Conditional Estimation of Vector Patterns in Remote Sensing and GIS

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 06, 2000
Accession Number
ADA383811

Entities

People

  • J. M. Masuch

Organizations

  • University of Amsterdam

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Computational Science
  • Data Sets
  • Equations
  • Information Science
  • Mathematical Models
  • Models
  • Pattern Recognition
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Recognition
  • Remote Sensing
  • Simulations

Readers

  • Computational Modeling and Simulation
  • Database Systems and Applications
  • Statistical inference.

Technology Areas

  • AI & ML