of minimizing error are discussed.

Wetzel, P. J.↗

A case study on the application of geosynchronous satellite infrared data to estimate soil moisture

The use of GOES IR temperature data to estimate soil moisture content is discussed and demonstrated, modifying the procedure proposed by Wetzel et al. (1984) to provide for incorporation of independent measurements of vegetation biomass, geostrophic wind speed, and surface dewpoint. Data acquisition, processing, and the statistical approach employed are described; data for Kansas and Nebraska during a six-day period in July 1978 are analyzed; and a statistical relationship between observed surface temperature and antecedent precipitation index is established. The results are presented in tables, graphs, and maps, and the regression procedure is found to predict antecedent precipitation with statistically significant precision.

Woodward, R. H.↗