Do not use this data to make zoning determinations. This data does not show all zoning regulations for an address, including overlays and situations where an address has more than one zoning. Also, the data may be out of date. Use the interactive mapping application https://maps.austintexas.gov/GIS/PropertyProfile/ to make zoning determinations, and call 311 if you have questions about zoning. Zoning only applies to addresses within the City of Austin city limits. This dataset is a list of addresses with their zoning provided to answer questions such as "what property addresses have CS zoning." This data is derived from GIS layer for address and zoning. The place_id field is provided for linking to the addresses GIS layer. This product is produced by the City of Austin for informational purposes. No warranty is made they City of Austin regarding specific accuracy or completeness.

Geospatial data about City of Austin, Texas Zoning. Export to CAD, GIS, PDF, CSV and access via API.

Geospatial data about City of Austin, Texas Zoning Ordinance. Export to CAD, GIS, PDF, CSV and access via API.

This feature class represents the zoning classification boundaries in the City of Austin and surrounding counties.

Map showing land uses in the City of Austin jurisdictions. Upated during October of even years.

This feature class represents the boundaries of the City of Austin Neighborhood Planning Areas (NPA). The status of these areas, as directed by City Council, can either be plan approved, planning underway/set to begin, future planning area, or non-neighborhood planning area. Future planning area boundaries may change before they are set by the City Council to begin. See https://www.austintexas.gov/department/planning-and-zoning/plans for more information. Terms of Use This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, or surveying purposes. It does not represent an on-the-ground survey and represents only the approximate relative location of property boundaries. This product has been produced by the City of Austin for the sole purpose of geographic reference. No warranty is made by the City of Austin regarding specific accuracy or completeness.

Composite map of Future Land Use. This is a pdf document.

This layer represents the jurisdiction and regulatory boundaries of the City of Austin.

© Acknowledgment of the City of Austin GIS Division would be appreciated in products derived from these data This layer is a component of FloodPro_Webapp_Map.

To allow the development of vertical mixed-use buildings where the Core Transit Corridor or Future Core Transit Corridor is the primary street, subject to compliance in the City Development Code. Core Transit Corridors identified in the May 12, 2005 City Council Approved Design Standards Policy Document, with recommended amendments made August 4, 2006. A copy of the ordinance can be found at http://www.ci.austin.tx.us/planning/neighborhood/downloads/nl/nlcnpa_code_change_ctc.pdf. Additional information can be found at the following: http://www.ci.austin.tx.us/development/downloads/final.pdf

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq This dataset was created to depict approximate tree canopy cover for all land within the City of Austin's "full watershed regulation area." Intended for planning purposes and measuring citywide percent canopy. Definition: Tree canopy is defined as the layer of leaves, branches, and stems of trees that cover the ground when viewed from above. Methods: The 2022 tree canopy layer was derived from satellite imagery (Maxar) and aerial imagery (NAIP). Images were used to extract tree canopy into GIS vector features. First, a “visual recognition engine” generated the vector features. The engine used machine learning algorithms to detect and label image pixels as tree canopy. Then using prior knowledge of feature geometries, more modeling algorithms were used to predict and transform probability maps of labeled pixels into finished vector polygons depicting tree canopy. The resulting features were reviewed and edited through manual interpretation by GIS professionals. When appropriate, NAIP 2022 aerial imagery supplemented satellite images that had cloud cover, and a manual editing process made sure tree canopy represented 2022 conditions. Finally, an independent accuracy assessment was performed by the City of Austin and the Texas A&M Forest Service for quality assurance. GIS professionals assessed agreement between the tree canopy data and its source satellite imagery. An overall accuracy of 98% was found. Only 23 errors were found out of a total 1,000 locations reviewed. These were mostly omission errors (e.g. not including canopy in this dataset when canopy is shown in the satellite or aerial image). Best efforts were made to ensure ground-truth locations contained a tree on the ground. To ensure this, location data were used from City of Austin and Texas A&M Forest Service databases. Analysis: The City of Austin measures tree canopy using the calculation: acres of tree canopy divided by acres of land. The area of interest for the land acres is evaluated at the City of Austin's jurisdiction including Full Purpose, Limited Purpose, and Extraterritorial jurisdictions as of May 2023. New data show, in 2022, tree canopy covered 41% of the total land area within Austin's city limits (using city limit boundaries May 2023 and included in the download as layer name "city_of_austin_2023"). 160,046.50 canopy acres (2022) / 395,037.53 land acres = 40.51% ~41%. This compares to 36% last measured in 2018, and a historical average that’s also hovered around 36%. The time period between 2018 and 2022 saw a 5 percentage point change resulting in over 19K acres of canopy gained (estimated). Data Disclaimer: It's possible changes in percent canopy over the years is due to annexation and improved data methods (e.g. higher resolution imagery, AI, software used, etc.) in addition to actual in changes in tree canopy cover on the ground. For planning purposes only. Dataset does not account for individual trees, tree species nor any metric for tree canopy height. Tree canopy data is provided in vector GIS format housed in a Geodatabase. Download and unzip the folder to get started. Please note, errors may exist in this dataset due to the variation in species composition and land use found across the study area. This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, or surveying purposes. It does not represent an on-the-ground survey and represents only the approximate relative location of property boundaries. This product has been produced by the City of Austin for the sole purpose of geographic reference. No warranty is made by the City of Austin regarding specific accuracy or completeness. Data Provider: Ecopia AI Tech Corporation and PlanIT Geo, Inc. Data derived from Maxar Technologies, Inc. and USDA NAIP imagery

This feature class is made up of City of Austin zoning ordinance boundaries. Work on this layer began in 2001 with zoning ordinance polygons entered on a day forward basis. Therefore, polygons for older ordinances are less likely to be included in this data.

This is dataset contains the height subdistricts that apply to areas rezoned into the density bonus program of the Equitable Transit-Oriented Development (ETOD) Overlay, known as Density Bonus ETOD or DBETOD.

The associated map displays Height Subdistrict 1 (in purple) allows a maximum of 120 feet, while height Subdistrict 2 (in blue) allows a maximum of 90 feet.

These data are up to date as of September 2024.

The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

This layer represents the area and attributes for the Future Land Use Map.

This dataset entails the delineation of impervious surfaces and artificial land cover types extracted from aerial imagery captured in early 2021.
Utilization within the City of Austin
The dataset plays a pivotal role in several municipal functions, encompassing the computation of the Drainage Charge managed by the Watershed Protection Department, wildfire assessments, emergency operations planning, transportation asset monitoring, urban forest management, and more.
Data Updates
New aerial imagery and impervious cover data are acquired by the city every two years, resulting in distinct datasets for each capture. As of its initial capture in early 2021, there have been no subsequent updates to this dataset.
Downloading Instructions
Some users have reported issues downloading the data. Due to the large size of the dataset, downloading can take longer than expected. We recommend following these instructions to download the data.

1. Click on 'Export'.
2. Choose the desired export format from the dropdown menu.
3. Initiate the download by clicking 'Download'.
4. It's essential to allow your browser ample time to process the download. Even if no immediate action appears to occur, please refrain from closing the browser window. Depending on your internet speed, the download process can take between 10 to 30 minutes due to the substantial size of the data.
5. Once the download commences in your browser, allow it to finish entirely.
6. Should you encounter any issues during the download process, kindly contact the dataset owner for assistance.

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq

The general neighborhood and zip code location of active short term rentals (including type) across Austin, TX. Licenses are only active for one year. We have not included specific addresses, at the request of residents for safety reasons, but we have included street name and zip code. For more information or for records of licenses older than a year, concerned parties can pursue a public information request: public.information@austintexas.gov. FYI: your request will not be considered received unless it is sent to the proper address.

To determine displacement risk, researchers at the University of Texas conducted a three-part analysis: the presence of vulnerable populations, residential market appreciation, and demographic change. To determine vulnerable populations, the authors used indicators to identify residents who, according to academic research, are least able to absorb housing costs, which includes: communities of color, low-income households, heads of households without a bachelor's degree or higher, families with children in poverty, and renters.

In 2019 and 2020, the City of Austin Housing and Planning staff updated the data and simplified the categories below.

Vulnerable: Vulnerable populations present, no significant demographic change, some tracts are near or contain high-value and high-appreciation areas. Active Displacement Risk: Vulnerable populations present, active demographic change, accelerating or appreciating housing market. Chronic Displacement Risk: Vulnerable populations have been displaced, demographic change has occurred and the housing market is high value and appreciated or appreciating. Historic Displacement: Tracts previously identified as at-risk to displacement in earlier Uprooted models (2016, 2019)