The City of Longview is sharing the map service URL found at the TNRIS DataHub, https://data.tnris.org/collection/54abd8ee-3a1a-4206-8b39-742f13ec8ad6, under the Public Domain (Creative Commons CC0) license.

This resource contains Lidar-DEM collection status shapefiles from the Texas Natural Resources Information System (TNRIS) [http://tnris.org]. November 2023 updates: this year, TNRIS changed its name to Texas Geographic Information Office (TxGIO). The domain name hasn't changed yet, but the data hub is continually evolving. See [1], [2] for current downloadable data.

For purposes of Hurricane Harvey studies, the 1-m DEM for Harris County (2008) has also been uploaded here as a set of 4 zipfiles containing the DEM in tiff files. See [1] for a link to the current elevation status map and downloadable DEMs.
Project name: H-GAC 2008 1m Datasets: 1m Point Cloud, 1M Hydro-Enforced DEM, 3D Breaklines, 1ft and 5ft Contours Points per sq meter: 1 Total area: 3678.56 sq miles Source: Houston-Galveston Area Council (H-GAC) Acquired by: Merrick, QA/QC: Merrick Catalog: houston-galveston-area-council-h-gac-2008-lidar

References: [1] TNRIS/TxGIO StratMap elevation data [https://tnris.org/stratmap/elevation-lidar/] [2] TNRIS/TxGIO DataHub [https://data.tnris.org/]

Web mapping viewer developed by the Texas Natural Resources Information System (TNRIS) for public sharing of information.

This resource contains statewide networks of roadways, railroads, bridges, and low-water crossings, for Texas only.

Roadways detail: The Transportation Planning and Programming (TPP) Division of the Texas Department of Transportation (TxDOT) maintains a spatial dataset of roadway polylines for planning and asset inventory purposes, as well as for visualization and general mapping. M values are stored in the lines as DFOs (Distance From Origin), and provide the framework for managing roadway assets using linear referencing. This dataset covers the state of Texas and includes on-systems routes (those that TxDOT maintains), such as interstate highways, U.S. highways, state highways, and farm and ranch roads, as well as off-system routes, such as county roads and local streets. Date valid as of: 12/31/2014. Publish Date: 05/01/2015. Update Frequency: Quarterly.

Bridges detail: As with the roadways, both on-system and off-system bridges are maintained in separate datasets (54,844 total bridges, 36,007 on-system and 18,837 off-system). Bridges have numerous useful attributes, see coding guide [1] for documentation. One such attribute identifies structures that cross water: the second digit of Item 42 “Type of Service”. If the second digit is between 5 and 9 (inclusive) then the structure is over water. The bridges datasets are valid as of December 2016.

The roadways and bridges datasets contained here were obtained directly from TxDOT through personal correspondence. An additional transportation data resource is the Texas Natural Resources Information System (TNRIS) [3]. The railroads and low-water crossings were obtained through TNRIS.

November 2023 updates: in the years since this data archive was first published, TxDOT has developed an open data portal for downloading their roadway inventory and other datasets. Also, in 2023 TNRIS was renamed as the Texas Geographic Information Office (TxGIO). Their datahub [3] is continually evolving, but still has the tnris.org domain for now. We are not updating any of the basemap data in the contents list below, which was current at the time of Hurricane Harvey.

References [1] TxDOT Bridges Coding Guide (download below) [2] TxDOT Open Data Portal [https://gis-txdot.opendata.arcgis.com/] [3] TNRIS/TxGIO data downloads [https://data.tnris.org/]

After storms, users document high water marks in and near bayous and tributaries, storm surge high water marks along the coast, and the approximate number of structures that were flooded. Most of the information in this dataset comes from the Harris Flood Control District; additional information is the result of Texas Geographic Information Office (TxGIO formerly TNRIS) research.

This resource links to the Texas Address and Base Layers Story Map (Esri ArcGIS Online web app) [1] that provides a graphical overview and set of interactive maps to download Texas statewide address points, as well as contextual map layers including roads, rail, bridges, rivers, dams, low water crossings, stream gauges, and others. The addresses were compiled over the period from June 2016 to December 2017 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.

For detailed compilation notes, see [2]. Contextual map layers will be found at [3] and [4].

November 2023 update: in 2019, TNRIS took over maintenance of the Texas Address Database, which is now updated annually as part of the StratMap program [5]. Also, TNRIS changed its name this year to the Texas Geographic Information Office (TxGIO). The StratMap and DataHub download sites still use the tnris.org domain but that may change .

References [1] Texas Address and Base Layers story map [https://arcg.is/19PWu1] [2] Texas-Harvey Basemap - Addresses and Boundaries [https://www.hydroshare.org/resource/3e251d7d70884abd928d7023e050cbdc/] [3] Texas Basemap - Hydrology Map Data [https://doi.org/10.4211/hs.adb14c9c073e4eee8be82fadb21a0a93/] [4] Texas Basemap - Transportation Map Data [https://www.hydroshare.org/resource/ab3a463be73c4fd988a492b5d1b4c573/] [5] TNRIS/TxGIO StratMap Address Points data downloads [https://tnris.org/stratmap/address-points/]

A bare earth Digital Elevation Model (DEM) created from 2013 LiDAR LAS files for Wilson and Karnes counties in Texas. LiDAR data collection was funded by the Texas Water Development Board. LiDAR LAS files were acquired from Texas Natural Resources Information System (TNRIS). The DEM is a dataset that depicts the topography of the bare earth surface (i.e. surface minus vegetation, buildings, powerlines, etc). This dataset was developled to be used in conjunction with the DSM to create a vegetation height surface (nDSM). The LAS point cloud was filtered to ground points only and the mean z value was calculated. A Digital Surface Model (DSM) created from 2013 LiDAR LAS files for Wilson and Karnes counties in Texas. LiDAR data collection was funded by the Texas Water Development Board. LiDAR LAS files were acquired from Texas Natural Resources Information System (TNRIS). The DSM is an elevation surface created by using the maximum z value to depict the tallest features on the landscape (i.e. tops of buildings, trees, powerlines, etc.). The DSM can be used along with a DEM surface to create a normailzed DSM, or vegetation height layer.This LiDAR data set was fully classified, the classification was accurate enough to consistently and reliable filter out buildings, power lines and other man-made structures.

The Kerrville 2019 2-ft Contour is intended to be used for general reference and visualization, and is not a substitute for an on-the-ground survey conducted by, or under the supervision of, a registered professional land surveyor.The two foot contours were derived from 2019 lidar data. The lidar was filtered to ground points only and exported to a multipoint dataset. The multipoint dataset, breaklines, and project extent were used to create a terrain dataset. A digital elevation model (DEM) was created from the terrain dataset with a 10-ft cell size. The 10-ft DEM was smoothed using focal statistics by averaging a 3x3 cell sized rectangular area across the entire DEM. Contours were created from the smoothed DEM at a two foot interval with a base elevation of 1,500 feet. Contours smaller than 39.5-ft were removed and contours completely within waterbodies were removed. The contours were then split into 20 rows by 10 columns to improve performance. Then the contours were run through a smoothing process to remove sharp bends in the lines without affecting the general location of the lines. Index intervals were calculated for 10-ft, 20-ft, 50-ft, and 100-ft. Finally the contours were projected to the NAD 1983 (2011) State Plane Texas S Central horizontal coordinate system and the NAVD88 (height) (ftUS) vertical coordinate system.The USGS lidar project covers portions of 45 counties in the central to coastal regions of Texas. The acquisition was conducted from January 4, 2019, through February 20, 2019. Fugro served as the prime contractor for the project and was responsible for planning, acquiring, processing, and producing derivative products of high resolution lidar data (QL2) over the project area. Further details regarding this acquisition can be found by downloading the USGS 2019 Hurricane Project Reports from the TNRIS DataHub website.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here.

To complete the automated phase, CTI subcontracted with Photo Science (based in Lexington, KY) to create a BIBE landform layer and a drainage/wash layer. Photo Science reviewed and acquired all National Elevation Dataset (NED) 10-meter DEMs for the project area and mosaiced them into a seamless coverage. The DEM data was then manipulated to create the following derived spatial layers: aspect, slope, three hillshade datasets (different azimuth angles), a contour range layer, and a compound topographic index (or wetness index) that models water flow and accumulation. Similarly, Photo Science also acquired the 2012 National Agriculture Imagery Program (NAIP) imagery for the entire project area as high-resolution (1-meter pixels) digital ortho quarter quadrangles (DOQQs). The NAIP DOQQs were mosaiced and resampled from 1-meter to 10-meter pixels to match the DEM resolution. Erdas Imagine software was then used to derive a normalized difference vegetation index (NDVI) and a near infrared (NIR) band texture layer from the imagery using a 9x9 moving window. During the planning and coordination phase, CTI staff reviewed all available digital imagery for its potential use as the BIBE basemap. The most promising and easy to access was the data catalog found on the Texas Natural Resource Information System (TNRIS) website. Navigating to the orthoimagery-statewide web page, the list of existing imagery covering BIBE included multiple NAIP products. The corresponding 2010 and 2012 NAIP 1-meter DOQQs for BIBE were downloaded and used during the early planning stages of this project and to produce field maps and interim products.