Back to Search
Start Over
Assessing Glacier Boundaries in the Ala-Archa Valley of Kyrgyzstan by Using Sentinel-1 SAR Dataset and High-Resolution UAV Imagery
- Source :
- Remote Sensing, Vol 15, Iss 4, p 1131 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- The significant retreat of glaciers in terms of climate change compels researchers to increase the frequency of studies regarding the transformations occurring in glacier boundaries. In this study, we provided glacier area delineation of Ala-Archa valley glaciers by using a Sentinel-1 SAR dataset and the InSAR Coherence technique. Since glaciers have specific patterns of movement, the low coherence method signals the presence of ice. The analysis used the pair of Sentinel-1 datasets for the summer, to ensure the lowest coherence and provide an areal estimation during the peak of ablation. The independence of the SAR images from cloud and light conditions permits us to acquire the images in a timely manner, which highly affects the results of glacier monitoring. This method has shown high potential in the mapping of debris-covered ice and the indication of dead ice. To identify and separate areas of low coherence, such as glacier lakes and unstable slopes, we used object-based mapping by using the geomorphological features of the ice. In this study, we defined a coherence value of less than 0.3 in the glacier area. Our research identified a number of 56 glaciers within the study area of 31.45 km2 and obtained highly accurate glacier maps for the glaciers with a smooth terminus. The analysis shows that automatic and manual delineation of the glaciers’ boundaries have certain limitations, but using the advantages of both scientific approaches, further studies will generate more accurate results.
- Subjects :
- Sentinel-1
InSAR coherence
glacier inventory
UAV
Science
Subjects
Details
- Language :
- English
- ISSN :
- 15041131 and 20724292
- Volume :
- 15
- Issue :
- 4
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.87dd32873ef4f08b4caa59c555ed049
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs15041131