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.

Enroll in this plan to get familiar with the user interface, apply commonly used tools, and master the basics of mapping and analyzing data using ArcGIS Pro.Goals Install ArcGIS Pro and efficiently locate tools, options, and user interface elements. Add data to a map, symbolize map features to represent type, categories, or quantities; and optimize map display at various scales. Create a file geodatabase to organize and accurately maintain GIS data over time. Complete common mapping, editing, and analysis workflows.

This file geodatabase consists of all publicly available (Open) products extracted from the Land Information Ontario (LIO) Warehouse excluding Wetlands, Contours and OHN products. This data represents the data housed in the LIO Warehouse as of the date the extraction occurred. The file geodatabase will be refreshed on a bi-weekly basis and has been prepared as a convenience to users wanting access to all LIO Warehouse Open Data products in file geodatabase structure. Metadata for each layer is available in the Ontario GeoHub and can be found by searching for the various layers individually.StatusOn going: Data is continually being updatedMaintenance and Update FrequencyFortnightly: Data is updated every two weeksContactGeospatial Ontario Support, Ministry of Natural Resources and Forestry, geospatial@ontario.ca

This street centerline lines feature class represents current right of way in the City of Los Angeles. It shows the official street names and is related to the official street name data. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most current geographic information of the public right of way. The right of way information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works. Street Centerline layer was created in geographical information systems (GIS) software to display Dedicated street centerlines. The street centerline layer is a feature class in the LACityCenterlineData.gdb Geodatabase dataset. The layer consists of spatial data as a line feature class and attribute data for the features. City of LA District Offices use Street Centerline layer to determine dedication and street improvement requirements. Engineering street standards are followed to dedicate the street for development. The Bureau of Street Services tracks the location of existing streets, who need to maintain that road. Additional information was added to Street Centerline layer. Address range attributes were added make layer useful for geocoding. Section ID values from Bureau of Street Services were added to make layer useful for pavement management. Department of City Planning added street designation attributes taken from Community Plan maps. The street centerline relates to the Official Street Name table named EASIS, Engineering Automated Street Inventory System, which contains data describing the limits of the street segment. A street centerline segment should only be added to the Street Centerline layer if documentation exists, such as a Deed or a Plan approved by the City Council. Paper streets are street lines shown on a recorded plan but have not yet come into existence on the ground. These street centerline segments are in the Street Centerline layer because there is documentation such as a Deed or a Plan for the construction of that street. Previously, some street line features were added although documentation did not exist. Currently, a Deed, Tract, or a Plan must exist in order to add street line features. Many street line features were edited by viewing the Thomas Bros Map's Transportation layer, TRNL_037 coverage, back when the street centerline coverage was created. When TBM and BOE street centerline layers were compared visually, TBM's layer contained many valid streets that BOE layer did not contain. In addition to TBM streets, Planning Department requested adding street line segments they use for reference. Further, the street centerline layer features are split where the lines intersect. The intersection point is created and maintained in the Intersection layer. The intersection attributes are used in the Intersection search function on NavigateLA on BOE's web mapping application NavigateLA. The City of Los Angeles Municipal code states, all public right-of-ways (roads, alleys, etc) are streets, thus all of them have intersections. Note that there are named alleys in the BOE Street Centerline layer. Since the line features for named alleys are stored in the Street Centerline layer, there are no line features for named alleys in those areas that are geographically coincident in the Alley layer. For a named alley , the corresponding record contains the street designation field value of ST_DESIG = 20, and there is a name stored in the STNAME and STSFX fields.List of Fields:SHAPE: Feature geometry.OBJECTID: Internal feature number.STNAME_A: Street name Alias.ST_SUBTYPE: Street subtype.SV_STATUS: Status of street in service, whether the street is an accessible roadway. Values: • Y - Yes • N - NoTDIR: Street direction. Values: • S - South • N - North • E - East • W - WestADLF: From address range, left side.ZIP_R: Zip code right.ADRT: To address range, right side.INT_ID_TO: Street intersection identification number at the line segment's end node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.SECT_ID: Section ID used by the Bureau of Street Services. Values: • none - No Section ID value • private - Private street • closed - Street is closed from service • temp - Temporary • propose - Proposed construction of a street • walk - Street line is a walk or walkway • known as - • numeric value - A 7 digit numeric value for street resurfacing • outside - Street line segment is outside the City of Los Angeles boundary • pierce - Street segment type • alley - Named alleySTSFX_A: Street suffix Alias.SFXDIR: Street direction suffix Values: • N - North • E - East • W - West • S - SouthCRTN_DT: Creation date of the polygon feature.STNAME: Street name.ZIP_L: Zip code left.STSFX: Street suffix. Values: • BLVD - BoulevardADLT: To address range, left side.ID: Unique line segment identifierMAPSHEET: The alpha-numeric mapsheet number, which refers to a valid B-map or A-map number on the Cadastral tract index map. Values: • B, A, -5A - Any of these alpha-numeric combinations are used, whereas the underlined spaces are the numbers.STNUM: Street identification number. This field relates to the Official Street Name table named EASIS, to the corresponding STR_ID field.ASSETID: User-defined feature autonumber.TEMP: This attribute is no longer used. This attribute was used to enter 'R' for reference arc line segments that were added to the spatial data, in coverage format. Reference lines were temporary and not part of the final data layer. After editing the permanent line segments, the user would delete temporary lines given by this attribute.LST_MODF_DT: Last modification date of the polygon feature.REMARKS: This attribute is a combination of remarks about the street centerline. Values include a general remark, the Council File number, which refers the street status, or whether a private street is a private driveway. The Council File number can be researched on the City Clerk's website http://cityclerk.lacity.org/lacityclerkconnect/INT_ID_FROM: Street intersection identification number at the line segment's start node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.ADRF: From address range, right side.

The Digital Geologic-GIS Map of the Rozel Quadrangle, Utah is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (roze_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 3.X map file (.mapx) file (roze_geology.mapx) and individual Pro 3.X layer (.lyrx) 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 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 readme file (gosp_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (gosp_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 (roze_geology_metadata_faq.pdf). Please read the gosp_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: 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 (roze_geology_metadata.txt or roze_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 Pro, 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 Digital Surficial Geologic-GIS Map of Minuteman National Historical Site and Vicinity, Massachusetts 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 (mima_surficial_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 and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (mima_surficial_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 (mima_geology.gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (mima_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 (mima_surficial_geology_metadata_faq.pdf). Please read the mima_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: http://www.google.com/earth/index.html. 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 (mima_surficial_geology_metadata.txt or mima_surficial_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 1:50,000 and United States National Map Accuracy Standards features are within (horizontally) 25.4 meters or 83.3 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 dataset is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into a Conterminous US-wide extent, and adding a Conterminous US-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing 'ready to map 'attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format. The raster and vector map data have a Conterminous US-wide extent. The raster map data have a 10 meter cell size that approximates the vector polygons in an Albers Equal Area projection. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link to raster cells and polygons to attribute tables, including the new value added look up (valu) table that contains additional derived data.The value added look up (valu) table contains attribute data summarized to the map unit level using best practice generalization methods intended to meet the needs of most users. The generalization methods include map unit component weighted averages and percent of the map unit meeting a given criteria.The Gridded SSURGO dataset was created for use in national, regional, and state-wide resource planning and analysis of soils data. The raster map layer data can be readily combined with other national, regional, and local raster layers, e.g., National Land Cover Database (NLCD), the National Agricultural Statistics Service (NASS) Crop Data Layer, or the National Elevation Dataset (NED).

The geodatabase is one of ten that – together with several supplementary geodatabases, a web map viewer, and a data dictionary – compose the Data Atlas (Atlas) component of the 2020 New Mexico Forest Action Plan (Forest Action Plan). It contains the data for Habitat for terrestrial, aerial, and aquatic animals, and plants are valued for the biodiversity they sustain. This model maps the value provided by our forests to plants, animals and biodiversity.Integrated into the Atlas in 2019-2020 with wall-to-wall coverage across all jurisdictions in New Mexico, these data serve to guide the implementation of natural resource management strategies in New Mexico by the Forestry Division and its collaborators in accord with the Forest Action Plan. The data in the ten primary geodatabases characterize the spatial distribution and condition of forest and other natural resources (or, assets) valued by New Mexicans, major threat factors (or, hazards), and risk indices characterizing the susceptibility of resources to applicable threats. The data were prepared for use in spatial prioritization of resource protection and restoration strategies over 2020 – 2030 by the Forestry Division and its partners. Under direction of the New Mexico Forest and Watershed Health Coordinating Group (NMFWHCG), the Assessment was structured for spatial risk analysis by (a) grouping resource data into eight “themes” in accord with common beneficiaries and similarities in mapping approach, and (b) in preparing data for six major threat factors:Resource themes:Water Quality and Supply Wildland Communities Recreation and Cultural Use Timber and GrazingCarbon Sequestration and StorageBiodiversity Indigenous and Traditional Use Urban Forests and CommunitiesThreat factors:WildfirePost-wildfire Flooding, Erosion and Debris Flow Disease and InsectsClimate ChangeDevelopment and FragmentationUse and Forest Management ActivitiesBiodiversity Feature Classes• Aquatic CHAT SERI• Aquatic COA• Aquatic CritHab• Aquatic CritHab Line• COA• Connectivity LCC Bear• Connectivity LCC Elk• Connectivity LCC Lpc• Connectivity LCC Max• Connectivity LCC Maz riskHumMod• Connectivity LCC Pronghorn• Connectivity LCC Sheep• Connectivity LCC Sum• Connectivity Omni ImportPreserve• Connectivity Omni ImportPreserve_riskHumMod• Naturalness• Naturalness_riskHumMod• RiparianCorridors• Terrestrial_BatUse• Terrestiral_CHAT_SERI• Terrestrial_CHAT_SOC• Terrestrial_COA• Terrestrial_CritHab• Terrestial_IBA• Terrestrial_IPAEach dataset’s membership in a resource or threat category is indicated by its file name (e.g., debris flow, which falls under the Post-wildfire Flooding, Erosion, and Debris Flow threat factor, is denoted as “NMFAP2020_Threat_Postfire_DebrisFlow”). Datasets for risk indices are named first by the affected resource, then with the word “risk” followed by the applicable threat (e.g., “NMFAP2020_Theme_Water_IrrigatorsAF_Surface_riskWildfire” is the index of risk from wildfire to acre-feet of surface water accessible to irrigators). In integrating the best available statewide spatial data for the Assessment, The Nature Conservancy (TNC) relied on contributions from a range of partner agencies, organizations, and individual researchers. Scope and detail of written documentation varied by source and dataset. In a few cases, understanding of data and confidence in their inclusion in the Assessment was assured through personal communication with the originators and/or discursive review by subject matter experts on technical panels convened around the resource themes. Metadata provided in the Atlas are written to conform to the information set exposed in the Item Description style of the ArcGIS Metadata format. Beyond this baseline, links to external references are provided whenever appropriate. If additional information on a dataset is sought beyond what is detailed in the Atlas and Assessment narrative, please contact the responsible entity or entities listed under the Credits metadata header for that item. Most of the raster data provided are 30 meter or coarser in resolution and are intended to guide prioritization of areas considered at scales generally no larger (i.e., no finer) than 1:100,000.

This dataset captures in digital form the results of previously published U.S. Geological Survey (USGS) Water Mission Area studies related to water resource assessment of Cenozoic strata and unconsolidated deposits within the Mississippi Embayment and the Gulf Coastal Plain of the south-central United States. The data are from reports published from the late 1980s to the mid-1990s by the Gulf Coast Regional Aquifer-System Analysis (RASA) studies and in 2008 by the Mississippi Embayment Regional Aquifer Study (MERAS). These studies, and the data presented here, describe the geologic and hydrogeologic units of the Mississippi embayment, Texas coastal uplands, and the coastal lowlands aquifer systems, south-central United States. This dataset supercedes a previously released dataset on USGS ScienceBase (https://doi.org/10.5066/P9JOHHO6) that was found to contain errors. Following initial release of data, several types of errors were recognized in the well downhole stratigraphic data. Most of these errors were the result of unrecognized improper results in the optical character recognition conversion from the original source report. All downhole data have been thoroughly checked and corrected, data tables were revised, and new point feature classes were created for well location and WellHydrogeologicUnit. GIS data related to the geologic map and subsurface contours were correct in original release and are retained here in original form; only the well data have been revised from the initial data release. The Mississippi embayment, Texas coastal uplands, and coastal lowlands aquifer systems underlie about 487,000 km2 in parts of Alabama, Arkansas, Florida, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee, and Texas from the Rio Grande on the west to the western part of Florida on the east. The previously published investigations divided the Cenozoic strata and unconsolidated deposits within the Mississippi Embayment and the Gulf Coastal Plain into 11 major geologic units, typically mapped at the group level, with several additional units at the formational level, which were aggregated into six hydrogeologic units within the Mississippi embayment and Texas coastal uplands and into five hydrogeologic units within the Coastal Lowlands aquifer system. These units include the Mississippi River Valley alluvial aquifer, Vicksburg-Jackson confining unit (contained within the Jackson Group), the upper Claiborne aquifer (contained within the Claiborne Group), the middle Claiborne confining unit (contained within the Claiborne Group), the middle Claiborne aquifer (contained within the Claiborne Group), the lower Claiborne confining unit (contained within the Claiborne Group), the lower Claiborne aquifer (contained within the Claiborne Group), the middle Wilcox aquifer (contained within the Wilcox Group), the lower Wilcox aquifer (contained within the Wilcox Group), and the Midway confining unit (contained within the Midway Group). This dataset includes structure contour and thickness data digitized from plates in two reports, borehole data compiled from two reports, and a geologic map digitized from a report plate. Structure contour and thickness maps of hydrogeologic units in the Mississippi Embayment and Texas coastal uplands had been previously digitized by a USGS study from georeferenced images of altitude and thickness contours in USGS Professional Paper 1416-B (Hosman and Weiss, 1991). These data, which were stored on the USGS Water Mission Area’s NSDI node, were downloaded, reformatted, and attributed for present dataset. Structure contour maps of geologic units in the Mississippi Embayment and Texas coastal uplands were digitized and attributed from georeferenced images of altitude and thickness contours in USGS Professional Paper 1416-G (Hosman, 1996) for this data release. Borehole data in this data release include data compiled for USGS Gulf Coast RASA studies in which a scanned version of a USGS report (Wilson and Hosman, 1987) was converted through optical character recognition and then manipulated to form a data table, and from borehole data compiled for the subsequent MERAS study (Hart and Clark, 2008) where an Excel workbook was downloaded and manipulated for use in a GIS and as part of this dataset. The digital geologic map was digitized from Plate 4 of USGS Professional Paper 1416-G (Hosman, 1996) and then attributed according to the USGS National Cooperative Geologic Mapping Program’s GeMS digital geologic map schema. The digital dataset a digital geologic map with contacts and faults and geologic map polygons distributed as separate feature classes within a geographic information system geodatabase. The geologic map database is a digital representation of the geologic compilation of the Guld Coast region originally published as Plate 4 of USGS Professional Paper 1416-G (Hosman, 1996). The dataset includes a second geographic information system geodatabase that contain digital structure contour and thickness data as polyline feature classes for all of the hydrogeologic units contoured in USGS Professional Paper 1416-B (Hosman and Weiss, 1991) and all of the geologic units contoured in USGS Professional Paper 1416-G (Hosman, 1996). The geodatabase also contains separate point feature classes that portray borehole location and the depth to hydrogeologic units penetrated downhole for all boreholes compiled for the USGS RASA sturdies by Wilson and Hosman (1987) and for the subsequent USGS MERAS study (Hart and Clark, 2008). Borehole data are provided in Microsoft Excel spreadsheet that includes separate TABs for well location and tabulation of the depths to top and base of hydrogeologic units intercepted downhole, in a format suitable for import into a relational database. Each of the geographic information system geodatabases include non-spatial tables that describe the sources of geologic or hydrogeologic information, a glossary of terms, and a description of units. Also included is a Data Dictionary that duplicates the Entity and Attribute information contained in the metadata file. To maximize usability, spatial data are also distributed as shapefiles and tabular data are distributed as ascii text files in comma separated values (CSV) format. The landing page to for this data release contains a url to an external web resource where the downhole well data and a single contoured surface from the data release are rendered in 3D and can be interactively viewed by the user.

Earth Sciences New Zealand can no longer maintain this feature layer nor the underlying hosting infrastructure and a hosted vector tile layer has been created as a replacement for simple visualisation tasks. To access the vector tile layer, you can click “Open in Map Viewer” (Add this layer as the basemap https://niwa.maps.arcgis.com/home/item.html?id=f5e9b17de4794f1d8d2d8cd7b7375b54. You can then add another basemap and move this one to the top - then you have the basemap of your choice plus the catchment information layers) [THIS PAGE IS ONLY KEPT FOR REFERENCE] This layer is based on the New Zealand River Environment Classification REC2 V5 and describes the larger catchments of New Zealand that are a Strahler order five and greater. It also has the associated names that belong to the parent sea draining catchment. It was originally derived by dissolving local Strahler Order 1 watersheds. REC2 (River Environment Classification, v2.5) - June 2019 [Hosted Feature Layer] This service depicts rivers as lines and catchments as polygons The River Environment Classification (REC) is a database of catchment spatial attributes, summarised for every segment in New Zealand's network of rivers. The attributes were compiled for the purposes of river classification, while the river network description has been used to underpin models. Typically, models (e.g. CLUES and TopNet) would use the dendritic (branched) linkages of REC river segments to perform their calculations. Since its release and use over the last decade, some errors in the location and connectivity of these linkages have been identified. The current revision corrects those errors, and updates a number of spatial attributes with the latest data. REC2 provides a re-cut framework of rivers for modelling and classification.It is built on a newer version of the 30m digital elevation model, in which the original 20m contours were supplemented with, for example, more spot elevation data and a better coastline contour. Boundary errors were minimised by processing contiguous areas (such as the whole of the North Island) together, which wasn't possible when it was originally created.Major updates include the revision of catchment land use information, by overlaying with the land cover database (LCDB3, current as at 2008), and the update of river and rainfall statistics with data from 1960-2006. The river network and associated attributes have been assembled within an ArcGIS geodatabase. Topological connectivity has been established to allow upstream and downstream tracing within the network. REC2 can be downloaded or streamed and used directly in ArcMap. (A file geodatabase version for ArcGIS of REC2 can be downloaded as a zip file and used directly for analyses in ArcMap from here)This is REC2 (Version 5) , June 2019 - a publicly available dataset from NIWA Taihoro Nukurangi.NIWA acknowledges funding from the MBIE SSIF towards the preparation of REC v2.5Coordinate Reference System: NZTM (New Zealand Transverse Mercator, EPSG: 2193) Geometric Representation of Rivers: LinesExtent (Bounding Box): Top(Latitude) -33.9534Bottom(Latitude) -47.4867 Left (Longitude) 166.2634 Right (Longitude) 178.9733 _Item Page Created: 2021-10-05 03:41 Item Page Last Modified: 2025-08-21 09:14Owner: NIWA_OpenDataDN2_large_odr6_catchNo data edit dates availableFields: Shape,FID_1,diss,FID_2,HydroID,CATAREA,CUM_AREA,nzsegment,StreamOrde,upElev,downElev,upcoordX_1,downcoor_1,downcoor_2,upcoordY_1,RivName,Distance,ord_diff,Distance_1,Shape_Length,Shape_Area

The IISD Experimental Lakes Area (IISD-ELA) bathymetry data package provides bathymetric data on IISD-ELA lakes in a variety of formats and degrees of processing. The data package has been organized into four parts: tabular, geospatial, maps, and additional metadata. Tabular data include cumulative and interval values for area and volume at specific depth ranges, summary statistics (perimeter, surface area, total volume, mean depth, and maximum depth), and metadata for the lakes (such as water level on date of survey and methods used to collect and process the data). Geospatial data are suitable for map-making and geospatial analysis. The geospatial folder includes raw coordinate data (CSV) and processed geospatial outputs: contour lines (geodatabase and geopackage), lake polygons (geodatabase and geopackage), and raster DEMs (geodatabase and TIFF). Maps are provided in PDF format in black and white or colour. Where current maps are not available, historical maps have been provided, which are black and white scans. Additional metadata files include the Info Sheet PDF, which provides details for interpreting column names and understanding surveying and processing methods. A materials overview CSV table is provided, outlining which data types are available for each lake. A lake polygon metadata CSV table specifies which satellite imagery providers and dates were used to refine lake polygon outlines. The data package is ongoing - updated data will be provided as more lakes are surveyed and data processed. If current data do not exist for the lake you are interested in, please get in touch with us - we may be able to add a survey of that lake to our bathymetry survey schedule.

This geodatabase reflects the U.S. Geological Survey’s (USGS) ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports in Africa. The geodatabase and geospatial data layers serve to create a new geographic information product in the form of a geospatial portable document format (PDF) map. The geodatabase contains data layers from USGS, foreign governmental, and open-source sources as follows: (1) mineral production and processing facilities, (2) mineral exploration and development sites, (3) mineral occurrence sites and deposits, (4) undiscovered mineral resource tracts for Gabon and Mauritania, (5) undiscovered mineral resource tracts for potash, platinum-group elements, and copper, (6) coal occurrence areas, (7) electric po ...

The Gridded SSURGO dataset was created for use in national, regional, and statewide resource planning and analysis of soils data.The gSSURGO Database is derived from the official Soil Survey Geographic (SSURGO) Database. SSURGO generally has the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging the traditional vector-based SSURGO digital map data and tabular data into statewide extents, adding a statewide gridded map layer derived from the vector layer, and adding a new value-added look up table (valu) containing “ready to map” attributes. The gridded map layer is in an ArcGIS file geodatabase in raster format. The raster and vector map data have a statewide extent. The raster map data have a 10-meter cell size that approximates the vector polygons in an Albers Equal Area projection. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link the raster cells and polygons to attribute tables.Other Documents to Reference:gSSURGO FactsheetgSSURGO User Guide ArcMap version 2.4Soil Data Development Toolbox User Guide v5 for ArcMapgSSURGO Mapping Detailed GuidegSSURGO Valu1 table column descriptions

Please note that this dataset is not an official City of Toronto land use dataset. It was created for personal and academic use using City of Toronto Land Use Maps (2019) found on the City of Toronto Official Plan website at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/official-plan-maps-copy, along with the City of Toronto parcel fabric (Property Boundaries) found at https://open.toronto.ca/dataset/property-boundaries/ and Statistics Canada Census Dissemination Blocks level boundary files (2016). The property boundaries used were dated November 11, 2021. Further detail about the City of Toronto's Official Plan, consolidation of the information presented in its online form, and considerations for its interpretation can be found at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/ Data Creation Documentation and Procedures Software Used The spatial vector data were created using ArcGIS Pro 2.9.0 in December 2021. PDF File Conversions Using Adobe Acrobat Pro DC software, the following downloaded PDF map images were converted to TIF format. 9028-cp-official-plan-Map-14_LandUse_AODA.pdf 9042-cp-official-plan-Map-22_LandUse_AODA.pdf 9070-cp-official-plan-Map-20_LandUse_AODA.pdf 908a-cp-official-plan-Map-13_LandUse_AODA.pdf 978e-cp-official-plan-Map-17_LandUse_AODA.pdf 97cc-cp-official-plan-Map-15_LandUse_AODA.pdf 97d4-cp-official-plan-Map-23_LandUse_AODA.pdf 97f2-cp-official-plan-Map-19_LandUse_AODA.pdf 97fe-cp-official-plan-Map-18_LandUse_AODA.pdf 9811-cp-official-plan-Map-16_LandUse_AODA.pdf 982d-cp-official-plan-Map-21_LandUse_AODA.pdf Georeferencing and Reprojecting Data Files The original projection of the PDF maps is unknown but were most likely published using MTM Zone 10 EPSG 2019 as per many of the City of Toronto's many datasets. They could also have possibly been published in UTM Zone 17 EPSG 26917 The TIF images were georeferenced in ArcGIS Pro using this projection with very good results. The images were matched against the City of Toronto's Centreline dataset found here The resulting TIF files and their supporting spatial files include: TOLandUseMap13.tfwx TOLandUseMap13.tif TOLandUseMap13.tif.aux.xml TOLandUseMap13.tif.ovr TOLandUseMap14.tfwx TOLandUseMap14.tif TOLandUseMap14.tif.aux.xml TOLandUseMap14.tif.ovr TOLandUseMap15.tfwx TOLandUseMap15.tif TOLandUseMap15.tif.aux.xml TOLandUseMap15.tif.ovr TOLandUseMap16.tfwx TOLandUseMap16.tif TOLandUseMap16.tif.aux.xml TOLandUseMap16.tif.ovr TOLandUseMap17.tfwx TOLandUseMap17.tif TOLandUseMap17.tif.aux.xml TOLandUseMap17.tif.ovr TOLandUseMap18.tfwx TOLandUseMap18.tif TOLandUseMap18.tif.aux.xml TOLandUseMap18.tif.ovr TOLandUseMap19.tif TOLandUseMap19.tif.aux.xml TOLandUseMap19.tif.ovr TOLandUseMap20.tfwx TOLandUseMap20.tif TOLandUseMap20.tif.aux.xml TOLandUseMap20.tif.ovr TOLandUseMap21.tfwx TOLandUseMap21.tif TOLandUseMap21.tif.aux.xml TOLandUseMap21.tif.ovr TOLandUseMap22.tfwx TOLandUseMap22.tif TOLandUseMap22.tif.aux.xml TOLandUseMap22.tif.ovr TOLandUseMap23.tfwx TOLandUseMap23.tif TOLandUseMap23.tif.aux.xml TOLandUseMap23.tif.ov Ground control points were saved for all georeferenced images. The files are the following: map13.txt map14.txt map15.txt map16.txt map17.txt map18.txt map19.txt map21.txt map22.txt map23.txt The City of Toronto's Property Boundaries shapefile, "property_bnds_gcc_wgs84.zip" were unzipped and also reprojected to EPSG 26917 (UTM Zone 17) into a new shapefile, "Property_Boundaries_UTM.shp" Mosaicing Images Once georeferenced, all images were then mosaiced into one image file, "LandUseMosaic20211220v01", within the project-generated Geodatabase, "Landuse.gdb" and exported TIF, "LandUseMosaic20211220.tif" Reclassifying Images Because the original images were of low quality and the conversion to TIF made the image colours even more inconsistent, a method was required to reclassify the images so that different land use classes could be identified. Using Deep learning Objects, the images were re-classified into useful consistent colours. Deep Learning Objects and Training The resulting mosaic was then prepared for reclassification using the Label Objects for Deep Learning tool in ArcGIS Pro. A training sample, "LandUseTrainingSamples20211220", was created in the geodatabase for all land use types as follows: Neighbourhoods Insitutional Natural Areas Core Employment Areas Mixed Use Areas Apartment Neighbourhoods Parks Roads Utility Corridors Other Open Spaces General Employment Areas Regeneration Areas Lettering (not a land use type, but an image colour (black), used to label streets). By identifying the letters, it then made the reclassification and vectorization results easier to clean up of unnecessary clutter caused by the labels of streets. Reclassification Once the training samples were created and saved, the raster was then reclassified using the Image Classification Wizard tool in ArcGIS Pro, using the Support...

The Digital Geologic-GIS Map of the Craters of the Moon National Monument Area, Idaho is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (cotm_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 3.X map file (.mapx) file (cotm_geology.mapx) and individual Pro 3.X layer (.lyrx) 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 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 readme file (crmo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (crmo_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 (cotm_geology_metadata_faq.pdf). Please read the crmo_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: 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 (cotm_geology_metadata.txt or cotm_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 Pro, 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 need to manage water resources is timeless. The "Monuments of Fontus" story map describes how and where ancient Roman engineers delivered water resources. The story starts at a water source and courses downstream through an aqueduct and into a city distribution facility. There the water is divided and released into pipes, traveling up and down water towers and into bath houses, factories, fountains, and homes. The story map makes a final stop in Roman Pompeii, where the tragic eruption of Mt Vesuvius in AD 79 preserved water features worthy of a geodatabase model complete with domains and subtypes. The "Monuments of Fontus" story map was conceived as an extension of a GIS data management class project to create a geodatabase to model components of ancient Roman city water distribution systems. The story map would be lifeless without the kind permission of Larry Mays and Wilke Schram for the use of their images.

This is a demonstration layer implementing streamlined INSPIRE data according to the INSPIRE rules for Alternative Encoding. It is provided as a courtesy and should not be used for any purpose other than demonstration.ArcGIS INSPIRE Open Data is a lightweight solution for European public sector organizations implementing the INSPIRE and PSI-2/Open Data Directives. See the Getting to know ArcGIS INSPIRE Open Data story map to learn more.Geodatabase (GDB) templates are available on the ArcGIS INSPIRE Open Data demonstration Hub. INSPIRE Alternative Encoding documentation on GitHub is publicly available per the Implementing Rules on interoperability of spatial data sets and services (Commission Regulation (EU) No 1089/2010). These resources are provided as-is and are freely available.

REC2 (River Environment Classification, v2.5) - June 2019 [Hosted Feature Layer]This service depicts rivers as lines and catchments as polygons The River Environment Classification (REC) is a database of catchment spatial attributes, summarised for every segment in New Zealand's network of rivers. The attributes were compiled for the purposes of river classification, while the river network description has been used to underpin models. Typically, models (e.g. CLUES and TopNet) would use the dendritic (branched) linkages of REC river segments to perform their calculations. Since its release and use over the last decade, some errors in the location and connectivity of these linkages have been identified. The current revision corrects those errors, and updates a number of spatial attributes with the latest data. REC2 provides a re-cut framework of rivers for modelling and classification. It is built on a newer version of the 30m digital elevation model, in which the original 20m contours were supplemented with, for example, more spot elevation data and a better coastline contour. Boundary errors were minimised by processing contiguous areas (such as the whole of the North Island) together, which wasn't possible when it was originally created.Major updates include the revision of catchment land use information, by overlaying with the land cover database (LCDB3, current as at 2008), and the update of river and rainfall statistics with data from 1960-2006. The river network and associated attributes have been assembled within an ArcGIS geodatabase. Topological connectivity has been established to allow upstream and downstream tracing within the network. REC2 can be downloaded or streamed and used directly in ArcMap. (A file geodatabase version for ArcGIS of REC2 can be downloaded as a zip file and used directly for analyses in ArcMap from here)This layer is using Esri's ArcGIS Online Optimizations for fast rendering.This is REC2 (Version 5) , June 2019 - a publicly available dataset from NIWA Taihoro Nukurangi.NIWA acknowledges funding from the MBIE SSIF towards the preparation of REC v2.5Coordinate Reference System: NZTM (New Zealand Transverse Mercator, EPSG: 2193)Geometric Representation of Rivers: LinesExtent (Bounding Box):

Top(Latitude) -33.9534Bottom(Latitude) -47.4867

Left (Longitude) 166.2634

Right (Longitude) 178.9733

Riverlines table Attributes associated directly with network:

Field Type Description

Catarea Real Watershed area in m2 CUM_Area Real Area upstream of a reach (and including this reach area) in m2. Nzsegment Integer Reach identifier to be used with REC2 (supercedes nzreach in REC1).

Lengthdown Real The distance to coast from any reach to its outlet reach, where the river drains (m). Headwater Integer Number (0) denoting whether a stream is a “source” (headwater) stream. Non-zero for non-headwater streams.

Hydseq Integer A unique number denoting the hydrological processing order of a river segment relative to others in the network.

StreamOrder Integer A number describing the Strahler order a reach in a network of reaches.

euclid_dist Real The straight line distance of a reach from the reach “inlet” to its “outlet”. upElev Real Height (asl) of the upstream end of a reach section in a watershed (m). downElev Real Height (asl) of the downstream end of a reach section in a watershed (m).

upcoordX Real Easting of the upstream end of a river segment in m (NZTM2000). upcoordY Real Northing of the upstream end of a river segment in m (NZTM2000). downcoordX Real Easting of the downstream end of a river segment in m (NZTM2000).

downcoordY Real Northing of the downstream end of a river segment in m (NZTM2000). sinuosity Real Actual distance divided by the straight line distance giving the degree of curvature of the stream nzreach_re Integer The REC1 identifiying number for the corresponding\closest reach from REC1 (can be used to retrieve the REC management classes) headw_dist Integer Distance of the furthermost “source” or headwater reach from any reach (m). Shape_leng Real The length of the reach (vector) as calculated by ArcGIS. Segslpmean Real Mean segment slope along length of reach.

LID Integer Lake Identifier number(LID) of overlapping lake.

Reachtype

Integer A value of 2 is assigned if the segment is an outlet to the lake, otherwise 0 or null. nextdownid integer segment number of the most downstream reach

_Item Page Created: 2019-06-13 00:29 Item Page Last Modified: 2025-04-05 16:27Owner: NIWA_OpenDataRiver LinesNo data edit dates availableFields: OBJECTID_1,HydroID,NextDownID,CATAREA,CUM_AREA,nzsegment,Enabled,LENGTHDOWN,Headwater,Hydseq,StreamOrde,euclid_dis,upElev,downElev,upcoordX,downcoordX,downcoordY,upcoordY,sinuosity,nzreach_re,headw_dist,segslpmean,LID,reachtype,FROM_NODE,TO_NODE,Shape_Leng,FLOWDIRWatershedsNo data edit dates availableFields: OBJECTID_1,HydroID,nzsegment,nzreach_rec1,Area