Collaborative Research: Multisensor Approach Mapping of 2D and 3D Geologic Features from Remotely Sensed Imagery

Abstract

The goal of this research project was to develop, implement, and evaluate computational methods for extracting information from multiple sources of remotely sensed data for thematic and topographic mapping of geologic features. The research focused on three primary areas: Integration of multisource topographic information in a multiresolution framework; Development of supervised classification methods for multi spectral and hyperspectral data. Extraction of topographic features from multiple return LIDAR data acquired from airborne platforms. The project focused on the first two problems during the original three year study, which was augmented to conduct a two year intensive study of LIDAR and hyperspectral data for coastal mapping applications Summary descriptions of the methodologies and example results are provided.

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Document Details

Document Type
Technical Report
Publication Date
Sep 23, 2005
Accession Number
ADA440923

Entities

People

  • Melba M. Crawford

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Computational Science
  • Computer Science
  • Data Analysis
  • Detection
  • Detectors
  • Feature Extraction
  • High Resolution
  • Information Science
  • Lidar
  • Machine Learning
  • Partial Differential Equations
  • Pattern Recognition
  • Photography
  • Remote Sensing
  • Sea Level
  • Supervised Machine Learning
  • Synthetic Aperture Radar

Readers

  • Coastal Oceanography
  • Image Processing and Computer Vision.
  • Sensor Fusion and Tracking Systems.