Ready to use PDF map of the city of Annona including roads and city limits. Dimensions are ANSI D 22 in x 34 in (559 mm x 864 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org https://atcog.org/ Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

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.

Ready to use PDF map of Hopkins County, Texas including roads and city limits. Dimensions are ANSI E 34 in x 44 in (864 mm x 1118 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org https://atcog.org/ Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu.We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024.Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area.The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

The global mapping software market is experiencing robust growth, driven by increasing demand across various sectors. While precise figures for market size and CAGR are absent from the provided data, a reasonable estimation can be made based on industry trends. Considering the presence of major players like Adobe, Autodesk, and Microsoft, and the consistent advancements in GIS technology and location-based services, a conservative estimate places the 2025 market size at approximately $15 billion USD. Assuming a steady growth trajectory influenced by factors like increasing adoption of cloud-based solutions, the integration of AI and machine learning for enhanced mapping capabilities, and the growing need for precise location data in logistics, urban planning, and environmental monitoring, a Compound Annual Growth Rate (CAGR) of 8-10% over the forecast period (2025-2033) seems plausible. This would project market values significantly higher by 2033. This growth is fueled by several key trends. The increasing availability of high-resolution satellite imagery and other geospatial data provides richer inputs for mapping applications. Furthermore, the rising adoption of mobile devices equipped with GPS technology and the proliferation of location-based services (LBS) are expanding the market's addressable user base. However, challenges remain, such as the high cost of advanced mapping software and the complexities associated with data integration and management. Nevertheless, the overall market outlook remains positive, with continued expansion anticipated across various segments and geographic regions. The competitive landscape is marked by a mix of established players and emerging startups, leading to innovation and the continuous improvement of mapping technologies.

This map was created as part of a worldwide series of geologic maps for the U.S. Geological Survey's World Energy Project. These products are available on CD-ROM and the Internet. The goal of the project is to assess the undiscovered, technically recoverable oil and gas resources of the world. Two previously published digital geologic data sets (U.S. and Caribbean) were clipped to the map extent, while the dataset for Mexico was digitized for this project. Original attributes for all data layers were maintained, and in some cases, graphically merged with common symbology for presentation purposes. The world has been divided into geologic provinces that are used for allocation and prioritization of oil and gas assessments. For the World Energy Project, a subset of those provinces is shown on this map. Each province has a set of geologic characteristics that distinguish it from surrounding provinces. These characteristics may include dominant lithologies, the age of the strata, and/or structural type. The World Geographic Coordinate System of 1984 is used for data storage, and the data are presented in a Lambert Conformal Conic Projection on the OFR 97-470-L map product. Other details about the map compilation and data sources are provided in metadata documents in the data section on this CD-ROM. Several software packages were used to create this map including: Environmental Systems Research Institute, Inc. (ESRI) ArcGIS 8.3, ArcInfo software, Adobe Photoshop CS, Illustrator CS, and Acrobat 6.0. Tips

This map was created as part of a worldwide series of geologic maps for the U.S. Geological Survey's World Energy Project. These products are available on CD-ROM and the Internet. The goal of the project is to assess the undiscovered, technically recoverable oil and gas resources of the world. Two previously published digital geologic data sets (U.S. and Caribbean) were clipped to the map extent, while the dataset for Mexico was digitized for this project. Original attributes for all data layers were maintained, and in some cases, graphically merged with common symbology for presentation purposes. The world has been divided into geologic provinces that are used for allocation and prioritization of oil and gas assessments. For the World Energy Project, a subset of those provinces is shown on this map. Each province has a set of geologic characteristics that distinguish it from surrounding provinces. These characteristics may include dominant lithologies, the age of the strata, and/or structural type. The World Geographic Coordinate System of 1984 is used for data storage, and the data are presented in a Lambert Conformal Conic Projection on the OFR 97-470-L map product. Other details about the map compilation and data sources are provided in metadata documents in the data section on this CD-ROM. Several software packages were used to create this map including: Environmental Systems Research Institute, Inc. (ESRI) ArcGIS 8.3, ArcInfo software, Adobe Photoshop CS, Illustrator CS, and Acrobat 6.0.

Ready to use PDF map of the city of Avery including roads and city limits. Dimensions are ANSI D 22 in x 34 in (559 mm x 864 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org https://atcog.org/ Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

This map was created as part of a worldwide series of geologic maps for the U.S. Geological Survey's World Energy Project. These products are available on CD-ROM and through the Internet. The goal of the project is to assess the undiscovered, technically recoverable oil and gas resources of the world. Most of the source data for this map compilation were digitized from the Geologic-Tectonic Map of the Caribbean Region by J.E. Case and T.L. Holcombe, at a scale of 1:2,500,000. For data management purposes, the world was divided into eight energy regions based on political boundaries and corresponding approximately to the economic regions of the world as defined by the U.S. Department of State. Region Six encompasses the Caribbean area, Central America, and South America. Other products are also available related to Region Six, including the Geologic Map of South America (USGS Open File Report 97-470-D). Countries listed below are shown whole or in part within the map extent of the Caribbean region: Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Colombia Costa Rica Cuba Dominica Dominican Republic El Salvador Grenada Guadeloupe Guatemala Guyana Haiti Honduras Jamaica Martinique Mexico Montserrat Netherlands Antilles Nicaragua Panama Puerto Rico St. Kitts and Nevis St. Lucia St. Vincent and the Grenadines Trinidad and Tobago Turks and Caicos Islands United States Venezuela Virgin Islands The world was previously divided into geologic provinces for the World Energy Project, of which a subset is shown on the map. Each province has a set of geologic characteristics that distinguish it from surrounding provinces. These characteristics may include dominant lithologies, the age of the strata, and/or structural type. Each province is assigned a unique number and may fall within two or more countries or assessment regions. The World Geographic Coordinate System of 1984 was used for data storage and map display. Other details about the map compilation and data sources are provided in several metadata formats in the data section on this CD-ROM. Various software packages were used to create this map including: Environmental Systems Research Institute, Inc. (ESRI) ArcGIS 8.3, ArcInfo software, Adobe Photoshop CS, Illustrator CS, and Acrobat 6.0.

Explore the dynamic Mapping Software market, driven by engineering and industrial design needs. Discover growth drivers, key trends, restraints, and leading companies shaping the future of geospatial solutions from 2019-2033.

(See USGS Digital Data Series DDS-69-Q) This report contains maps and associated spatial data showing historical oil and gas exploration and production in the United States. Because of the proprietary nature of many oil and gas well databases, the United States was divided into cells one-quarter square mile and the production status of all wells in a given cell was aggregated. Base-map reference data are included, using the U.S. Geological Survey (USGS) National Map, the USGS and American Geological Institute (AGI) Global GIS, and a World Shaded Relief map service from the ESRI Geography Network. A hardcopy map was created to synthesize recorded exploration data from 1859, when the first oil well was drilled in the U.S., to 2005. In addition to the hardcopy map product, the data have been refined and made more accessible through the use of Geographic Information System (GIS) tools. The cell data are included in a GIS database constructed for spatial analysis via the USGS Internet Map Service or by importing the data into GIS software such as ArcGIS. The USGS internet map service provides a number of useful and sophisticated geoprocessing and cartographic functions via an internet browser. Also included is a video clip of U.S. oil and gas exploration and production through time. Adobe Acrobat Reader software allows the user to view and interact with the hardcopy Adobe Acrobat Portable Document Format (PDF) map.

The Portland Basin is a prime location to assess the feasibility of DDU-TES because natural geologic conditions provide thermal and hydraulic separation from overlying aquifers that would otherwise sweep away stored heat. Under the Portland Basin, the lower Columbia River Basalt Group (CRBG) aquifers contain brackish water (1,000-10,000 mg/L TDS), indicating low groundwater flow rates and poor connection with the overlying regional aquifer. Further, CRBG lavas tend to have comparatively low thermal conductivity, indicating that the 400-1,000 ft thick CRBG may be an effective thermal barrier to the overlying aquifer. A temporally and spatially limited previous study of a Portland Basin CRBG aquifer demonstrated that the injection of waste heat resulted in an increase in temperature by more than a factor of two, indicating a high potential for storing heat.

This data submission includes ASCII grid surfaces for the Portland and Tualatin Basins including a DEM of modern topography, the top of Columbia River Basalt (CRB), the base of CRB, and basement. It also includes three isochore (thickness) maps between these intervals. In addition, there is an ArcGIS attribute table for associated data points, a map of data types used to constrain the top of CRB, and cross-sections, all made using IHS Kingdom Suite, Petrosys PRO, ESRI ArcGIS, and Adobe Illustrator software.

Ready to use PDF map of the city of Atlanta including roads and city limits. Dimensions are ANSI E 34 in x 44 in (864 mm x 1118 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org https://atcog.org/ Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

Ready to use PDF map of Titus County, Texas including roads, city limits, and unincorporated communities. Dimensions are ANSI E 34 in x 44 in (864 mm x 1118 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org Ark-Tex Council of Governments Homepage: https://atcog.org/Open Data Portal Homepage: https://open-data-portal-atcog.hub.arcgis.com/Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

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

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu. We used a DJI Mavic 2 Pro to capture aerial photos in Beaumont-Port Arthur, TX, in February 2023, including: I. Beaumont Soccer Club II. Corps’ Port Arthur Resident Office III. Halbouty Pump Station comprises its vicinity IV. Lamar University (Including Exxon Power Plants close to Lamar Univ.) V. MLK Boulevard for aerial images of the industry and the ship channel VI. Salt Water Barrier (include some aerial images about the Big Thicket) Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each location. The processed data package including 3D models, geospatial data, mappings, point clouds, and the animation video of Halbouty Pump Station has various file types: The Adobe Suite gives you great software to open .Tif files. You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.

Ready to use PDF map of the city of Bogata including roads, city limits, and city hall. Dimensions are ANSI D 22 in x 34 in (559 mm x 864 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org Ark-Tex Council of Governments Homepage: https://atcog.org/Open Data Portal Homepage: https://open-data-portal-atcog.hub.arcgis.com/Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

Ready to use PDF map of Bowie County, Texas including roads, city limits, and unincorporated communities. Dimensions are ANSI E 34 in x 44 in (864 mm x 1118 mm). PDF documents may be downloaded and viewed in PDF software such as Adobe Acrobat Reader. For questions, problems, or more information, contact gis@atcog.org Ark-Tex Council of Governments Homepage: https://atcog.org/Open Data Portal Homepage: https://open-data-portal-atcog.hub.arcgis.com/Reference in this site to any specific commercial product, process, service, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the Ark-Tex Council of Governments.

The Historically Underutilized Business Zones (HUBZone) program was enacted into law as part of the Small Business Reauthorization Act of 1997 Download Adobe Reader to read this link content. The program falls under the auspices of the U.S. Small Business Administration. The program encourages economic development in historically underutilized business zones - "HUBZones" - through the establishment of preferences.SBA's HUBZone program is in line with the efforts of both the Administration and Congress to promote economic development and employment growth in distressed areas by providing access to more federal contracting opportunities.

This map is based on the ecological risk assessment data of the China Nepal transportation corridor, edited and produced using ArcGIS and Adobe Illustrator software, as well as spatial drawing and vector editing methods. This includes ecological risk maps of Lhasa, Shigatse, and transportation corridors at different scales, in JPG format with a temporal resolution of years (1992, 1995, 2000, 2005, 2010, 2015, 2022, and predicted years of 2030 and 2050). The spatial resolution of ecological risk assessment data is 1km, the temporal resolution is year (1992, 1995, 2000, 2005, 2010, 2015, 2022, and the predicted years are 2030 and 2050), and the data format is TIFF. Using the European Space Agency's global land use cover dataset and the SSP-RCP scenario land use dataset published by Scientific Data, a 5 * 5km grid was established. ArcGIS software and Fragstats software were used to calculate the landscape disturbance degree (landscape fragmentation, landscape separation, and landscape dominance index) and landscape vulnerability index, and a 1km grid scale ecological risk dataset was obtained through Kriging interpolation.