Purpose and Use: This dataset was created to help with locating the GPS Benchmarks in and around San Marcos.Data Source: Data in this GPS Survey Benchmarks layer is created and maintained by the City of San Marcos, Texas, Geographic Information Systems (GIS) department.Contact: Geographic Information Systems (GIS): gisinfo@sanmarcostx.govUpdate Frequency: As needed.Jurisdiction: City of San Marcos.Fields:OBJECTID: System-generated unique identifier for each record within the feature class. SOURCE: Organization that provided the data. NAME: Name associated to the GPS Monument by the number at which it was recorded. INSTALLDATE: Date of installation for the real-world feature represented in the feature class. ELEVATION: Elevation recorded during monument placement, above sea level. XCOORDINATE: The horizontal value in a pair of coordinates: how far along the point is. The X Coordinate is always written first in an ordered pair. YCOORDINATE: The vertical value in a pair of coordinates. How far up or down the point is. The Y Coordinate is always written second in an ordered pair. DISTANCE1: This is the footage distance from the described location in 'Distance1Description' field. DISTANCE2: This is the footage distance from the described location in 'Distance2Description' field. DISTANCE3: This is the footage distance from the described location in 'Distance3Description' field. AZIMUTH: An angular measurement in a spherical coordinate system. The vector from an observer to a point of interest is projected perpendicularly onto a reference plane; the angle between the projected vector and a reference vector on the reference plane is called the azimuth. BEARING: The actual (corrected) compass direction of the forward course of the aircraft. In land navigation, a bearing is the angle between a line connecting two points and a north-south, or meridian. DISTANCE1DESCRIPTION: This is the described location from which the distance is collected as a total of 3 location points. DISTANCE2DESCRIPTION: This is the described location from which the distance is collected as a total of 3 location points. DISTANCE3DESCRIPTION: This is the described location from which the distance is collected as a total of 3 location points. ROUTEDESCRIPTION: General description for where the marker is located in reference to known locations. MARKERCATEGORY: The way in which the marker is placed for GPS such as being placed in an aluminum disk set in concrete which is found physically in the ground. MEDIALINK: URL for a website related to the record. PRODUCTIONNOTES: Technical notes from GIS personnel. DESCRIPTION: Statement illustrating the feature. CREATEDBY: Name of the person logged into the system that GIS automatically stamps as the original creator. CREATEDDATE: Date/time stamp from the moment the GIS record was created. MODIFIEDBY: Name of the person logged into the system that GIS automatically stamps as the feature is modified. MODIFIEDDATE: Date/time stamp from the last moment the GIS record was changed. SHAPE: System-generated geometry type of the feature. Shape.len: System-generated length of the feature. GlobalID: System-generated unique identifier for each record that is required in replicated geodatabases.

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. The data is 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. 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 (Erwin) VCR Birds 1995 and 1996 (Erwin) Mike Erwin/ Rachel Rounds/ Shellpile Points, August 2001 Miscellaneous Post-processed GPS data: Is It Accurate? (1998) Miscellaneous GPS Points (pre-1992) 1992 and 1994 GPS Work by VCR/LTER UTM's OF RESEARCH SITES VCR/LTER GPS NETWORK (gif image)

The Spatial Location Services market is experiencing robust growth, driven by increasing adoption of location-based technologies across diverse sectors. The market, estimated at $15 billion in 2025, is projected to expand significantly over the next decade, fueled by a Compound Annual Growth Rate (CAGR) of 12%. This growth is primarily attributed to several key factors. Firstly, the proliferation of smart devices and the ubiquitous nature of mobile internet connectivity are creating a massive demand for precise and reliable location information. Secondly, the rising need for enhanced navigation, asset tracking, and location-based analytics across various industries, including logistics, transportation, retail, and public safety, is propelling market expansion. The integration of spatial location services with other technologies, such as AI and IoT, further amplifies its utility and market potential. The market is segmented by application (commercial, municipal, military, and others) and by type (indoor and outdoor positioning), with commercial applications currently dominating the market share. Competition is fierce, with both established tech giants and specialized startups vying for market leadership. Key players are continuously innovating to improve the accuracy, speed, and affordability of their services, leading to a dynamic and rapidly evolving market landscape. Looking ahead, several trends will shape the future of the spatial location services market. The increasing demand for real-time location tracking, the development of more sophisticated indoor positioning technologies, and the adoption of 5G networks will all contribute to market growth. However, challenges remain, such as data privacy concerns, the need for accurate and consistent data across various platforms, and the high cost of implementing advanced location technologies in certain sectors. Addressing these challenges will be crucial for unlocking the full potential of the spatial location services market. Regions like North America and Europe currently hold the largest market share, driven by high technology adoption and robust infrastructure. However, rapidly developing economies in Asia-Pacific are poised for significant growth in the coming years, presenting attractive opportunities for market expansion. The market's trajectory suggests a bright outlook for innovative companies able to navigate the technological and regulatory landscape.

GPS Positioning System Market Outlook

As of 2023, the global market size for GPS Positioning System stands at approximately USD 38.1 billion. Projecting forward with a robust CAGR of 15.2%, the market is anticipated to reach USD 103.2 billion by 2032. The primary growth drivers include the increasing adoption of GPS technology in various sectors such as transportation, military & defense, agriculture, and consumer electronics, coupled with advancements in satellite and connectivity technologies.

One of the significant growth factors contributing to the expansion of the GPS positioning system market is the burgeoning demand for location-based services across different industries. With the proliferation of smartphones and other wearable devices, the need for precise and real-time positioning information has surged. Additionally, advancements in GIS (Geographic Information Systems) and IoT (Internet of Things) technologies are enabling more sophisticated applications of GPS in sectors like smart cities and autonomous vehicles. These technological advancements are not only providing a boost to the market but are also paving the way for new use cases and applications.

Another critical growth factor is the increasing reliance on GPS technology for military and defense applications. GPS systems are crucial for navigation, surveillance, and reconnaissance missions. Governments globally are investing heavily in upgrading their defense systems, which includes the integration of advanced GPS technology. This continuous investment is expected to drive the market significantly. Furthermore, the development of anti-jamming and anti-spoofing technologies is enhancing the reliability and security of military GPS applications, thereby further driving market growth.

The agricultural sector is also witnessing a significant transformation due to the integration of GPS technology. Precision farming, which relies on GPS for accurate field mapping, soil sampling, and tractor guidance, is gaining traction globally. This technology helps farmers optimize their resources and improve crop yields, thereby driving the adoption of GPS systems in agriculture. The increasing focus on sustainable farming practices and the need for efficient resource management are expected to further propel the market in this sector.

As the GPS positioning system market continues to evolve, the emergence of GPS Spoofer technology poses both challenges and opportunities. GPS spoofing involves the transmission of false signals to deceive GPS receivers, which can lead to incorrect positioning data. This technology, while potentially harmful, is also driving the development of more robust and secure GPS systems. Companies are investing in advanced anti-spoofing technologies to safeguard their systems against such threats. The growing awareness and need for secure GPS solutions are expected to spur innovation and enhance the reliability of GPS systems across various sectors.

Regionally, the Asia Pacific is expected to witness the highest growth rate due to the rapid industrialization and urbanization in countries like China and India. The growing adoption of GPS technology in various sectors such as transportation, construction, and consumer electronics is fueling the market growth in this region. Moreover, government initiatives to develop smart cities and improve public safety are expected to provide a significant boost to the GPS positioning system market in the Asia Pacific.

Component Analysis

The GPS positioning system market by component is divided into hardware, software, and services. Hardware components, including GPS receivers, antennas, and modules, form the backbone of GPS systems. With the increasing demand for accurate and reliable location data, there is a growing emphasis on developing advanced hardware that can provide better precision and durability. The development of multi-frequency and multi-constellation receivers is one such advancement that is enhancing the performance of GPS systems in various applications.

Software components play a crucial role in processing and analyzing the data gathered by GPS hardware. This includes mapping and navigation software, tracking and fleet management applications, and GIS software. The increasing complexity of applications and the need for real-time data processing are driving the demand for advanced GPS software solutions. The integration of AI and machine learning algorithms in GPS software is ena

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.

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

Geographic Information System (GIS) Market Outlook

The global Geographic Information System (GIS) market size was valued at approximately USD 8.1 billion in 2023 and is projected to reach around USD 16.3 billion by 2032, growing at a CAGR of 8.2% during the forecast period. One of the key growth factors driving this market is the increasing adoption of GIS technology across various industries such as agriculture, construction, and transportation, which is enhancing operational efficiencies and enabling better decision-making capabilities.

Several factors are contributing to the robust growth of the GIS market. Firstly, the increasing need for spatial data in urban planning, infrastructure development, and natural resource management is accelerating the demand for GIS solutions. For instance, governments and municipalities globally are increasingly relying on GIS for planning and managing urban sprawl, transportation systems, and utility networks. This growing reliance on spatial data for efficient resource allocation and policy-making is significantly propelling the GIS market.

Secondly, the advent of advanced technologies like the Internet of Things (IoT), Artificial Intelligence (AI), and machine learning is enhancing the capabilities of GIS systems. The integration of these technologies with GIS allows for real-time data analysis and predictive analytics, making GIS solutions more powerful and valuable. For example, AI-powered GIS can predict traffic patterns and help in effective city planning, while IoT-enabled GIS can monitor and manage utilities like water and electricity in real time, thus driving market growth.

Lastly, the rising focus on disaster management and environmental monitoring is further boosting the GIS market. Natural disasters like floods, hurricanes, and earthquakes necessitate the need for accurate and real-time spatial data to facilitate timely response and mitigation efforts. GIS technology plays a crucial role in disaster risk assessment, emergency response, and recovery planning, thereby increasing its adoption in disaster management agencies. Moreover, environmental monitoring for issues like deforestation, pollution, and climate change is becoming increasingly vital, and GIS is instrumental in tracking and addressing these challenges.

Regionally, the North American market is expected to hold a significant share due to the widespread adoption of advanced technologies and substantial investments in infrastructure development. Asia Pacific is anticipated to witness the fastest growth, driven by rapid urbanization, industrialization, and supportive government initiatives for smart city projects. Additionally, Europe is expected to show steady growth due to stringent regulations on environmental management and urban planning.

Component Analysis

The GIS market by component is segmented into hardware, software, and services. The hardware segment includes devices like GPS, imaging sensors, and other data capture devices. These tools are critical for collecting accurate spatial data, which forms the backbone of GIS solutions. The demand for advanced hardware components is rising, as organizations seek high-precision instruments for data collection. The advent of technologies such as LiDAR and drones has further enhanced the capabilities of GIS hardware, making data collection faster and more accurate.

In the software segment, GIS platforms and applications are used to store, analyze, and visualize spatial data. GIS software has seen significant advancements, with features like 3D mapping, real-time data integration, and cloud-based collaboration becoming increasingly prevalent. Companies are investing heavily in upgrading their GIS software to leverage these advanced features, thereby driving the growth of the software segment. Open-source GIS software is also gaining traction, providing cost-effective solutions for small and medium enterprises.

The services segment encompasses various professional services such as consulting, integration, maintenance, and training. As GIS solutions become more complex and sophisticated, the need for specialized services to implement and manage these systems is growing. Consulting services assist organizations in selecting the right GIS solutions and integrating them with existing systems. Maintenance and support services ensure that GIS systems operate efficiently and remain up-to-date with the latest technological advancements. Training services are also crucial, as they help users maximize the potential of GIS technologies.

The annual Asia Pacific Regional Geodetic Project (APRGP) GPS campaign is an important activity of the Geodetic Technologies and Applications Working Group (WG) of the Permanent Committee on GIS …Show full descriptionThe annual Asia Pacific Regional Geodetic Project (APRGP) GPS campaign is an important activity of the Geodetic Technologies and Applications Working Group (WG) of the Permanent Committee on GIS Infrastructure for Asia and the Pacific Region (PCGIAP). This document overviews the data analysis of the APRGP GPS campaign undertaken in 2010. The GPS data was processed using version 5.0 of the Bernese GPS Software in a regional network together with selected IGS (International GNSS Service) sites. The GPS solution was constrained to the ITRF2005 reference frame through adopting IGS05 coordinates on selected IGS reference sites and using the final IGS earth orientation parameters and satellite ephemerides products.

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

We combined a detailed field study of canopy gap fraction with spectral mixture analysis of Landsat ETM+ satellite imagery to assess landscape and regional dynamics of canopy damage following selective logging in an eastern Amazon forest. Our field studies encompassed measurements of ground damage and canopy gap fractions along multitemporal sequences of post-harvest regrowth of 0.5-3.5 yr. Areas used to stage harvested logs prior to transport, called log decks, had the largest forest gap fractions, but their contribution to the landscape-level gap dynamics was minor. Tree falls were spatially the most extensive form of canopy damage following selective logging, but the canopy gap fractions resulting from them were small. Reduced-impact logging resulted in consistently less damage to the forest canopy than did conventional logging practices. This was true at the level of individual landscape strata such as roads, skids, and tree falls as well as at the area-integrated scale. A spectral mixture model was employed that utilizes bundles of field and image spectral reflectance measurements with a Monte Carlo analysis to estimate high spatial resolution (subpixel) cover of forest canopies, exposed nonphotosynthetic vegetation, and soils in the Landsat imagery. The method proved highly useful for quantifying forest canopy cover fraction in the log decks, roads, skids, tree fall, and intact forest areas, and it tracked caopy damage up to 3.5 yr post-harvest. Forest canopy cover fractions derived from satellite observations were highly and inversely correlated with field- and satellite-based measurements. A 450-km^2 study of gap fraction showed that approximately one-half of the canopy opening caused by logging is closed within one year of regrowth following timber harvests. This is the first regional-scale study utilizing field measurements, satellite observations, and models to quantify forest canopy damage and recovery following selective logging in the Amazon.

Dredge Positioning GPS Market Outlook

According to our latest research, the global Dredge Positioning GPS market size reached USD 945.2 million in 2024, reflecting robust demand across diverse marine and offshore sectors. The market is poised to expand at a CAGR of 7.8% from 2025 to 2033, reaching a projected value of USD 1,963.5 million by 2033. This impressive growth is propelled by the increasing need for precision in marine construction and dredging activities, as well as the rising adoption of advanced GPS technologies for enhanced operational efficiency and regulatory compliance.

The growth trajectory of the Dredge Positioning GPS market is underpinned by the accelerating pace of global infrastructure development, particularly in coastal and riverine regions. Governments and private entities are investing heavily in port expansions, harbor maintenance, and offshore construction projects to accommodate the surge in global trade and maritime transport. These initiatives necessitate highly accurate positioning systems to ensure the safety and efficiency of dredging operations, driving the adoption of advanced GPS solutions. Furthermore, the integration of real-time monitoring and automation capabilities in dredge positioning systems is significantly improving project outcomes, reducing operational costs, and minimizing environmental impacts, which further fuels market expansion.

Another critical factor contributing to market growth is the increasing focus on environmental sustainability and regulatory compliance. Stringent regulations related to marine and coastal ecosystem protection are compelling dredging companies and port authorities to adopt precise and reliable GPS-based positioning systems. These systems enable operators to monitor dredging activities in real-time, ensuring that operations are confined to designated areas and that sediment removal is conducted within permissible limits. This not only helps in maintaining ecological balance but also mitigates the risk of regulatory penalties and project delays, thereby enhancing the value proposition of dredge positioning GPS solutions.

Technological advancements are also playing a pivotal role in shaping the Dredge Positioning GPS market. The evolution from basic GPS to more sophisticated technologies such as Differential GPS (DGPS), Real-Time Kinematic (RTK) GPS, and Global Navigation Satellite System (GNSS) has revolutionized the accuracy and reliability of positioning solutions. These innovations are enabling dredging and marine construction companies to achieve centimeter-level precision, optimize resource utilization, and improve project timelines. The increasing integration of GPS with other digital technologies, such as Geographic Information Systems (GIS), remote sensing, and cloud-based analytics, is opening up new avenues for operational excellence and data-driven decision-making in the marine sector.

From a regional perspective, Asia Pacific continues to be the largest and fastest-growing market for dredge positioning GPS solutions, supported by massive infrastructure investments, rapid urbanization, and expanding seaborne trade. North America and Europe follow closely, driven by ongoing modernization of ports and stringent environmental regulations. Meanwhile, Latin America and the Middle East & Africa are emerging as promising markets, owing to their strategic focus on port development and offshore energy projects. The competitive landscape remains dynamic, with global and regional players vying for market share through technological innovation, strategic partnerships, and customer-centric solutions.

Component Analysis

The component segment of the Dredge Positioning GPS market comprises hardware, software, and services, each playing a vital role in the overall value chain. Hardware forms the backbone of the market, encompassing GPS receivers, antennas, control units, and related accessories. The demand for high-precision and ruggedized hardware components is intensifying, as operators

A culvert is a pipe used to enclose a flowing body of water and typically used to allow water to pass underneath a road, railway, or embankment. Last update date shows the last time each assest was manipulated in any way. Install update source is how the install date was added into GIS. Last editor should show who the last person to manipulate the assest was. Install date gives an estimation of when each asset was actually installed in the ground, not put into GIS. Update source is the accuracy of each asset in our GIS system, GPS-SURVEY-GRADE is the most accurate form of data we have available

Alistair Grinbergs (Heritage Officer) was on Heard island in January and February 2000) as part of the 2000 ANARE, to make an assessment of the heritage value of the old ANARE station ruins. This GPS survey data of the corners of buildings and other artefacts will form part of the record of the station site, together with drawings and other measurements.

The assessment will be used to formulate a conservation management plan for the site.

Interagency Wildland Fire Perimeter History (IFPH) Overview This national fire history perimeter data layer of conglomerated agency perimeters was developed in support of the WFDSS application and wildfire decision support. The layer encompasses the fire perimeter datasets of the USDA Forest Service, US Department of Interior Bureau of Land Management, Bureau of Indian Affairs, Fish and Wildlife Service, and National Park Service, the Alaska Interagency Fire Center, CalFire, and WFIGS History. Perimeters are included thru the 2024 fire season. Requirements for fire perimeter inclusion, such as minimum acreage requirements, are set by the contributing agencies. WFIGS, NPS and CALFIRE data now include Prescribed Burns. Data InputSeveral data sources were used in the development of this layer, links are provided where possible below. In addition, many agencies are now using WFIGS as their authoritative source, beginning in mid-2020.Alaska fire history (WFIGS pull for updates began 2022)USDA FS Regional Fire History Data (WFIGS pull for updates began 2024)BLM Fire Planning and Fuels (WFIGS pull for updates began 2020)National Park Service - Includes Prescribed Burns (WFIGS pull for updates began 2020)Fish and Wildlife Service (WFIGS pull for updates began 2024)Bureau of Indian Affairs (Incomplete, 2017-2018 from BIA, WFIGS pull for updates began 2020)CalFire FRAS - Includes Prescribed Burns (CALFIRE only source, non-fed fires)WFIGS - updates included since mid-2020, unless otherwise noted Data LimitationsFire perimeter data are often collected at the local level, and fire management agencies have differing guidelines for submitting fire perimeter data. Often data are collected by agencies only once annually. If you do not see your fire perimeters in this layer, they were not present in the sources used to create the layer at the time the data were submitted. A companion service for perimeters entered into the WFDSS application is also available, if a perimeter is found in the WFDSS service that is missing in this Agency Authoritative service or a perimeter is missing in both services, please contact the appropriate agency Fire GIS Contact listed in the table below.Attributes This dataset implements the NWCG Wildland Fire Perimeters (polygon) data standard.https://www.nwcg.gov/sites/default/files/stds/WildlandFirePerimeters_definition.pdfIRWINID - Primary key for linking to the IRWIN Incident dataset. The origin of this GUID is the wildland fire locations point data layer maintained by IrWIN. (This unique identifier may NOT replace the GeometryID core attribute) FORID - Unique identifier assigned to each incident record in the Fire Occurence Data Records system. (This unique identifier may NOT replace the GeometryID core attribute) INCIDENT - The name assigned to an incident; assigned by responsible land management unit. (IRWIN required). Officially recorded name. FIRE_YEAR (Alias) - Calendar year in which the fire started. Example: 2013. Value is of type integer (FIRE_YEAR_INT). AGENCY - Agency assigned for this fire - should be based on jurisdiction at origin. SOURCE - System/agency source of record from which the perimeter came. DATE_CUR - The last edit, update, or other valid date of this GIS Record. Example: mm/dd/yyyy. MAP_METHOD - Controlled vocabulary to define how the geospatial feature was derived. Map method may help define data quality.GPS-Driven; GPS-Flight; GPS-Walked; GPS-Walked/Driven; GPS-Unknown Travel Method; Hand Sketch; Digitized-Image; Digitized-Topo; Digitized-Other; Image Interpretation; Infrared Image; Modeled; Mixed Methods; Remote Sensing Derived; Survey/GCDB/Cadastral; Vector; Other GIS_ACRES - GIS calculated acres within the fire perimeter. Not adjusted for unburned areas within the fire perimeter. Total should include 1 decimal place. (ArcGIS: Precision=10; Scale=1). Example: 23.9 UNQE_FIRE_ - Unique fire identifier is the Year-Unit Identifier-Local Incident Identifier (yyyy-SSXXX-xxxxxx). SS = State Code or International Code, XXX or XXXX = A code assigned to an organizational unit, xxxxx = Alphanumeric with hyphens or periods. The unit identifier portion corresponds to the POINT OF ORIGIN RESPONSIBLE AGENCY UNIT IDENTIFIER (POOResonsibleUnit) from the responsible unit’s corresponding fire report. Example: 2013-CORMP-000001 LOCAL_NUM - Local incident identifier (dispatch number). A number or code that uniquely identifies an incident for a particular local fire management organization within a particular calendar year. Field is string to allow for leading zeros when the local incident identifier is less than 6 characters. (IRWIN required). Example: 123456. UNIT_ID - NWCG Unit Identifier of landowner/jurisdictional agency unit at the point of origin of a fire. (NFIRS ID should be used only when no NWCG Unit Identifier exists). Example: CORMP COMMENTS - Additional information describing the feature. Free Text.FEATURE_CA - Type of wildland fire polygon: Wildfire (represents final fire perimeter or last daily fire perimeter available) or Prescribed Fire or Unknown GEO_ID - Primary key for linking geospatial objects with other database systems. Required for every feature. This field may be renamed for each standard to fit the feature. Globally Unique Identifier (GUID). Cross-Walk from sources (GeoID) and other processing notesAK: GEOID = OBJECT ID of provided file geodatabase (4,781 Records thru 2021), other federal sources for AK data removed. No RX data included.CA: GEOID = OBJECT ID of downloaded file geodatabase (8,480 Records, federal fires removed, includes RX. Significant cleanup occurred between 2023 and 2024 data pulls resulting in fewer perimeters).FWS: GEOID = OBJECTID of service download combined history 2005-2021 (2,959 Records), includes RX.BIA: GEOID = "FireID" 2017/2018 data (382 records). No RX data included.NPS: GEOID = EVENT ID 15,237 records, includes RX. In 2024/2023 dataset was reduced by combining singlepart to multpart based on valid Irwin, FORID or Unique Fire IDs. RX data included.BLM: GEOID = GUID from BLM FPER (23,730 features). No RX data included.USFS: GEOID=GLOBALID from EDW records (48,569 features), includes RXWFIGS: GEOID=polySourceGlobalID (9724 records added or replaced agency record since mid-2020)Attempts to repair Unique Fire ID not made. Attempts to repair dates not made. Verified all IrWIN IDs and FODRIDs present via joins and cross checks to the respective dataset. Stripped leading and trailing spaces, fixed empty values to

Sewer network structures such as treatment plants and pump stations. Last update date shows the last time each assest was manipulated in any way. Install update source is how the install date was added into GIS. Last editor should show who the last person to manipulate the assest was. Install date gives an estimation of when each asset was actually installed in the ground, not put into GIS. Update source is the accuracy of each asset in our GIS system, GPS-SURVEY-GRADE is the most accurate form of data we have available.

Outdoor GPS Device Market Outlook

According to our latest research, the global Outdoor GPS Device market size reached USD 2.7 billion in 2024, reflecting robust demand across consumer, commercial, and government sectors. The market is projected to grow at a CAGR of 8.1% from 2025 to 2033, reaching an estimated USD 5.3 billion by 2033. This growth is primarily driven by the increasing adoption of location-based services, advancements in satellite technology, and the rising popularity of outdoor recreational activities worldwide. As per our latest research, the Outdoor GPS Device market is experiencing a significant transformation, fueled by technological innovations and expanding applications in diverse industries.

One of the primary growth factors for the Outdoor GPS Device market is the surge in outdoor recreational activities such as hiking, trekking, cycling, and boating. The global trend towards healthier lifestyles and adventure tourism has stimulated consumer demand for reliable navigation solutions. Additionally, advancements in display technology, battery life, and rugged device construction have made outdoor GPS devices more user-friendly and durable, further increasing their appeal to outdoor enthusiasts. The integration of GPS technology with other sensors and wireless connectivity options has also enhanced the functionality and accuracy of these devices, making them indispensable tools for both amateurs and professionals engaged in outdoor pursuits.

Another key driver for the Outdoor GPS Device market is the growing need for asset tracking and fleet management in commercial and government sectors. Industries such as logistics, transportation, and military & defense are increasingly leveraging GPS devices to monitor vehicle movement, optimize routes, and ensure personnel safety. The proliferation of GPS-enabled trackers and wearable devices has also expanded the marketÂ’s footprint in areas such as wildlife conservation, search and rescue operations, and law enforcement. The ability of modern GPS devices to provide real-time data, geofencing, and integration with Geographic Information Systems (GIS) has significantly enhanced operational efficiency and situational awareness across these sectors.

Technological advancements in satellite navigation systems have played a pivotal role in driving market growth. The introduction of multi-constellation support, including GPS, GLONASS, Galileo, and BeiDou, has improved the accuracy, reliability, and coverage of outdoor GPS devices. This has enabled manufacturers to cater to a wider range of applications and geographic regions. Moreover, the advent of compact and lightweight form factors, coupled with the integration of smart features such as Bluetooth, Wi-Fi, and mobile app connectivity, has made these devices more versatile and appealing to a broader user base. The ongoing evolution in IoT and wearable technologies is expected to further propel market expansion over the forecast period.

From a regional perspective, North America remains the dominant market for Outdoor GPS Devices, supported by a well-established outdoor recreation culture, high disposable incomes, and significant investments in defense and security. Europe follows closely, driven by strong demand in adventure sports and automotive navigation. The Asia Pacific region is witnessing the fastest growth, fueled by rising consumer awareness, expanding tourism, and increasing government initiatives for disaster management and public safety. Latin America and the Middle East & Africa are also emerging as promising markets, although their share remains comparatively smaller due to infrastructural and economic constraints.

Handheld GPS devices have become indispensable tools for outdoor enthusiasts, offering a blend of portability and functionality that caters to a wide range of activities. These devices provide users with real-time navigation, route planning, and geocaching capabilities, making them ideal companions for hiking, trekking, and other adventure sports. The rugged design and user-friendly interface of Handheld GPS units ensure that they can withstand the challenges of outdoor environments while providing accurate and reliable data. As technology advances, features such as high-resolution displays, long battery life, and wireless connectivity are becoming standard, further e

Very little information is known about the distribution and abundance of snow petrels at the regional scale. This dataset contains locations of bird nests, mostly snow petrels, mapped in the Windmill Islands during the 2002-2003 season. Location of nests were recorded with handheld GPS receivers connected to a pocket PC and stored as a shapefile using Arcpad (ESRI software). Descriptive information relating to each bird nest was recorded and a detailed description of data fields is provided in the detailed description of the shapefiles.

Two observers conducted the surveys using distinct methodologies, Frederique Olivier (FO) and Drew Lee (DL). Three separate nest location files (ArcView point shapefiles) were produced and correspond to each of the survey methodologies used. Methodology 1 was the use of 200*200 m grid squares in which exhaustive searches were conducted (FO). Methodology 2 was the use of 2 transects within each the 200*200 m grid squares; methodology 3 was the use of 4 small quadrats (ca 25 m) located within the 200*200m grid squares (DL). Nests mapped in a non-systematic manner (not following a specific methodology) are clearly identified within each dataset. Datasets were kept separate due to the uncertainties caused by GPS errors (the same nest may have different locations due to GPS error).

Three separate shapefiles describe survey methodologies:
- one polygon shapefile locates the 200*200 grid sites searched systematically (FO)
- one polygon shapefile locates the small quadrats (DL)
- one line shapefile locates line transects (DL)

Spatial characteristics, date of survey, search effort, number of nests found and other parameters are recorded for the grid sites, transect and quadrats.

See the word document in the file download for more information.

This work has been completed as part of ASAC project 1219 (ASAC_1219).

The fields in this dataset are:

Species
Activity
Type
Entrances
Slope
Remnants
Latitude
Longitude
Date
Snow
Eggchick
Cavitysize
Cavitydepth
Distnn
Substrate
Comments
SitedotID
Aspect
Firstfred
Systematic/Edge/Incidental
RecordCode

The full dataset, including a word document providing further information about the dataset, is publicly available for download from the provided URL.

Also available for download from another URL is polygon data representing flying bird nesting areas. The polygon data was derived from the flying bird nest locations by the Australian Antarctic Data Centre for displaying on maps.

A point in which the main is tapped for the purposes of customer service.. Last update date shows the last time each assest was manipulated in any way. Install update source is how the install date was added into GIS. Last editor should show who the last person to manipulate the assest was. Install date gives an estimation of when each asset was actually installed in the ground, not put into GIS. Update source is the accuracy of each asset in our GIS system, GPS-SURVEY-GRADE is the most accurate form of data we have available

Water network valves that do not have a pressure controlling mechanism. Last update date shows the last time each assest was manipulated in any way. Install update source is how the install date was added into GIS. Last editor should show who the last person to manipulate the assest was. Install date gives an estimation of when each asset was actually installed in the ground, not put into GIS. Update source is the accuracy of each asset in our GIS system, GPS-SURVEY-GRADE is the most accurate form of data we have available

Separated and combined sewer gravity mains. Last update date shows the last time each assest was manipulated in any way. Install update source is how the install date was added into GIS. Last editor should show who the last person to manipulate the assest was. Install date gives an estimation of when each asset was actually installed in the ground, not put into GIS. Update source is the accuracy of each asset in our GIS system, GPS-SURVEY-GRADE is the most accurate form of data we have available