This dataset was created by the Transportation Planning and Programming (TPP) Division of the Texas Department of Transportation (TxDOT) for planning and asset inventory purposes, as well as for visualization and general mapping. County boundaries were digitized by TxDOT using USGS quad maps, and converted to line features using the Feature to Line tool. This dataset depicts a generalized coastline.Update Frequency: As NeededSource: Texas General Land OfficeSecurity Level: PublicOwned by TxDOT: FalseRelated LinksData Dictionary PDF [Generated 2025/03/14]

The geographic extent of a County, this file represents 3 counties (Dallas, Collin, Denton) clipped from a statewide 2010 Census dataset that are in the Tx N. Central 4202 State Plane projection. The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most States are termed counties. The 2010 Census boundaries for counties and equivalent entities are as of January 1, 2010, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).Metadata edited 01/2021

This site provides access to download an ArcGIS geodatabase or shapefiles for the 2017 Texas Address Database, compiled by the Center for Water and the Environment (CWE) at the University of Texas at Austin, with guidance and funding from the Texas Division of Emergency Management (TDEM). These addresses are used by TDEM to help anticipate potential impacts of serious weather and flooding events statewide. This is part of the Texas Water Model (TWM), a project to adapt the NOAA National Water Model [1] for use in Texas public safety. This database was compiled over the period from June 2016 to December 2017. A number of gaps remain (towns and cities missing address points), see Address Database Gaps spreadsheet below [4]. Additional datasets include administrative boundaries for Texas counties (including Federal and State disaster-declarations), Councils of Government, and Texas Dept of Public Safety Regions. An Esri ArcGIS Story Map [5] web app provides an interactive map-based portal to explore and access these data layers for download.

The address points in this database include their "height above nearest drainage" (HAND) as attributes in meters and feet. HAND is an elevation model developed through processing by the TauDEM method [2], built on USGS National Elevation Data (NED) with 10m horizontal resolution. The HAND elevation data and 10m NED for the continental United States are available for download from the Texas Advanced Computational Center (TACC) [3].

The complete statewide dataset contains about 9.28 million address points representing a population of about 28 million. The total file size is about 5GB in shapefile format. For better download performance, the shapefile version of this data is divided into 5 regions, based on groupings of major watersheds identified by their hydrologic unit codes (HUC). These are zipped by region, with no zipfile greater than 120mb: - North Tx: HUC1108-1114 (0.52 million address points) - DFW-East Tx: HUC1201-1203 (3.06 million address points) - Houston-SE Tx: HUC1204 (1.84 million address points) - Central Tx: HUC1205-1210 (2.96 million address points) - Rio Grande-SW Tx: HUC2111-1309 (2.96 million address points)

Additional state and county boundaries are included (Louisiana, Mississippi, Arkansas), as well as disaster-declaration status.

Compilation notes: The Texas Commission for State Emergency Communications (CSEC) provided the first 3 million address points received, in a single batch representing 213 of Texas' 254 counties. The remaining 41 counties were primarily urban areas comprising about 6.28 million addresses (totaling about 9.28 million addresses statewide). We reached the GIS data providers for these areas (see Contributors list below) through these emergency communications networks: Texas 9-1-1 Alliance, the Texas Emergency GIS Response Team (EGRT), and the Texas GIS 9-1-1 User Group. The address data was typically organized in groupings of counties called Councils of Governments (COG) or Regional Planning Commissions (RPC) or Development Councils (DC). Every county in Texas belongs to a COG, RPC or DC. We reconciled all counties' addresses to a common, very simple schema, and merged into a single geodatabase.

November 2023 updates: In 2019, TNRIS took over maintenance of the Texas Address Database, which is now a StratMap program updated annually [6]. In 2023, TNRIS also changed its name to the Texas Geographic Information Office (TxGIO). The datasets available for download below are not being updated, but are current as of the time of Hurricane Harvey.

References: [1] NOAA National Water Model [https://water.noaa.gov/map] [2] TauDEM Downloads [https://hydrology.usu.edu/taudem/taudem5/downloads.html] [3] NFIE Continental Flood Inundation Mapping - Data Repository [https://web.corral.tacc.utexas.edu/nfiedata/] [4] Address Database Gaps, Dec 2017 (download spreadsheet below) [5] Texas Address and Base Layers Story Map [https://www.hydroshare.org/resource/6d5c7dbe0762413fbe6d7a39e4ba1986/] [6] TNRIS/TxGIO StratMap Address Points data downloads [https://tnris.org/stratmap/address-points/]

This dataset includes county boundaries for all 16 counties in the North Central Texas Council of Governments region. This file is for reference use only. NCTCOG and its members are not responsible for errors or inaccuracies in the file.

This data release supports the U.S. Geological Survey Scientific Investigation Map (SIM) by Clark and others (2020) by documenting the data used to create the geologic maps and describe geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers for a 442 square-mile area in northern Medina County in south Texas. The karstic Edwards and Trinity aquifers that are the subject of the SIM by Clark and others (2020) are classified as major sources of water in south-central Texas by the Texas Water Development Board (George and others, 2011). The geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers largely control groundwater-flow paths and storage in northern Medina County (Kuniasky and Ardis, 2004). The data provided in this data release and the detailed maps and descriptions of the geologic framework and hydrostratigraphy in Clark and others (2020) are intended to help provide water managers information that is useful for effectively managing available groundwater resources in the study area. These digital data accompany Clark, A.K., Morris, R.E., and Pedraza, D.E., 2020, Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas: U.S. Geological Survey Scientific Investigations Map 3461, 13 p. pamphlet, 1 pl., scale 1:24,000, https://doi.org/10.3133/sim3461.

Flight-line data release for a helicopter electromagnetic (HEM) and magnetic geophysical survey flown in early December 2003, in Northern Bexar County, Texas. The U.S. Geological Survey (USGS) contracted the survey to Fugro Airborne of Toronto, Canada. Data include coordinates in UTM zone 14 meters, longitude and latitude WGS84, and latitude and longitude (degrees, minutes, and decimal seconds) NAD27.

The karstic Edwards and Trinity aquifers are classified as major sources of water in south-central Texas by the Texas Water Development Board, and both are classified as major aquifers by the State of Texas. The Edwards and Trinity aquifers developed because of the original depositional history of the carbonate limestone and dolomite rocks that contain them, and the primary and secondary porosity, diagenesis, fracturing, and faulting that modified the porosity, permeability, and transmissivity of each aquifer and of the geologic units separating the aquifers. Previous studies such as those by the U.S. Geological Survey (USGS) and the Edwards Aquifer Authority (EAA) have mapped the geology, hydrostratigraphy, and structure in these areas at various scales. The purpose of this data release is to present the data that were collected and compiled to describe the geologic framework and hydrostratigraphy of northern Medina county, Texas in order to help water managers, water purveyors, and local residents better understand and manage water resources. The scope of the larger work and this accompanying data release is focused on the geologic framework and hydrostratigraphy of the outcrops and hydrostratigraphy of the rocks that contain the Edwards and Trinity aquifers within northern Medina county, Texas. These digital data accompany Clark and others (2024), which supersedes Scientific Investigations Map 3461.

description: The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event,the 0.2-percent-annual-chance flood event, Floodway, and areas of minimal flood risk. The DFIRM Database is derived from the JONES County Flood Insurance Study (FIS), the City of Espanola FIS, and the Village of Chama FIS flood hazard analyses performed in support of the Flood Insurance Studies and FIRMs, and new mapping data, where available. The Flood Insurance Studies and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Universal Transverse Mercator projection Zone 13 coordinate system referenced to the North American Datum of 1983. The specifications for the horizontal control of Base Map data files are consistent with those required for mapping at a scale of 1:6,000 and 1:12,000.; abstract: The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event,the 0.2-percent-annual-chance flood event, Floodway, and areas of minimal flood risk. The DFIRM Database is derived from the JONES County Flood Insurance Study (FIS), the City of Espanola FIS, and the Village of Chama FIS flood hazard analyses performed in support of the Flood Insurance Studies and FIRMs, and new mapping data, where available. The Flood Insurance Studies and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Universal Transverse Mercator projection Zone 13 coordinate system referenced to the North American Datum of 1983. The specifications for the horizontal control of Base Map data files are consistent with those required for mapping at a scale of 1:6,000 and 1:12,000.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

Predictive Service Areas (PSAs) are geographic areas for which national-level fire weather or fire danger services and products are produced by wildland fire agency meteorologists and intelligence staffs in support of resource allocation and prioritization. A PSA boundary defines areas where 2 or more weather elements or National Fire Danger Rating System (NFDRS) indices exist with a high correlation to historical significant fire size. "Significant fires" are the 95th percentile fire size for the PSA. 1/9/2023 - Spatial and tabular changes made at request of Basil Newmerzhycky (Great Basin), and Gina McGuire (Fire Meterologist). PSA boundaries between Great Basin (GB14) and Northern California (NC08) GACCs aligned to follow GACC boundary in area of East Fork High Rock Canyon Wilderness and Grassy Canyon. Edits by JKuenzi. 8/29/2022 - 8/30/2022 - Spatial and tabular changes made at request of Southern Area GACC (submitted by Dana "Nancy" Ellsworth and Subject Matter Experts). Edits by JKuenzi. Specific changes include:Puerto Rico changed from 6 PSAs to 1 PSA. PSAName changed to PR for all areas. PSANationalCode changed to "SA52A" for all areas. PSANames and PSANationalCodes = "PR Northwest (number SA52A remains active), PR Southwest (SA52B), PR North (SA53), PR Central (SA54), PR South (SA55), and PR East (SA56)" were all removed. Florida changed from 10 PSAs to 4 PSAs. PSANames and PSANationalCodes = "FL North Coast (SA44), FL Northeast (SA45A), FL Northeast Coast (SA45B), FL Pan (SA43), FL SE Coast (SA51B), and FL SW Coast (SA51A)" were all removed. Remaining PSAs realigned using linework by AHepworth, and authoritative datasets (Census Counties, and PADUS Modified Jurisdictional Boundaries) to cover all of Florida. Louisiana changed PSAName from "MS South" to "LA East" where PSANationalCode = "SA22B" .1/12/2022 - Spatial and tabular changes made while assigning PSAs to islands and merging a handful of small slivers with larger areas Islands identified by Geographic Area Coordination Center (GACC) PSA representatives, Heidi Strader, Julia Rutherford, Dana "Nancy" Ellsworth, and Matt Shameson. Edits by JKuenzi.1/10/2022 - Spatial and tabular changes made as part of the request to replace all PSAs in the Rocky Mountain Geographic Area Coordination Center (GACC) by Valerie Meyers and Coleen Haskell, both Predictive Services Fire Weather Meteorologists. The total number of PSAs within the Rocky Mountain area went from 74 to 28. Along with new linework, PSAs were re-numbered and named. Topology was used to find and remove gaps and overlaps.Edits by JKuenzi.10/29/2021 - Spatial changes made. Coastlines matched to other base data layers including: Geographic Area Coordination Centers (GACCs), Dispatch Areas, and Initial Attach Frequency Zones. Process completed with approval from the PSA representatives in each GACC, in order to begin process of vertical integration of PSA data, where appropriate, with other wildland fire base data layers. No interior lines moved except along coast. A few island areas were not specifically labeled with a PSA and have been assigned a PSANationalCode = "None" and "PSAName = "No PSA Assigned". Edits by JKuenzi, 10/25/2021 - Spatial and tabular changes made resulting from proposed change between Southwest and Southern Geographic Area Coordination Centers (GACCs) for use starting 1/10/2022. Seven Predictive Service Areas re-aligned boundaries as described by Charles Maxwell (USFS) Predictive Services Meteorologist, in conjunction with Rich Naden (NPS), Basil Newmerzhycky (BLM), Dana Ellsworth (USFS), and Calvin Miller (USFS). Edits by JKuenzi, USFS. Specific changes made include:SW13 - split at Texas/New Mexico state line. Area in NM remains SW13. Area in TX/OK becomes SA01.SW14N - split at Texas/New Mexico state line. Area in NM remains SW14N. Area in TX is split into SA04 and SA09SW14S - split at Texas/New Mexico state line. Area in NM absorbed by SW14N. Area in TX is split into SA09 and SA08 along county lines.SW09 - split at Texas/New Mexico state line. Area in NM remains SW09 or is absorbed by SW12. Area in TX is absorbed by SA08. SW12 - absorbs sliver of SW09 along TX/NM border and the Guadalupe Mtns in TX. 10/20/2021-10/21/2021 - Spatial and tabular changes made while completing topology checks for overlaps and gaps. Over 3400 errors found, but most were because of islands. 1367 errors remain, but are all marked as exceptions. Only major changes, such as complete deletion and re-creation of polygons were noted in the Comments or DateCurrent field. Edits by JKuenzi, USFS. 2/3/2021 - Tabular change made in Alaska to the peninsula where the St. Michael Airport is located. PSA National Code changed from AK14 to AK08 per Nicholas Nauslar, BLM, and Heidi Strader, Fire Weather Program Mgr at Alaska Interagency Coordination Center. Edits by JKuenzi, USFS. 6/20/2020 - PSA dataset attribute table brought into alignment with NWCG Data Standards for Predictive Service Areas. Edits by JKuenzi, USFS.8/3/2019 - Great Basin updated. Edits by DSampson, BLM.

ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)

**When using the GIS data included in these map packages, please cite all of the following:

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, 2019. PLoSONE 14(8):e0220457. http://doi.org/10.1371/journal.pone.0220457

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. ArcGIS Map Packages for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al., 2019. Version 1. Zenodo. https://doi.org/10.5281/zenodo.2572018

OVERVIEW OF CONTENTS

This repository contains map packages for Gillreath-Brown, Nagaoka, and Wolverton (2019), as well as the raw digital elevation model (DEM) and soils data, of which the analyses was based on. The map packages contain all GIS data associated with the analyses described and presented in the publication. The map packages were created in ArcGIS 10.2.2; however, the packages will work in recent versions of ArcGIS. (Note: I was able to open the packages in ArcGIS 10.6.1, when tested on February 17, 2019). The primary files contained in this repository are:

Raw DEM and Soils data

Digital Elevation Model Data (Map services and data available from U.S. Geological Survey, National Geospatial Program, and can be downloaded from the National Elevation Dataset)

DEM_Individual_Tiles: Individual DEM tiles prior to being merged (1/3 arc second) from USGS National Elevation Dataset.

DEMs_Merged: DEMs were combined into one layer. Individual watersheds (i.e., Goodman, Coffey, and Crow Canyon) were clipped from this combined DEM.

Soils Data (Map services and data available from Natural Resources Conservation Service Web Soil Survey, U.S. Department of Agriculture)

Animas-Dolores_Area_Soils: Small portion of the soil mapunits cover the northeastern corner of the Coffey Watershed (CW).

Cortez_Area_Soils: Soils for Montezuma County, encompasses all of Goodman (GW) and Crow Canyon (CCW) watersheds, and a large portion of the Coffey watershed (CW).

ArcGIS Map Packages

Goodman_Watershed_Full_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the full Goodman Watershed (GW).

Goodman_Watershed_Mesa-Only_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the mesa-only Goodman Watershed.

Crow_Canyon_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Crow Canyon Watershed (CCW).

Coffey_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Coffey Watershed (CW).

For additional information on contents of the map packages, please see see "Map Packages Descriptions" or open a map package in ArcGIS and go to "properties" or "map document properties."

LICENSES

Code: MIT year: 2019 Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton

CONTACT

Andrew Gillreath-Brown, PhD Candidate, RPA Department of Anthropology, Washington State University andrew.brown1234@gmail.com – Email andrewgillreathbrown.wordpress.com – Web

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 ...

Point locations of churches, cemeteries, post offices, libraries, recreational facilities, and the like within the 16-county NCTCOG region. Data can be viewed in the Development Monitoring in North Central Texas web mapping application. For the program overview, visit NCTCOG Development Monitoring Program Overview.pdf

Land parcels for the purpose of fuel mitigation of the Bastrop County North Fuel Mitigation Project TX-1999-012.

2024-2025 School Year Texas School Districts. Information was collected from all 253 central appraisal districts and from the Texas Education Agency. GIS staff of the Texas Legislative Council created the school district boundaries using the 2020 TIGER/Line Shapefile as base geography and made further corrections to match the school district boundary updates and name changes for the 2024-2025 School Year. These changes include lines that are not census geography. Changes to school district boundaries may include one or all of the following types: school district annexations or de-annexations; school district consolidations, deletions or additions; boundary corrections to the Texas Legislative Council database; boundary adjustments due to more spatially accurate data involving land parcels and survey data received from a county central appraisal district.Note: The 2024-2025 School Year school districts in the council's geographic file are not the same as the districts in the Census Bureau's 2020 TIGER/Line Shapefile. School district population data published by the Texas Legislative Council using the 2024-2025 School Year school districts will not correspond with the school district population data published by the Census Bureau.This geographic data should be used as a reference for determining the boundaries of school districts. This depiction and designation of the school district boundaries do not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions.

This map contains the 4 Regional Areas: Border and Permian Basin, Central Texas, Coastal and East Texas, North Central and West Texas and the 16 Regions of the TCEQ. The areas for this data was obtained from TXDOT county boundaries (no coastal detail). General purpose use is to delineate TCEQ Region boundaries on maps and other products. Originating feature class was digitized by TXDOT at 1:24,000 using DRGs (USGS Topos) in the NAD 83 Datum.

A work in progress that documents currently-known alignments of historical streetcars and interurbans in North Central Texas. Assembled from historical maps from the Texas State Archives Map Collection, Tarrant County Archives, and other sources.Like many other urban areas in the US, North Central Texas was historically served by a network of electrified streetcar and interurban lines. These systems became popular when electricity, electric motors, and related technology became widespread around the turn of the 20th century. As one of the first means of affordable, widespread transit, it enabled the first wave of suburban development in many urban areas including North Central Texas. At the system's peak, a sprawling network of streetcars served then-new suburban development while the interurbans connected cities in the region as far away as Denison and Waco. As with most other American systems, the streetcar network in North Central Texas declined and was eventually abandoned after WWII due to a combination of factors including disinvestment, the continuing growth of suburbs beyond their reach, and the increasing popularity of personal automobiles. Though little of the historical network remains, the McKinney Avenue Transit Authority has operated a fleet of restored historical streetcars on the streets of Uptown Dallas since 1989. Dallas Area Rapid Transit also operates modern streetcar and light rail systems, the latter of which utilizes abandoned streetcar/interurban right-of-way in some locations.This dataset provides important historical context to the region's transportation system, land use, and growth patterns in the parts of the region that they served. Please contact NCTCOG Transportation if you would like to contribute information to this ongoing effort.

This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Coastal Services Center's Sea Level Rise and Coastal Flooding Impacts Viewer. The DEM includes the 'best available' lidar data known to exist at the time of DEM creation that meets project specifications for those counties within the boundary of the Brownsville TX Weather Forecast Office (WFO), as defined by the NOAA National Weather Service. The counties within this boundary are: Cameron, Willacy, and Kenedy. For Cameron and Willacy counties the DEM is derived from LiDAR data sets collected for the Texas Water Development Board (TWDB) in 2005 and 2006 with a point density of 1.4 m GSD. The LiDAR data for Kenedy County is based on the US Geological Survey (USGS) National Elevation Dataset (NED) 1/9 arc-second elevation data. Hydrographic breaklines used in the creation of the DEM were delineated using LiDAR intensity imagery generated from the data sets. Hydrography for Kenedy County is based on the National Hydrography Dataset (NHD) and the National Wetlands Inventory (NWI). The DEM is hydro flattened such that water elevations are less than or equal to 0 meters.The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 10 meters.