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]

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/]

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

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.

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.

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.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) 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) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. State Legislative Districts (SLDs) are the areas from which members are elected to state legislatures. The SLDs embody the upper (senate - SLDU) and lower (house - SLDL) chambers of the state legislature. Nebraska has a unicameral legislature, and the District of Columbia has a single council, both of which the Census Bureau treats as upper-chamber legislative areas for the purpose of data presentation; there are no data by SLDL for either Nebraska or the District of Columbia. A unique three-character census code, identified by state participants, is assigned to each SLD within a state. States that had SLDL updates between the previous and current session include Georgia, Michigan, Minnesota, Montana, New York, North Carolina, North Dakota, Ohio, South Carolina, Washington, and Wisconsin. In Connecticut, Illinois, Louisiana, New Hampshire, Wisconsin, and Puerto Rico, the Redistricting Data Program (RDP) participant did not define the SLDLs to cover the entirety of the state or state equivalent area. In the areas with no SLDLs defined, the code "ZZZ" has been assigned, which is treated as a single SLDL for purposes of data presentation. There are no SLDL TIGER/Line shapefiles for the District of Columbia, Nebraska, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). The state legislative district boundaries reflect information provided to the Census Bureau by the states by May 31, 2024.

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.

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

The 2023 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states based on census population counts, each state is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The 118th Congress is seated from January 2023 through December 2024. In Connecticut, Illinois, and New Hampshire, the Redistricting Data Program (RDP) participant did not define the CDs to cover all of the state or state equivalent area. In these areas with no CDs defined, the code "ZZ" has been assigned, which is treated as a single CD for purposes of data presentation. The cartographic boundary files for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) each contain a single record for the non-voting delegate district in these areas. The generalzied boundaries of all other congressional districts are based on information provided to the Census Bureau by the states by August 31, 2022.

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 ...

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/ .

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.

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

One route equals one feature. "Hooked" routes are stored as 2 separate features: ie 52 Hirsch, 52 Scott. Routes are coincident with METmap - METRO's version of the Houston region STAR Map.Changes since Previous Service Change:Routes using N. Main St through the Hernandez Tunnel have been rerouted during construction to Washington - Houston - Crockett - Quitman. These routes include the 1 Hospital, 5 Kashmere, 9 North Main, 52 Hirsch, and 78 Irvington. The original routing on the west end of the 58 Hammerly has been modified to its original loop, but in reverse direction.

© Metropolitan Transit Authority of Harris County, Texas Planning Department Division of Service Planning, Evaluation and Scheduling This layer is sourced from mycity.houstontx.gov.

Last updated from Metro on April 10, 2015

This dataset includes U.S. Congressional district boundaries for the State of Texas. The dataset was downloaded from https://tlc.texas.gov/data Texas Legislative Council and processed but otherwise unaltered. This file is for reference use only. NCTCOG and its members are not responsible for errors or inaccuracies in the file.

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.

The Sea Level Affecting Marshes Model (SLAMM) simulates the dominant processes involved in wetland conversions and shoreline modifications during long-term sea level rise. Map distributions of wetlands are predicted under conditions of accelerated sea level rise.

Tidal marshes are among the most susceptible ecosystems to climate change, especially accelerated sea-level rise (SLR). The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) suggested that global sea level will increase by approximately 30 cm to 100 cm by 2100 (IPCC 2001). Rahmstorf (2007) suggests that this range may be too conservative and that the feasible range by 2100 is 50 to 140 cm. Rising sea levels may result in tidal marsh submergence (Moorhead and Brinson 1995) and habitat migration as salt marshes transgress landward and replace tidal freshwater and irregularly-flooded marsh (R. A. Park et al. 1991).

The model used the 1/1.5/2 meter of sea-level rise by 2100 scenario and was produced for the Nature Conservancy by Warren Pinnacle Consulting, Inc. The purpose of this series of maps was to show how marshes are predicted to migrate inland due to increases in sea level by 2100. The SLAMM model produced landcover maps for 5 points in time for this specific sea level rise scenario, which included actual landcover maps from either 2004 or 2009 and predicted landcover maps for 2025, 2050, 2075 and 2100 for each project site.

Impacts of Sea-level Rise, Habitat Conservation & Spatial Data Platform Project in Northern Gulf of Mexico

Contact detail for the project: The Nature Conservancy

Jorge Brenner, Ph.D. Associate Director of Marine Science The Nature Conservancy of Texas 205 N. Carrizo St. Corpus Christi, Texas 78401 Phone: (361) 882-3584; ext: 104 Email: jbrenner@tnc.org