Digital Extraction of Altitudinal Belt Spectra in the West Kunlun Mountains Using SPOT-VGT NDVI and SRTM DEM

In this paper, a digital identification method for the extraction of altitudinal belt spectra of montane natural belts is presented. Acquiring the sequential spectra of digital altitudinal belts in mountains at an acceptable temporal frequency and over a large area requires extensive time and work if traditional methods of field investigation are to be used. Such being the case, often the altitudinal belts of a whole mountain or the belts at a regional scale are represented by single points. However, single points obviously cannot accurately reflect the spatial variety of altitudinal belts. In this context, a digital method was developed to extract the spectra of altitudinal belts from remote sensing data and SRTM DEM in the We.st Kunlun Mountains. By means of the 4km resolution SPOT-4 vegetation 10-day composite NDVI, the horizontal distribution of altitudinal belts were extracted through supervised classification, with a total classification accuracy of 72.23%. Then, a way of twice-scan was used to realize the automatic transition of horizontal maps to vertical belts. The classification results of remote-sensing data could thus be transformed automatically to sequential spectra of digital altitudinal belts. The upper and lower lines of the altitudinal belts were then extracted by vertical scanning of the belts. Relationships between the altitudinal belts based on the montane natural zones concerning vegetation types and the geomorphological altitudinal belts discussed. As a tentative method, were also the digital extraction method presented here is effective at digitally identifying altitudinal belts, and could be helpful in rapid information extraction over large-scale areas.

Accuracy Improvement of ASTER Stereo Satellite Generated DEM Using Texture Filter

The grid DEM(digital elevation model) generation can be from any of a number of sources:for instance,analogue to digital conversion of contour maps followed by application of the TIN model,or direct elevation point modelling via digital photogrammetry applied to airborne images or satellite images.Currently,apart from the deployment of point-clouds from LiDAR data acquisition,the generally favoured approach refers to applications of digital photogrammetry.One of the most important steps in such deployment is the stereo matching process for conjugation point(pixel) establishment:very difficult in modelling any homogenous areas like water cover or forest canopied areas due to the lack of distinct spatial features.As a result,application of automated procedures is sure to generate erroneous elevation values.In this paper,we present and apply a method for improving the quality of stereo DEMs generated via utilization of an entropy texture filter.The filter was applied for extraction of homogenous areas before stereo matching so that a statistical texture filter could then be applied for removing anomalous evaluation values prior to interpolation and accuracy assessment via deployment of a spatial correlation technique.For exemplification,we used a stereo pair of ASTER 1B images.