This File Geodatabase download, (last updated September 25, 2024), contains all the feature classes within the Transportation Network. The City of Langley has compiled all the Transportation Network feature classes into one file geodatabase. File Geodatabase Feature Classes:Bicycle RoutesBridgesDisaster Response RoutesMediansRailwayRoadsSidewalksStreet Names

Complete Cadastral dataset in file geodatabase format. Consume this dataset if you wish to download the entire Cadastral dataset at once.

Complete Water Utility Network in file geodatabase format. Consume this dataset if you wish to download the entire Water Utility network dataset at once.

Abstract This dataset was derived by the Bioregional Assessment Programme from the GEODATA TOPO 250K Series 3 dataset (GUID: a0650f18-518a-4b99-a553-44f82f28bb5f). The source dataset is identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This dataset is a copy of the original Geodata Topo 250k Series 3 data, converted from Personal (Microsoft Access) Databases, to ESRI File Geodatabases. This was done to ensure .mdb lock files would not restrict map makers from using the topographic data in their cartographic products. The data and folders are structured the same as the original dataset. ## Dataset History A new file geodatabase schema was created in the same structure as the original .mdb data (including database and feature dataset names and projections). Feature Classes were then copied from the .mdb format to the .gdb format, using ArcCatalog 10.0. ## Dataset Citation Bioregional Assessment Programme (2014) GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb). Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/96ebf889-f726-4967-9964-714fb57d679b. ## Dataset Ancestors * Derived From GEODATA TOPO 250K Series 3

The downloaded .zip file contains a file geodatabase of the road centerlines in the City of Harrisonburg, Virginia.The file available for download is updated every month.

The Digital Bedrock Geologic-GIS Map of the Saint-Gaudens National Historical Park and Vicinity, New Hampshire is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (saga_bedrock_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (saga_bedrock_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (saga_bedrock_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) this file (saga_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (saga_bedrock_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (saga_bedrock_geology_metadata_faq.pdf). Please read the saga_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (saga_bedrock_geology_metadata.txt or saga_bedrock_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

This packaged data collection contains all of the outputs from our primary model, including the following data layers: Habitat Cores (vector polygons) Least-cost Paths (vector lines) Least-cost Corridors (raster) Least-cost Corridors (vector polygon interpretation) Modeling Extent (vector polygon) Please refer to the embedded spatial metadata and the information in our full report for details on the development of these data layers. Packaged data are available in two formats: Geodatabase (.gdb): A related set of file geodatabase rasters and feature classes, packaged in an ESRI file geodatabase. ArcGIS Pro Map Package (.mpkx): The same data included in the geodatabase, presented as fully-symbolized layers in a map. Note that you must have ArcGIS Pro version 2.0 or greater to view. See Cross-References for links to individual datasets, which can be downloaded in shapefile (.shp) or raster GeoTIFF (.tif) formats.

Complete File Geodatabase containing various layers and tables for Boundaries, Census, Environment, Land, Place, PLSS, Transportation, Tables, Utility, and Water datasets. This includes relationship classes (joins) between the Taxlot layer and related table data.OR State Plane NAD83 Projection

The downloaded .zip file contains a geodatabase of the Addresses in the City of Harrisonburg, Virginia.The file available for download is updated every month.

This zip file contains geodatabases with raster mosaic datasets. The raster mosaic datasets consist of georeferenced tiff images of mineral potential maps, their associated metadata, and descriptive information about the images. These images are duplicates of the images found in the georeferenced tiff images zip file. There are four geodatabases containing the raster mosaic datasets, one for each of the four SaMiRA report areas: North-Central Montana; North-Central Idaho; Southwestern and South-Central Wyoming and Bear River Watershed; and Nevada Borderlands. The georeferenced images were clipped to the extent of the map and all explanatory text, gathered from map explanations or report text was imported into the raster mosaic dataset database as ‘Footprint’ layer attributes. The data compiled into the 'Footprint' layer tables contains the figure caption from the original map, online linkage to the source report when available, and information on the assessed commodities according to the legal definition of mineral resources—metallic, non-metallic, leasable non-fuel, leasable fuel, geothermal, paleontological, and saleable. To use the raster mosaic datasets in ArcMap, click on “add data”, double click on the [filename].gdb, and add the item titled [filename]_raster_mosaic. This will add all of the images within the geodatabase as part of the raster mosaic dataset. Once added to ArcMap, the raster mosaic dataset appears as a group of three layers under the mosaic dataset. The first item in the group is the ‘Boundary’, which contains a single polygon representing the extent of all images in the dataset. The second item is the ‘Footprint’, which contains polygons representing the extent of each individual image in the dataset. The ‘Footprint’ layer also contains the attribute table data associated with each of the images. The third item is the ‘Image’ layer and contains the images in the dataset. The images are overlapping and must be selected and locked, or queried in order to be viewed one at a time. Images can be selected from the attribute table, or can be selected using the direct select tool. When using the direct select tool, you will need to deselect the ‘overviews’ after clicking on an image or group of images. To do this, right click on the ‘Footprint’ layer and hover over ‘Selection’, then click ‘Reselect Only Primary Rasters’. To lock a selected image after selecting it, right-click on the ‘Footprint’ layer in the table of contents window and hover over ‘Selection’, then click ‘Lock To Selected Rasters’. Another way to view a single image is to run a definition query on the image. This is done by right clicking on the raster mosaic in the table of contents and opening the layer properties box. Then click on the ‘Definition Query’ tab and create a query for the desired image.

This File Geodatabase download, (last updated September 25, 2024), contains all the feature classes within the Land and Property Information group. The City of Langley has compiled all the Land and Property Information feature classes into one file geodatabase. Data is updated on a regular basis; however, lot sizes, legal descriptions and encumbrances must be confirmed at the Land Title Office.File Geodatabase Feature Classes:Address (Anno)Address PointsCity BoundaryEasement AnnoEasementsFacilitiesFolioLegal DescriptionsLot LinesParcelsRoad AllowanceSchools

The downloaded .zip file contains a geodatabase of the City Boundaries for the City of Harrisonburg, Virginia.The file available for download is updated every month.

"Due to the size of this dataset, both Shapefile and Spreadsheet download options will not work as expected. The File Geodatabase is an alternative option for this data download"SCAG has developed and maintained its regional geospatial dataset of land use information at parcel-level—approximately five million parcels in the SCAG Region. The parcel-based land use dataset is developed (1) to aid in SCAG’s regional transportation planning, scenario planning and growth forecasting, (2) facilitate policy discussion on various planning issues, and (3) enhance information database to better serve SCAG member jurisdictions, research institutes, universities, developers, general public, etc. After the successful release of SCAG’s 2016 regional land use dataset for the development of the Connect SoCal (the 2020 RTP/SCS), SCAG has initiated a process to annually update its regional land use information at the parcel-level (the Annual Land Use Update). For the Annual Land Use Update process, SCAG collected county assessor’s tax roll records (including parcel polygons and property information) from county assessor’s offices, plus other reference layers including California Protected Areas Database (CPAD), California School Campus Database (CSCD), Farmland Mapping and Monitoring Program (FMMP)'s Important Farmland, U.S. Department of Defense's Military Installations, Ranges, and Training Areas (MIRTA) as well as SCAG's regional geospatial datasets, such as airport polygons and water body polygons.Note: This dataset is intended for planning purposes only, and SCAG shall incur no responsibility or liability as to the completeness, currentness, or accuracy of this information. SCAG assumes no responsibility arising from use of this information by individuals, businesses, or other public entities. The information is provided with no warranty of any kind, expressed or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Users should consult with each local jurisdiction directly to obtain the official land use information.Data DescriptionFIELD_NAMEDESCRIPTIONPID202020 SCAG's unique parcel identifierAPN202020 Assessor Parcel NumberAPN20_P2020 Assessor Parcel Number - Parent Parcel (if applicable)COUNTYCounty nameCOUNTY_IDCounty FIPS codeCITYCity nameCITY_IDCity FIPS codeMULTIPARTMultipart feature (the number of multipart polygons; '1' = singlepart feature)STACKDuplicate geometry (the number of stacked polygons; '1' = no duplicate polygons)ACRESParcel area (in acres)SLOPESlope information1GEOID202020 Census Block GEOIDAPN_DUPDuplicate APN (the number of multiple tax roll property records; '0' = no duplicate APN)IL_RATIORatio of improvements assessed value to land assessed valueALU202020 Existing Land UseALU20_SRC2020 Existing Land Use Source2GP19_CITY2019 Jurisdiction’s general plan land use designationGP19_SCAG2019 SCAG general plan land use codeSP19_CITY2019 Jurisdiction’s specific plan land use designationSP19_SCAG2019 SCAG specific plan land use codeZN19_CITY2019 Jurisdiction’s zoning codeZN19_SCAG2019 SCAG zoning codeSP19_INDEX2019 Specific Plan Index ('0' = outside specific plan area; '1' = inside specific plan area)DC_BLTDecade built of existing structure (example: year built between 1960-1969 is '1960s')3BF_SQFT Building footprint area (in square feet)4PUB_OWNPublic-owned land index ('1' = owned by public agency)PUB_TYPEType of public agency5ADU_STATEThis field is a rudimentary estimate of which parcels have adequate physical space to accommodate a typical detached Accessory Dwelling Unit (ADU)6, (1 = ADU eligible parcel, 0 = Not ADU eligible parcel)SF_UNBUILTDifference between parcel land area and building footprint area expressed in square feetFLOODParcel intersects with flood areas delineated by the Federal Emergency Management Agency (FEMA), obtained from the Digital Flood Insurance Rate Map from FEMA in August 2017. FIREParcel intersects with CalFire State Responsibility Areas Fire Hazard Severity zones (high and very high severity), dated 9/29/2023 and implemented 4/1/2024. WUIParcel intersects with Wildland-Urban Interface or Intermix zones, utilized from CAL FIRE’s Fire and Resource Assessment Program (FRAP), Wildland-Urban Interface (WUI) and Wildland-Urban Intermix (2020). See CAL FIRE for details. SEARISE36Parcel intersects with USGS Coastal Storm Modeling System (CoSMos) One-Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2, 2018)WETLANDParcel intersects a wetland or deepwater habitat, obtained from the US Fish and Wildlife Services National Wetlands Inventory Data (2020)HABITATParcel intersects with habitat connectivity corridors. Data is obtained from the California Department of Fish and Wildlife Habitat Essential Connectivity Project (2010).CONSERVParcel intersects with Areas of Conservation Emphasis (ACEIIv2), obtained from California Department of Fish and Wildlife Areas of Conservation Emphasis (2015)SOARParcel intersects with publicly owned open space identified by the County of Ventura Save Our Agricultural Resources (SOAR, 2017), which consist of a series of voter initiatives that require a majority vote of the people before agricultural land or open space areas can be rezoned for developmentCPADParcel intersects with publicly owned protected open space lands in the State of California through fee ownership as identified in the 2021 California Protected Areas Database (CPAD)CCEDParcel intersects with lands protected under conservation easements as identified in the 2021 California Conservation Easement Database (CCED)TRIBALParcel intersects with the tribal lands for the 16 Federally Recognized Tribal entities in the SCAG region, obtained from the American Indian Reservations/ Federally Recognized Tribal Entities dataset (2021)MILITARYParcel intersects with military lands managed by the US Department of Defense as of 2018FARMLANDParcel intersects with farmlands as identified in the Farmland Mapping and Monitoring Program (FMMP) in the Division of Land Resource Protection in the California Department of Conservation (2018)GRRA_INDEXThe number of Green Region Rresource Areas (GRRAs) that the parcel intersects with. GRRAs are areas where climate hazard zones, environmental sensitivities, and administrative areas where growth would generally not advance SB 375 objectives. See Connect SoCal 2024 Land Use & Communities Technical Report for details. UAZParcel centroid lies within Caltrans 2020 Adjusted Urbanized Area TCAC_2024The opportunity/resource level in the 2024 CTCAC/HCD Opportunity Map SB535_INDEXField takes a value of 1 if parcel intersects with SB 535 Disadvantaged Communities. See Connect SoCal 2024 Equity Analysis Technical Report for details. PEC_INDEXField takes a value of 1 if parcel's block falls within Priority Equity Communities. See Connect SoCal 2024 Equity Analysis Technical Report for details. PDA_INDEXThe number of Priority Development Areas (PDAs) that the parcel's largest overlapping area falls in. PDAs in Connect SoCal 2024 include Neighborhood Mobility Areas (NMAs), Transit Priority Areas (TPAs), Livable Corridors and Spheres of Influence (SOIs) (in unincorporated areas only). See Connect SoCal 2024 for details. PDA_NMAField takes a value of 1 if the parcel's largest overlapping area falls within Neighborhood Mobility Areas. See Connect SoCal 2024 for details. PDA_LCField takes a value of 1 if the parcel's largest overlapping area falls within Livable Corridors. See Connect SoCal 2024 for details. PDA_SOIField takes a value of 1 if the parcel's largest overlapping area falls within Spheres of Influence (SOIs) (in unincorporated areas only). See Connect SoCal 2024 for details. PDA_TPAField takes a value of 1 if the parcel's largest overlapping area falls within Transit Priority Areas. See Connect SoCal 2024 for details. APPAREL1MIThe number of apparel stores within a 1-mile drive7EDUC1MIThe number of educational institutions within a 1-mile drive7GROCERY1MIThe number of grocery stores within a 1-mile drive7HOSPIT1MIThe number of hospitals within a 1-mile drive7RESTAUR1MIThe number of restaurants within a 1-mile drive7JOBS_30MINThe number of the region's jobs accessible within a 30-minute commute by car during morning peak hour (6-9am) in 2050 based on Connect SoCal 2024 travel demand modeling. See Equity Technical Report for details. VMT_TOTAverage daily vehicle miles traveled (VMT) per average resident in the parcel’s transportation analysis zone (TAZ) in 2019, rounded to the nearest mile. This field contains results derived from Connect SoCal 2024’s activity-based travel demand model and do not reflect survey data, do not reflect VMT in any particular parcel within a TAZ, and are not validated at the TAZ-level. SCAG assumes no liability arising from the use of this data.8VMT_WORKAverage daily vehicle miles traveled (VMT) per average resident for work purposes in the parcel’s transportation analysis zone (TAZ) in 2019, rounded to the nearest mile. This field contains results derived from Connect SoCal 2024’s activity-based travel demand model and do not reflect survey data, do not reflect VMT in any particular parcel within a TAZ, and are not validated at the TAZ-level. SCAG assumes no liability arising from the use of this data.8JURIS_PLUSSub-jurisdictional geography in Los Angeles City (Community Plan Areas) and unincorporated areas of Los Angeles County (Planning Areas)YEARDataset YearShape_LengthLength of feature in internal unitsShape_AreaArea of feature in internal units squared1. Slope: '0' - 0~4 percent; '5' - 5~9 percent; '10' - 10~14 percent; '15' = 15~19 percent; '20' - 20~24 percent; '25' = 25 percent or greater.2. ASSESSOR- Assessor's 2020 tax roll records; CPAD- California Protected Areas Database (version 2020b; released in December 2020); CSCD- California School Campus Database (version 2021; released in March 2020); FMMP- Farmland Mapping and

The Digital Geohazards-GIS Map of Everglades National Park and Vicinity (2005 Mapping), Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (ever_geohazard.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (ever_geohazard.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (ever_geohazard.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (ever_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (ever_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (ever_geohazard_metadata_faq.pdf). Please read the ever_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Florida Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (ever_geohazard_metadata.txt or ever_geohazard_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The Los Angeles County Storm Drain System is a geometric network model representing the storm drain infrastructure within Los Angeles County. The long term goal of this network is to seamlessly integrate the countywide drainage infrastructure, regardless of ownership or jurisdiction. Current uses by the Department of Public Works (DPW) include asset inventory, operational maintenance, and compliance with environmental regulations.

GIS DATA DOWNLOADS: (More information is in the table below)

File geodatabase: A limited set of feature classes comprise the majority of this geometric network. These nine feature classes are available in one file geodatabase (.gdb). ArcMap versions compatible with the .gdb are 10.1 and later. Read-only access is provided by the open-source software QGIS. Instructions on opening a .gdb file are available here, and a QGIS plugin can be downloaded here.

Acronyms and Definitions (pdf) are provided to better understand terms used.

ONLINE VIEWING: Use your PC’s browser to search for drains by street address or drain name and download engineering drawings. The Web Viewer link is: https://dpw.lacounty.gov/fcd/stormdrain/

MOBILE GIS: This storm drain system can also be viewed on mobile devices as well as your PC via ArcGIS Online. (As-built plans are not available with this mobile option.)

More About these Downloads All data added or updated by Public Works is contained in nine feature classes, with definitions listed below. The file geodatabase (.gdb) download contains these eleven feature classes without network connectivity. Feature classes include attributes with unabbreviated field names and domains.

ArcMap versions compatible with the .gdb are 10.1 and later.

Feature Class Download Description

CatchBasin In .gdb Catch basins collect urban runoff from gutters

Culvert In .gdb A relatively short conduit that conveys storm water runoff underneath a road or embankment. Typical materials include reinforced concrete pipe (RCP) and corrugated metal pipe (CMP). Typical shapes are circular, rectangular, elliptical, or arched.

ForceMain In .gdb Force mains carry stormwater uphill from pump stations into gravity mains and open channels.

GravityMain In .gdb Underground pipes and channels.

LateralLine In .gdb Laterals connect catch basins to underground gravity mains or open channels.

MaintenanceHole In .gdb The top opening to an underground gravity main used for inspection and maintenance.

NaturalDrainage In .gdb Streams and rivers that flow through natural creek beds

OpenChannel In .gdb Concrete lined stormwater channels.

PumpStation In .gdb Where terrain causes accumulation, lift stations are used to pump stormwater to where it can once again flow towards the ocean

Data Field Descriptions

Most of the feature classes in this storm drain geometric network share the same GIS table schema. Only the most critical attributes are listed here per LACFCD operations.

Attribute Description

ASBDATE The date the design plans were approved “as-built” or accepted as “final records”.

CROSS_SECTIN_SHAPE The cross-sectional shape of the pipe or channel. Examples include round, square, trapezoidal, arch, etc.

DIAMETER_HEIGHT The diameter of a round pipe or the height of an underground box or open channel.

DWGNO Drain Plan Drawing Number per LACFCD Nomenclature

EQNUM Asset No. assigned by the Department of Public Works’ (in Maximo Database).

MAINTAINED_BY Identifies, to the best of LAFCD’s knowledge, the agency responsible for maintaining the structure.

MOD_DATE Date the GIS features were last modified.

NAME Name of the individual drainage infrastructure.

OWNER Agency that owns the drainage infrastructure in question.

Q_DESIGN The peak storm water runoff used for the design of the drainage infrastructure.

SOFT_BOTTOM For open channels, indicates whether the channel invert is in its natural state (not lined).

SUBTYPE Most feature classes in this drainage geometric nature contain multiple subtypes.

UPDATED_BY The person who last updated the GIS feature.

WIDTH Width of a channel in feet.

Community Wildfire Protection Plan The City of Austin’s Wildfire Database and Risk Models were developed to support wildfire planning and mitigation efforts in the City of Austin. The areas in Austin most likely to be impacted by wildfire are referred to as the Wildland Urban Interface. This data helps identify the potential impacts of wildfire to a diverse set of values ranging from the built environment and Critical Infrastructure to habitat and green infrastructure. A full description of the Risk model can be access through this link. http://www.austintexas.gov/sites/default/files/files/hsem/Section_4_-_Risk_Assessment.pdf The Data was collected and analyzed by Joseph White Fire Behavior Researcher with Baylor University. It was derived from numerous sources as listed in the CWPP Risk Assessment Guide http://www.austintexas.gov/sites/default/files/files/hsem/Section_9_-_References.pdf The data was created during the CWPP development process starting in April of 2013 and was refined up to the adoption of the CWPP and data in November of 2014. The goal is to update the data every 5 years or as more updated data becomes available.

This dataset provides supplementary material for the previously published dataset GDB-9-Ex (1), which is available at the following website: https://www.osti.gov/dataexplorer/biblio/dataset/1890227 The dataset contains a file called "gdb9_ex.csv" that synthesizes the information contained in GDB-9-Ex. Each row in a .CSV file is associated with a molecule, and the columns contain the following information: 1) molecules ID 2) SMILES string representation 3) DFTB-PE (eV): formation energy 4) first 50 electronic excitation modes 5) oscillators strengths of the first 50 electronic excitation modes The compression of this information into CSV files will allow a more agile extraction and management of information to the users that do not have access to large scale HPC platforms. REFERENCES (1) Lupo Pasini, Massimiliano, Yoo, Pilsun, Mehta, Kshitij, and Irle, Stephan. GDB-9-Ex: Quantum chemical prediction of UV/Vis absorption spectra for GDB-9 molecules. United States: N. p., 2022. Web. doi:10.13139/OLCF/1890227.

DOI retrieved: 2018

"Due to the size of this dataset, both Shapefile and Spreadsheet download options will not work as expected. The File Geodatabase is an alternative option for this data download"This is SCAG's 2019 Annual Land Use (ALU v. 2019.1) at the parcel-level, updated as of February 2021. This dataset has been modified to include additional attributes in order to feed SCAG's Housing Element Parcel Tool (HELPR), version 2.0. The dataset will be further reviewed and updated as additional information is released. Please refer to the tables below for data dictionary and SCAG’s land use classification.Field NameData TypeField DescriptionPID19Text2019 SCAG’s parcel unique IDAPN19Text2019 Assessor’s parcel numberCOUNTYTextCounty name (based on 2016 county boundary)COUNTY_IDDoubleCounty FIPS code (based on 2016 county boundary)CITYTextCity name (based on 2016 city boundary)CITY_IDDoubleCity FIPS code (based on 2016 city boundary)MULTIPARTShort IntegerMultipart feature (the number of multiple polygons; '1' = singlepart feature)STACKLong IntegerDuplicate geometry (the number of duplicate polygons; '0' = no duplicate polygons)ACRESDoubleParcel area (in acreage)GEOID20Text2020 Census Block Group GEOIDSLOPEShort IntegerSlope information1APN_DUPLong IntegerDuplicate APN (the number of multiple tax roll property records; '0' = no duplicate APN)IL_RATIODoubleRatio of improvement assessed value to land assessed valueLU19Text2019 existing land useLU19_SRCTextSource of 2019 existing land use2SCAGUID16Text2016 SCAG’s parcel unique IDAPNText2016 Assessor’s parcel numberCITY_GP_COText2016 Jurisdiction’s general plan land use designationSCAG_GP_COText2016 SCAG general plan land use codeSP_INDEXShort IntegerSpecific plan index ('0' = outside specific plan area; '1' = inside specific plan area)CITY_SP_COText2016 Jurisdiction’s specific plan land use designationSCAG_SP_COText2016 SCAG specific plan land use codeCITY_ZN_COText2016 Jurisdiction’s zoning codeSCAG_ZN_COText2016 SCAG zoning codeLU16Text2016 existing land useYEARLong IntegerDataset yearPUB_OWNShort IntegerPublic-owned land index ('1' = owned by public agency)PUB_NAMETextName of public agencyPUB_TYPETextType of public agency3BF_SQFTDoubleBuilding footprint area (in square feet)4BSF_NAMETextName of brownfield/superfund site5BSF_TYPETextType of brownfield/superfund site5FIREShort IntegerParcel intersects CalFire Very High Hazard Local Responsibility Areas or State Responsibility Areas (November 2020 version) (CalFIRE)SEARISE36Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)1 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)SEARISE72Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)2 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)FLOODShort IntegerParcel intersects with a FEMA 100 Year Flood Plain data from the Digital Flood Insurance Rate Map (DFIRM), obtained from Federal Emergency Management Agency (FEMA) in August 10, 2017EQUAKEShort IntegerParcel intersects with an Alquist-Priolo Earthquake Fault Zone (California Geological Survey; 2018)LIQUAFAShort IntegerParcel intersects with a Liquefaction Susceptibility Zone (California Geological Survey; 2016)LANDSLIDEShort IntegerParcel intersects with a Landslide Hazard Zone (California Geological Survey; 2016)CPADShort IntegerParcel intersects with a protected area from the California Protected Areas Database(CPAD) – www.calands.org (accessed April 2021)RIPARIANShort IntegerParcel centroid falls within Active River Areas(2010)or parcel intersects with a Wetland Area in the National Wetland Inventory(Version 2)WILDLIFEShort IntegerParcel intersects with wildlife habitat (US Fish & Wildlife ServiceCritical Habitat, Southern California Missing Linkages, Natural Lands & Habitat Corridors from Connect SoCal, CEHC Essential Connectivity Areas,Critical Coastal Habitats)CNDDBShort IntegerThe California Natural Diversity Database (CNDDB)includes the status and locations of rare plants and animals in California. Parcels that overlap locations of rare plants and animals in California from the California Natural Diversity Database (CNDDB)have a greater likelihood of encountering special status plants and animals on the property, potentially leading to further legal requirements to allow development (California Department of Fish and Wildlife). Data accessed in October 2020.HCPRAShort IntegerParcel intersects Natural Community & Habitat Conservation Plans Reserve Designs from the Western Riverside MHSCP, Coachella Valley MHSCP, and the Orange County Central Coastal NCCP/HCP, as accessed in October 2020WETLANDShort IntegerParcel intersects a wetland or deepwater habitat as defined by the US Fish & Wildlife Service National Wetlands Inventory, Version 2.UAZShort IntegerParcel centroid lies within a Caltrans Adjusted Urbanized AreasUNBUILT_SFDoubleDifference between parcel area and building footprint area expressed in square feet.6GRCRY_1MIShort IntegerThe number of grocery stores within a 1-mile drive7HEALTH_1MIShort IntegerThe number of healthcare facilities within a 1-mile drive7OPENSP_1MIShort IntegerQuantity of open space (roughly corresponding to city blocks’ worth) within a 1-mile drive7TCAC_2021TextThe opportunity level based on the 2021 CA HCD/TCAC opportunity scores.HQTA45Short IntegerField takes a value of 1 if parcel centroid lies within a 2045 High-Quality Transit Area (HQTA)JOB_CTRShort IntegerField takes a value of 1 if parcel centroid lies within a job centerNMAShort IntegerField takes a value of 1 if parcel centroid lies within a neighborhood mobility area.ABS_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within an absolute constraint area. See the Sustainable Communities Strategy Technical Reportfor details.VAR_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within a variable constraint area. See the Sustainable Communities Strategy Technical Reportfor details.EJAShort IntegerField takes a value of 1 if parcel centroid lies within an Environmental Justice Area. See the Environmental Justice Technical Reportfor details.SB535Short IntegerField takes a value of 1 if parcel centroid lies within an SB535 Disadvantaged Community area. See the Environmental Justice Technical Reportfor details.COCShort IntegerField takes a value of 1 if parcel centroid lies within a Community of Concern See the Environmental Justice Technical Reportfor details.STATEShort IntegerThis field is a rudimentary estimate of which parcels have adequate physical space to accommodate a typical detached Accessory Dwelling Unit (ADU)8.SBShort IntegerIndex of ADU eligibility according to the setback reduction policy scenario (from 4 to 2 feet) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SMShort IntegerIndex of ADU eligibility according to the small ADU policy scenario (from 800 to 600 square feet ADU) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)PKShort IntegerIndex of ADU eligibility according to parking space exemption (200 square feet) policy scenario (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SMShort IntegerIndex of ADU eligibility according to both the setback reduction and small ADU policy scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_PKShort IntegerIndex of ADU eligibility according to both the setback reduction and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SM_PKShort IntegerIndex of ADU eligibility according to both the small ADU policy and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SM_PKShort IntegerIndex of ADU eligibility according to the setback reduction, small ADU, and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)1. Slope: '0' - 0~4 percent; '5' - 5~9 percent; '10' - 10~14 percent; '15' = 15~19 percent; '20' - 20~24 percent; '25' = 25 percent or greater.2. Source of 2019 existing land use: SCAG_REF- SCAG's regional geospatial datasets;ASSESSOR- Assessor's 2019 tax roll records; CPAD- California Protected Areas Database (version 2020a; accessed in September 2020); CSCD- California School Campus Database (version 2018; accessed in September 2020); FMMP- Farmland Mapping and Monitoring Program's Important Farmland GIS data (accessed in September 2020); MIRTA- U.S. Department of Defense's Military Installations, Ranges, and Training Areas GIS data (accessed in September 2020)3. Type of public agency includes federal, state, county, city, special district, school district, college/university, military.4. Based on 2019 building footprint data obtained from BuildingFootprintUSA (except that 2014 building footprint data was used for Imperial County). Please note that 2019 building footprint data does not cover the entire SCAG region (overlapped with 83% of parcels in the SCAG Region).5. Includes brownfield/superfund site whose address information are matched by SCAG rooftop address locator. Brownfield data was obtained from EPA's Assessment, Cleanup and Redevelopment Exchange System (ACRES) database, Cleanups in my community (CIMC), DTSC brownfield Memorandum of Agreement (MOA). Superfund site data was obtained from EPA's Superfund Enterprise Management System (SEMS) database.6. Parcels with a zero value for building footprint area are marked as NULL to indicate this field is not reliable.7. These values are intended as a rudimentary indicator of accessibility developed by SCAG using 2016 InfoUSA business establishment data and 2017 California Protected Areas data. See documentation for details.8. A detailed study conducted by Cal Poly Pomona (CPP) and available hereconducted an extensive review of state and local requirements and development trends for ADUs in the SCAG region and developed a baseline set of assumptions for estimating how many of a jurisdiction’s parcels

An ESRI File Geodatabase containing all the Telecommunication feature classes available for download.