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.

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.

Scott County GPS Control: Scott County GPS Control Network monument locations. Originally collected in 2005 and subsequently reoccupied in 2015 and delivered in Iowa State Plane South, NAD83 (2011) and Iowa RCS Zone 11 coordinates. Davenport PLSS Corner Survey: Survey data acquired from Davenport regarding PLSS corners that they occupied over time using in-house survey equipment. Detailed information not available.PLSS Survey: Scott County PLSS corners occupied between 2007-2010 and originally referenced to Iowa State Plane, South NAD83 (HARN96) coordinate system. In 2015, a township level positional analysis and readjustment to NAD (2011) was conducted by third-party survey firms GB Consulting and DCI, Inc both incorporated in the State of Iowa.PLSS Index: Section corner reference database which represents locations of all known recorded corner certificates in Scott County as well as section corner documents kept by the Scott County Secondary Road Departments referred to as "Tie Books" (not recorded). Note that the physical location of corners in the PLSS Index database are approximate only. In contrast to the corners in layer PLSS Survey, the ones in PLSS Index are not survey grade and are for reference purposes only. However, the PLSS Index contains useful reference information such as when the corner was recorded, who recorded it, etc. and includes an online link to every section corner certificates and county tie book in the collection. There is a one-to-many relationship between features in the PLSS Index layer and the table, Certificate and Tie Book Records.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Global Positioning System Ground Control Points and Field Site Locations from 1995

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem.

The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

This data set is in ARC/INFO export format and contains Global Positioning Systems (GPS) ground control points in and around the International Paper Experimental Forest, Howland ME.

A Trimble roving receiver placed on the top of the cab of a pick-up truck and leveled was used to collect position information at selected sites (road intersections) across the FED project study area. The field collected data was differentially corrected using base files measured by a Trimble Community Base Station. The Community Base Station is run by the Forestry Department at the University of Maine, Orono (UMO). The base station was surveyed by the Surveying Engineering Department at UMO using classical geodetic methods. Trimble software was used to produce coordinates in Universal Transverse Mercator (UTM) WGS84. Coordinates were adjusted based on field notes. All points were collected during January 1995 and differentially corrected.

Long-standing tensions between Protestant and Catholic communities in Northern Ireland have led to high levels of segregation. This article explores the spaces within which residents of north Belfast move within everyday life and the extent to which these are influenced by segregation. We focus in particular on the role that interconnecting tertiary streets have on patterns of mobility. We adapt Grannis’s (1998) concept to define T-communities from sets of interconnecting tertiary streets within north Belfast. These are combined with more than 6,000 Global Positioning System (GPS) tracks collected from local residents to assess the amount of time spent within different spaces. Spaces are divided into areas of residents’ own community affiliations (in-group), areas not clearly associated with either community (mixed), or areas of opposing community affiliation (out-group). We further differentiate space as being either within a T-community or along a section of main road. Our work extends research on T-communities by expanding their role beyond exploring residential preference, to explore, instead, networks of (dis)connection through which social divisions are expressed via everyday mobility practices. We conclude that residents are significantly less likely to move within mixed and out-group areas and that this is especially true within T-communities. It is also evident that residents are more likely to travel along out-group sections of a main road if they are in a vehicle and that women show no greater likelihood than men to move within out-group space. Evidence from GPS tracks also provides insights into some areas where mixing appears to occur. Key Words: GIS, Northern Ireland, postconflict, segregation, T-communities.

This dataset is a compendium of GPS Data collected by Randy Carlson and collaborators on the Virginia Coast Reserve (primarily), Plum Island and North Inlet. A master data table was extracted by Charles L. Carlson during 2013 that includes all the individual point locations recovered from individual surveys. In addition to the data table, the data is also shared as a .zip file containing a static web page with links to particular projects and the underlying data. To use the data, unzip it and use your web browser to open the index.html file. Web page contents include: American Oyster Catchers on the Virginia Coast Reserve - 2003 Lynette Winters - Salicornia - MSL elevation project Dynamic Evolution of Barrier Island Morphology and Ecology from 1996-2002 Documented Using High -Resolution GPS-GIS Topographic Mapping Surveys, Virginia Coast Reserve (for GSA, Denver, CO Oct 27-30, 2002 Broadwater Tower Overwash Fan Photos - Feburary 15, 2002 Hog Island Bay DGPS Drifter Study 2001 Ray Dueser/Nancy Moncrief Small Mammal GPS/GIS A Topographical History of North Myrtle Island, 1974 to 2001 Ray Dueser/Nancy Moncrief - Highest Elevations on VCR Barrier Islands Myrtle Island Planimetric area, Surface area & Volumetric Calculations 1996-2001 Myrtle, Ship Shoal GIS/GPS UTM Shape Files and Grids Myrtle, Ship Shoal, ESNWR, Shirley, Steelman's Landing Text Files Complete List of All Small Mammal Trap locations 1995 - 2001 Ship Shoal Island Small Mammal Traps 1997 - 2000 LTER Cross-Site GPS Surveys Hobcaw Barony / Baruch Institue SET/GPS Survey, South Carolina, December 2000 PIE/LTER - Plum Island Sound GPS Network, July 1998 Montandon Marsh at Bucknell University, Lewisburg, Pennsylvania 1997 Bathymetric Survey Procedures, Schematic Diagrams and Instructions The following instructions and procedures are used with reference to the Trimble 4000 SE Global Positioning System receiver, the Trimble NavBeacon XL, the Innerspace Digital Fathometer (Model 448) and the Innerspace DataLog with Guidance Software. GPS-referenced digital bathymetry Schematic Diagram of DGPS/Digital Fathometer connections for bathymetry Instructions for DataLog w/Guidance Software (Innerspace Digital Fathometer) Instructions for Trimble 4000 SE GPS Receiver and Trimble Navbeacon XL Innerspace Digital Fathometer - Model 448 - Field Protocol for Bathymetric Surveys Archived Bathymetric Projects Hog Island Bay DGPS Bathymetric Survey, 1999/2000 Phillip's Creek DGPS Bathymetric Survey 1999/2000 Oyster Harbor Bathymetric Survey (February 2000) Smith Point, Chesapeake Bay, Maryland DGPS Bathymetric Survey, Sept. 2001 Fishermans/Smith/Mockhorn Bay Bathymetric Survey 2000 to 2001 Post-processed Kinematic GPS data: Is It Precise? (1998) Small Mammal GPS/GIS Applications Hog Island Small Mammal Traps on T1, T2, T4, T5 Fowling Point 1996, 1997 Geomorphology Applications Parramore Island, Virginia Parramore Pimple Overwash Fans 1996 Parramore Pimple Overwash Fans 1997 Parramore Island Overwash Fans June 1998 Parramore Island Plugs - August 1998 Parramore Island Overwash Fan 1999 Hog Island, Virginia Broadwater Tower Overwash Fan June 1998 Photos of Broadwater Tower Overwash Fan - March 13, 1999 Broadwater Tower Overwash Fan 1999 Myrtle Island, Virginia A Topographical History of Myrtle Island, 1996 to 2001 Cobb and Fisherman's Islands, Virginia Cobb Island Overwash Fan July 1998 Fisherman's Island - ESNWR and ODU September /1998 Brownsville Farm GPS/GIS Project Long-Term Inundation Project, Christian/Thomas Brinson/Christian/Blum Project Eileen Appolone (ECU) Lisa Ricker's Static GPS Points in Northampton County Eileen Applone (East Carolina University) Static Survey d99124 Brownsville Farm GPS/GIS Project, Christian/Blum/Brinson VCR/LTER Tide Gauges and Water Level Recorders Red Bank Tide Gauge (part of Fowling Pt. survey) Hog Island WLR's 1996 (Brinson) Hog Island Tide Gauge 12/96 High tide surveys at PIE/LTER with Chuck Hopkinson Jim Morris, USC, at Debidue Island, South Carolina Benchmark BRNV in Brownsville, VCR/LTER Miscellaneous Static Sub-Networks Frank Day/Don Young - North Hog 2/99 (Excel File) or a TEXT file Frank Day 120 YR Old Dune Survey (Excel File) or a TEXT file Kindra Loomis GPS Kinematic/Topographic Survey 12/97 Clubhouse Creek at Parramore Island 1997 Phragmites on Southern Hog Island - (dataset only) (9/98) Oyster Harbor 1997 (Hayden & Porter) Southern Hog 1996 (Zieman) VCR/LTER Sediment Elevation Tables - Mockhorn/Wachapreague, August 2001 Aaron Mills Benchmarks - Research Field in Oyster, October 2001 Birds Nests on the Virginia Coast Reserve VCR Birds 1997 (Erwi... Visit https://dataone.org/datasets/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-vcr%2F156%2F20 for complete metadata about this dataset.

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.

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.The Service Locations feature class was created by Southern Geospatial Services (SGS) from a shapefile of customer service locations generated by dataVoice International (DV) as part of their agreement with the Town of Apex (TOA) regarding the development and implemention of an Outage Management System (OMS).Point features in this feature class represent service locations (consumers of TOA electric services) by uniquely identifying the features with the same unique identifier as generated for a given service location in the TOA Customer Information System (CIS). This is also the mechanism by which the features are tied to the OMS. Features are physically located in the GIS based on CIS address in comparison to address information found in Wake County GIS property data (parcel data). Features are tied to the GIS electric connectivity model by identifying the parent feature (Upline Element) as the transformer that feeds a given service location.SGS was provided a shapefile of 17992 features from DV. Error potentially exists in this DV generated data for the service location features in terms of their assigned physical location, phase, and parent element.Regarding the physical location of the features, SGS had no part in physically locating the 17992 features as provided by DV and cannot ascertain the accuracy of the locations of the features without undertaking an analysis designed to verify or correct for error if it exists. SGS constructed the feature class and loaded the shapefile objects into the feature class and thus the features exist in the DV derived location. SGS understands that DV situated the features based on the address as found in the CIS. No features were verified as to the accuracy of their physical location when the data were originally loaded. It is the assumption of SGS that the locations of the vast majority of the service location features as provided by DV are in fact correct.SGS understands that as a general rule that DV situated residential features (individually or grouped) in the center of a parcel. SGS understands that for areas where multiple features may exist in a given parcel (such as commercial properties and mobile home parks) that DV situated features as either grouped in the center of the parcel or situated over buildings, structures, or other features identifiable in air photos. It appears that some features are also grouped in roads or other non addressed locations, likely near areas where they should physically be located, but that these features were not located in a final manner and are either grouped or strung out in a row in the general area of where DV may have expected they should exist.Regarding the parent and phase of the features, the potential for error is due to the "first order approximation" protocol employed by DV for assigning the attributes. With the features located as detailed above, SGS understands that DV identified the transformer closest to the service location (straight line distance) as its parent. Phase was assigned to the service location feature based on the phase of the parent transformer. SGS expects that this protocol correctly assigned parent (and phase) to a significant portion of the features, however this protocol will also obviously incorretly assign parent in many instances.To accurately identify parent for all 17992 service locations would require a significant GIS and field based project. SGS is willing to undertake a project of this magnitude at the discretion of TOA. In the meantime, SGS is maintaining (editing and adding to) this feature class as part of the ongoing GIS maintenance agreement that is in place between TOA and SGS. In lieu of a project designed to quality assess and correct for the data provided by DV, SGS will verify the locations of the features at the request of TOA via comparison of the unique identifier for a service location to the CIS address and Wake County parcel data address as issues arise with the OMS if SGS is directed to focus on select areas for verification by TOA. Additionally, as SGS adds features to this feature class, if error related to the phase and parent of an adjacent feature is uncovered during a maintenance, it will be corrected for as part of that maintenance.With respect to the additon of features moving forward, TOA will provide SGS with an export of CIS records for each SGS maintenance, SGS will tie new accounts to a physical location based on address, SGS will create a feature for the CIS account record in this feature class at the center of a parcel for a residential address or at the center of a parcel or over the correct (or approximately correct) location as determined via air photos or via TOA plans for commercial or other relevant areas, SGS will identify the parent of the service location as the actual transformer that feeds the service location, and SGS will identify the phase of the service address as the phase of it's parent.Service locations with an ObjectID of 1 through 17992 were originally physically located and attributed by DV.Service locations with an ObjectID of 17993 or higher were originally physically located and attributed by SGS.DV originated data are provided the Creation User attribute of DV, however if SGS has edited or verified any aspect of the feature, this attribute will be changed to SGS and a comment related to the edits will be provided in the SGS Edits Comments data field. SGS originated features will be provided the Creation User attribute of SGS. Reference the SGS Edits Comments attribute field Metadata for further information.

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 a compendium of GPS Data collected by Randy Carlson and collaborators on the Virginia Coast Reserve (primarily), Plum Island and North Inlet. A master data table was extracted by Charles L. Carlson during 2013 that includes all the individual point locations recovered from individual surveys. In addition to the data table, the data is also shared as a .zip file containing a static web page with links to particular projects and the underlying data. To use the data, unzip it and use your web browser to open the index.html file. Web page contents include:

     American Oyster Catchers on the Virginia Coast Reserve - 2003


     Lynette Winters - Salicornia - MSL elevation project


     Dynamic Evolution of Barrier Island Morphology and Ecology from 1996-2002 Documented Using High -Resolution GPS-GIS Topographic Mapping Surveys, Virginia Coast Reserve (for GSA, Denver, CO Oct 27-30, 2002


     Broadwater Tower Overwash Fan Photos - Feburary 15, 2002


     Hog Island Bay DGPS Drifter Study 2001


     Ray Dueser/Nancy Moncrief Small Mammal GPS/GIS


     A Topographical History of North Myrtle Island, 1974 to 2001


     Ray Dueser/Nancy Moncrief - Highest Elevations on VCR Barrier Islands


     Myrtle Island Planimetric area, Surface area & Volumetric Calculations 1996-2001


     Myrtle, Ship Shoal GIS/GPS UTM Shape Files and Grids


     Myrtle, Ship Shoal, ESNWR, Shirley, Steelman's Landing Text Files


     Complete List of All Small Mammal Trap locations 1995 - 2001


     Ship Shoal Island Small Mammal Traps 1997 - 2000



 LTER Cross-Site GPS Surveys



     Hobcaw Barony / Baruch Institue SET/GPS Survey, South Carolina, December


     2000 PIE/LTER - Plum Island Sound GPS Network, July 1998 Montandon Marsh at Bucknell University, Lewisburg, Pennsylvania 1997



 Bathymetric Survey Procedures, Schematic Diagrams and Instructions The following instructions and procedures are used with reference to the Trimble 4000 SE Global Positioning System receiver, the Trimble NavBeacon XL, the Innerspace Digital Fathometer (Model 448) and the Innerspace DataLog with Guidance Software. GPS-referenced digital bathymetry Schematic Diagram of DGPS/Digital Fathometer connections for bathymetry
 Instructions for DataLog w/Guidance Software (Innerspace Digital Fathometer)
 Instructions for Trimble 4000 SE GPS Receiver and Trimble Navbeacon XL
 Innerspace Digital Fathometer - Model 448 - Field Protocol for Bathymetric Surveys Archived Bathymetric Projects



     Hog Island Bay DGPS Bathymetric Survey, 1999/2000


     Phillip's Creek DGPS Bathymetric Survey 1999/2000


     Oyster Harbor Bathymetric Survey (February 2000)


     Smith Point, Chesapeake Bay, Maryland DGPS Bathymetric Survey, Sept. 2001


     Fishermans/Smith/Mockhorn Bay Bathymetric Survey 2000 to 2001






     Post-processed Kinematic GPS data: Is It Precise? (1998)


     Small Mammal GPS/GIS Applications


     Hog Island Small Mammal Traps on T1, T2, T4, T5


     Fowling Point 1996, 1997



  Geomorphology Applications 



     Parramore Island, Virginia


     Parramore Pimple Overwash Fans 1996


     Parramore Pimple Overwash Fans 1997


     Parramore Island Overwash Fans June 1998


     Parramore Island Plugs - August 1998


     Parramore Island Overwash Fan 1999


     Hog Island, Virginia


     Broadwater Tower Overwash Fan June 1998


     Photos of Broadwater Tower Overwash Fan - March 13, 1999


     Broadwater Tower Overwash Fan 1999


     Myrtle Island, Virginia


     A Topographical History of Myrtle Island, 1996 to 2001


     Cobb and Fisherman's Islands, Virginia


     Cobb Island Overwash Fan July 1998


     Fisherman's Island - ESNWR and ODU September /1998

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.

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.

Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from a workshop that was conducted on August 17-21, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.

Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.

In the 2000 field season of the BRASS/El Pilar Program, the UCSB Maya Forest GIS collected and processed GPS data for drivable roads in parts of Western Belize and the Peten of Guatemala. Selected for the work were Garmin GPS units accurate from 3-10m (after the US government released Selective Availability SA of error).

[From The Landmap Project: Introduction, "http://www.landmap.ac.uk/background/intro.html"]

 A joint project to provide orthorectified satellite image mosaics of Landsat,
 SPOT and ERS radar data and a high resolution Digital Elevation Model for the
 whole of the UK. These data will be in a form which can easily be merged with
 other data, such as road networks, so that any user can quickly produce a
 precise map of their area of interest.

 Predominately aimed at the UK academic and educational sectors these data and
 software are held online at the Manchester University super computer facility
 where users can either process the data remotely or download it to their local
 network.

 Please follow the links to the left for more information about the project or
 how to obtain data or access to the radar processing system at MIMAS. Please
 also refer to the MIMAS spatial-side website,
 "http://www.mimas.ac.uk/spatial/", for related remote sensing materials.

GIS applications that link natural language text to geographic space using gazetteers are essential for managing spatial data in archived geological records. However, these applications face limitations due to limited gazetteer scope of coverage. Crowdsourced gazetteers often have global coverage, making them excellent reference data for resolving spatial details in records, including converting textual descriptions of locations to GPS features. This can be useful for rectifying missing GPS information in field-captured geological records, especially those obtained from remote and hard-to-reach areas. However, accurately transforming location descriptions in text to GPS coordinates is challenging, and reference data quality can be crucial in minimizing errors and uncertainties. A list of mineral specimen localities referencing geological sampling sites in the Northwest Territories and Nunavut were geoparsed using Geonames and OpenStreetMap geocoders and match rates, positional accuracy, and lexical similarity were quantified to assess performance.

Annual crop harvest yields of corn, soy and wheat from the Main Cropping System Experiment at...

NMFWRI represents the state’s only dedicated capability for supporting the spatial data analysis needs of external stakeholders in the natural resources sector, as well as the GIS/GPS capacity for Highlands University and for most of northern New Mexico. NMFWRI’s GIS work also provides help with maps and other geographic information to New Mexico groups engaged in forest restoration and land management, but who are too small to maintain their own GIS capability. These groups include soil and water conservation districts, municipalities, private groups and individuals, and tribal organizations.

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 Resources in this dataset:Resource Title: Website Pointer to html file. File Name: Web Page, url: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-kbs&identifier=37 Webpage with information and links to data files for download

Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from workshops that were conducted on February 19-21 and October 6-7, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.

Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.