Science Inventory

Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery - PRK

Citation:

HALL, R., R. L. Watkins, D. T. HEGGEM, K. Jones, P. R. KAUFMANN, S. B. Moore, AND S. J. Gregory. Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery - PRK. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, 159:63-83, (2009).

Impact/Purpose:

Structural physical habitat attributes include indices of stream size, channel gradient, substrate size, habitat complexity, and riparian vegetation cover and structure.

Description:

Structural physical habitat attributes include indices of stream size, channel gradient, substrate size, habitat complexity, and riparian vegetation cover and structure. The Environmental Monitoring and Assessment Program (EMAP) is designed to assess the status and trends of ecological resources at different scales. High-resolution remote sensing provides unique capabilities in detecting a variety of features and indicators of environmental health and condition. LIDAR is an airborne scanning laser system that provides data on topography, channel dimensions (width, depth), slope, channel complexity (residual pools, volume, morphometric complexity, hydraulic roughness), riparian vegetation (height and density), dimensions of riparian zone, anthropogenic alterations and disturbances, and channel and riparian interaction. Hyperspectral aerial imagery offers the advantage of high spectral and spatial resolution allowing for the detection and identification of riparian vegetation and natural and anthropogenic features at a resolution not possible with satellite imagery. When combined, or fused, these technologies comprise a powerful geospatial data set for assessing and monitoring lentic and lotic environmental characteristics and condition.

URLs/Downloads:

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Record Details:

Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Product Published Date: 12/01/2009
Record Last Revised: 02/10/2010
OMB Category: Other
Record ID: 203124