Mathematics – Logic
Scientific paper
Dec 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008agufm.c23a0589f&link_type=abstract
American Geophysical Union, Fall Meeting 2008, abstract #C23A-0589
Mathematics
Logic
0720 Glaciers, 0722 Rock Glaciers, 0798 Modeling
Scientific paper
Satellite-based remote sensing is critical for monitoring highly dynamic environments that include rapidly changing alpine glaciers, melt-water production, and a variety of natural hazards. Multi-spectral and multi- temporal satellite data in conjunction with digital elevation models can be utilized to assess supraglacial and proglacial lakes, valley impoundment water volumes, and the potential for flood and debris-flow hazards. Advanced remote sensing and GIS-based methodologies represent the only effective approach for periodic assessment and detection of glacier hazards using spatio-temporal data and analysis. Such approaches, however, do not address all of the requirements needed for the development of hazard/disaster warning systems and the generation of unique information to help establish mitigation strategies. Consequently, our objectives are to introduce the methods of fuzzy logic as an additional level of analysis and interpretation to demonstrate how intelligent, knowledge-driven algorithms can be used to assess glacier dynamics and glacier-induced hazards. Operational monitoring of dynamic environments and natural hazards will require multiple levels of analysis and information production using on-board automation. These systems must autonomously assess the hazard potential related to surface processes and the topography, while being able to identify disaster conditions. Such systems should (1) include analytical capabilities to permit automated and comprehensive identification, characterization, and quantification of terrain features (e.g., via Automated Global Feature Analyzer "AGFA"); (2) permit operational multi-scale hazard potential assessment (e.g., automatic global, regional and local assessment capabilities); and (3) permit data integration that fuses existing data and real-time data acquisition into a spatio-temporal framework that facilitates intelligent assessment and monitoring. The fuzzy logic framework may be an ideal approach that serves to represent the intelligent analysis requirement of an operation system because application domain knowledge can be represented in linguistic and numeric form, and can be easily incorporated into a conceptual and numerical model. Such fuzzy systems recently have been proposed as the basis for intelligent, autonomous, science- driven planetary reconnaissance, including systems specifically designed to assess the potential for habitability on Mars and Titan. Here we demonstrate the utility of remote sensing, GIS and fuzzy systems for operational assessment of glacier dynamics and glacier-induced hazards, with an emphasis on design and implementation examples.
Bishop Michael P.
Fink Wolfgang
Furfaro Roberto
Kargel Jeff S.
No associations
LandOfFree
Fuzzy Logic and Glacier Dynamics Assessment: New Paradigms for Operational Hazard Detection Systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Fuzzy Logic and Glacier Dynamics Assessment: New Paradigms for Operational Hazard Detection Systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fuzzy Logic and Glacier Dynamics Assessment: New Paradigms for Operational Hazard Detection Systems will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1233830