Literature DB >> 35389121

Application of "OTSU"-an image segmentation method for differentiation of snow and ice regions of glaciers and assessment of mass budget in Chandra basin, Western Himalaya using Remote Sensing and GIS techniques.

Vinay Kumar Gaddam1,2, Ramya Boddapati3, Tanooj Kumar4, Anil V Kulkarni5, Helgi Bjornsson6.   

Abstract

In this study, an image segmentation algorithm ("OTSU") is applied for differentiation of snow/ice regions followed by interpretation of snowlines and estimation of mass budget of glaciers in Chandra basin, Western Himalaya, India between 2014 and 2020. The observations strongly suggest that the OTSU method can be used to differentiate the snow and ice regions on a glacier accurately from any satellite image, irrespective of the sensor characteristics. Also, this method suits well to delineate the snowlines for large sample of glaciers, other than the manual interpretation and semi-automated methods. The estimates of mass budget of the glaciers are observed varying from - 1.20 ± 0.51 m w.e to almost 0.64 ± 0.51 m w.e, with a total loss of - 61.91 ± 6.70 m w.e of ice mass at basin scale during the observation period. Based on this study, it is highly recommended the application of OTSU method for the differentiation of snow/ice zones of glaciers and snowline demarcation at a large spatial scale in the harsh weather rugged terrain of the Western Himalaya.
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Entities:  

Keywords:  Chandra basin; OTSU method; Snow line demarcation; Specific mass balance

Mesh:

Year:  2022        PMID: 35389121     DOI: 10.1007/s10661-022-09945-2

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  1 in total

1.  Performance and Robustness of Regional Image Segmentation Driven by Selected Evolutionary and Genetic Algorithms: Study on MR Articular Cartilage Images.

Authors:  Jan Kubicek; Alice Varysova; Martin Cerny; Kristyna Hancarova; David Oczka; Martin Augustynek; Marek Penhaker; Ondrej Prokop; Radomir Scurek
Journal:  Sensors (Basel)       Date:  2022-08-23       Impact factor: 3.847

  1 in total

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