GLeSI: A system for extraction of glacial lakes using satellite imagery. (14th July 2022)

• Record Type: Journal Article
• Authors: Thati, Jagadeesh; Ari, Samit
• Is Part Of: Concurrency and computation. Volume 34:Number 23(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-07-14
• Subjects: glacial lakes -- modified normalized difference water index -- outburst susceptibility -- satellite image -- segmentation; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.7184
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: For outburst susceptibility assessment of glacial lakes, manual field survey is a time‐consuming, expensive, and very tedious process. Therefore, an automatic and reliable system is required for efficient extraction of glacial lake's from satellite imagery. Low spectral contrast and heterogeneous backgrounds of satellite images are the major challenges for finding information of the glacial lake's region. Therefore, to overcome these challenges, an automatic technique for extraction of glacial lakes using satellite imagery which is termed as GLeSI, is proposed in this article. In the GLeSI system, normalized cut ( Ncut ) segmentation technique with region adjacency graph and simple linear iterative clustering is proposed for accurate extraction of the glacial lake's region. The proposed system achieved an overall accuracy of 93.21%, 91.57%, 97.65% on Landsat 8 datasets for Imja, Chandra basin, and Bhaga basin glacier lake region, respectively. The qualitative and quantitative performance analysis shows the significant improvement of the proposed technique compared to state‐of‐the‐art techniques for extraction of glacial lake's region.