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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.
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TwitterThe Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida 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 (guis_geomorphology.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 (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.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 GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.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 (guis_geomorphology_metadata_faq.pdf). Please read the guis_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: 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 (guis_geomorphology_metadata.txt or guis_geomorphology_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 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).
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The digital map market, currently valued at $25.55 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 13.39% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing adoption of location-based services (LBS) across diverse sectors like automotive, logistics, and smart city initiatives is a primary catalyst. Furthermore, advancements in technologies such as AI, machine learning, and high-resolution satellite imagery are enabling the creation of more accurate, detailed, and feature-rich digital maps. The shift towards cloud-based deployment models offers scalability and cost-effectiveness, further accelerating market growth. While data privacy concerns and the high initial investment costs for sophisticated mapping technologies present some challenges, the overall market outlook remains overwhelmingly positive. The competitive landscape is dynamic, with established players like Google, TomTom, and ESRI vying for market share alongside innovative startups offering specialized solutions. The segmentation of the market by solution (software and services), deployment (on-premise and cloud), and industry reveals significant opportunities for growth in sectors like automotive navigation, autonomous vehicle development, and precision agriculture, where real-time, accurate mapping data is crucial. The Asia-Pacific region, driven by rapid urbanization and technological advancements in countries like China and India, is expected to witness particularly strong growth. The market's future hinges on continuous innovation. We anticipate a rise in the demand for 3D maps, real-time updates, and integration with other technologies like the Internet of Things (IoT) and augmented reality (AR). Companies are focusing on enhancing the accuracy and detail of their maps, incorporating real-time traffic data, and developing tailored solutions for specific industry needs. The increasing adoption of 5G technology promises to further boost the market by enabling faster data transmission and real-time updates crucial for applications like autonomous driving and drone delivery. The development of high-precision mapping solutions catering to specialized sectors like infrastructure management and disaster response will also fuel future growth. Ultimately, the digital map market is poised for continued expansion, driven by technological advancements and increased reliance on location-based services across a wide spectrum of industries. Recent developments include: December 2022 - The Linux Foundation has partnered with some of the biggest technology companies in the world to build interoperable and open map data in what is an apparent move t. The Overture Maps Foundation, as the new effort is called, is officially hosted by the Linux Foundation. The ultimate aim of the Overture Maps Foundation is to power new map products through openly available datasets that can be used and reused across applications and businesses, with each member throwing their data and resources into the mix., July 27, 2022 - Google declared the launch of its Street View experience in India in collaboration with Genesys International, an advanced mapping solutions company, and Tech Mahindra, a provider of digital transformation, consulting, and business re-engineering solutions and services. Google, Tech Mahindra, and Genesys International also plan to extend this to more than around 50 cities by the end of the year 2022.. Key drivers for this market are: Growth in Application for Advanced Navigation System in Automotive Industry, Surge in Demand for Geographic Information System (GIS); Increased Adoption of Connected Devices and Internet. Potential restraints include: Complexity in Integration of Traditional Maps with Modern GIS System. Notable trends are: Surge in Demand for GIS and GNSS to Influence the Adoption of Digital Map Technology.
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GIS data is available on the Forest’s FTP site in the form of “shape files” or layers and is available free for downloading. To utilize these data layers you will need a program that uses the Geographic Information System (GIS) such as ESRI’s ArcMap, ArcView or the free map reading program ArcGIS Explorer. ArcGIS Explorer has tools that let you zoom in/out, print the map, and query data. It also has map tips to identify features, and a help menu. ArcGIS Explorer is available as a free download from the ESRI website. Included is a list of GIS data files available for the Shawnee National Forest. These GIS data files are updated on a continuing basis. It should be noted that this data may have been developed from sources of differing accuracy, accurate only at certain scales, based on modeling or interpretation, or incomplete while being created or revised. Overall accuracy, completeness and timeliness may vary. The following geospatial information/data was prepared by the Shawnee National Forests (US Forest Service). The Forest Service reserves the right to correct, update, modify or replace GIS data without notification. Resources in this dataset:Resource Title: Geospatial Data. File Name: Web Page, url: https://www.fs.usda.gov/main/shawnee/landmanagement/gis Information about the geospatial data and a ftp link to download Forest GIS Data Shapefiles.
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The Professional Map Services market is experiencing robust growth, projected to reach $1003.7 million in 2025. While the exact CAGR isn't provided, considering the rapid technological advancements in GIS, AI-powered mapping, and the increasing reliance on location-based services across various sectors, a conservative estimate of the CAGR for the forecast period (2025-2033) would be between 8% and 12%. This growth is fueled by several key drivers. The burgeoning adoption of smart city initiatives necessitates detailed and accurate mapping solutions. Furthermore, the increasing demand for precise navigation systems in the transportation and logistics industries, coupled with the rising popularity of location-based marketing and advertising, significantly contribute to market expansion. The integration of advanced technologies like AI and machine learning into mapping solutions is further enhancing accuracy, efficiency, and functionality, driving market growth. The market is segmented by service type (consulting and advisory, deployment and integration, support and maintenance) and application (utilities, construction, transportation, government, automotive, others), reflecting the diverse needs of various industries. The competitive landscape is characterized by a mix of established players like Esri, Google, TomTom, and Mapbox, alongside emerging innovative companies. Geographic expansion, particularly in developing economies with rapidly urbanizing populations, presents a significant opportunity for growth. However, challenges such as data security concerns and the high cost of advanced mapping technologies could act as potential restraints. The market's future growth hinges on continuous technological advancements and the expansion of data accessibility. The increasing adoption of cloud-based mapping solutions is streamlining data management and improving collaboration. Furthermore, the growing integration of map data into various applications, such as autonomous vehicles and augmented reality experiences, is creating new market avenues. Regulatory changes and data privacy regulations will play a crucial role in shaping the market landscape in the coming years. The diverse application segments ensure market resilience, as growth in one sector can offset potential slowdowns in another. The ongoing expansion into new geographical territories, particularly in Asia-Pacific and other developing regions, presents substantial growth opportunities for market participants.
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TwitterThis map shows the free and open data status of county public geospatial (GIS) data across Minnesota. The accompanying data set can be used to make similar maps using GIS software.
Counties shown in this dataset as having free and open public geospatial data (with or without a policy) are: Aitkin, Anoka, Becker, Beltrami, Benton, Big Stone, Carlton, Carver, Cass, Chippewa, Chisago, Clay, Clearwater, Cook, Crow Wing, Dakota, Douglas, Grant, Hennepin, Hubbard, Isanti, Itasca, Kittson, Koochiching, Lac qui Parle, Lake, Lyon, Marshall, McLeod, Meeker, Mille Lacs, Morrison, Mower, Norman, Olmsted, Otter Tail, Pipestone, Polk, Pope, Ramsey, Renville, Rice, Scott, Sherburne, St. Louis, Stearns, Steele, Stevens, Traverse, Wabasha, Waseca, Washington, Wilkin, Winona, Wright, and Yellow Medicine.
To see if a county's data is distributed via the Minnesota Geospatial Commons, check the Commons organizations page: https://gisdata.mn.gov/organization
To see if a county distributes data via its website, check the link(s) on the Minnesota County GIS Contacts webpage: https://www.mngeo.state.mn.us/county_contacts.html
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Discover the booming interactive map creation tools market! This in-depth analysis reveals a $2.5 billion market in 2025, projected to reach $8 billion by 2033, driven by cloud-based solutions and growing data visualization needs. Learn about key players, market segmentation, and regional trends shaping this exciting sector.
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The professional map services market is booming, projected to reach $625.6 million by 2025 with a 7% CAGR. Discover key trends, leading companies, and regional insights in this comprehensive market analysis. Learn about the impact of AI, IoT, and autonomous vehicles on this rapidly growing sector.
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TwitterJALBTCX National Coastal Mapping Program Derived ProductsThe layers depicted in this web map were developed to serve regional geospatial data needs of USACE Districts and agency partners to discover and download products derived from USACE National Coastal Mapping Program (NCMP) high resolution, topo-bathymetric lidar and imagery. The USACE NCMP acquires high-resolution, high-accuracy topographic/bathymetric lidar elevation and imagery on a recurring basis along the sandy shorelines of the US. The program's survey footprint includes an approximately 1-mile wide swath of topography, bathymetry and imagery 500-m onshore and 1000-m offshore. The standard suite of NCMP data products include topographic/bathymetric lidar point clouds, digital surface and elevation models, shoreline vectors and both true-color and hyperspectral imagery mosaics. Value-added derivative information products may include laser reflectance images, landcover classification images, volume change metrics, and the products to help address District project requirements. USACE Headquarters initiated the NCMP in 2004. The program's update cycle follows counter-clockwise along the US West Coast, Gulf Coast, East Coast and Great Lakes approximately every 5 years. Surveys in support of USACE project-specific missions and external partners are included constituent to the current NCMP schedule and reimbursable funding. All work is coordinated with Federal mapping partners through the Interagency Working Group on Ocean and Coastal Mapping (IWGOCM) and the 3D Elevation Program (3DEP).NCMP operations are executed by the Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX). The JALBTCX mission is to perform operations, research and development in airborne lidar bathymetry and complementary technologies to support the coastal mapping and charting requirements of the US Army Corps of Engineers, the US Naval Meteorology and Oceanography Command and the National Oceanic and Atmospheric Administration. Survey operations are conducted worldwide using the Coastal Zone Mapping and Imaging (CZMIL) system and other industry-based coastal mapping and charting systems. CZMIL is JALBTCX's in-house survey capability that includes and Optech International, CZMIL 03-1 lidar instrument with simultaneous topographic and bathymetric capabilities. CZMIL is integrated with an Itres CASI-1500 hyperspectral imager and an 80 MP Leica RCD30 RGBN camera. CZMIL collects 10-kHz lidar data with spatially- and temporally-concurrent digital true-color and hyperspectral imagery.The Wetlands Classification Image Service layer can be accessed directly here: https://arcgis.usacegis.com/arcgis/rest/services/ERDC/ERDC_Wetlands_Classification/ImageServer
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The digital cartography market is booming, projected to reach $45 billion by 2033, driven by autonomous vehicles, e-commerce, and GIS advancements. Explore market trends, key players (Google, TomTom, etc.), and regional analysis in this comprehensive report.
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TwitterThis specialized location dataset delivers detailed information about marina establishments. Maritime industry professionals, coastal planners, and tourism researchers can leverage precise location insights to understand maritime infrastructure, analyze recreational boating landscapes, and develop targeted strategies.
How Do We Create Polygons?
-All our polygons are manually crafted using advanced GIS tools like QGIS, ArcGIS, and similar applications. This involves leveraging aerial imagery, satellite data, and street-level views to ensure precision. -Beyond visual data, our expert GIS data engineers integrate venue layout/elevation plans sourced from official company websites to construct highly detailed polygons. This meticulous process ensures maximum accuracy and consistency. -We verify our polygons through multiple quality assurance checks, focusing on accuracy, relevance, and completeness.
What's More?
-Custom Polygon Creation: Our team can build polygons for any location or category based on your requirements. Whether it’s a new retail chain, transportation hub, or niche point of interest, we’ve got you covered. -Enhanced Customization: In addition to polygons, we capture critical details such as entry and exit points, parking areas, and adjacent pathways, adding greater context to your geospatial data. -Flexible Data Delivery Formats: We provide datasets in industry-standard GIS formats like WKT, GeoJSON, Shapefile, and GDB, making them compatible with various systems and tools. -Regular Data Updates: Stay ahead with our customizable refresh schedules, ensuring your polygon data is always up-to-date for evolving business needs.
Unlock the Power of POI and Geospatial Data
With our robust polygon datasets and point-of-interest data, you can: -Perform detailed market and location analyses to identify growth opportunities. -Pinpoint the ideal locations for your next store or business expansion. -Decode consumer behavior patterns using geospatial insights. -Execute location-based marketing campaigns for better ROI. -Gain an edge over competitors by leveraging geofencing and spatial intelligence.
Why Choose LocationsXYZ?
LocationsXYZ is trusted by leading brands to unlock actionable business insights with our accurate and comprehensive spatial data solutions. Join our growing network of successful clients who have scaled their operations with precise polygon and POI datasets. Request your free sample today and explore how we can help accelerate your business growth.
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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. GIS Database 2002-2005: Project Size = 1,898 acres Fort Larned National Historic Site (including the Rut Site) = 705 acres 16 Map Classes 11 Vegetated 5 Non-vegetated Minimum Mapping Unit = ½ hectare is the program standard but this was modified at FOLS to ¼ acre. Total Size = 229 Polygons Average Polygon Size = 8.3 acres Overall Thematic Accuracy = 92% To produce the digital map, a combination of 1:8,500-scale (0.75 meter pixels) color infrared digital ortho-imagery acquired on October 26, 2005 by the Kansas Applied Remote Sensing Program and 1:12,000-scale true color ortho-rectified imagery acquired in 2005 by the U.S. Department of Agriculture - Farm Service Agency’s Aerial Photography Field Office, and all of the GPS referenced ground data were used to interpret the complex patterns of vegetation and land-use. In the end, 16 map units (11 vegetated and 5 land-use) were developed and directly cross-walked or matched to corresponding plant associations and land-use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed and revised. One hundred and six accuracy assessment (AA) data points were collected in 2006 by KNSHI and used to determine the map’s accuracy. After final revisions, the accuracy assessment revealed an overall thematic accuracy of 92%.
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Explore the dynamic Custom Digital Map Service market, driven by automotive innovation and location intelligence. Discover market size, CAGR, key drivers, and future trends for 2025-2033.
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The interactive map creation tools market is experiencing robust growth, driven by increasing demand for visually engaging data representation across diverse sectors. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $7.8 billion by 2033. This expansion is fueled by several key factors. The rising adoption of location-based services (LBS) and geographic information systems (GIS) across industries like real estate, tourism, logistics, and urban planning is a major catalyst. Businesses are increasingly leveraging interactive maps to enhance customer engagement, improve operational efficiency, and gain valuable insights from geospatial data. Furthermore, advancements in mapping technologies, including the integration of AI and machine learning for improved data analysis and visualization, are contributing to market growth. The accessibility of user-friendly tools, coupled with the decreasing cost of cloud-based solutions, is also making interactive map creation more accessible to a wider range of users, from individuals to large corporations. However, the market also faces certain challenges. Data security and privacy concerns surrounding the use of location data are paramount. The need for specialized skills and expertise to effectively utilize advanced mapping technologies may also hinder broader adoption, particularly among smaller businesses. Competition among established players like Mapbox, ArcGIS StoryMaps, and Google, alongside emerging innovative solutions, necessitates constant innovation and differentiation. Nevertheless, the overall market outlook remains positive, with continued technological advancements and rising demand for data visualization expected to propel growth in the coming years. Specific market segmentation data, while unavailable, can be reasonably inferred from existing market trends, suggesting a strong dominance of enterprise-grade solutions, but with substantial growth expected from simpler, more user-friendly tools designed for individuals and small businesses.
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TwitterThis 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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Some of the finest mountain scenery in the Southwest is found in the 1.6-million-acre Santa Fe National Forest. Here, you can find the headwaters of Pecos, Jemez, and Gallinas Rivers; mountain streams; lakes; and trout fishing. Travel into Pecos, San Pedro Parks, Chama, and Dome Wildernesses via wilderness pack trips, saddle, or on 1,000 miles of hiking trails. Try whitewater rafting on the Rio Chama or Rio Grande from May to September. Consider turkey, elk, deer, and bear hunting, or visit one of many nearby Indian pueblos, Spanish missions, and Indian ruins. Golden aspen grace the high country from September to October and snow blankets Santa Fe Ski Basin in winter. The Santa Fe National Forest GIS data available for download includes Santa Fe National Forest Geospatial (GIS) Datasets, Motor Vehicle Use Map (MVUM) Travel Aids - digital maps and data of the SFNF to upload to GPS units or Smart Phones, 7.5 Minute Topographic Maps (PDF and GeoTIFF) - US Forest Service topo maps only, USFS Geospatial Clearinghouse - includes GIS data of vegetation treatments, administrative boundaries, inventoried roadless areas, FSTopo datasets, USGS Map Locator and Downloader - download current and historic topo maps, Hardcopy Maps with information on how to purchase hard copy visitor, wilderness, or topographic maps. Resources in this dataset:Resource Title: Santa Fe National Forest Geospatial Data. File Name: Web Page, url: https://www.fs.usda.gov/main/santafe/landmanagement/gis
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Discover the booming digital map ecosystem market, projected to reach $450 billion by 2033. Explore key drivers, regional trends, and leading companies shaping this rapidly evolving landscape, including autonomous vehicle integration and LBS advancements. Learn more about market size, CAGR, and segmentation analysis in this comprehensive report.
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Planning, Engineering & Permitting - GIS Mapping files
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TwitterThe Nature Conservancy celebrates GIS Day each November with our TNC-wide GIS Day Map Contest! Map makers from across the Conservancy submit their static maps, animated maps, and interactive web mapping applications, and a panel of judges from the Geospatial Systems Team scores each submission and selects the winners.This gallery application displays submissions and award winners from past years' GIS Day Map Contest. Check out the home page at gisday.tnc.org for more!
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TwitterMaps and spatial apps from agencies around Colorado
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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.