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.

For downloading additional formats including AutoCAD, File geodatabase, please click here

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.

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

This series of web pages presents site information for 63 Ground Control Points (GCP's) measured near Barrow, Alaska, during the summer of 2001 using Differential GPS. The GCP's were measured on the corners of buildings, ends of snowfences, base of telephone poles, and other features visible on small- to large-scale imagery. They are concentrated generally within 2 km of the Chukchi coast (coinciding with extent of the year 2000 air photos). The GCP's will help researchers and other scientists working in the area to establish precise geographic or UTM coordinates for field sites, and to assist with georectification of aerial photography and satellite imagery.

 The GCP's were measured as part of an ongoing research project, Alaska North
 Slope Climate Impact Assessment (ANSCIA), which is funded by the National
 Science Foundation's program on Human Dimensions of the Arctic System. This
 database is being made publicly available as part of our objectives for data
 sharing and outreach to both the scientific community and the public at large.

 [Summary provided by University of Colorado.]

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.

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

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

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 …Show full descriptionThe 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.

Images were acquired from approximately 80 m above ground surface on the 12th of February 2021, using a Phantom 4 Advanced drone with an FC330 camera. The images are in file input_images.zip.

The mission planning software DJI GS Pro was used to automatically acquire images at suitable locations across the survey area to enable the reconstruction of a three dimensional model.

Images 422 to 531 were imported to the photogrammetry software Pix4D (version 4.6.4). The created Pix4D project is Station12Feb2021_limited.p4d, and the processing report is Station12Feb2021_limited_report.pdf.

Four three-dimensional ground control points were used to improve the positioning of the model. No two dimensional control points or check points were used.

These points were in ITRF 2000@2000 datum (UTM Zone 49S), with co-ordinates as per the table below:

Label, Type, X(m), Y(m), Z(m), Accuracy Horz(m), Accuracy Vert(M) BM05, 3D GCP, 478814.460, 2648561.910, 38.558, 0.050, 0.100 EW-05, 3D GCP, 478635.540, 2648617.260, 27.260, 0.050, 0.100 FuelFlange, 3D GCP, 478970.810, 2648642.250, 21.920, 0.050, 0.100 MeltbellFootingA, 3D GCP, 478680.270, 2648466.547, 35.850, 0.050, 0.100

BM-05 is a survey benchmark near the Casey flagpoles, see https://data.aad.gov.au/aadc/survey/display_station.cfm?station_id=600 EW-05 is a 44 gallon drum used as a groundwater extraction well by the remediation project Fuel Flange is the last fuel flange located on the elevated fuel line prior to the fuel line “dipping” under the wharf road. Meltbell footing A is a concrete footing for the Casey melt bell (surveyed in 2019/20).

No point cloud processing (e.g. removal of errant points) was done prior to orthomosaic and model generation.

The resulting orthomosaic (Station12Feb2021_limited_transparent_mosaic_group1.tif) has an average ground sampling distance of 2.9 cm, and covers an area of approximately 15.8 hectares, encompassing the majority of buildings along “main street” at Casey. The quarry, biopiles, helipad, and upper fuel farm area are all visible.

Contour lines were generated in Pix4D at 0.5 m intervals.

Due to the limited number of ground control points, and their imprecision, the estimated residual mean squared error across three dimensions is 0.17 m (17cm), and will be worse on the periphery of the imaged area.

The orthomosaic was exported from ArcGIS to a Google Earth file (CaseyStation Orthomosaic Feb 12 2021.kmz) using XTools Pro Version 17.2.

A map was created in ArcGIS showing the orthomosaic with a background showing contour lines obtained from the AADC data product windmill_is.mdb.

The map was exported in .jpg and .pdf format at 250 dpi. Casey Station Orthomosaic Feb 12 2021.pdf Casey Station Orthomosaic Feb 12 2021.jpg

The Pix4D folder structure has been copied across (with the exception of the temp folder) and is included in this dataset.

Pix4D Folder Structure:

Station12Feb2021_limited.zip 1_intitial • Contains Pix4D files created during the project • Contains the final processing report (as .pdf) 2_densification • Contains the 3D mesh as an .obj file • Contains the point cloud as a .LAS and .PLY file • Contains the point cloud as a .p4b file 3_dsm_ortho • Contains the digital surface model as a georeferenced .tif file • Contains the orthomosaic as a georeferenced .tif file

A text readable log file from the project processing is in the file Station12Feb2021_limited.log

Ground control points are necessary for achieving the required accuracy of the orthophotography. Information included in this data include the control points' x & y location, description, and elevation.This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Imagery/MD_ImageryAcquisitionFlightInformation/FeatureServer/0

This dataset holds the process chain to produce a orthomosaic from 220 aerial photographs acquired by IGN in 1963 under the mission AOF 566P5000. The dataset covers the Lamto reserve. We orthorectified the scanned images using ground control points from Google Maps and a structure from motion software (SfM). This dataset contains the scanned aerial photographes, the ground control points and the finale orthomosaic with a 17 cm ground resolution.

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.

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 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 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 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.

This dataset holds the process chain to produce a orthomosaic from oblique aerial photographs acquired by Gautier using a cessna airplane and a handheld 35 mm camera on April 11, 1988 . We digitized the original colour diapos and created a orthomosaic using ground control points from Google Maps and a structure from motion software (SfM). The datasets contains the scanned diapos, the ground control points and the finale orthomosaic with a 20 cm ground resolution.

All ground control monuments utilized for the PSLC King County Lidar dataset. Ground control monuments are used to provide redundant control within 13 nautical miles of mission areas for Lidar flights, as well as the collection of ground control points using real-time kinematic (RTK) and post-precessed kinematic (PPK) survey techniques. 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 LiDAR data for the Puget Sound LiDAR Consortium between 02/24/16 and 05/25/17.

A digital elevation Model (DEM) of the Bunger Hills with a five metre grid interval,and held in UTM Zone 47, WGS 84 horizontal coordinates and EGM 96 elevation datum. Heights are referenced to Ellipsoid EGM96. The DEM was produced by SPOT image and conforms to standard SPOT image specifications.

See PDF document SPOT DEM Product Description Version 1.2 January 1, 2005. SPOT DEM accuracies.

The DEM accuracy specifications below are valid for a full square degree and solely apply to DEMs generated from HRS imagery and not to DEMs derived from external sources. The SPOT DEM absolute horizontal and vertical accuracies depend on the dimensions of the area of interest or on the availability of Reference3D on this area:

Absolute planimetric accuracy: Circular error with respect to WGS84 (confidence level 90%) 15m to 30m

Absolute elevation accuracy: Linear error with respect to EGM96 (confidence level 90%) flat or rolling terrain (slope - 20%) 10m to 20m

SPOT DEM products may have variable planimetric and elevation performances: Small areas: One to a few HRS stereopairs HRS intrinsic accuracies 30m @90% planimetric accuracies 20m@90% elevation accuracy

The absolute planimetric accuracy of 15m can be achieved if excellent-quality ground control points (better than 10m) are used. NOTE: No ground control points were used in the DEM.

DEM layer corrections SPOT DEM production systematically includes: Automatic filtering to eliminate correlation artifacts Flattening of non-running water bodies (rivers etc excluded) exceeding 0.5km2

In the spring of 2008, the City of Baltimore expressed an interest to upgrade the City GIS Database with mapping quality airborne LiDAR data. The City of Baltimore currently had in place a contract for mapping GIS/services with the KCI/Sanborn Joint Venture Partnership, L.L.C. under Project 1051. The City of Baltimore issued Change Order #1 on on Project 1051 for the LiDAR acquisition and processing. KCI/Sanborn acquired the LiDAR data over the City of Baltimore (approximately 90 square miles) during one long mission on 15 April 2008. A Leica Airborne Airborne Laser Scanner Model ALS 50 was used in a Sanborn Aero Commander 500B (Registration N6172X) to acquire the data. The airborne mission was flown 15 April 2008. The LiDAR system acquired calibration data the same day by conducting flight passes over a known ground surface before and the LiDAR mission. During final data processing, the calibration parameters were used in the final post-processing software. The acquired LiDAR data were processed to obtain the following deliverables: -DEMs of first and last returns and bare earth (all point data) -LAS format data in a tile grid provided by the City/KCI -Gridded DEM in ESRI format (Arc Binary Grid -Arc/INFO Lattice ) produced from Bare Earth Mass Points in 1-meter resolution (Grid size) -Associated FGDC compliant metadata in XML format The project specifications called for the LiDAR survey to comply with industry standard FEMA guidelines for accuracy. The FEMA requirement for this type of mapping calls for vertical errors not to exceed 0.185 meter (0.61 feet) RMSE when compared with ground check points over open flat terrain and 0.370 meter (1.22 feet) for other types of terrain. This accuracy requirement was comfortably met with comparing LiDAR derived elevations against 50 ground control check points provided by KCI Technologies. These control points were photo control points used as part of the photogrammetric mapping project and independent LiDAR checkpoints surveyed by KCI and Mercado after the data was delivered. The RMSE error observed was 0.058 meter (0.189 feet) over all 50 check points.