Kevin D Henry
Kevin Henry is a geographer with the USGS Western Geographic Science Center and is located at the USGS California Water Science Center in Sacramento, California.
Kevin Henry researches risk and vulnerability to natural hazards, using geographic information systems, agent-based modeling, and advanced data visualization techniques. His recent work involves visualizing hazard exposure and vulnerability analyses through emerging interactive web mapping frameworks. He also researches community vulnerability through modeling vehicular evacuation from tsunamis using agent-based simulation. The work aims to identify strategies to improve a community's capacity to evacuate, to inform emergency management practices.
Science and Products
Filter Total Items: 17
Threat prioritization framework and input data for a multi-hazard risk analysis for the U.S. Department of the Interior
An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This data supports an article that summarizes a new mixed-methods and
Community Exposure in California to Coastal Groundwater Hazards Enhanced by Climate Change, reference year 2020
The data set contains information on potential population, economic, land cover, and infrastructure groundwater inundation exposure for San Francisco Bay and coastal communities of the state of California, USA. The type of information includes U.S. Census data on the number and types of residents, Data Axle data on numbers and types of employees, county parcel values, HAZUS building replacement va
Community Exposure in California to Coastal Flooding Hazards Enhanced by Climate Change, reference year 2010
The data set contains information on potential population, economic, land cover, and infrastructure flooding exposure for San Francisco Bay and coastal communities of the state of California, USA. The type of information includes U.S. Census data on the number and types of residents, InfoGroup USA data on numbers and types of employees, county parcel values, HAZUS building replacement values, NLC
Influence of demand and capacity in transportation simulations of short-notice, distant-tsunami evacuations
Distant tsunamis require short-notice evacuations in coastal communities to minimize threats to life safety. Given the available time to evacuate and potential distances out of hazard zones, coastal transportation planners and emergency managers can expect large proportions of populations to evacuate using vehicles. A community-wide, short-notice, distant-tsunami evacuation is challenging because
Pedestrian tsunami evacuation results for three California probabilistic tsunami hazard zones and four travel speeds (shapefiles) and impaired walk travel times for all zones by parcel land-use and flow depth class (tables)
These datasets supports the conclusions in the journal article entitled "Variations in community evacuation potential related to average return periods in probabilistic tsunami hazard analysis" as described in the abstract below:
Tsunami risk management requires strategies that can address multiple sources with different recurrence intervals, wave-arrival times, and inundation extents. Probabilis
Science and Products
Filter Total Items: 17
Threat prioritization framework and input data for a multi-hazard risk analysis for the U.S. Department of the Interior
An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This data supports an article that summarizes a new mixed-methods and
Community Exposure in California to Coastal Groundwater Hazards Enhanced by Climate Change, reference year 2020
The data set contains information on potential population, economic, land cover, and infrastructure groundwater inundation exposure for San Francisco Bay and coastal communities of the state of California, USA. The type of information includes U.S. Census data on the number and types of residents, Data Axle data on numbers and types of employees, county parcel values, HAZUS building replacement va
Community Exposure in California to Coastal Flooding Hazards Enhanced by Climate Change, reference year 2010
The data set contains information on potential population, economic, land cover, and infrastructure flooding exposure for San Francisco Bay and coastal communities of the state of California, USA. The type of information includes U.S. Census data on the number and types of residents, InfoGroup USA data on numbers and types of employees, county parcel values, HAZUS building replacement values, NLC
Influence of demand and capacity in transportation simulations of short-notice, distant-tsunami evacuations
Distant tsunamis require short-notice evacuations in coastal communities to minimize threats to life safety. Given the available time to evacuate and potential distances out of hazard zones, coastal transportation planners and emergency managers can expect large proportions of populations to evacuate using vehicles. A community-wide, short-notice, distant-tsunami evacuation is challenging because
Pedestrian tsunami evacuation results for three California probabilistic tsunami hazard zones and four travel speeds (shapefiles) and impaired walk travel times for all zones by parcel land-use and flow depth class (tables)
These datasets supports the conclusions in the journal article entitled "Variations in community evacuation potential related to average return periods in probabilistic tsunami hazard analysis" as described in the abstract below:
Tsunami risk management requires strategies that can address multiple sources with different recurrence intervals, wave-arrival times, and inundation extents. Probabilis