20260323 11573100 1.0 FALSE Building_Footprints 002 -104.068135 -97.157686 28.201763 32.084647 1 Geographic GCS_WGS_1984 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WKT>GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4326]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4326</WKID><LatestWKID>4326</LatestWKID></GeographicCoordinateSystem> 20260223 15532200 20260223 15532200 150000000 5000 dataset 20260223 File Geodatabase Feature Class Esri ArcGIS 13.3.0.52636 Building Footprints with Flooding Sources This layer shows building footprints to determine exposed buildings/property as locations of known exposure and a proxy for transient populations. <DIV STYLE="text-align:Left;"><DIV><DIV>TXGIO developed the Building Footprints using multiple sources including:<UL><LI>Microsoft Artificial Intelligence Version 2</LI><LI>Open Street Map (OSM) (July 2021 version)</LI><LI>LiDAR building footprints from 2010 to 2019</LI></UL>The August 2021 Building Footprints from TXGIO have been used as the spatial foundation for this 2025 dataset.Estimated Number of FloorsTXGIO determined building height and roof type from LiDAR data (where available) and then estimated the number of floors in the building. This number was then used in square footage calculations used for distributing Landscan population among buildings in each Landscan cell. Estimated Floors are provided in the Buildings with population datasets as background information.Land Use Type("Simp_Type") is based on the building type from StratMap 2019 Land Parcel (TxGIO). Different Computer Automated Design (CAD) systems use different categories for the land parcel use and type. The data was assigned to simplified groupings that align with Building Category Definitions (as per the Texas Property Classification Guide).Social Vulnerability Index (SVI)The SVI ranking is the CDC's Social Vulnerability Index (2022). SVI is an index to identify census tracts that are especially at risk during public health emergencies due to factors such as socioeconomic status, household composition, minority status, or housing type and transportation. The overall track ranking summary index (RPL_THEMES field) was used.Texas Flood Social Vulnerability Index (TX F-SVI)The TX F-SVI was developed to provide information on social vulnerability to flooding. It considers factors such as socioeconomic status, household composition, minority status, housing type, and transportation. This index helps identify areas that are particularly vulnerable to flooding events and can inform flood risk management and mitigation strategies.PopulationLandscan population estimates were made available from ORNL 2019 dataset where nighttime (residential) and daytime population data are produced at 3 arc-second (~90 m) resolution. For background on Landscan data, please visit this link.Population information was distributed to building footprints based on square footage of the building in the Landscan cell. For buildings which have an estimated number of floors (based on LiDAR information from TXGIO), the square footage is the footprint square footage multiplied by the number of floors. Otherwise, the square footage is based on the footprint.Some population is unaccounted for in buildings due to some Landscan cells showing population but no building intersections.Method and Statistics for Adding PopulationThe estimated nighttime and daytime populations were derived from 2019 Landscan data. This process involved dividing buildings along Landscan cell boundaries, determining each building’s share of the Landscan cell's building area, assigning population based on that share, and then recombining the buildings.Note:<UL><LI>Approximately 0.02% (579,918 of day population, 614,848 of night population) of the population resides in Landscan cells that do not intersect with buildings and, therefore, are not assigned to buildings in this process. This is expected and reflected in Table 1 below as “Day/Night Population without buildings”.</LI><LI>Population data is provided in integer fields within the feature class, with values rounded at the building level.</LI></UL></DIV></DIV></DIV> This data was generated by AtkinsRéalis, using the Exposed Building Data and Flood Quilt (2024) provided by Texas Water Development Board (TWDB) Regional Flood Planning Group (RFPG). The Median DV Category was developed by WERC, using the Base Level Engineering (BLE) models, the FEMA Flood Severity Categories, TWDB RFPG Exposed Building Data, and the TWDB RFPG Flood Quilt (2024). Downloaded November 2025. Agricultural Count Agricultural Population Commercial Count Commercial Population Industrial Count Industrial Population Public Count Public Population Residential Count Residential Population Vacant/Unknown Count Vacant/Unknown Population Building Count in 500yr Population in 500yr <DIV STYLE="text-align:Left;"><DIV><DIV>The FFRA is provided for the 30-county area at a spatial resolution of 1-kilometer by 1-kilometer for better computational efficiency as well as to align with input data with the coarsest resolution among those that were used in this study. In addition, the selection of the 1-kilometer by 1-kilometer pixel grid for processing FFRA can avoid confusion about the intent of the product – a finer resolution may give a false impression about the precision or intent of this study. This study is not intended to site sirens as part of outdoor warning siren systems but to identify flash flood-prone areas that warrant sirens. FFRA with a resolution of 1x1 kilometer can adequately serve as foundational information for identifying flash flood-prone areas that warrant sirens given the audible radius for outdoor warning sirens typically ranging from approximately 1 to 2 miles.</DIV></DIV></DIV> 0.000000 0.000000 1 -104.068135 -97.157686 32.084647 28.201763 1778667 EPSG 6.2(3.0.1) Building_Footprints Feature Class 1778667 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. Bldg_ID Bldg_ID String 254 0 0 Simp_type Simp_type String 254 0 0 SVI SVI Double 8 0 0 Est_floors Est_floors String 254 0 0 EstNtPop_Float EstNtPop_Float Double 8 0 0 EstDayPop_Float EstDayPop_Float Double 8 0 0 Est_Day_Pop Est_Day_Pop Integer 4 0 0 TXF_SVI TXF_SVI Double 8 0 0 Est_Night_Pop Est_Night_Pop Integer 4 0 0 in_500 in_500 String 1 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. Simple FALSE 1778667 TRUE FALSE