Accurately surveyed coordinate location used to maintain survey control during acquistion of various products for Kentucky's Aerial Photography and Elevation Data program. https://ky.box.com/v/kyaped-ground-control

The City of Fort Collins GIS Online Mapping tool (FCMaps) provide current, timely and local geographic information in an easy to use viewer. FCMaps is mobile friendly and will work well on tablets and smartphones as well as a desktop browser.

Here you will find locations of ground control points in NAD83 stateplane coordinates.

Accurately surveyed coordinate location used to maintain survey control during acquistion of various products for Kentucky's Aerial Photography and Elevation Data program.https://ky.box.com/v/kymartian-gcp-phase2

RTK (real time kinematic) ground control points collected for the PSLC King County Delivery Lidar dataset. RTK ground control points are used during the calibration process to help refine the vertical accuracy of the LiDAR data. Data was processed in reference to NAD83 (CORS96), however the horizontal datum for this dataset is defined as NAD83 (HARN) as the difference is generally small and allows for greater ease of use with data in different datums. The vertical datum is NAVD88, Geoid 03, and the data is projected in Washington State Plane North. Units are in US Survey Feet. Quantum Spatial collected the PSLC King County Delivery Lidar data for the Puget Sound LiDAR Consortium between 02/24/16 and 05/25/17.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Global Positioning System Ground Control Points and Field Site Locations from 1993

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 December 1993 and differentially corrected.

This is a web map used for TESTING the collection of Ground Control Points for sUAS imagery.

In May 2021, the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey’s (USGS), Southwest Biological Science Center (SBSC) acquired airborne multispectral high resolution data for the Colorado River in Grand Canyon in Arizona, USA. The imagery data consist of four bands (Band 1 – red, Band 2 – green, Band 3 – blue, and Band 4 – near infrared) with a ground resolution of 20 centimeters (cm). These image data are available to the public as 16-bit GeoTIFF files, which can be read and used by most geographic information system (GIS) and image-processing software. The spatial reference of the image data are in the State Plane (SP) map projection using the central Arizona zone (FIPS 0202) and the North American Datum of 1983 (NAD83) National Adjustment of 2011 (NA2011). The airborne data acquisition was conducted under contract by Fugro Earthdata Inc (Fugro) using two fixed wing aircraft from May 29th to June 4th, 2021 at flight altitudes from approximately 2,440 to 3,350 meters above mean sea level. Fugro produced a corridor-wide mosaic using the best possible flight line images with the least amount of smear, the smallest shadow extent, and clearest, most glint-free water possible. The mosaic delivered by Fugro was then further corrected by GCMRC for smear, shadow extent and water clarity as described in the process steps of this metadata and for previous image acquisitions in Durning et al. (2016) and Davis (2012). 47 ground controls points (GCPs) were used to conduct an independent spatial accuracy assessment by GCMRC. The accuracy calculated from the GCPs is reported at 95% confidence as 0.514 m and a Root Mean Square Error (RMSE) of 0.297 m.

Ground control in Rutherford County. Data will not be updated in the future. Coordinate System: GCS_North_American_1983.Credits: Data created and managed by Rutherford County GIS.Terms of Use/Disclaimer: Rutherford County, its employees, agents and personnel, MAKE NO WARRANTY OF MERCHANTABILITY OR ANY CLAIM OF ACCURACY REGARDING DATA OR LAYERS CONTAINED WITHIN. Any user of this information accepts the same AS IS, WITH ALL FAULTS, and assumes all responsibility for the use or misuse or interpretation of this data and information. Rutherford County makes no representation or warranty as to its accuracy of the placement and location of any map feature or data. Independent verification of all information should be obtained by the USER. These maps are NOT LEGALLY BINDING OR CERTIFIED DOCUMENTS. Rutherford County, its employees, agents and personnel, disclaims, and shall not be held liable for, any and all damage, loss, or liability, whether direct, indirect, or consequential which arises or may arise from the use of any data or information for the use thereof by any person or entity.

Click here to access the data directly from the Illinois State Geospatial Data Clearinghouse. These lidar data are processed Classified LAS 1.4 files, formatted to 2,117 individual 2500 ft x 2500 ft tiles; used to create Reflectance Images, 3D breaklines and hydro-flattened DEMs as necessary. Geographic Extent: Lake county, Illinois covering approximately 466 square miles. Dataset Description: WI Kenosha-Racine Counties and IL 4 County QL1 Lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a derived nominal pulse spacing (NPS) of 1 point every 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011), State Plane, U.S Survey Feet and vertical datum of NAVD88 (GEOID12B), U.S. Survey Feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 2,117 individual 2500 ft x 2500 ft tiles, as tiled Reflectance Imagery, and as tiled bare earth DEMs; all tiled to the same 2500 ft x 2500 ft schema. Ground Conditions: Lidar was collected April-May 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Ayers established a total of 66 ground control points that were used to calibrate the lidar to known ground locations established throughout the WI Kenosha-Racine Counties and IL 4 County QL1 project area. An additional 195 independent accuracy checkpoints, 116 in Bare Earth and Urban landcovers (116 NVA points), 79 in Tall Grass and Brushland/Low Trees categories (79 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. Users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. Acknowledgement of the U.S. Geological Survey would be appreciated for products derived from these data. These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.Link Source: Illinois Geospatial Data Clearinghouse

Photogrammetry Ground Control for Corridors Market Outlook

According to our latest research, the global Photogrammetry Ground Control for Corridors market size reached USD 1.12 billion in 2024, reflecting robust growth driven by the increasing adoption of advanced geospatial technologies in infrastructure development and asset management. The market is projected to expand at a CAGR of 12.3% from 2025 to 2033, with the total market value expected to reach USD 3.18 billion by 2033. This surge is primarily attributed to the rising demand for precision mapping and monitoring solutions across transportation, utilities, and environmental sectors, as organizations prioritize data-driven decision-making and regulatory compliance.

The growth of the Photogrammetry Ground Control for Corridors market is fundamentally driven by the escalating need for accurate spatial data in corridor mapping projects. Infrastructure expansion, particularly in transportation and utilities, necessitates precise ground control points to ensure the reliability of photogrammetric outputs. As governments and private entities invest heavily in smart infrastructure and digital twins, the integration of photogrammetry with ground control solutions is becoming indispensable. This trend is further amplified by the proliferation of UAVs and drones, which have made aerial data collection more accessible and cost-effective, thereby broadening the market’s user base and application scope.

Another significant factor fueling market growth is the evolution of software and analytical tools tailored for corridor applications. Advances in artificial intelligence, machine learning, and cloud computing have transformed how photogrammetric data is processed, stored, and analyzed. Modern software platforms now offer automated feature extraction, real-time data synchronization, and seamless integration with GIS and BIM systems. These capabilities are critical for large-scale corridor projects, where timely and accurate information can mitigate risks, reduce costs, and optimize maintenance schedules. The growing emphasis on interoperability and open data standards is also encouraging more organizations to adopt photogrammetry ground control solutions for corridor management.

The increasing focus on sustainability and environmental monitoring is another key growth driver for the market. Governments and regulatory bodies are imposing stricter guidelines for corridor projects, particularly those intersecting sensitive ecological zones. Photogrammetry ground control solutions play a vital role in environmental impact assessments, habitat monitoring, and compliance reporting. By providing high-resolution, geo-referenced data, these solutions enable stakeholders to make informed decisions that balance development needs with environmental stewardship. This regulatory impetus, combined with rising public awareness about environmental issues, is expected to sustain demand for photogrammetry ground control technologies in the coming years.

Regionally, North America continues to dominate the Photogrammetry Ground Control for Corridors market, accounting for over 38% of global revenue in 2024. This leadership is underpinned by substantial investments in infrastructure modernization, coupled with a mature ecosystem of technology providers and end-users. Europe follows closely, benefiting from large-scale transportation and energy corridor projects across the continent. Meanwhile, the Asia Pacific region is poised for the fastest growth, driven by rapid urbanization, government-led smart city initiatives, and increasing adoption of digital construction methodologies. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as infrastructure development accelerates in these regions.

Component Analysis

The component segment of the Photogrammetry Ground Control for Corridors market is categorized into hardware, software, and services. Hardware remains a foundational element, encompassing GNSS receivers, total stations, drones, and specialized ground control markers. These devices are critical for collecting precise ground coordinates, which serve as reference points for aerial photogrammetry. The hardware segment continues to witness innovation, with manufacturers introducing lightweight, rugged, and high-accuracy equipment tailored for corridor mapping in challenging terrains. The growing adoption of UA

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We developed the vegetation map for Petroglyph National Monument (PETR) using a strategy that combined automated digital image classification and direct analog image interpretation of aerial photography and satellite imagery. Initially, the aerial photography and satellite imagery were processed and entered into a GIS, along with ancillary spatial layers. We developed a working map legend of ecologically-based vegetation map units using the NVCS classification described in Chapter 2 as the foundation. The intent was to develop map units that targeted the plant-association level wherever possible, within the constraints of image quality, information content, and resolution. With the provisional legend and ground-control points provided by the field-plot data (the same data used to develop the vegetation classification), we conducted heads-up screen digitizing of polygons based on image interpretation, and supervised image classifications. The outcome was a vegetation map composed of a suite of map units defined by plant associations and represented by sets of mapped polygons with similar spectral and site characteristics. The PETR vegetation map is at a 1:12,000 scale with 0.25 ha minimum map unit size, and was designed to facilitate ecologically- based natural resources management.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The WHSA vegetation map was developed using a combined strategy of automated digital image classification and direct analog image interpretation of aerial photography and satellite imagery. Initially, the aerial photography and satellite imagery were processed and entered into a GIS along with ancillary spatial layers. A working map legend of ecologically based vegetation map units was developed using the vegetation classification described in the report as the foundation. The intent was to develop map units that targeted the plant-association level wherever possible within the constraints of image quality, information content, and resolution. With the provisional legend and ground-control points provided by the field-plot data (the same data used to develop the vegetation classification), a combination of heads-up screen digitizing of polygons based on image interpretation and supervised image classifications were conducted. The outcome was a vegetation map composed of a suite of map units defined by plant associations and represented by sets of mapped polygons with similar spectral and site characteristics.

The datum of this dataset is as described in GIS dataset AAT_Coastline_Landsat7.

The Landsat 7 image (2002-01-30 Path 126 Row 109) georeferencing was checked using Ground Control Points derived from a survey report prepared by Hydro Tasmania for the Mapping Officer of the AAD, summer 2000/2001.

The Ground Control Point locations were found to be within the image pixel resolution. The georeferencing of the image could not be improved on.

Therefore no transformation, scaling or rotation was applied to the Landsat 7 image.

gis136 (Larsemann Hills - mapping from Landsat 7 data captured January 2000) data were merged with the newly mapped Larsemann Hills aerial photogrammetric plotting dataset gis135.

A report on the project is available at the url given below.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The vegetation map for Pecos National Historical Park was developed using a combined strategy of automated digital-image classification and direct analog-image interpretation of aerial photography and satellite imagery. Initially, the aerial photography and satellite imagery were processed and entered into a GIS along with ancillary spatial layers. A working legend of ecologically based vegetation map units was developed using the vegetation classification described in Chapter 2 as the foundation. The intent was to develop map units that targeted the plant-association level wherever possible within the constraints of image quality, information content, and resolution. With the provisional legend and ground-control points provided by the field-plot data (the same data used to develop the vegetation classification), a series of automated image segmentation and supervised image classifications were conducted, followed by fine-scale map refinement using direct image interpretation and manual editing. The outcome was a vegetation map composed of a suite of map units defined by plant associations and represented by sets of mapped polygons with similar spectral and physical characteristics

The ground control points collected for the New York City LiDAR dataset. Collected between 05/03/17 and 07/26/17.

The Point layer covers the State of Washington with a variety of different types of locations. The great majority of Points, point type 1, Corner Point, are located at the corners, or angle points, of Legal Description and Parcel areas. (See the metadata for Legal Description and Parcel.) Corner Points can represent differing types of locations such as surveyed monuments, locations calculated by survey, locations digitized from various maps like US Geological Survey quadrangles, and locations that serve no other purpose than to stabilize the endpoint of a Boundary or angle point of a Legal Description or Parcel. Points are the only features in the upland Cadastre that have attributes regarding the source and accuracy of the data. The known accuracy of the data varies dramatically from place to place. The attributes also indicate whether there is a known physical object to look for on the ground. The second type of Point, Geodetic Control Point, point type 2, is not currently populated. The third type of Point, Significant Coordinated Location, point type 3, can be used to store any type of point location that has cadastral significance. At present, the only Significant Coordinated Points in Cadastre are those points along the Washington Pacific Ocean coast which were used by the US Minerals Management Service to calculate the boundary of the State at one marine league from the coast.WA Public Land Survey Points MetadataClick to download

This dataset holds the map “Carte du recouvrement ligneux de la réserve de Lamto" published by Gautier, L. in 1990. We georeferenced the scanned paper map using ground control points derived from Google Maps. The dataset contains the scanned map, the ground control points and the raster layer of the georeferenced map.

Accurately surveyed coordinate location used to maintain survey control during acquistion of various products for Kentucky's Aerial Photography and Elevation Data programhttps://ky.box.com/v/kymartian-gcp-phase3

This dataset holds the unpublished map “Carte physionomique des faciès savaniens de Lamto" drawn by de la Souchère; P. and Badarello, L. in 1969. We georeferenced the scanned paper map using ground control points derived from Google Maps. The dataset contains the scanned map, the ground control points and the raster layer of the georeferenced map.