2014 ILHMP Lidar: Madison County, IL

Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.

Bulk download of data files in LAZ format, IL State Plane West NAD83, US survey feet coordinates and in NAVD88 (Geoid12A) elevations in feet.

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

Link to view the point cloud, using the Entwine Point Tile (EPT) format, in the 3D Potree viewer.

Link to the lidar report.

Link to the reports, breaklines, metadata, and spatial metadata.

Ground based survey points are collected to be compared as check points with airborne data points. Measurements are recorded by Quantum Spatial for use in establishment of the LiDAR point set to ground elevations (indexing). Additional ground survey points are made in representative ground cover categories to provide for vertical accuracy assessment of LiDAR data or derivative models.

Airborne LiDAR collection survey is conducted using fixed wing aircraft equipped with a LiDAR scanning system following specifications of the flight plan. Acquisition flights are planned to assure full coverage of the project area in consideration of local surface terrains. Flight plan is accessed by the aircraft navigation system to achieve predetermined flight specifications. The LiDAR sensor is calibrated prior to each mission. GPS and IMU data are collected during LiDAR acquisition to aid in LiDAR swath calibration.

Airborne GPS and IMU data are merged to develop a Single Best Estimate Trajectory for each swath. LiDAR data are calibrated using previous best parameters for this instrument and aircraft. Relative calibration is evaluated using plane-matching analysis and parameter corrections are derived. This is repeated iteratively until residual errors between overlapping swaths, across all project lifts, is reduced to acceptable levels. Data are block adjusted to surveyed control points.

Raw FVA is checked using surveyed ground checkpoints. Swath overage points are identified and tagged within each swath. Overage points may be classed as Overlap (12) or classed to Non-ground (1).

Points in the calibrated swaths are classified using analysis routines and proprietary software. The routines analyze information on all points to establish appropriate Class designations.

Classified LiDAR is inspected on a per tile basis for local classification, manual editing, and peer-based QC checks. The bare earth surface is manually reviewed to ensure correct classification of Class 2 (Ground) points. After the bare-earth surface is finalized, it is used to guide hydro-breaklines generation through heads-up digitization.

All data was manually reviewed and any remaining artifacts removed using controls and tools in TerraScan and TerraModeler. Global Mapper is used as a final check of the bare earth dataset. GeoCue creates the deliverable industry-standard LAS files for both the All Point Cloud Data and the Bare Earth.

All classification tags are stored in the original swath files.

Classifications follow ASPRS guidelines: Non-ground (Class 1), Ground (Class 2), Low Vegetation (Class 3). Medium Vegetation (Class 4), High Vegetation (Class 5), Buildings (Class 6),Noise/Low Points (Class 7), Model Key Point (Class 8) Water (Class 9), Ignored Ground/Breakline proximity (Class 10)

After completion of classification and final QC approval, the FVA, SVAs, and CVA for the project are calculated. Vertical accuracy is determined by comparison of elevation of the ground survey check points to elevations of DEMs derived from the LiDAR Ground points. Differences are calculated to establish a RSME, FVA, CVA and SVA.

Ground (class 2) LiDAR is used to create a bare earth surface model. The surface model is then used to heads-up digitize 2D breaklines of rivers of specific width and lakes of specific size. Breaklines delineate the margin where surface water and ground meet.

Elevation values are assigned to lakes in accordance with ground data where the water and ground surfaces meet. Elevation values are assigned to rivers of adequate width and are created to depict the flow of the drainage; following the change in ground elevation at the edge of the drainage.

All ground (Class 2) LiDAR data inside of the collected inland breaklines are classified to water (Class 9) using TerraScan macro functionality. A buffer of 1 meter is maintained along breaklines of each hydro flattened feature. Points within this one meter buffer are classed from ground (Class 2) to Ignored Ground (Class 10).

The breakline files are then translated to ESRI Shapefile format using ESRI conversion tools.

Ground (Class 2) points in conjunction with the hydro breaklines are used to generate DEM files in ASCII format on a per tile basis with hydro Breaklines in place to delineate surface water and with neighboring tile data available to minimize seams between tiles. The DEM are converted to ESRI Grid format. Resulting DEM are reviewed in ArcMap for adherence, completeness and any anomalies or inconsistencies.

On a per tile basis, data files and Triangulated Integrated Network (TIN) files are generated by processing finalized Ground (class 2) LiDAR points with hydro breaklines delineating surface water through a Geopak macro. Subsequent files are reviewed for adherence and completeness to the data and tile layout used during the creation process.

Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 web mercator (EPSG 3857) and the vertical units were converted to meters (NAVD88 GEOID12A).

The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tile (EPT) that was ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container.

This is the AWS URL being accessed:

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_IL_MadisonCo_2014_LAS_2016/ept.json