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Morphological Characteristics of Shrub Coppice Dunes in Desert Grasslands of Southern New Mexico derived from Scanning LIDAR

Author:
Rango, A., Chopping, M., Ritchie, J., Havstad, K., Kustas, W., Schmugge, T.
Source:
Remote sensing of environment 2000 v.74 no.1 pp. 26
Subject:
grasslands, vegetation structure, spatial data, remote sensing, lidar, shrublands, shrubs, rangelands, multispectral imagery, Prosopis, dunes, deserts, New Mexico
Abstract:
Since the 1880s rangeland vegetation in southern New Mexico has changed dramatically over widespread areas, typically with shrublands displacing native grasslands. Coincident with these changes in vegetation dominance are increases in soil erosion, stream channel cutting, and shrub coppice dune formation on sandy soils. Where marked transitions in vegetation type from grassland to honey mesquite shrubland have occurred, the local topography has been transformed with previously flat mesa becoming rolling duneland. The size, distribution, and morphological characteristics of these dunes have an important impact on fluxes of energy and nutrients at the surface; they also render the land far less useful as grazing land for domestic livestock. These shrub coppice dunes and the mesquite shrubs that grow on them may be considered roughness elements. Quantifying their morphology is important for the calculation of aerodynamic roughness length and displacement height. This article tests the ability of active scanning laser remote sensing techniques to provide accurate estimates of the three-dimensional shapes and areal distributions of dune and interdune areas. It shows that scanning laser with a footprint diameter of 0.38 m and a sampling interval of 1.5 m to 2 m can be used to measure the morphological characteristics of shrub coppice dunes in the desert grasslands of southern New Mexico with acceptable accuracy and precision for a range of uses, including important geomorphological and hydrological applications. The use of scanning laser systems together with optical multispectral data is shown to be highly synergistic, providing information that is not easily obtainable via other surveying methods.
Agid:
37431
Handle:
10113/37431