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Focus on Geodatabases in ArcGIS Pro introduces readers to the geodatabase, the comprehensive information model for representing and managing geographic information across the ArcGIS platform.Sharing best practices for creating and maintaining data integrity, chapter topics include the careful design of a geodatabase schema, building geodatabases that include data integrity rules, populating geodatabases with existing data, working with topologies, editing data using various techniques, building 3D views, and sharing data on the web. Each chapter includes important concepts with hands-on, step-by-step tutorials, sample projects and datasets, 'Your turn' segments with less instruction, study questions for classroom use, and an independent project. Instructor resources are available by request.AUDIENCEProfessional and scholarly.AUTHOR BIODavid W. Allen has been working in the GIS field for over 35 years, the last 30 with the City of Euless, Texas, and has seen many versions of ArcInfo and ArcGIS come along since he started with version 5. He spent 18 years as an adjunct professor at Tarrant County College in Fort Worth, Texas, and now serves as the State Director of Operations for a volunteer emergency response group developing databases and templates. Mr. Allen is the author of GIS Tutorial 2: Spatial Analysis Workbook (Esri Press, 2016).Pub Date: Print: 6/17/2019 Digital: 4/29/2019 Format: PaperbackISBN: Print: 9781589484450 Digital: 9781589484467 Trim: 7.5 x 9.25 in.Price: Print: $59.99 USD Digital: $59.99 USD Pages: 260
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Multiuser geodatabases allow multiple users to edit the content of a database without inadvertently duplicating data. Versions allow you to avoid the overhead of storing redundant data, and can be merged together by reconciling differences. This seminar discusses what a version is, how it is implemented, and how it functions. The presentation also covers how changes between versions can be reconciled and posted, and finally how the database can be compressed.This seminar was developed to support the following:ArcGIS 10.0 For Desktop (ArcInfo)ArcGIS Server 10.0 Workgroup (Basic, Standard, or Advanced)
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TwitterThe National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses. For more information on the NHDPlus dataset see the NHDPlus v2 User Guide.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territories not including Alaska.Geographic Extent: The United States not including Alaska, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: EPA and USGSUpdate Frequency: There is new new data since this 2019 version, so no updates planned in the futurePublication Date: March 13, 2019Prior to publication, the NHDPlus network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the NHDPlus Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, On or Off Network (flowlines only), Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original NHDPlus dataset. No data values -9999 and -9998 were converted to Null values for many of the flowline fields.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute. Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map. Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.
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TwitterGeostrat Report – The Sequence Stratigraphy and Sandstone Play Fairways of the Late Jurassic Humber Group of the UK Central Graben This non-exclusive report was purchased by the NSTA from Geostrat as part of the Data Purchase tender process (TRN097012017) that was carried out during Q1 2017. The contents do not necessarily reflect the technical view of the NSTA but the report is being published in the interests of making additional sources of data and interpretation available for use by the wider industry and academic communities. The Geostrat report provides stratigraphic analyses and interpretations of data from the Late Jurassic to Early Cretaceous Humber Group across the UK Central Graben and includes a series of depositional sequence maps for eight stratigraphic intervals. Stratigraphic interpretations and tops from 189 wells (up to Release 91) are also included in the report. The outputs as published here include a full PDF report, ODM/IC .dat format sequence maps, and all stratigraphic tops (lithostratigraphy, ages, sequence stratigraphy) in .csv format (for import into different interpretation platforms). In addition, the NSTA has undertaken to provide the well tops, stratigraphic interpretations and sequence maps in an ESRI ArcGIS format that is intended to facilitate the integration of these data into projects and data storage systems held by individual organisations. As part of this process, the Geostrat well names have been matched as far as possible to the NSTA well names from the NSTA Offshore Wells shapefile (as provided on the NSTA’s Open Data website) and the original polygon files have been incorporated into an ArcGIS project. All the files within the GIS folder of this delivery have been created by the NSTA. NSTA web feature services (WFSs) have been included in the map document in this delivery. They replace the use of a shapefile or feature class to represent block, licence and quadrant data. By using a WFS, the data is automatically updated when it becomes available via the NSTA. A version of this delivery containing shapefiles for well tops, stratigraphic interpretations and sequence maps is available on the NSTA’s Open Data website for use in other GIS software packages. All releases included in the Data Purchase tender process that have been made openly available are summarised in a mapping application available from the NSTA website. The application includes an area of interest outline for each of the products and an overview of which wellbores have been included in the products.
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For complete collection of data and models, see https://doi.org/10.21942/uva.c.5290546.Original model developed in 2016-17 in ArcGIS by Henk Pieter Sterk (www.rfase.org), with minor updates in 2021 by Stacy Shinneman and Henk Pieter Sterk. Model used to generate publication results:Hierarchical geomorphological mapping in mountainous areas Matheus G.G. De Jong, Henk Pieter Sterk, Stacy Shinneman & Arie C. Seijmonsbergen. Submitted to Journal of Maps 2020, revisions made in 2021.This model creates tiers (columns) of geomorphological features (Tier 1, Tier 2 and Tier 3) in the landscape of Vorarlberg, Austria, each with an increasing level of detail. The input dataset needed to create this 'three-tier-legend' is a geomorphological map of Vorarlberg with a Tier 3 category (e.g. 1111, for glacially eroded bedrock). The model then automatically adds Tier 1, Tier 2 and Tier 3 categories based on the Tier 3 code in the 'Geomorph' field. The model replaces the input file with an updated shapefile of the geomorphology of Vorarlberg, now including three tiers of geomorphological features. Python script files and .lyr symbology files are also provided here.
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TwitterNOTE: An updated Introduction to ArcGIS GeoEvent Server Tutorial is available here. It is recommended you use the new tutorial for getting started with GeoEvent Server. The old Introduction Tutorial available on this page is relevant for 10.8.x and earlier and will not be updated.The Introduction to GeoEvent Server Tutorial (10.8.x and earlier) introduces you to the Real-Time Visualization and Analytic capabilities of ArcGIS GeoEvent Server. GeoEvent Server allows you to:
Incorporate real-time data feeds in your existing GIS data and IT infrastructure. Perform continuous processing and analysis on streaming data, as it is received. Produce new streams of data that can be leveraged across the ArcGIS system.
Once you have completed the exercises in this tutorial you should be able to:
Use ArcGIS GeoEvent Manager to monitor and perform administrative tasks. Create and maintain GeoEvent Service elements such as inputs, outputs, and processors. Use GeoEvent Simulator to simulate event data into GeoEvent Server. Configure GeoEvent Services to append and update features in a published feature service. Work with processors and filters to enhance and direct GeoEvents from event data.
The knowledge gained from this tutorial will prepare you for other GeoEvent Server tutorials available in the ArcGIS GeoEvent Server Gallery.
Releases
Each release contains a tutorial compatible with the version of GeoEvent Server listed. The release of the component you deploy does not have to match your version of ArcGIS GeoEvent Server, so long as the release of the component is compatible with the version of GeoEvent Server you are using. For example, if the release contains a tutorial for version 10.6; this tutorial is compatible with ArcGIS GeoEvent Server 10.6 and later. Each release contains a Release History document with a compatibility table that illustrates which versions of ArcGIS GeoEvent Server the component is compatible with.
NOTE: The release strategy for ArcGIS GeoEvent Server components delivered in the ArcGIS GeoEvent Server Gallery has been updated. Going forward, a new release will only be created when
a component has an issue,
is being enhanced with new capabilities,
or is not compatible with newer versions of ArcGIS GeoEvent Server.
This strategy makes upgrades of these custom
components easier since you will not have to
upgrade them for every version of ArcGIS GeoEvent Server
unless there is a new release of
the component. The documentation for the
latest release has been
updated and includes instructions for updating
your configuration to align with this strategy.
Latest
Release 7 - March 30, 2018 - Compatible with ArcGIS GeoEvent Server 10.6 and later.
Previous
Release 6 - January 12, 2018 - Compatible with ArcGIS GeoEvent Server 10.5 thru 10.8.
Release 5 - July 30, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Release 4 - July 30, 2015 - Compatible with ArcGIS GeoEvent Server 10.3.x.
Release 3 - April 24, 2015 - Compatible with ArcGIS GeoEvent Server 10.3.x. Not available.
Release 2 - January 22, 2015 - Compatible with ArcGIS GeoEvent Server 10.3.x. Not available.
Release 1 - April 11, 2014 - Compatible with ArcGIS GeoEvent Server 10.2.x.
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TwitterContains a set of regional geological maps for the given area including: depth structure, isochores, subcrop and supercrop, structural elements, depositional facies, reservoir distribution, source rock, well penetration and hydrocarbon occurrence. Includes PDF documents with stratigraphic and petroleum systems charts and explanations of the various maps. Also include digital copies of sand flags (.las) and depth and thickness grids (.xyz).
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TwitterArcGIS and QGIS map packages, with ESRI shapefiles for the DSM2 Model Grid. These are not finalized products. Locations in these shapefiles are approximate.
Monitoring Stations - shapefile with approximate locations of monitoring stations.
7/12/2022: The document "DSM2 v8.2.1, historical version grid map release notes (PDF)" was corrected by removing section 4.4, which incorrectly stated that the grid included channels 710-714, representing the Toe Drain, and that the Yolo Flyway restoration area was included.
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TwitterEsri has developed a modern set of cartographic symbols for emergency management, fire service, and law enforcement agencies. They relate to damage assessment, debris reporting, preparedness, response activities, etc. These symbols are designed to be used in ArcGIS Pro.The style includes point, line, polygon, and text symbols, as well as colors and color schemes. This style is compatible with the most recent released version of ArcGIS Pro. You can view a PDF of the symbols here.This style is not compatible with ArcGIS Pro 1.x and 2.x versions.2.x version of this style can be downloaded here.
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TwitterEsri has developed a modern set of cartographic symbols for land records, public works, fire service, law enforcement, planning and development, elections, health and human services, fish and wildlife, agriculture, natural resources, and economic development. These symbols are designed to be used in ArcGIS Pro.The style includes point, line, polygon, and text symbols, as well as colors and color schemes. This style is compatible with the most recent released version of ArcGIS Pro. You can view a PDF of the symbols here.This style is not compatible with ArcGIS Pro 1.x version.3.x version of this style can be downloaded here.
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TwitterThe USDA Long-Term Agroecosystem Research was established to develop national strategies for sustainable intensification of agricultural production. As part of the Agricultural Research Service, the LTAR Network incorporates numerous geographies consisting of experimental areas and locations where data are being gathered. Starting in early 2019, two working groups of the LTAR Network (Remote Sensing and GIS, and Data Management) set a major goal to jointly develop a geodatabase of LTAR Standard GIS Data Layers. The purpose of the geodatabase was to enhance the Network's ability to utilize coordinated, harmonized datasets and reduce redundancy and potential errors associated with multiple copies of similar datasets. Project organizers met at least twice with each of the 18 LTAR sites from September 2019 through December 2020, compiling and editing a set of detailed geospatial data layers comprising a geodatabase, describing essential data collection areas within the LTAR Network. The LTAR Standard GIS Data Layers geodatabase consists of geospatial data that represent locations and areas associated with the LTAR Network as of late 2020, including LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This geodatabase was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. The creation of the geodatabase began with initial requests to LTAR site leads and data managers for geospatial data, followed by meetings with each LTAR site to review the initial draft. Edits were documented, and the final draft was again reviewed and certified by LTAR site leads or their delegates. Revisions to this geodatabase will occur biennially, with the next revision scheduled to be published in 2023. Resources in this dataset:Resource Title: LTAR Standard GIS Data Layers, 2020 version, File Geodatabase. File Name: LTAR_Standard_GIS_Layers_v2020.zipResource Description: This file geodatabase consists of authoritative GIS data layers of the Long-Term Agroecosystem Research Network. Data layers include: LTAR site locations, LTAR site points of contact and street addresses, LTAR experimental boundaries, LTAR site "legacy region" boundaries, LTAR eddy flux tower locations, and LTAR phenocam locations.Resource Software Recommended: ArcGIS,url: esri.com Resource Title: LTAR Standard GIS Data Layers, 2020 version, GeoJSON files. File Name: LTAR_Standard_GIS_Layers_v2020_GeoJSON_ADC.zipResource Description: The contents of the LTAR Standard GIS Data Layers includes geospatial data that represent locations and areas associated with the LTAR Network as of late 2020. This collection of geojson files includes spatial data describing LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This dataset was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. Resource Software Recommended: QGIS,url: https://qgis.org/en/site/
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TwitterThis style comprises 20 distinct hues, plus a white version, of the firefly symbol family for points, lines, and polygons.Points have two flavors of symbols. One is a standard radial opacity decay with a molten white core. The other is a variant with a shimmer effect, if that's what you need.Line symbols are available in solid or dashed. Lines are a stack of colorized semitransparent strokes beneath a white stroke, to create a glow effect.Polygons are also available in two versions. One version applies the glow to the perimeter of the polygon in both inner and outer directions, with a semi-transparent fill. This is effective for non-adjacent polygons. The alternate version only applies an inner glow, to prevent blending and overlapping of adjacent polygons.This is an early version of these symbols and only the points respond to color selection.Learn how to install this style by visiting this salacious blog post.Learn more about Firefly Cartography here.Happy Firefly Mapping! John
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TwitterAs part of the NSTA’s published 2018/19 Activity Plan, the NSTA is publishing a set of regional geological maps for the Engish Channel area of the UKCS. These maps represent the fifth set of deliverables from a 3 year contract with Lloyd’s Register (LR) to produce a series of maps and associated databases for the whole of the UKCS.All data released with this set of geological maps is public domain data. The project has, however, benefited from a number of additional third party data sources which have been used to help inform final maps and/or derive interpreted products. These include the seismic interpretation work carried out by Heriot-Watt University (Rachel Brackenridge), the 21CXRM Palaeozoic project (which is now available in the public domain), CGG’s Target database and relevant products available via the BGS’s Offshore Geoindex. CDA is also kindly acknowledged for their support in downloading and providing much of the released well data to LR as part of this project.Due to the high level, regional nature of the project, the maps are being produced for the main geological time intervals e.g. Paleocene, Lower Cretaceous, Upper Jurassic. Each time interval includes the following products:• Depth structure maps• Isochore maps• Subcrop & supercrop maps• Structural elements maps• Depositional facies maps• Reservoir distribution maps• Source rock maps• Well penetration maps• Hydrocarbon occurrence maps
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TwitterThis dataset was updated May, 2025.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes:* Clipping input datasets to the California boundary* Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc)* Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California.* Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only.* Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs)* In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD* As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset. Data Sources:* GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf* US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore* Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases* Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov* Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.html Data Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.25_1: The CPAD Input dataset was amended to merge large gaps in certain areas of the state known to be erroneous, such as Yosemite National Park, and to eliminate overlaps from the original input. The FWS input dataset was updated in February of 2025, and the DOD input dataset was updated in October of 2024. The BIA input dataset was the same as was used for the previous ownership version.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.
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TwitterThe Spatiotemporal Big Data Store Tutorial introduces you the the capabilities of the spatiotemporal big data store in ArcGIS Data Store, available with ArcGIS Enterprise. Observation data can be moving objects, changing attributes of stationary sensors, or both. The spatiotemporal big data store enables archival of high volume observation data, sustains high velocity write throughput, and can run across multiple machines (nodes). Adding additional machines adds capacity, enabling you to store more data, implement longer retention policies of your data, and support higher data write throughput.
After completing this tutorial you will:
Understand the concepts and best practices for working with the spatiotemporal big data store available with ArcGIS Data Store. Have configured the appropriate security settings and certificates on a enterprise server, real-time server, and a data server which are necessary for working with the spatiotemporal big data store. Have learned how to process and archive large amounts of observational data in the spatiotemporal big data store. Have learned how to visualize the observational data that is stored in the spatiotemporal big data store.
Releases
Each release contains a tutorial compatible with the version of GeoEvent Server listed. The release of the component you deploy does not have to match your version of ArcGIS GeoEvent Server, so long as the release of the component is compatible with the version of GeoEvent Server you are using. For example, if the release contains a tutorial for version 10.6; this tutorial is compatible with ArcGIS GeoEvent Server 10.6 and later. Each release contains a Release History document with a compatibility table that illustrates which versions of ArcGIS GeoEvent Server the component is compatible with.
NOTE: The release strategy for ArcGIS GeoEvent Server components delivered in the ArcGIS GeoEvent Server Gallery has been updated. Going forward, a new release will only be created when
a component has an issue,
is being enhanced with new capabilities,
or is not compatible with newer versions of ArcGIS GeoEvent Server.
This strategy makes upgrades of these custom
components easier since you will not have to
upgrade them for every version of ArcGIS GeoEvent Server
unless there is a new release of
the component. The documentation for the
latest release has been
updated and includes instructions for updating
your configuration to align with this strategy.
Latest
Release 4 - February 2, 2017 - Compatible with ArcGIS GeoEvent Server 10.5 and later.
Previous
Release 3 - July 7, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Release 2 - May 17, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Release 1 - March 18, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Southern North Sea Regional Geological Maps
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TwitterThe Digital Geologic-GIS Map of the Moore Hill Quadrangle, Wyoming 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 (mooh_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 (mooh_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 (mooh_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.) a readme file (deto_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (deto_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 (mooh_geology_metadata_faq.pdf). Please read the deto_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 (mooh_geology_metadata.txt or mooh_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).
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License information was derived automatically
Crowther_Nature_Files.zip This description pertains to the original download. Details on revised (newer) versions of the datasets are listed below. When more than one version of a file exists in Figshare, the original DOI will take users to the latest version, though each version technically has its own DOI. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al 2015 and Glick et al 2016). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. Additionally, due to data limitations, estimates for Mangroves and Tropical coniferous forest (as identified by WWF and TNC) were generated using models constructed from Topical moist broadleaf forest data and Temperate coniferous forest data, respectively. Because we used ecological analogy, the estimates for these two biomes should be considered less reliable than those of other biomes . These two maps initially appeared in Crowther et al (2015), with the biome map being featured more prominently. Explicit publication of the data is associated with Glick et al (2016). As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Versions (see below).
Methods: We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally. All modeling was done in R. Mapping was done using R and ArcGIS 10.1.
Viewing Instructions: Load the files into an appropriate geographic information system (GIS). For the original download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files (see Additional Versions), load them into any compatible GIS or image management program.
Comments: The original download provides a zipped folder that contains (1) an ArcGIS File Geodatabase (.gdb) containing one raster file for each of the two global models of tree density – one based on biomes and one based on ecoregions; (2) a layer file (.lyr) for each of the global models with the symbology used for each respective model in Crowther et al (2015); and an ArcGIS Map Document (.mxd) that contains the layers and symbology for each map in the paper. The data is delivered in the Goode homolosine interrupted projected coordinate system that was used to compute biome, ecoregion, and global estimates of the number and density of trees presented in Crowther et al (2015). To obtain maps like those presented in the official publication, raster files will need to be reprojected to the Eckert III projected coordinate system. Details on subsequent revisions and alternative file formats are list below under Additional Versions.----------
Additional Versions: Crowther_Nature_Files_Revision_01.zip contains tree density predictions for small islands that are not included in the data available in the original dataset. These predictions were not taken into consideration in production of maps and figures presented in Crowther et al (2015), with the exception of the values presented in Supplemental Table 2. The file structure follows that of the original data and includes both biome- and ecoregion-level models.
Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ (substantially at greater latitudes) as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files.
References:
Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A. 2015. Mapping tree density at a global scale. Nature, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., and Crowther, T. W. 2016. Spatially explicit models of global tree density. Scientific Data, 3(160069), doi:10.1038/sdata.2016.69.
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TwitterThe Digital Geologic-GIS Map of San Miguel Island, California 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 (smis_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 (smis_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 (smis_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 (chis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (chis_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 (smis_geology_metadata_faq.pdf). Please read the chis_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: American Association of Petroleum Geologists. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (smis_geology_metadata.txt or smis_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).
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TwitterNovember 2025 will be the last update to the Public Safety ArcGIS Pro Style 2.x.Esri has developed a modern set of cartographic symbols for emergency management, fire service, and law enforcement agencies. They relate to damage assessment, debris reporting, preparedness, response activities, etc. These symbols are designed to be used in ArcGIS Pro. The style includes point, line, polygon, and text symbols, as well as colors and color schemes. This style is compatible with the most recent released version of ArcGIS Pro. You can view a PDF of the symbols here.This style is not compatible with ArcGIS Pro 1.x version.3.x version of this style can be downloaded here.
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Focus on Geodatabases in ArcGIS Pro introduces readers to the geodatabase, the comprehensive information model for representing and managing geographic information across the ArcGIS platform.Sharing best practices for creating and maintaining data integrity, chapter topics include the careful design of a geodatabase schema, building geodatabases that include data integrity rules, populating geodatabases with existing data, working with topologies, editing data using various techniques, building 3D views, and sharing data on the web. Each chapter includes important concepts with hands-on, step-by-step tutorials, sample projects and datasets, 'Your turn' segments with less instruction, study questions for classroom use, and an independent project. Instructor resources are available by request.AUDIENCEProfessional and scholarly.AUTHOR BIODavid W. Allen has been working in the GIS field for over 35 years, the last 30 with the City of Euless, Texas, and has seen many versions of ArcInfo and ArcGIS come along since he started with version 5. He spent 18 years as an adjunct professor at Tarrant County College in Fort Worth, Texas, and now serves as the State Director of Operations for a volunteer emergency response group developing databases and templates. Mr. Allen is the author of GIS Tutorial 2: Spatial Analysis Workbook (Esri Press, 2016).Pub Date: Print: 6/17/2019 Digital: 4/29/2019 Format: PaperbackISBN: Print: 9781589484450 Digital: 9781589484467 Trim: 7.5 x 9.25 in.Price: Print: $59.99 USD Digital: $59.99 USD Pages: 260