Developing Innovative Geospatial Techniques for Assessing the Surface in Alpine Settings: San Juan Mountains, Co and Patagonia Ice Field, Argentina
Abstract
Geospatial technology has rapidly developed over the past ten years and is making substantial impacts in geomorphology. The new techniques, which have been developed, require high computational ability to produce in-depth analysis, accurate mapping, and precise characterization of details. Thus, geospatial technology is an excellent technology for completing sophisticated tasks in geomorphology. Unfortunately, existing commercial software coupled with traditional geomorphological methods do not adequately satisfy the demands of geomorphologists today. In addition, current geospatial technology consistently lags behind the technology advancement in other relevant domains (e.g., computer vision and digital image processing). It also appears many geomorphologists because of their lack of training in computational programming skills, are forced to use only commercially available software. Unfortunately, this leads to inadequate and incomplete analysis because many of the commercial software, in many instances, are too generalized to address specific geomorphological problems. To overcome the above-mentioned limitations in geomorphologic studies, this dissertation focuses on designing multiple, innovative geospatial algorithms for mapping and studying in the alpine and glacial environments.
The objective of this dissertation was to 1) develop an ANN (artificial neural network) based protocol to map basic geomorphology in the alpine and glacial environments; 2) create a protocol by using graph theory with object-oriented analysis to quantify changes in the surface structure of glaciers.
Two study sites were selected for this research: the San Juan Mountains in Southwestern Colorado and the Southern Patagonia Ice Field, Argentina. Results from the ANN analysis of the San Juan Mountains suggest that the combination of ANN and innovative topographic indices can facilitate the geomorphology mapping in alpine settings.
Secondly, this dissertation focused on two glaciers in Patagonia: the Glacier Perito Moreno (GPM) and Glacier Ameghino (GA) for the period 2000-2011, which was the best available DEMs to study the area. GPM has been stable since the first in situ field measurement in Patagonia, whereas GA has been retreating during the same time. Thus, this dissertation suggests that a stable terminus does not necessarily represent a stable supra-glacier surface structure or a decrease in the dynamic activities of a glacier. The result suggests that the surface structure of GPM has more rapidly transitioned into a more fragmented system when compared to GA. Four underlying reasons could account for this contrasting pattern: solar panel effect, prehistorical landslide relict, glacier orientation shift, and AAR (accumulation area ratio) difference. Both glaciers are located side-by-side and flow in the same direction.
This dissertation does not diminish the need for field work but does facilitate study of areas of extreme accessibility.
Citation
Zhao, Panshu (2021). Developing Innovative Geospatial Techniques for Assessing the Surface in Alpine Settings: San Juan Mountains, Co and Patagonia Ice Field, Argentina. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /196310.