Spatial and temporal monitoring of glacial surfaces and their linkages with glacier lake formation: a study of remote sensing methods to detect glacial crevasses

Authors: Saeideh Gharehchahi*, Texas State University - San Marcos, Jennifer L.R. Jensen, Texas State University
Topics: Remote Sensing, Mountain Environments, Climatology and Meteorology
Keywords: Glacial surfaces,crevasses, glacier lake formation,mountain glaciers, remote sensing
Session Type: Paper
Day: 4/4/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Buchanan, Marriott, Mezzanine Level
Presentation File: No File Uploaded

This study aims to monitor glacial lake formation and correlate it with surficial crevasse patterns and other geomorphic factors such as slope as well as debris-covered glacier faces versus debris-free areas. There is still a gap in utilizing remote sensing in detection and mapping of glacier faces, particularly remote sensing research that combines both optical and thermal bands. In addition, crevasse detection and potential implications and links with lake formation have been not been thoroughly addressed, especially for the European Alps. To fill this gap, we will develop a framework to monitor changes in the spatial and temporal patterns of glacier faces and the consequent lake formation using data from the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) of Landsat 8, and digital elevation models in glacier groups within the Bernese and Valais Alps in the southwestern part of Switzerland. Here, we observe the histograms and spectral profiles of OLI and TIRS bands and use the reflectance and at-sensor brightness temperature characteristics of these bands to select the appropriate band ratios in order to classify the glacier faces. To monitor lake formation, we create an inventory of the lakes and measure the rate of lake expansion, using ratioing and spectral indexing of multi-temporal Landsat imagery within two recent 10-year intervals. A better understanding of spatial and temporal characteristics of glacier surfaces can assist in modeling of the mountain landscapes without glaciers, and the potential lake formation sites for the early monitoring of glacier hazards.

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