This data release is comprised of a set of six time travel map shapefiles (two tsunami evacuation zones and three travel times) and three population exposure by travel time tables (residents, employees, and hotel visitors). The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS (https://geography.wr.usgs.gov/science/vulnerability/tools.html). The travel time analysis uses ESRI's Path Distance tool to find the shortest distance across a cost surface from any point in the hazard zone to a safe zone. This cost analysis considers the direction of movement and assigns a higher cost to steeper slopes, based on a table contained within the model. The analysis also adds in the energy costs of crossing different types of land cover, assuming that less energy is expended walking along a road than walking across a sandy beach. To produce the time map, the evacuation surface output from the model is grouped into 1-minute increments for easier visualization. The times in the attribute table represent the estimated time to travel on foot to the nearest safe zone at the speed designated in the map title. The file name indicates whether the map is of the standard or extreme evacuation zone used by the City and County of Honolulu and which travel speed was used in the modelling (impaired, slow, or fast walk). The resident exposure by travel time dataset contains O'ahu resident count estimates as a function of travel time out of the standard and extreme tsunami-evacuation zones for three different travel speeds (impaired, slow, and fast walk). The data are organized in a manner which permits summarizing or visualizing the data by tsunami-evacuation zone and/or travel time, with communities listed across the top as columns and individual rows representing the number of residents present in the specific evcuation zone/travel time combination. Due to the nature of the methodology used to distribute residential population to structures, resident numbers are not integers. This dataset is intended for use in the U.S. Geological Survey's O'ahu, HI tsunami evacuation web page (https://geography.wr.usgs.gov/science/vulnerability/oahuEvacDashboard.html). The employee exposure by travel time dataset contains O'ahu employee count estimates as a function of travel time out of the standard and extreme tsunami-evacuation zones for three different travel speeds (impaired, slow, and fast walk). The data are organized in a manner which permits summarizing or visualizing the data by business classification (community support, dependent-care, emergency service, infrastructure, public venue, and remaining businesses), at-risk population-serving facility type (adult assistance services, child services, correctional facilities, medical and health services, medical center, and schools), tsunami-evacuation zone, and/or travel speed, with business details and evacuation zone/travel speed combinations listed across the top as columns and individual rows representing unique businesses' details and the number of employees working for a specific business in the different evacuation zone/travel speed combinations. This dataset is intended for use in the U.S. Geological Survey's O'ahu, HI tsunami evacuation web page (https://geography.wr.usgs.gov/science/vulnerability/oahuEvacDashboard.html). The hotel visitor exposure by travel time dataset contains O'ahu hotel visitor estimates as a function of travel time out of the standard and extreme tsunami-evacuation zones for three different travel speeds (impaired, slow, and fast walk). The data are organized in a manner which permits summarizing or visualizing the data by tsunami-evacuation zone and/or travel time, with communities listed across the top as columns and individual rows representing the number of hotel visitors present in the specific evacuation zone/travel time combination. These data support the following publication: Wood, N.J., Jones, J.L., Peters, J., and Richards, K., 2018, Pedestrian-evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawai'i: International Journal of Disaster Risk Reduction, v. 28, p. 271–283, https://doi.org/10.1016/j.ijdrr.2018.03.009.