Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer displays POST`s relative non-residential structures exposure rank. A relative exposure of structures within the hazard extent is calculated based on the US National Grid System (USNG) as the unit of analysis, in a spatial resolution of either 1km2 and 5km2. Structures are extracted from the Federal Emergency Management Agency (FEMA) USA Structures dataset, which includes footprints for all structures (buildings) greater than 450 square feet in the United States and its territories, and classified into nine non-residential occupancy types (Agriculture/rural; Commercial (offices); Commercial (retail); Exempt, Government and Historical; Heavy industrial and Transportation/Communication; Industrial (general); Miscellaneous; Recreation; Vacant land). Non-residential structures that overlap with the hazard extent are selected (notes: (1) the displayed occupancy types may vary between POST runs and hence, not all occupancy types may be accounted for; (2) for floods and hurricanes, a flood or surge depth threshold is set to select the most impacted structures). Next, the selected structures are overlaid with the impacted USNG grid cells and the number of structures (in total and per occupancy type) is calculated for each USNG cell. Relative exposure scores are assigned to each cell using the Jenks Natural Breaks Classification (Optimization) system. These scores range between 1 and 5, with 1 being the highest score. A high score signifies a cell with a large number of structures compared to all impacted USNG cells. </SPAN></P><P><SPAN /></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Ran Goldblatt, Ph.D.</SPAN></P><P><SPAN>Chief Scientist</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>Ran.Goldblatt@NLTGis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P></DIV>
exposurescore_heavyindustria
(
type: esriFieldTypeSmallInteger, alias: Exposure score: Heavy Industrial and Transportation / Communication structures
)
Description: <DIV STYLE="text-align:Left;font-size:12pt"><DIV><P><SPAN>This layer displays POST`s relative residential structures exposure rank. A relative exposure of residential structures within the hazard extent is calculated based on the US National Grid System (USNG) as the unit of analysis, in a spatial resolution of either 1km2 and 5km2. First, residential structures that overlap with the hazard extent are selected (note: for floods and hurricanes, a flood or surge depth threshold is set to select the most impacted structures, i.e., structures where a high flood or surge depth is predicted or measured). Residential structures are extracted from the Federal Emergency Management Agency (FEMA) USA Structures dataset, which includes footprints for all structures (buildings) greater than 450 square feet in the United States and its territories. Next, the number of residential structures within each impacted USNG cell is calculated and a relative residential structures exposure score is assigned to each cell using a Jenks Natural Breaks Classification (Optimization) system. This score ranges between 1 and 5, where 1 is the highest score. A high score signifies a cell with a large number of residential structures compared to all impacted USNG cells. </SPAN></P><P><SPAN /></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Ran Goldblatt, Ph.D.</SPAN></P><P><SPAN>Chief Scientist</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>Ran.Goldblatt@NLTGis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P></DIV></DIV>
Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer displays POST`s relative Food, Water and Shelter impacts. The layer reports shelters open, population in open shelters, the shelter capacity per county, shelters closed, and the capacity of shelters at a percentage value when activated for an event. This data is pulled from the NSS Shelter Service: FEMA ESF#6 Shelter System (formerly known as the FEMA National Shelter System.) Disclaimer: The NSS does not always provide the real time data in day to day scenarios. Team is currently working on finding a real time data source for shelter updates at the national level.</SPAN></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Brooke Hatcher, M.S.</SPAN></P><P><SPAN>Lead Geospatial Consultant</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>brooke.hatcher@nltgis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>U.S. Counties (Generalized) represents the counties of the United States in the 50 states and the District of Columbia.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>U.S. Counties (Generalized) represents the counties of the United States in the 50 states and the District of Columbia.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer shows the number of cell tower outages by county and the percentage out for the county. The data is provided daily during an incident from FCC Disaster Information Reporting System (DIRS) and aggregated to the county level.</SPAN></P><P><SPAN>DIRS is a voluntary, web-based system through which the Commission collects operational status and restoration information from communications providers during major disasters and subsequent recovery efforts. DIRS provides communications providers with a single, coordinated, consistent process to report their communications infrastructure status information during disasters. DIRS collects infrastructure status information from wireline, wireless, broadcast, cable, interconnected VoIP, and broadband service providers. </SPAN></P><P><SPAN>DIRS activations typically precede an anticipated major emergency, like a major hurricane, or follow an unpredictable disaster. The FCC announces DIRS activations through public notices and emails to DIRS participants. The announcements list the counties covered in the activation and provide reporting and contact information. These announcements will also note whether the FCC will suspend its rules on network outage reporting for DIRS participants during the DIRS activation period.</SPAN></P><P><SPAN /></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Brooke Hatcher, M.S.</SPAN></P><P><SPAN>Lead Geospatial Consultant</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>brooke.hatcher@nltgis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P></DIV>
Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer displays POST`s relative Transportation Lifeline impact rank, with the US National Grid System (USNG) as the unit of analysis, in a spatial resolution of either 1km2 and 5km2. First, USNG cells within the impacted area are selected. Then, using data from Waze (https://www.waze.com/) we calculate for each impacted cell (1) the number of traffic alerts and (2) the total length of each road segment multiplied by its reported traffic jam level (1 to 4; referred to as traffic jams impact). A percentile rank approximation procedure is used to calculate a relative Transportation impact score for each impacted cell based on (1) the number of traffic alerts in a given cell relative to all impacted cells and (2) the traffic jams impact in a given cell relative to all impacted cells. A Jenks Natural Breaks Classification (Optimization) system is used to calculate a Transportation impact score (for each cell, relative to all impacted cells). The impact score ranges between 1 to 5, with 1 signifying the highest impact (i.e., cells with the largest number of traffic alerts or largest traffic jams impact). </SPAN></P><P><SPAN /></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Ran Goldblatt, Ph.D.</SPAN></P><P><SPAN>Chief Scientist</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>Ran.Goldblatt@NLTGis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P></DIV>
Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer displays POST`s relative population exposure rank. The relative exposure of the population is calculated based on the US National Grid System (USNG) as the unit of analysis, in a spatial resolution of either 1km2 and 5km2. First, a Hazard Probability Score (HPS) is calculated for each unit of analysis based on either (i) hazard extent, (ii) the National Risk Index (NRI) or (iii) modeled / observed hazard data, weighted by the number of structures within a cell (utilizing the USA Structures dataset, which includes footprints for all structures (buildings) greater than 450 square feet in the United States and its territories). A high HPS signifies a cell with a relatively large number of structures that are most likely to be severely affected or damaged. To determine potential impacts on vulnerable populations, POST relies on socio-economic and demographic data made available by LandScan USA 2019 (Mohel, 2019) and collected by the American Community Survey (ACS) of the U.S. Census Bureau (e.g., number of elderly people, unemployment rate, number of people on public assistance or food stamps, number of mobile housing units). These data have been aggregated or disaggregated from the administrative block group or census tract division to the USNG division. POST then calculates a weighted Population Vulnerability Scores (PVS) for each affected USNG cell, which in turn, are translated into a relative population exposure rank (values range between 1 and 5, where 1 is the highest exposure rank). A high rank signifies cells that are (1) most likely to be severely affected by the hazard; (2) populated by a relatively large number of structures; and (3) where the most vulnerable population is most likely to be affected.</SPAN></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Ran Goldblatt, Ph.D.</SPAN></P><P><SPAN>Chief Scientist</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>Ran.Goldblatt@NLTGis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P><P><SPAN>References:</SPAN></P><P><SPAN>Moehl, J., Weber, E., Sims, K., Trombley, N., Weston, S., & Rose, A. (2020). LandScan USA 2019 [Data set]. Oak Ridge National Laboratory. https://doi.org/10.48690/1523374</SPAN></P><P><SPAN /></P></DIV>
Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer estimates the logistic commodities needed for the response to a given incident. The estimation process begins with the estimated exposed population in each USNG grid cell from the POST population model, visible here in the Population layer. Then, we estimate the vulnerable population using the Center for Disease Control (CDC) Social Vulnerability Index (SVI). Based on the vulnerable population and the number of days of incident response, we apply formulas from FEMA’s Office of Response and Recovery to approximate the number of key logistic commodities needed. These logistic commodities include requirements of meals, bottled water, plastic sheeting rolls, and blankets. For each commodity, we calculate both the total number and a relative priority score in each USNG grid cell. Priority scores range from 1 to 5, with 1 being the highest priority.</SPAN></P><P><SPAN /></P><P><SPAN>Data Sources </SPAN></P><P><SPAN>Center for Disease Control (CDC) Social Vulnerability Index (SVI)</SPAN></P><P><SPAN>Prioritizing Operations Support Tool (POST) model’s predictions</SPAN></P><P><SPAN>U.S. National Grid System (USNG)</SPAN></P><P><SPAN>United States Census TIGER</SPAN></P><P><SPAN /></P><P><SPAN /></P></DIV>
Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer displays POST`s relative Health and Medical Lifeline impact rank. A relative impact score is calculated based on the approximate number of health and medical facilities without electric power, with the US National Grid System (USNG) as the unit of analysis, in a spatial resolution of either 1km2 and 5km2. First, counties within the impacted area are selected, where the percentage of customers without power exceeds a user-defined threshold. County power data is based on the US Department of Energy EAGLE-I system, which automatically gathers electrical grid service status data from company websites every 15 minutes, and organizes it into an easy to read picture of electrical service status nationwide. USNG cells within the impacted counties are selected and the number of hospitals, nursing homes, urgent care facilities and dialysis centers are calculated for each impacted cell (per type and in total; data is extracted from HIFLD). A Jenks Natural Breaks Classification (Optimization) system is used to calculate a Health and Medical impact score for each cell, relative to all impacted cells. This impact score is calculated per health and medical facility type and for all facilities. The impact score ranges between 1 to 5, with 1 signifying the highest impact (i.e., cells with the largest number of health and medical facilities, relative to all impacted cells). </SPAN></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Ran Goldblatt, Ph.D.</SPAN></P><P><SPAN>Chief Scientist</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>Ran.Goldblatt@NLTGis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P></DIV>
Description: <DIV STYLE="text-align:Left;font-size:12pt"><P><SPAN>This layer displays POST`s relative Energy Lifeline impact score. A relative impact score is calculated based on the approximate number of people without electric power and the number of gas stations without fuel and/or power, with the US National Grid System (USNG) as the unit of analysis, in a spatial resolution of either 1km2 and 5km2. First, counties within the impacted area are selected, where at least one customer without power has been reported in the US Department of Energy EAGLE-I system. EAGLE-I automatically gathers electrical grid service status data from company websites every 15 minutes, and organizes it into an easy to read picture of electrical service status nationwide. The number of customers without power in each USNG cell is estimated based on the number of people in a cell at nighttime relative to the total number of people at nighttime in the overlapping county (population estimates based on LandScan data). All USNG cells with at least one customer (potentially) without power are selected. Next, utilizing GasBuddy data (https://www.gasbuddy.com/), the number of gas stations without fuel and / or power in each of these impacted cells is estimated and a relative impact score is calculated. The impact scores range between 1 and 5, with 1 signifying a high impact (for example, a relatively large number of gas stations without fuel and without power). </SPAN></P><P><SPAN /></P><P><SPAN /></P><P><SPAN /></P><P><SPAN /></P><P><SPAN>Contact Details</SPAN></P><P><SPAN>Ran Goldblatt, Ph.D.</SPAN></P><P><SPAN>Chief Scientist</SPAN></P><P><SPAN>New Light Technologies, Inc. (NLT)</SPAN></P><P><SPAN>https://NewLightTechnologies.com</SPAN></P><P><SPAN>Ran.Goldblatt@NLTGis.com</SPAN></P><P><SPAN /></P><P><SPAN>Adam Barker, Ph.D.</SPAN></P><P><SPAN>Geospatial Office | HQ Response</SPAN></P><P><SPAN>adam.barker@fema.dhs.gov</SPAN></P><P><SPAN /></P></DIV>