Gourmelen, Noel

Rossi, B. E.

2019-11-18T15:33:05Z

2019-11-18T15:33:05Z

2019-11-26

Identifying glacial lakes in a given area is a common preliminary step in glacial lake research, especially in relation to glacial lake outburst flooding and how it can be monitored, mitigated, and measured for hazard risk. While more traditional methods of acquiring this data requires field work and manually recording data, it is becoming increasingly common to use remote sensing and geographical information sciences to remotely extract lake locations using satellite imagery, especially in areas with rugged terrain and harsh environments. The Karakoram Mountains are among such environments, where satellite imagery could become obstructed by shadows, ice, snow, and clouds, causing false classification of glacial lakes. This project ultimately introduces the Glacial Lake Identifier (GLIDER), a python-scripted geoprocessing tool for ArcGIS, and tests it on data from Shimshal, located in Pakistan’s region of the Karakoram Mountains. Based off the methodology of Li and Sheng (2012), GLIDER combines slope and hillshade calculations from a digital elevation model with a Normalized Difference Water Index from Landsat data to classify the most likely locations of glacial lakes. Leading up to the creation of GLIDER, the project also addresses the following research objectives: testing the ArcGIS suite for versatility, evaluating the compatibility of the methods to a range of Landsat missions, and exploring the performance of a python-scripted geoprocessing tool.

https://hdl.handle.net/1842/36252

en

The University of Edinburgh

ArcGIS

Glacial Lakes

Glaciology

GIS

Remote Sensing

Glacial lake identification using the ArcGIS Suite

Thesis or Dissertation

Masters

MSc Master of Science