Geostrat 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.

The 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.

This survey is used to assess the awareness, use, and training needs related to GIS services and Esri technologies across departments. It helps the GIS team evaluate how employees are interacting with tools like ArcGIS Online, ArcGIS Pro, EagleView, and internal mapping resources like TexarkanaMaps.com. The survey includes conditional content that adapts based on user responses, presenting relevant information, media, and follow-up questions to gather detailed insights.Metadata Elements FieldDescriptionPurposeGather feedback on GIS tool usage, software installation, training needs, and general awareness.Target AudienceInternal staff who interact with spatial data, GIS tools, or mapping platforms.Key Tools CoveredArcGIS Pro, ArcGIS Online (AGOL), EagleView Connect, Pictometry Extension, Street View Extension, TexarkanaMaps.com, Google MapsFeaturesConditional visibility, dynamic guidance, embedded images and links, personalized thank-you screenDevice Metadatadeviceid is included for submission tracking but is currently not functional.Submission DateCaptured automatically using now() in the today field.Thank-You ScreenPersonalized closing message with the user’s first name and branded image.Data Collected TypeFieldsPersonal Infofirst_name, last_name, city, department, primary_dutiesUsage Feedbackinternal_map, accessed_map, google_access, access_eagle, arcgis_pro_installed, usage_frequency, meets_needs, etc.Extensions Usedpictometry_ext, street_view_extTraining & Supportneed_training, training_detailsData Handlingcreate_data, type_of_data, spreadsheet_data, type_of_spreadsheet_dataSystem Metadatadevice_id (not working), today (auto-timestamp)

Contains 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).

Geostrat 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 OGA 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 OGA 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 OGA 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 OGA well names from the OGA Offshore Wells shapefile (as provided on the OGA’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 OGA. OGA 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 OGA.

A version of this delivery containing shapefiles for well tops, stratigraphic interpretations and sequence maps is available on the OGA’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 OGA 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.

This 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

MDOT LRS Version 20 Geodatabase containing the Route, Control Section (CS) and Physical Reference (PR) routes and mile points.

As 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

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. 2021. Matheus G.G. De Jong, Henk Pieter Sterk, Stacy Shinneman & Arie C. Seijmonsbergen. Journal of Maps

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.

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 21CXRM Palaeozoic project (which is now available in the public domain),the Southern Permian Basin Atlas (SPBA),PGS’s North Sea Digital Atlas and East Shetland Platform seismic interpretation project, Frogtech’s East Shetland Platform Project, IGI’s Source Rock Evaluation for the East Shetland Platform, research data from the University of Aberdeen, seismic interpretation work and other geological studies carried out by Durham University on the SW Approaches, seismic interpretation work carried out by Heriot-Watt University on the Mid North Sea High, seismic interpretation work carried out by Aberdeen University on the Rockall area CGG’s Target database and relevant products available via the BGS’s Offshore Geoindex. TGS are gratefully acknowledged for providing joined digital log data from LogLinePlus to enable the production of sand flag curves. Schlumberger, TGS and BP are acknowledged for providing additional seismic data to help QC interpretation carried out within the project and CDA are 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 depth structure and structural elements maps have been produced for the main geological time intervals, e.g. Paleocene, Lower Cretaceous, Upper Jurassic. Depositional facies maps and reservoir distribution maps were produced for a higher number of stratigraphic intervals such as the Danian, Selandian and Thanetian (Paleocene). The following products are available: •Depth structure maps •Isochore maps •Structural elements maps •Depositional facies maps •Reservoir distribution maps •Well penetration maps •Hydrocarbon occurrence maps •Drill stem tests •Well tops (Groups, Formation and Members) •Sand data (N/G, sand thickness)

November 2025 will be the last update to the Government ArcGIS Pro Style 2.x.Esri 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.

Data Usage and Deployment This guide intends to describe how the provided datasets can be used within the environment of ArcGIS version 10.4, although the same rules and guidelines apply for usage in the QGIS and ArcGIS Pro environment. In the ZENODO data repository (accessed at https://doi.org/10.5281/zenodo.17579289), end users can find four compressed files. Use Winrar, Winzip or the Windows embedded decompression tools to open the files and decompress the included filed. The file titled “FSim_Dataset_Greece_LYR_files_ARCGIS_QGIS_ARCGISPRO.rar” contains .lyr files that are an ArcGIS file type that is a container that stores the visualization and metadata properties for a single map layer, such as symbology, labeling, and transparency. It does not contain the actual geographic data itself but acts as a "pointer" to the source data (like a shapefile or a raster). These files can be used withing the ArcGIS environment to assign the proper colors and classes, as portrayed on the maps of the paper. Layer files are available only for raster type datasets. In addition, we provide the layer files that hold the symbology and classes at the format of .qml, for use in QGIS, and .lyrx for use in ArcGIS Pro. The file titled “Metadata.rar” contains all the individual .xml files holding information about the metadata of each dataset, created with the ISO 19139 XML format. The Geodatabase_metadata.xml contains the metadata of the File Geodatabase. The FSim_Geodatabase_Schema_Report is the schema report of the File Geodatabase, created with ArcGIS Pro 3.5 in four readable versions (Excel, JSON, PDF, and HTML). They can be directly opened with any relevant software that supports each file type, and users can navigate to the different sections of metadata information for all datasets included in the File Geodatabase. The file titled “FSim_Dataset_Greece_raw_files.rar” contains all datasets in file formats that are not part of a File Geodatabase, like ESRI shapefiles (.shp) and ERDAS IMAGINE raster filed (.img), intended for use in GIS software that are not owned by the ESRI (like the QGIS). Each dataset contained in the File Geodatabase can be found in this compressed file with the same name, as reported in the paper. Below the image shows how the data in folder appear when viewed inside ArcCatalog. The file titled “FSim_Dataset_Greece.gdb.rar” contains the File Geodatabase, created with ArcGIS version 10.4. The File Geodatabase has all the datasets, including their accompanying metadata. This File Geodatabase can be opened with any version of ArcGIS or ArcGIS Pro. To Open ESRI File (gdb) using GDAL (Geospatial Data Abstraction Library) follow these steps: Install GDAL: If you don’t have GDAL installed on your system, download and install it from the official website (https://gdal.org/download.html). Make sure to get the version that supports the OpenFileGDB driver. Open a command prompt or terminal window: Launch the command prompt (Windows) or terminal (macOS/Linux). Use ogrinfo: To list the layers available in the gdb file, use the ogrinfo command followed by the path to the gdb folder. For example: ogrinfo path/to/your/geodatabase.gdb Replace path/to/your/geodatabase.gdb with the actual path to your gdb file. This command will display information about the layers in the geodatabase. Access specific layers: To access a specific layer within the gdb, you can use the ogr2ogr command to convert the layer to another format, such as a shapefile, GeoJSON, or CSV. For example, to convert a layer named “example_layer” to a shapefile, use: ogr2ogr -f "ESRI Shapefile" output_shapefile.shp path/to/your/geodatabase.gdb example_layer Replace output_shapefile.shp with the desired name for the output shapefile, and path/to/your/geodatabase.gdb with the actual path to your gdb file. This command will convert the “example_layer” to a shapefile format. To open the File Geodatabase in QGIS, follow these steps: 1. Open QGIS: Launch your QGIS application to begin the import process. 2. Access Data Source Manager: Click on the Data Source Manager button in the toolbar. 3. Select Directory: In the Data Source Manager window, click on the Directory tab. Choose Open File GDB as the source type. 4. Browse to the .gdb Folder: Click the Browse button and navigate to the unzipped .gdb folder. Select the folder and click Add. 5. Adding Layers: After adding the folder, you will see the layers contained within the geodatabase. Click Close to finish the process. An example of how the Metadata appear when viewed through ArcCatalog is provided in the figure below: Open the datasets in ArcGIS version 10.4 and use the .lyr files First, open the ArcGIS, navigate to the decompress folder of the File Geodatabase after pressing “Add Data”, and select a dataset (in this case, the Burn Probability raster). Then, double click on the Burn_Prob layer in the Table of Contents, move to Symbology, select “Classified” since all layers have a

Geostrat 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 OGA 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 OGA 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 OGA 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 OGA well names from the OGA Offshore Wells shapefile (as provided on the OGA’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 OGA. OGA 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 OGA. A version of this delivery containing shapefiles for well tops, stratigraphic interpretations and sequence maps is available on the OGA’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 OGA 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.

For complete collection of data and models, see https://doi.org/10.21942/uva.c.5290546.Map package for use in ArcGIS Pro containing three-tiered geomorphological data and geographical datasets such as rivers and hillshading. Datasets were used to generate figures for publication: 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. All data is in MGI Austria GK West projected coordinate system (EPSG: 31254) and was clipped to the study area.

This 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.

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.

For complete collection of data and models, see https://doi.org/10.21942/uva.c.5290546.Map package for use in ArcGIS Pro containing three-tiered geomorphological data and geographical datasets such as rivers, roads and hillshading. Datasets were used to generate figures for publication: 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. All data is in MGI Austria GK West projected coordinate system (EPSG: 31254) and was clipped to the study area.

Quick guide to assist sharing workflows during response.

ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)

**When using the GIS data included in these map packages, please cite all of the following:

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, 2019. PLoSONE 14(8):e0220457. http://doi.org/10.1371/journal.pone.0220457

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. ArcGIS Map Packages for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al., 2019. Version 1. Zenodo. https://doi.org/10.5281/zenodo.2572018

OVERVIEW OF CONTENTS

This repository contains map packages for Gillreath-Brown, Nagaoka, and Wolverton (2019), as well as the raw digital elevation model (DEM) and soils data, of which the analyses was based on. The map packages containall GIS data associated with the analyses described and presented in the publication. The map packages were created in ArcGIS 10.2.2; however, the packages will work in recent versions of ArcGIS. (Note: I was able to open the packages in ArcGIS 10.6.1, when tested on February 17, 2019).The primary files contained in this repository are:

Raw DEM and Soils data

  Digital Elevation Model Data(Map services and data available from U.S. Geological Survey, National Geospatial Program, and can be downloaded from the National Elevation Dataset)


    DEM_Individual_Tiles: Individual DEM tiles prior to being merged (1/3 arc second) from USGS National Elevation Dataset.
    DEMs_Merged: DEMs were combined into one layer. Individual watersheds (i.e., Goodman, Coffey, and Crow Canyon) were clipped from this combined DEM.


  Soils Data(Map services and data available from Natural Resources Conservation Service Web Soil Survey, U.S.Department of Agriculture)

    Animas-Dolores_Area_Soils:Small portion of the soil mapunitscover the northeastern corner of the Coffey Watershed (CW).
    Cortez_Area_Soils: Soils for Montezuma County, encompasses all of Goodman (GW) and Crow Canyon (CCW) watersheds, and a large portion of the Coffey watershed (CW).




ArcGIS Map Packages

  Goodman_Watershed_Full_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the full Goodman Watershed (GW).
  Goodman_Watershed_Mesa-Only_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the mesa-only Goodman Watershed.
  Crow_Canyon_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Crow Canyon Watershed (CCW).
  Coffey_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Coffey Watershed (CW).

For additional information on contents of the map packages, please see see Map Packages Descriptions or open a map package in ArcGIS and go toproperties or map document properties.

LICENSES

Code:MITyear: 2019 Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton

CONTACT

Andrew Gillreath-Brown, PhD Candidate, RPA Department of Anthropology, Washington State University andrew.brown1234@gmail.com Email andrewgillreathbrown.wordpress.com Web

NOTE: 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.