Description

Wetlands in California are protected by several federal and state laws, regulations, and policies. This layer was extracted from the broader vegetation raster from the CA Nature project which was recently enhanced to include a more comprehensive definition of wetland. This wetlands dataset is used as an exclusion as part of the biological planning priorities in the CEC 2023 Land-Use Screens.

This layer is featured in the CEC 2023 Land-Use Screens for Electric System Planning data viewer.

For more information about this layer and its use in electric system planning, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.

All driveways are captured and the surface type noted (pavement type versus dirt or gravel, etc.). Street Sidewalks and Non-Street Sidewalks are captured as separate polygon features. The walkway leading from residences or commercial buildings are recorded as Non-Street Sidewalks. Features that serve as the primary walkway parallel to a street are recorded as a Street Sidewalk. Stairways that serve as part of the walkway are recorded with the walkway. This data was captured for use in general mapping at a scale of 1:100. Countywide data updated Spring 2020. For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

Bulk exports, in file-geodatabase format, of data that is shared via the VT EGC (Enterprise GIS Consortium) Geospatial Data Exchange Protocol.

Public and Private Colleges and Universities.For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

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 Residential Schools Locations Dataset in Geodatabase format (IRS_Locations.gbd) contains a feature layer "IRS_Locations" that contains the locations (latitude and longitude) of Residential Schools and student hostels operated by the federal government in Canada. All the residential schools and hostels that are listed in the Residential Schools Settlement Agreement are included in this dataset, as well as several Industrial schools and residential schools that were not part of the IRRSA. This version of the dataset doesn’t include the five schools under the Newfoundland and Labrador Residential Schools Settlement Agreement. The original school location data was created by the Truth and Reconciliation Commission, and was provided to the researcher (Rosa Orlandini) by the National Centre for Truth and Reconciliation in April 2017. The dataset was created by Rosa Orlandini, and builds upon and enhances the previous work of the Truth and Reconcilation Commission, Morgan Hite (creator of the Atlas of Indian Residential Schools in Canada that was produced for the Tk'emlups First Nation and Justice for Day Scholar's Initiative, and Stephanie Pyne (project lead for the Residential Schools Interactive Map). Each individual school location in this dataset is attributed either to RSIM, Morgan Hite, NCTR or Rosa Orlandini. Many schools/hostels had several locations throughout the history of the institution. If the school/hostel moved from its’ original location to another property, then the school is considered to have two unique locations in this dataset,the original location and the new location. For example, Lejac Indian Residential School had two locations while it was operating, Stuart Lake and Fraser Lake. If a new school building was constructed on the same property as the original school building, it isn't considered to be a new location, as is the case of Girouard Indian Residential School.When the precise location is known, the coordinates of the main building are provided, and when the precise location of the building isn’t known, an approximate location is provided. For each residential school institution location, the following information is provided: official names, alternative name, dates of operation, religious affiliation, latitude and longitude coordinates, community location, Indigenous community name, contributor (of the location coordinates), school/institution photo (when available), location point precision, type of school (hostel or residential school) and list of references used to determine the location of the main buildings or sites. Access Instructions: there are 47 files in this data package. Please download the entire data package by selecting all the 47 files and click on download. Two files will be downloaded, IRS_Locations.gbd.zip and IRS_LocFields.csv. Uncompress the IRS_Locations.gbd.zip. Use QGIS, ArcGIS Pro, and ArcMap to open the feature layer IRS_Locations that is contained within the IRS_Locations.gbd data package. The feature layer is in WGS 1984 coordinate system. There is also detailed file level metadata included in this feature layer file. The IRS_locations.csv provides the full description of the fields and codes used in this dataset.

2' Contour Lines generated from Lee County 1998 Digital Orthophotography project performed by EarthData International. Elevations are in NAVD88, standard vertical error should not exceed 0.6 ft. February-March 1998.

This dataset is available for download from: Parcelization (File Geodatabase)Parcelization, a measure of size and density of parcels in a localized area, is a development feasibility factor that is used in evaluating substations’ ability to support new utility-scale resources in long-term energy planning. A statewide dataset of parcel boundaries are used to develop this index. The parcels are converted into a 90-meter raster, containing values of a unique identifier reflective of Parcel APN. A focal statistics tool is used to count the number of unique parcels within a 0.5 mile radius of each parcel. This output is provided here and is an intermediate output to the final parcelization map. Users who wish to use this information to produce the final map should overlay parcel boundary data and extract the mean raster value within each parcel. The map is limited to the area considered with solar technical resource potential after a minimum set of land-use screens (referred to as the Base Exclusions) has been applied. More information on the methods developing this dataset as well as the main use of this dataset in state electric system planning processes can be found in a recent CEC staff report and workshops supporting the resource-to-busbar mapping methodology for the 2024-2025 Transmission Planning Process.

Spot elevations generated from Lee County 1998 Digital Orthophotography project performed by EarthData International Elevations are in NAVD88. February-March 1998

The Geodatabase to Shapefile Warning Tool examines feature classes in input file geodatabases for characteristics and data that would be lost or altered if it were transformed into a shapefile. Checks include:
1) large files (feature classes with more than 255 fields or over 2GB), 2) field names longer than 10 characters
string fields longer than 254 characters, 3) date fields with time values 4) NULL values, 5) BLOB, guid, global id, and raster field types, 6) attribute domains or subtypes, and 7) annotation or topology

The results of this inspection are written to a text file ("warning_report_[geodatabase_name]") in the directory where the geodatabase is located. A section at the top provides a list of feature classes and information about the geodatabase as a whole. The report has a section for each valid feature class that returned a warning, with a summary of possible warnings and then more details about issues found.

The tool can process multiple file geodatabases at once. A separate text file report will be created for each geodatabase. The toolbox was created using ArcGIS Pro 3.7.11.

For more information about this and other related tools, explore the Geospatial Data Curation toolkit

Note: please go to https://data.sfgov.org/d/ynuv-fyni to access the same data in additional open formats. These footprint extents are collapsed from an earlier 3D building model provided by Pictometry of 2010, and have been refined from a version of building masses publicly available on the open data portal for over two years. The building masses were manually split with reference to parcel lines, but using vertices from the building mass wherever possible. These split footprints correspond closely to individual structures even where there are common walls; the goal of the splitting process was to divide the building mass wherever there was likely to be a firewall.An arbitrary identifier was assigned based on a descending sort of building area for 177,023 footprints. The centroid of each footprint was used to join a property identifier from a draft of the San Francisco Enterprise GIS Program's cartographic base, which provides continuous coverage with distinct right-of-way areas as well as selected nearby parcels from adjacent counties. See accompanying document SF_BldgFoot_2017-05_description.pdf for more on methodology and motivation https://data.sfgov.org/d/ynuv-fyni/ about

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 points in this dataset represent the location of a site or structure in Lee County, FL to which an address has been assigned by Lee County Department of Public Safety/E911 Addressing Division.

One-foot and two-foot contours derived from LiDAR terrain model. The DTM was developed to support the Florida Division of Emergency Management (FDEM) development and maintenance of Regional Evacuation Studies (Study), which include vulnerability assessments and assist disaster response personnel in understanding threats to Florida's citizens and visitors. Breaklines improve the digital elevation model in areas where the point density is insufficient.This data set is one component of a digital terrain model (DTM) for the Florida Division of Emergency Management's (FDEM) Project Management and Technical Services for Mapping within Coastal Florida (Contract 07-HS-34-14-00-22-469), encompassing the entire coastline of Florida. The dataset is comprised of mass points, 2-D and 3-D breakline features, 1-foot and 2-foot contours, ground control, vertical test points, and a footprint of the data set, in the ESRI ArcGIS File Geodatabase format. In accordance with the Baseline Specifications 1.2, the following breakline features are contained within the database: closed water bodies (lakes, reservoirs, etc) as 2-D or 3-D polygons; linear hydrographic features (streams, shorelines, canals, swales, embankments, etc) as 3-D breaklines; coastal shorelines as 2-D or 3-D linear features; edge of pavement road features as 3-D breaklines; soft features (ridges, valleys, etc.) as 3-D breaklines; low confidence areas as 2-D polygons; island features as 2-D or 3-D polygons; overpasses and bridges as 3-D breaklines. Contours were generated from a gridded DEM: 2-foot contours meet National Map Accuracy Standards, with 1-foot contours for visualization purposes. The LiDAR masspoints are delivered in the LAS file format based on the FDEM's 5,000' by 5,000' grid. Breakline features were captured to develop a hydrologically correct DTM. Bare earth LiDAR masspoint data display a vertical accuracy of at least 0.3-feet root mean square error (RMSE) in open unobscured areas.

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.

Data in this layer is compiled from a variety of sources. Attributes have been added to distinguish the sources."LeePA Building Footprints" are created and maintained by the Lee County Property Appraiser's GIS. The geometry and attributes are extracted from their databases and combined based on the unique building key."LeePA Condo Buildings" are created from features in the Lee County Property Appraiser's parcel fabric. The geometry and attributes are extracted from their databases and combined using a variety of methods.Other buildings have been added by Lee County GIS. These are typically mobile/manufactured homes or time shares. Most mobile/manufactured homes were created using Esri's Building Footprint Extraction deep learning package and Regularize Building Footprint geoprocessing tool from 2024 aerial imagery. Additional attributes were added by Lee County GIS.

This dataset includes Park and Ride Lots located within Montgomery County. It was developed and is maintained by DTS-GIS. This dataset satisfies County basemap accuracy requirements (1:2400) and is included in the Places of Interest Guide. For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

Note: please go to https://res1datad-o-tsfgovd-o-torg.vcapture.xyz/d/ynuv-fyni to access the same data in additional open formats. These footprint extents are collapsed from an earlier 3D building model provided by Pictometry of 2010, and have been refined from a version of building masses publicly available on the open data portal for over two years. The building masses were manually split with reference to parcel lines, but using vertices from the building mass wherever possible. These split footprints correspond closely to individual structures even where there are common walls; the goal of the splitting process was to divide the building mass wherever there was likely to be a firewall.An arbitrary identifier was assigned based on a descending sort of building area for 177,023 footprints. The centroid of each footprint was used to join a property identifier from a draft of the San Francisco Enterprise GIS Program's cartographic base, which provides continuous coverage with distinct right-of-way areas as well as selected nearby parcels from adjacent counties. See accompanying document SF_BldgFoot_2017-05_description.pdf for more on methodology and motivation https://res1datad-o-tsfgovd-o-torg.vcapture.xyz/d/ynuv-fyni/ about

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.