--> Abstract: GIS and Remote Sensing for “Cradle to Grave” Hurricane Impact Assessment, by David Streit, Cynthia Dacre, Eric Wemmelmann, and Curtis Joyce; #90078 (2008)

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GIS and Remote Sensing for “Cradle to Grave” Hurricane Impact Assessment

David Streit, Cynthia Dacre, Eric Wemmelmann, and Curtis Joyce
MDA Federal Inc, Rockville, MD

GIS, meteorological, and remote sensing methods allow a “cradle-to-grave” approach for the energy industry to prepare for and recover from hurricanes. The results of these tools are used in assessing local and regional impacts on production; refining and pipeline operations; and in evaluating changes in regional energy supplies and demand.

Well ahead of a storm, satellite-derived imagery and layers such as elevation data, land cover, and first responder locations can be built into a GIS and used to identify and fortify areas of potential vulnerability. Just prior to storm impact, gridded mesoscale weather modeling from the National Weather Service are used to develop probabilistic risk assessments of key energy producing and processing locations (i.e., what specific area and what percent of production is at risk from the predicted path of a Category 3 hurricane-force winds).

During a storm event, observation sites are used to make ground-truth estimates of impact. Because radar data can be obtained through cloud cover, it can be used to start evaluating the extent of flooding even as the rain is still falling. Following a storm, various combinations of GIS tools, image data, and meteorological data are used for storm-damage assessment. For example, rapid infrastructure and environmental damage assessment at various scales is made by comparing multispectral satellite images from different dates after “normalizing” them for factors such as different vegetation phases (Cross Correlation Assessment). Meteorological data and GIS queries identify potential “choke points” where damaged infrastructure could affect fuel transportation. In addition, local or regional weather-related changes in energy usage (for example, due to a damaged manufacturing segment) may be identified.

 

AAPG Search and Discovery Article #90078©2008 AAPG Annual Convention, San Antonio, Texas