Updated Frequency: 10 minutes

Status	Color Hex Value	Color Name	Color	Description
NORMAL	#FFFFFF	White		No active public safety incidents.
EVACUATION WARNING	#E5C447	Yellow		Potential threat to life and/or property. Those who require additional time to evacuate, and those with pets and livestock should leave now.
EVACUATION ORDER	#D37072	Red		Immediate threat to life. This is a lawful order to leave now. The area is lawfully closed to public access.

Inventory of Counties whose Evacuation Order information is publicly shared by Cal OES through the California Active Evacuation Zones feature service.

This feature service is an aggregation of multiple California County Evacuation Zone services, and Genasys. The schema used mirrors the Zonehaven Schema. This service is fully updated every 10 minutes. During the update, there may be a brief period (~1 min) where the service is rebuilding and not all features are visible.Updated Frequency: 10 minutesContact: gissupport@caloes.ca.govSymbologyStatusColor Hex ValueColor NameColorDescriptionNORMAL#FFFFFFWhiteNo active public safety incidents.EVACUATION WARNING#E5C447YellowPotential threat to life and/or property. Those who require additional time to evacuate, and those with pets and livestock should leave now.EVACUATION ORDER#D37072RedImmediate threat to life. This is a lawful order to leave now. The area is lawfully closed to public access.SHELTER IN PLACE#BF6ADCPurpleGo indoors. Shut and lock doors and windows. Prepare to self-sustain until further notice and/or contacted by emergency personnel for additional direction.CLEAR TO REPOPULATE#90D260GreenIt is now safe to return to your home post evacuation.ADVISORY#6A95CBBlueBe on alert and follow county recommendations.

Note: This layer is a registered copy of the source evacuation layer hosted by California Dept. of Technology. To view the source layer, click here.This feature service consolidates active Evacuation Warning and Order zone information from various California county services, and Genasys. Please note that this data is provided as-is and is for reference only. For detailed information on Evacuation Warning and Order zones, please contact the respective county directly. Updated Frequency: 10 minutesContact: gissupport@caloes.ca.govSymbologyStatusColor Hex ValueColor NameColorDescriptionNORMAL#FFFFFFWhite No active public safety incidents.EVACUATION WARNING#E5C447YellowPotential threat to life and/or property. Those who require additional time to evacuate, and those with pets and livestock should leave now.EVACUATION ORDER#D37072RedImmediate threat to life. This is a lawful order to leave now. The area is lawfully closed to public access.SHELTER IN PLACE#BF6ADCPurpleGo indoors. Shut and lock doors and windows. Prepare to self-sustain until further notice and/or contacted by emergency personnel for additional direction.CLEAR TO REPOPULATE#90D260GreenIt is now safe to return to your home post evacuation.ADVISORY#6A95CBBlueBe on alert and follow county recommendations.Inventory of Counties whose Evacuation Order information is publicly shared by Cal OES through the California Active Evacuation Zones feature service.

Landslide evacuation zones, which represent the areas from which material is removed by landslide processes, have been mapped offshore of Southern California. Polygons were mapped from visual interpretation of high-resolution multibeam echosounder data (MBES) and single-beam echosounder data.

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. Probabilistic tsunami hazard analysis (PTHA) provides a structured way to integrate multiple sources, including the uncertainties due to the natural variability and limited knowledge of sources. PTHA-based products relate to specific average return periods (ARP) and while there has been considerable attention paid to ARP choice for building codes, guidance on ARP choice to support evacuation planning and related land-use is lacking. We use the State of California (USA) coastal communities as a case study to explore the use of geospatial analysis and pedestrian-evacuation modeling for comparing the societal implications of tsunamis based on evacuation areas that reflect 475-year, 975-year, and 2,475-year ARPs. Results demonstrate that changes in PTHA ARP had a substantial effect on the number of taxlot parcels in tsunami evacuation areas, but not on the primary land-use of these parcels or which communities had the highest number of exposed parcels. Composite PTHA maps provided high-level insights on hazard exposure and identified dominant sources; however, disaggregated PTHA outputs that reflect single source parameters (e.g., wave-arrival time) were necessary to quantify evacuation potential from local and distant tsunamis. Framing changes in ARP assumption based on changes in the number, land-use type, and potential evacuation challenges of parcels in evacuation areas can provide valuable insight on the real-world implications of which ARP to use in land-use or evacuation planning.

Source Item: https://calema.maps.arcgis.com/home/item.html?id=15fb71971c7246338440d39b9f158bd7The data for this feature service is derived from the CalOES feed indicated at the source item above, which compiles evacuation zone data from multiple local services into a single feed. Since the CalOES feed is a live service showing currently active evacuation orders and warnings, this historic feature service was developed by merging the backups of the live service run daily at 3AM Pacific Time. This database maintains all field headings, field values, and feature polygons of the original CalOES service while adding an EFFECTIVE_DATE_R9 date field to indicate the day and hour that the backup script was run. In order to isolate a specific period of active evacuations, apply a filter to the EFFECTIVE_DATE_R9 field.This service is currently in development. At this time it consists of evacuation data starting January 7th 2025 and is updated daily with the most recent daily backup.

This feature service is an aggregation of multiple California County Evacuation Zone services that are being refreshed every 10 minutes. We are NOT receiving California County Evacuation Zone Data from Zonehaven. The schema used mirrors the Zonehaven Schema. This service is fully updated every 10 minutes from county sources. During the update, there may be a brief period (~1 min) where the service is rebuilding and not all features are visible.

These maps show predictions for the estimated maximum extent of inundation for a LOCAL Cascadia tsunami (YELLOW) for all of Oregon and Washington overlaid on Google Maps. For portions of the Oregon coast only (e.g. currently Bandon to OR/CA border and Cannon Beach), these maps show TWO inundation lines: the estimated maximum extent of inundation for a LOCAL Cascadia tsunami (YELLOW) and a DISTANT tsunami (ORANGE). The entire Pacific coast including Puget Sound, are vulnerable to DISTANT tsunamis even if not depicted on this map. Sections of the coast marked by diagonal lines are currently unmapped, but are also vulnerable to tsunamis - Be vigilant and know what to do when at the coast.

The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS. 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 bridge or nobridge name in the map title identifies whether bridges were represented in the modeling or whether they were removed prior to modeling to estimate the impact on travel times from earthquake-damaged bridges.

The risk of natural disasters, many of which are amplified by climate change, requires the protection of emergency evacuation routes to permit evacuees safe passage. California has recognized the need through the AB 747 Planning and Zoning Law, which requires each county and city in California to update their - general plans to include safety elements from unreasonable risks associated with various hazards, specifically evacuation routes and their capacity, safety, and viability under a range of emergency scenarios. These routes must be identified in advance and maintained so they can support evacuations. Today, there is a lack of a centralized database of the identified routes or their general assessment. Consequently, this proposal responds to Caltrans’ research priority for “GIS Mapping of Emergency Evacuation Routes.†Specifically, the project objectives are: 1) create a centralized GIS database, by collecting and compiling available evacuation route GIS layers, and the safety eleme..., The project used the following public datasets: • Open Street Map. The team collected the road network arcs and nodes of the selected localities and the team will make public the graph used for each locality. • National Risk Index (NRI): The team used the NRI obtained publicly from FEMA at the census tract level. • American Community Survey (ACS): The team used ACS data to estimate the Social Vulnerability Index at the census block level. Then the author developed a measurement to estimate the road network performance risk at the node level, by estimating the Hansen accessibility index, betweenness centrality and the NRI. Create a set of CSV files with the risk for more than 450 localities in California, on around 18 natural hazards. I also have graphs of the RNP risk at the regional level showing the directionality of the risk., , # Data from: Improving public safety through spatial synthesis, mapping, modeling, and performance analysis of emergency evacuation routes in California localities

https://doi.org/10.5061/dryad.w9ghx3g0j

Description of the data and file structure

For this project’s analysis, the team obtained data from FEMA's National Risk Index, including the Social Vulnerability Index (SOVI).

To estimate SOVI, the team used data from the American Community Survey (ACS) to calculate SOVI at the census block level.

Using the graphs obtained from OpenStreetMap (OSM), the authors estimated the Hansen Accessibility Index (Ai) and the normalized betweenness centrality (BC) for each node in the graph.

The authors estimated the Road Network Performance (RNP) risk at the node level by combining NRI, Ai, and BC. They then grouped the RNP to determine the RNP risk at the regional level and generated the radial histogram. Finally, the authors calculated each ana...

Following the 2018 Carr Wildfire, an online survey was distributed by researchers from the University of California, Berkeley to collect information on the individual choices of those impacted by the fires in the Redding, California area. Collected from March to April 2019, the data includes questions regarding risk perceptions, communications, evacuation decisions, potential usage of the sharing economy in disasters, opinions of evacuation management, and demographic information. The survey was distributed with the assistance of local partners (i.e., transportation agencies, emergency management agencies, local city and county governments, CBOs, and news outlets). Partners were allowed to post the survey using electronic communication methods including but not limited to: Facebook, Twitter, Nextdoor, agency websites, news websites, email listservs, and alert subscription services. The survey received 647 valid responses, of which 338 were completed. Subsequent papers using this data retained 284 cleaned survey responses for discrete choice modeling, based on the respondents' completion of key choice and demographic questions. The survey was incentivized with the chance to win one of ten $200 gift cards. The survey questions are included in a separate Word document.

We request that those who download the data send a courtesy email to the lead author, Dr. Stephen Wong (swong1392@gmail.com). To ensure that any new research makes unique contributions to knowledge and does not duplicate past analyses, users are requested to read and cite publications using this data including:

Wong, S., Broader, J., Walker, J. & Shaheen, S. (2021). Understanding California Wildfire Evacuee Behavior and Joint Choice-Making. Retrieved from https://escholarship.org/uc/item/4fm7d34j

Wong, S., Walker, J., & Shaheen, S. (2020). Role of Trust and Compassion in Resource Sharing in Evacuations: A Case Study of the 2017 and 2018 California Wildfire. International Journal of Disaster Risk Reduction. https://www.sciencedirect.com/science/article/abs/pii/S2212420920314023

Wong, S., Broader, J., Shaheen, S. (2020). Review of California Wildfire Evacuations from 2017 to 2019. Retrieved from https://escholarship.org/uc/item/5w85z07g

Wong, S. & Shaheen, S. (2019). Current State of the Sharing Economy and Evacuations: Lessons from California. SB 1 Report. Retrieved from https://escholarship.org/uc/item/16s8d37x

Additional framing work on evacuations can be found here:

Wong, S. (2020). Compliance, Congestion, and Social Equity: Tackling Critical Evacuation Challenges through the Sharing Economy, Joint Choice Modeling, and Regret Minimization. University of California, Berkeley. Dissertation. https://escholarship.org/uc/item/9b51w7h6

The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS. 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 bridge or nobridge name in the map title identifies whether bridges were represented in the modeling or whether they were removed ...

A dashboard used in this web application showing the latest information of wildfires that WFTIIC is tracking, along with fire perimeters and active evacuation zones.California Active Wildfires are sourced from IRWIN and is updated every 15 minutes when new data is available. A WFTIIC tracked incident is defined as a fire that is <100 percent contained and it's origin is within the state of California.Fire Perimeter data is sourced from the Esri Living Atlas feed, which is aggregated from the National Interagency Fire Center (NIFC) dataset. For more information, see this feature layer.

During a declared emergency event, this file represents an aggregated dataset that shows all of the active Orders and Alerts in the Province as initiated by the Local Governments or First Nations. When an Order or Alert is rescinded, its status changes to All Clear. The polygon is removed from this layer and copied to the Historical Orders and Alerts dataset.

A map used in Know Your Zone application to display information about evacuation zones and, optionally evacuation notice information.

The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS. 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 bridge or nobridge name in the map title identifies whether bridges were represented in the modeling or whether they were removed prior to modeling to estimate the impact on travel times from earthquake-damaged bridges.

Due to the mixed distribution of buildings and vegetation, wildland-urban interface (WUI) areas are characterized by complex fuel distributions and geographical environments. The behavior of wildfires occurring in the WUI often leads to severe hazards and significant damage to man-made structures. Therefore, WUI areas warrant more attention during the wildfire season. Due to the ever-changing dynamic nature of California's population and housing, the update frequency and resolution of WUI maps that are currently used can no longer meet the needs and challenges of wildfire management and resource allocation for suppression and mitigation efforts. Recent developments in remote sensing technology and data analysis algorithms pose new opportunities for improving WUI mapping methods. WUI areas in California were directly mapped using building footprints extracted from remote sensing data by Microsoft along with the fuel vegetation cover from the LANDFIRE dataset in this study. To accommodate the new type of datasets, we developed a threshold criteria for mapping WUI based on statistical analysis, as opposed to using more ad-hoc criteria as used in previous mapping approaches. This method removes the reliance on census data in WUI mapping, and does not require the calculation of housing density. Moreover, this approach designates the adjacent areas of each building with large and dense parcels of vegetation as WUI, which can not only refine the scope and resolution of the WUI areas to individual buildings, but also avoids zoning issues and uncertainties in housing density calculation. Besides, the new method has the capability of updating the WUI map in real-time according to the operational needs. Therefore, this method is suitable for local governments to map local WUI areas, as well as formulating detailed wildfire emergency plans, evacuation routes, and management measures.

The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS. 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 bridge or nobridge name in the map title identifies whether bridges were represented in the modeling or whether they were removed prior to modeling to estimate the impact on travel times from earthquake-damaged bridges.

This dataset displays areas of the city vulnerable to damage from likely tsunami scenarios and displays what can be considered hazard zones of inundation. This data was created by SFDEM in 2015 based on data provided by the following agencies, and informs evacuation procedures: California Geological Survey and California Governor’s Office of Emergency Services. This was used for the 2019 HCR update process. However, this does not reflect the 2021 California Geological Survey, the California Governor's Office of Emergency Services, and AECOM update to the Tsunami Hazard zone. That can be found here:

Produced collectively by geologic hazard mapping scientists, and emergency planning specialists from the California Geological Survey, the California Governor’s Office of Emergency Services, and local agencies, organizations, and other stakeholders. The tsunami hazard evacuation areas were developed for all populated areas at risk to tsunamis in California and are based on the tsunami hazard defined in the Tsunami Inundation Maps for Emergency Planning. While the State assisted in the development of the evacuation areas, local agencies, organizations, and other stakeholders made the final determination on the location and coverage of these evacuation areas as they will be used for evacuation planning at the community level.