Ayres Associates provided Pepin County with topographic mapping services in 2013. The LiDAR data was collected on May 8, 2013 using a Riegl sensor mounted in a fixed-wing aircraft. LiDAR data was collected to support FEMA accuracy standards and to support generation of 2-foot contours. The LiDAR data was delivered according to the County's standard section tile schematic. The LiDAR data was calibrated using information collected at the time of flight from GPS base stations on the ground and airborne GPS/IMU in the aircraft. The calibrated LiDAR data was processed to a classified point cloud, bare earth DTM, DEM, contours, breaklines, and intensity images. Waveform data was collected with the Riegl sensor over the project area. The total project area is 250 square miles.
The 2013 Point Cloud files contain the total LiDAR point cloud. This dataset constitutes all classifications of lidar points.
Point Classes are as follows: 1 = Processed, Unclassified, 2 = Bare Earth Ground, 3 = Low vegetation, 4 = Medium vegetation, 5 = High vegetation, 6 = Building, 7 = Noise, 8 = Res. (Model keypoints), 9 = Water, 10 = Ignored Ground, 11 = Road, 12 = Res. (Overlap), 21 = High Points
ground condition
To be determined by client
740 7th Ave. West
The file parameters of all the data are correct.
Consistency was maintained throughout the dataset.
The files cover the full extent of the contract.
The LiDAR data was post processed and manually classified to develop the bare earth subset of the raw LiDAR point cloud.
LiDAR processing utilizes several software packages, including GeoCue and the TerraSolid suite of processing components. The GeoCue software is a database management system for housing the LiDAR dataset (usually multiple gigabytes in size). GeoCue incorporates a thorough checklist of processing steps and quality assurance/quality control (QA/QC) procedures that assist in the LiDAR workflow. The TerraSolid software suite is used to automate the initial classification of the LiDAR point cloud based on a set of predetermined parameters. Lidar technicians refer to ground cover research (natural and cultural features) within the project area and determine algorithms most suitable for the initial automated LiDAR classification. (Some algorithms/filters recognize the ground in forests well, while others have greater capability in urban areas). During this process each point is given an initial classification (e.g., as ground, vegetation, or noise) based on the point's coordinates and the relation to its neighbors. Classifications to be assigned include all those outlined by ASPRS standards. The initial classifications produce a coarse and inexact dataset, but offer an adequate starting point for the subsequent manual classification procedure. During this step, "overlap" points are automatically classified (those originating from neighboring flightlines) using information gathered from the ABGPS and IMU data. Any duplicate points existing from adjacent flightlines are removed during this process. Hydrographic breaklines are collected using LiDARgrammetry to ensure hydroflattened water surfaces. This process involves manipulating the LiDAR data's intensity information to create a metrically sound stereo environment. From this generated "imagery", breaklines are photogrammetrically compiled. Breakline polygons are created to represent open water bodies. The LiDAR points that fall within these areas are classified as "water." Breaklines representing streams and rivers shall be smooth, continuous, and monotonic, and represent the water surface without any stair steps except for dams and rapids. All hydrographic breaklines include a 1 foot buffer, with the points being re-classified as Class 10 (ignored ground). TerraSolid is further used for the subsequent manual classification of the LiDAR points allowing technicians to view the point cloud in a number of ways to ensure accuracy and consistency of points and uniformity of point coverage.
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