Author: A Lisson, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8Resource type: lessonSubject topic(s): gis, geographic thinkingRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

1. Explain the difference between two types of geospatial technologies - GPS and GIS.
2. Develop basic skills to effectively manipulate and use GPS receivers and ArcGIS software.
3. Explain uses of GPS and GIS.Summary: Students use GPS coordinates to discover geocaches at a local park, and they use ArcGIS to layer maps about the park. Frontenac State park is the example, but any park or area (including school grounds) could be used. Students also investigate careers that use GIS.

The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.

It is about updating to GIS information database, Decision Support Tool (DST) in collaboration with IWMI. With the support of the Fish for Livelihoods field team and IPs (MFF, BRAC Myanmar, PACT Myanmar, and KMSS) staff, collection of Global Positioning System GPS location data for year-1 (2019-20) 1,167 SSA farmer ponds, and year-2 (2020-21) 1,485 SSA farmer ponds were completed with different GPS mobile applications: My GPS Coordinates, GPS Status & Toolbox, GPS Essentials, Smart GPS Coordinates Locator and GPS Coordinates. The Soil and Water Assessment Tool (SWAT) model that integrates climate change analysis with water availability will provide an important tool informing decisions on scaling pond adoption. It can also contribute to a Decision Support Tool to better target pond scaling. GIS Data also contribute to identify the location point of the F4L SSA farmers ponds on the Myanmar Map by fiscal year from 1 to 5.

Discover the booming GIS Data Collector market! This comprehensive analysis reveals a $2.5B market in 2025, projected to reach $4.2B by 2033, fueled by precision agriculture, infrastructure development, and technological advancements. Explore key trends, drivers, restraints, and leading companies shaping this dynamic sector.

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.

Discover the booming handheld GNSS receiver market! This comprehensive analysis reveals market size, growth trends, key players (Trimble, Leica, Topcon), and regional insights (North America, Europe, Asia-Pacific). Learn about applications in surveying, agriculture, and more. Explore the future of precise positioning technology.

This data represents The Utah Reference Network Global Positioning System (TURN GPS) base station locations. It models the current base station locations on the network. In some areas we extends past the boundary of Utah when we have been invited by those communities.

DNRGPS is an update to the popular DNRGarmin application. DNRGPS and its predecessor were built to transfer data between Garmin handheld GPS receivers and GIS software.

DNRGPS was released as Open Source software with the intention that the GPS user community will become stewards of the application, initiating future modifications and enhancements.

DNRGPS does not require installation. Simply run the application .exe

See the DNRGPS application documentation for more details.

Compatible with: Windows (XP, 7, 8, 10, and 11), ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

Limited Compatibility: Interactions with ArcMap layer files and ArcMap graphics are no longer supported. Instead use shapefile or geodatabase.

Prerequisite: .NET 4 Framework

DNR Data and Software License Agreement

Subscribe to the DNRGPS announcement list to be notified of upgrades or updates.

This dataset is about books. It has 2 rows and is filtered where the book is The Global Positioning System and GIS : an introduction. It features 7 columns including author, publication date, language, and book publisher.

This data represents the measured distance between the The Utah Reference Network Global Positioning System (TURN GPS) base stations. It models the current coverage of the network and in some areas extends past the boundary of Utah. Baselines with a distance greater than 70 km will start to decrease your precision.

The Location Analytics Tools market is experiencing robust growth, projected to reach $15 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 16.93% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing adoption of location-based services across diverse sectors like transportation, retail, BFSI (Banking, Financial Services, and Insurance), media and entertainment, and telecommunications is a significant factor. Businesses are leveraging location data to optimize operations, personalize customer experiences, and gain a competitive edge. Furthermore, advancements in technologies such as GPS, GIS (Geographic Information System), and big data analytics are enabling more sophisticated location intelligence solutions. The market is segmented by end-user and type of location (outdoor and indoor), reflecting the diverse applications of these tools. North America currently holds a significant market share due to early adoption and the presence of major technology companies, but the Asia-Pacific region is expected to witness substantial growth in the coming years driven by increasing digitalization and infrastructure development. Competitive dynamics are shaped by a mix of established players like Google (Alphabet Inc.), Microsoft, and IBM, and innovative startups offering specialized solutions. These companies are employing various competitive strategies, including mergers and acquisitions, partnerships, and product innovation, to secure market share and cater to the evolving needs of businesses. The market faces certain restraints, such as data privacy concerns and the complexity involved in integrating location analytics into existing systems. However, the overall growth trajectory remains positive, indicating significant opportunities for market participants. The forecast period (2025-2033) anticipates continued expansion, driven by rising demand for real-time location intelligence and the increasing availability of high-quality location data. The transportation sector, for instance, benefits from route optimization and fleet management capabilities offered by these tools, while retailers utilize them for targeted advertising and store location analysis. The BFSI sector uses location analytics for risk management and fraud detection, highlighting the versatility of this market. The growing integration of location analytics with other emerging technologies like IoT (Internet of Things) and AI (Artificial Intelligence) further enhances its capabilities, promising even more innovative applications in the future. This convergence is expected to further accelerate market growth and drive innovation in location-based services, solidifying the long-term prospects of this dynamic market.

Raw data of annual crop harvests of corn, soy and wheat from the Main Cropping System...

The booming Spatial Location Services market is projected to reach $153.9 billion by 2033, driven by IoT, GPS advancements, and rising demand across sectors. Explore market trends, key players (Google Cloud, IBM, HERE Technologies), and regional insights in this comprehensive analysis.

India Location-based Services Market size was valued at USD 460 Million in 2024 and is projected to reach USD 1563 Million by 2032, growing at a CAGR of 16.7% from 2026 to 2032.India Location-based Services Market: Definition/ OverviewLocation-based services (LBS) are applications or services that use a user's geographic location to provide personalized content, services, or information. These services typically rely on technologies such as GPS, Wi-Fi, or cellular data to determine the user's position and tailor experiences based on that location. LBS can be offered through mobile apps, websites, or IoT devices, providing users with relevant information or guidance wherever they are.The application of location-based services spans across various industries, from navigation and travel to retail and marketing. For instance, apps like Google Maps or Uber use LBS to offer real-time route guidance, ride-hailing services, and traffic updates. Retailers use LBS for targeted advertising, sending promotional offers to customers when they are near a store. Additionally, LBS are used in healthcare for monitoring patient movement, in logistics for fleet management, and even in social networking apps where users can share their locations with friends.

This GIS dataset shows the locations of fire hydrants at Davis Station. The data are formatted according to the SCAR Feature Catalogue (see Related URL below). Enter the Qinfo number of any feature at the 'Search datasets and quality' tab to search for data quality information about the feature: for example, the source of the data.

Dataset Abstract The LTER annual crops (corn, soy and wheat), treatments 1-4, are harvested annually using a combine equipped with a GPS and precision agriculture software to allow detailed yield measurements with coincident GPS latitude and longitude data.. original data source http://lter.kbs.msu.edu/datasets/40

GOAL ○ Development of Korean route and infrastructure such as a research camp to approach the Antarctic inland ○ Establishment of a support system for the Antarctic inland research RESEARCH CONTENTS ○ A safe and reliable route expedition to the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland research ○ Construction of logistic camps at the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland research

Discover the booming spatial location services market! Our comprehensive analysis reveals a $15B market in 2025 projected to reach $45B by 2033, driven by IoT, AI, and smart city initiatives. Explore key trends, regional insights, and leading companies shaping this dynamic sector.

The global GIS Data Collector market is experiencing robust growth, driven by increasing adoption of precision agriculture techniques, expanding infrastructure development projects, and the rising need for accurate geospatial data across various industries. The market's Compound Annual Growth Rate (CAGR) is estimated to be around 8% for the forecast period of 2025-2033, projecting significant market expansion. This growth is fueled by technological advancements in GPS technology, improved data processing capabilities, and the increasing affordability of GIS data collection devices. Key segments driving market expansion include high-precision data collection systems and their application in agriculture, where farmers are increasingly leveraging real-time data for optimized resource management and increased yields. The industrial sector also contributes significantly to market growth, with applications ranging from construction and surveying to utility management and environmental monitoring. While the market faces certain restraints, such as the need for skilled professionals to operate the sophisticated equipment and the potential for data security concerns, these are outweighed by the overwhelming benefits of improved efficiency, accuracy, and cost savings provided by GIS data collectors. The market's regional landscape shows significant participation from North America and Europe, owing to established technological infrastructure and early adoption of advanced GIS technologies. However, rapid growth is expected in the Asia-Pacific region, especially in countries like China and India, fueled by infrastructure development and expanding agricultural activities. Leading players like Garmin, Trimble, and Hexagon are driving innovation and competition, while a growing number of regional players offer more cost-effective solutions. The competitive landscape is characterized by a mix of established global players and regional manufacturers. The established players leverage their technological expertise and extensive distribution networks to maintain market leadership. However, the increasing affordability and accessibility of GIS data collection technologies are attracting new entrants, creating a more dynamic market. Future growth will likely be shaped by the integration of artificial intelligence and machine learning into GIS data collection systems, further enhancing data processing capabilities and automation. The continued development of robust and user-friendly software applications will also contribute to market expansion. Furthermore, the adoption of cloud-based GIS platforms is expected to increase, facilitating greater data sharing and collaboration. This convergence of hardware and software innovations will drive market growth and broaden the applications of GIS data collectors across diverse sectors.

City of Champaign GPS control network.