|Title||Fractal modeling of airborne laser altimetry data|
|Publication Type||Journal Article|
|Year of Publication||1997|
|Authors||Pachepsky Y, Ritchie J., Gimenex D|
|Journal||Remote Sensing of Environment|
|Keywords||article, articles, JORNEX, remote sensing, journal, journals, landscape, surface roughness, laser altimetry, surface roughness, remote sensing, airborne laser altimetry, remote sensing, JORNEX, remote sensing, surface roughness, technique, airborne laser altimetry, technique, remote sensing, water balance, remote sensing|
Airborne laser altimetry is a remote sensing technique that can provide high resolution data on the roughness of the landscape both for estimating water balance components and for distinguishing between landscapes. Models of the scale-dependent roughness are needed to find scales most appropriate for these purposes. Our objectives were to apply fractal scaling to high-resolution profiling laser altimetry data and to determine fractal parameters fro differentiating land cover. Data were collected at the USDA-ARS Jornada Experimental Range in New Mexico over grass-dominated and shrub-dominated sites along four transects at each site. Scale-dependent root-mean-square (RMS) roughness and data power spectrums were computed from 100,000 data points (~2 km) from each transect. A linearity measure and piecewise linear approximation were applied to find intervals of the fractal scaling. The RMS roughness data had two intervals of self-affine fractal scaling on grass transects and four such intervals on shrub transects. Reduction in the number of data points did not lead to a decrease in roughness but caused a smoothing dependency of fractal dimension on scale. Ten- and hundred-meter scales were appropriate for distinguishing between grass and shrub transects on the basis of fractal dimensions. Published by Elsevier Science Inc.
|Reprint Edition||In File (05/07/01)|