Predicting Soil Strength with Remote Sensing Data

Abstract

Predicting soil strength from hyperspectral imagery enables amphibious planners to determine trafficability in the littorals. Trafficability maps can then be generated and used during the intelligence preparation of the battlespace allowing amphibious planners to select a suitable landing zone. In February and March 2010, the Naval Research Laboratory sponsored a multi-sensor remote sensing and field calibration and field validation campaign (CNMI'10). The team traveled to the islands of Pagan, Tinian, and Guam located in the Marianas archipelago. Airborne hyperspectral imagery along with ground truth data was collected from shallow water lagoons, beachfronts, vegetation, and anomalies such as World War II relics. In this thesis, beachfront hyperspectral data obtained on site was used as a reference library for evaluation against airborne hyperspectral data and ground truth data in order to determine soil strength for creating trafficability maps. Evaluation of the airborne hyperspectral images was accomplished by comparing the reference library spectra to the airborne images. The spectral angle between the reference library and airborne images was calculated producing the trafficability maps amphibious planners can use during the intelligence preparation of the battlespace.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2010
Accession Number
ADA531603

Entities

People

  • Jon T. Wende

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Counter WMD
  • Ground and Sea Platforms
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Bearing Strength
  • Data Analysis
  • Detectors
  • Electromagnetic Spectra
  • Geographic Information Systems
  • Hyperspectral Imagery
  • Jet Propulsion
  • Measurement
  • Military Research
  • Modulus Of Elasticity
  • Physical Properties
  • Remote Sensing
  • Second World War
  • Shallow Water
  • Spectra
  • Statistical Analysis
  • United States

Readers

  • Atmospheric Remote Sensing.
  • Pavement Materials Engineering.
  • Urban Planning and Geography.