Concepts for Sensor Data Fusion to Detect Vegetation Stress and Implications on Ecosystem Health Following Hurricane Katrina

Abstract

Forest ecosystems, in particular forest wetlands, are very dynamic and offer many ecological benefits because of their complex floral and faunal assemblages. It is important to understand these interactions, thus improving the ability to sustain this precious resource, and as stewards, pass it on. In addition, response to various natural influences, such as severe weather events, is also a vital part of understanding ecosystem health. It is important to quantify not only the obvious, visible damage but also the ambiguous stress these systems have undergone as a result of sustained wind damage. Satellite and airborne-based remote sensing (particularly imagery) are well-established methods for monitoring and assessing large-scale forest damage and are currently used to quantify visible damage. This research establishes proof of concept techniques for fusing sensor data from multiple remote sensing platforms to better understand the requirements needed to characterize subtle damage to forest environments impacted by hurricanes, in this case Hurricane Katrina. These advanced techniques may provide an indication of such vegetation stress before becoming visibly detectable, thus essentially predicting stress induced mortality before it occurs. This information can be used in formulating mitigation practices in riparian areas and along streams to help reduce sediment intake due to erosion from loss of vegetation, thus improving water quality.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2008
Accession Number
ADA489597

Entities

People

  • George T. Raber
  • Jerry A. Griffth
  • Mark R. Graves
  • Sam S. Jackson

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Biomedical
  • Space

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Data Fusion
  • Discriminant Analysis
  • Ecosystems
  • Environment
  • Ground Based
  • High Resolution
  • Hurricanes
  • Hyperspectral Imagery
  • Lidar
  • Remote Sensing
  • Standards
  • Statistics
  • Three Dimensional
  • Vegetation
  • Waveforms

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Riverine Ecology
  • Systems Analysis and Design

Technology Areas

  • Space