Abstract
Abstract. Glaciers, especially in mountain area are sensitive indicators of climate fluctuations and also contribute to present rates of sea level rise. In Central Asia, these glaciers are the primary resource for fresh water. Understanding the seasonal behavior of these glaciers would help to make efficient use of the available water reservoir. Different methods have been employed to study glacier displacements in past. The conventional survey techniques are very cost-intensive and highly depend on accessibility to high mountain glaciers also directs us to look for new ways to study these areas. Here remote sensing comes in handy with freely available data and a good coverage with high spatial and temporal resolution. Optical satellite imagery, available free can be effectively used for research purpose. The glacier in this region fed lake Karakul (380 km2), the largest Lake in Tajikistan. The objective is to study the displacement tendency of the Glacier in Pik Lenin area using Landsat 7 dataset. Normalized cross correlation algorithm has been implemented via CIAS to estimate the motion of glacier surface. A number of combination of reference block and search area size were tested for 30 m resolution dataset. As a result the specifications: reference block size of 15 pixels and search area size of 10 pixels was found out as the best set of parameters and considered for further processing. The study derives a reliable set of data depicting the velocities in the glacier which after post processing shows peak velocity of 121 m/y of the glacier.
Highlights
The Image matching is a group of techniques of finding corresponding features or image patches in two or more images taken of the same scene from different viewing positions, at different times and/or using different sensors
Image matching is used for a large variety of applications such as imageregistration, stereo parallax matching for generation of digital elevation models, particle image velocimetry (PIV), or displacement measurements (Brown, 1992; Westerweel, 1993; Zitová & Flusser, 2003)
The normalized crosscorrelation (NCC) algorithm has been used to investigate Earth mass movements such as glacier flow and land sliding in many empirical studies (e.g. Scambos et al, 1992;) NCC has been documented to be simple and reliable, a number of drawbacks have been reported as well ( Scambos et al, 1992;)
Summary
The Image matching is a group of techniques of finding corresponding features or image patches in two or more images taken of the same scene from different viewing positions, at different times and/or using different sensors. The group of area-based matching techniques is the most widely used method due to its relative simplicity (Zitová & Flusser, 2003). Cross-correlation, in its normalized form which accounts for brightness and contrast in image sequences, is the most widely used similarity measure of this method due to its reliability and simplicity (Lewis, 1995). For the measurement to be reliable the displacement has to be greater than the mean error of the image (co-)registration. Improving NCC precision, improves displacement accuracy two fold: by reducing the image co-registration error and by improving the matching accuracy directly. The study area is the highlands of Tajikistan and the surrounding high mountains, respectively. The goal is to study glacier dynamics in that area by feature tracking. Satellite-based systems allow multitemporal analysis of large glaciated areas
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