The geographic data are built from the Technical Information Management System (TIMS). TIMS consists of two separate databases: an attribute database and a spatial database. The attribute information for offshore activities is stored in the TIMS database. The spatial database is a combination of the ARC/INFO and FINDER databases and contains all the coordinates and topology information for geographic features. The attribute and spatial databases are interconnected through the use of common data elements in both databases, thereby creating the spatial datasets. The data in the mapping files are made up of straight-line segments. If an arc existed in the original data, it has been replaced with a series of straight lines that approximate the arc. The Gulf of America OCS Region stores all its mapping data in longitude and latitude format. All coordinates are in NAD 27. Data can be obtained in three types of digital formats: INTERACTIVE MAP: The ArcGIS web maps are an interactive display of geographic information, containing a basemap, a set of data layers (many of which include interactive pop-up windows with information about the data), an extent, navigation tools to pan and zoom, and additional tools for geospatial analysis. SHP: A Shapefile is a digital vector (non-topological) storage format for storing geometric location and associated attribute information. Shapefiles can support point, line, and area features with attributes held in a dBASE format file. GEODATABASE: An ArcGIS geodatabase is a collection of geographic datasets of various types held in a common file system folder, a Microsoft Access database, or a multiuser relational DBMS (such as Oracle, Microsoft SQL Server, PostgreSQL, Informix, or IBM DB2). The geodatabase is the native data structure for ArcGIS and is the primary data format used for editing and data management.

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

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The downloaded SSURGO data included an ArcGIS Shapefile of the soil type features for Oakland County, tabular data in text file format, and an empty pre-formatted Microsoft Access database containing queries, macros and reports. The Shapefile was intially projected in State Plane Michigan South Meters NAD 83, but was then reprojected by Oakland County staff to State Plane Michigan South International Feet NAD 83. The USDA-NRCS provided instructions for automatically importing the tabular text files into the Microsoft Access database. The key attribute of this feature class is the map unit key (MUSYM field), which relates the polygon features to the SoilAttribute table stored within SDE. The related SoilAttribute table in SDE contains some of the tabular data which was initially imported into the aforementioned Microsoft Access database.

The National Pollutant Release Inventory (NPRI) is Canada's public inventory of pollutant releases (to air, water and land), disposals and transfers for recycling. This database contains the full NPRI dataset from 1993 to the current reporting year. To help you navigate, a Microsoft Word file provides information on the database’s structure and schema. The database is available in Microsoft Access format (accdb). The data are in normalized or “list” format and are optimized for pivot table analyses. The data are also available in a CSV format : https://open.canada.ca/data/en/dataset/40e01423-7728-429c-ac9d-2954385ccdfb. Please consult the following resources to enhance your analysis: - Guide on using and Interpreting NPRI Data: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/using-interpreting-data.html - Access additional data from the NPRI, including datasets and mapping products: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/tools-resources-data/exploredata.html Supplemental Information This data is also available in non-proprietary CSV format on the Bulk Data page. http://open.canada.ca/data/en/dataset/40e01423-7728-429c-ac9d-2954385ccdfb These files contain data from 1993 to the latest reporting year available. These datasets are in normalized or ‘list’ format and are optimized for pivot table analyses. Supporting Projects: National Pollutant Release Inventory (NPRI)

This database contains drone-based mapping data of seven crevassed glaciers in Svalbard, Norway. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape (version 1.8.5) and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF, .JPG, and .PNG file format, and textured 3D models in .STL and .OBJ/.MTL/.JPG file format. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 2 Pro Enterprise and a DJI Phantom 4 Pro. The mapping area cover the crevassed glacier fronts. Data collection was conducted over several fieldwork seasons between 2019 and 2020. Spring fieldwork was conducted with snowscooters, summer and fall fieldwork with boat. The following glaciers are mapped: - Fridtjovbreen Spring 2020, 07/may/2020 - Koenigsbergbreen Spring 2020, 04/May/2020 - Nordenskiöldbreen Fall 2019, 19th-22nd/Aug/2019 - Nordenskiöldbreen Summer 2020, 21/Jul/2020 - Tunebreen Spring 2020, 28/Apr/2020 - Tunabreen Summer 2020, 06/Aug/2020 - Wahlenbergbreen Summer 2020, 05/Aug/2020

This database contains drone-based mapping data of three surging glaciers in Rindersbukta, Svalbard, Norway. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF, .JPG, and .PNG file format, and textured 3D models in .STL and .OBJ/.MTL/.JPG file format. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 2 Pro Enterprise. The mapping area covers the crevassed glacier fronts. Data collection was conducted during Spring 2022 (19-23.04.2022), Spring 2023 (23-24.03.2023), and Spring 2024 (10.03.2024). The following glaciers are mapped: Scheelebreen (2022, 2023), Vallåkrabreen (2022, 2023, 2024), and Paulabreen (2022). For Vallåkrabreen, two different datasets are available, where the "bulge" datasets only contains the area of the surge buldge, whereas the other dataset contains the entire glacier area.

This database contains drone-based mapping data of four glaciers in Svalbard, Norway. Fridtjovbreen on the west coast and Vallakrabreen, Paulabreen, and Scheelebreen which are three surging glaciers in Rindersbukta. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF, .JPG, and .PNG file format, and textured 3D models in .STL and .JPG file format. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 3 Pro Enterprise. The mapping area covers the crevassed glacier fronts. Data collection was conducted during Spring 2025 (29.03.2025-02.04.2025). For Fridtjovbreen, two different models are available, one high resolution and one baseline resolution. The datasets for Paulabreen and Scheelebreen are combined.

This database contains drone-based mapping data of the crevassed and surging glacier of Borebreen in Svalbard, Norway. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape (version 1.8.5) and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF, and textured 3D models in .STL and .PDF file format. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 2 Pro Enterprise. The fieldwork was conducted in August of 2023 over several days with access to Borebreen via boat. The mapping area covers the crevassed glacier front on five days between 01 Aug 2023 and 12 Aug 2023. In addition, the glacier forefield was mapped over several days and combined into one fileset. There are two subsets of data. First, there are the files Glacier-subset-A/B for the 20230811 dataset. This data contains a subset of the glacier which was taken before (A) anda after (B) a major calving event happening on the same day. It is intended to study very short time-span calving rates. The second dataset is the Forefield-subset, that includes a larger area that was mapped using oblique mapping (in constrast to the nadir mapping in the rest of the dataset. Processing of the data was conducted by Richard Hann. Data aquisiton by Richard Hann and Nil Rodes (20230801). Project and fieldwork support by Wojciech Gajek, Danni Pearce, and William Harcourt.

This database contains drone-based mapping data of three glaciers near Longyearbyen in Svalbard, Norway. There are three locations, Larsbreen, Longyearbreen, and Tellbreen. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape (version 1.8.5) and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format and orthomosaic maps in georeferenced .JPG or .TIF. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 2 Pro Enterprise. The fieldwork was conducted in September 2022 on Tellbreen by Eero Rinne and October on Larsbreen and Longyearbreen by Richard Hann.