Conditional Estimation of Vector Patterns in Remote Sensing and GIS
AMSTERDAM UNIV (NETHERLANDS)
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Within this project report we provide the mathematical theory for the extraction of primary topographic vectors using Bayesian statistical models. In particular, this effort documents the mathematical foundations for the algorithms used within the C, C, and JAVA computer languages, and further describes the related mathematical techniques for the vector model and class structure. This final report also contains the remaining C-code elements for the processing of digital raster data into a composite vector model. While this research includes only the working prototypes and sample code elements, it is anticipated that Corps researchers will use these examples to refine their respective methods for use in water control, digital elevation modeling, and land use analysis.
- Operations Research