Data Management Plan

2015 City of Portland Maine Lidar Data Acquisition and Processing

Woolpert Order No. 75564

Contractor: Woolpert, Inc.

This task is for a high resolution data set of lidar covering approximately 21 square miles of the City of Portland, Maine.

The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.5 meters. The final products include classified LAS, four (4) feet pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index and FGDC project level metadata in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. This metadata record is for the DEM data served by the NOAA Digital Coast.

Process Steps:

• 2015-05-10 00:00:00 - Using two Leica ALS70 (lidar) systems on board a Cessna 310 aircraft, high density data, at a nominal pulse spacing (NPS) of 0.5 meters, were collected for this task order (approximately 21 square miles). Leica Specs- AGL = 1,829 meters - Aircraft Speed = 140 Knots, Field of View (Full) = 28 degrees, Pulse Rate = 293 kHz, Scan Rate = 52.5 Hz, with an average side lap of 27.7%. Multiple returns were recorded for each laser pulse along with an intensity value for each return. One (1) mission was flown on May 10, 2015. One (1) Global Navigation Satellite System (GNSS) Base Station was used in support of the lidar data acquisition. Specific information regarding latitude, longitude, and ellipsoid height to the L1 phase center is included in the lidar processing report. Data for the task order is referenced to the NAD1983 (HARN) StatePlane Maine West FIPS 1802 in U.S. Survey Feet. The Vertical Datum is in NGVD29 with units in U.S. Survey Feet. Once the data acquisition and GPS processing phases are complete, the lidar data was processed immediately to verify the coverage had no voids. The GPS and IMU data was post processed using differential and Kalman filter algorithms to derive a best estimate of trajectory. The quality of the solution was verified to be consistent with the accuracy requirements of the project. The SBET was used to reduce the lidar slant range measurements to a raw reflective surface for each flight line. The coverage was classified to extract a bare earth digital elevation model (DEM) and separate last returns. The ALS70 calibration and system performance is verified on a periodic basis using Woolpert's calibration range. The calibration range consists of a large building and runway. The edges of the building and control points along the runway have been located using conventional survey methods. Inertial measurement unit (IMU) misalignment angles and horizontal accuracy are calculated by comparing the position of the building edges between opposing flight lines. The scanner scale factor and vertical accuracy is calculated through comparison of lidar data against control points along the runway. Field calibration is performed on all flight lines to refine the IMU misalignment angles. IMU misalignment angles are calculated from the relative displacement of features within the overlap region of adjacent (and opposing) flight lines. The raw lidar data is reduced using the refined misalignment angles. (Citation: Lidar acquisition)
• 2015-01-01 00:00:00 - Control used in calibration/accuracy reporting was provided by the City of Portland and delivered as ESRI shapefile (Citation: Survey Control Acquisition)
• 2015-05-11 00:00:00 - The individual flight lines were inspected to ensure the systematic and residual errors have been identified and removed. Then, the flight lines were compared to adjacent flight lines for any mismatches to obtain a homogeneous coverage throughout the project area. The point cloud underwent a classification process to determine bare-earth points and non-ground points utilizing "first and only" as well as "last of many" lidar returns. This process determined Default (Class 1), Ground (Class 2), Noise (Class 7), Water (Class 9), Ignored Ground (Class 10), Overlap Default (Class 17) and Overlap Ground (Class 18). The bare-earth (Class 2 - Ground) lidar points underwent a manual QA/QC step to verify the quality of the DEM as well as a peer-based QC review. This included a review of the DEM surface to remove artifacts and ensure topographic quality. Classification of water (class 9) and ignored ground (class 10) was completed via the use of the hydrologic breaklines collected for the hydro-flattening phase. The overlap classes were determined by first identifying the overlapping areas and reclassifying the LAS data by offset from a corridor. This allows the returns located on the edge of the swath to be removed from the bare earth coverage in an effort to produce a more uniform data density. The returns determined to be overlap including overlap default, ground, water, and ignored ground are then applied an overlap flag and reclassified to their respective standard classification value. The surveyed ground control points are used to make vertical adjustments to the data set and to perform the accuracy checks and statistical analysis of the lidar dataset. Supervisory QC monitoring of work in progress and completed editing ensured consistency of classification character and adherence to project requirements across the entire project area. The resulting deliverables for this task order consist of classified LAS file in LAS 1.4 format, 4 feet pixel size DEM files in ERDAS IMG format, 4 feet pixel size 8-bit Intensity files in GeoTIFF format, and Hydrologic Breakline data in ESRI shape file format. (Citation: Lidar deliverable processing)
• 2015-05-11 00:00:00 - The compilation procedure included use of lidar intensity, bare earth surface model, point cloud data, and open source imagery in an effort to manually compile hydrologic features in a 2-d environment. Following the compilation phase, a separate process was used to adjust the breakline data to best match the water level at the time of the lidar collection. Any ponds and/or lakes were adjusted to be at or just below the bank and to be at a constant elevation. Any streams were adjusted to be at or just below the bank and to be monotonic. Manual QAQC and peer-based QC review was performed on all delineated data to ensure horizontal placement quality and on all adjusted data to ensure vertical placement quality. The final hydrologic breakline product was delivered in ESRI shape file format and was also used in the processing of the DEM deliverable. (Citation: Lidar deliverable processing)
• 2015-05-11 00:00:00 - Tile Size: 5,000 ft x 5,000 ft. The tile file name was derived from the southwest corner of each tile.s (Citation: Tile index and data extent)
• 2017-03-16 00:00:00 - DEM data was received by NOAA/OCM from the City of Portland in Imagine format, State Plane NAD83(HARN) Maine West (zone 1802) with vertical feet referenced to NGVD29. NOAA converted the data vertical meters referenced to NAVD88. Conversion from NGVD29 to NAVD88 was done with gdal_translate and VDatum.
• 2023-08-15 00:00:00 - Data were converted to vertical feet using gdal_translate to be consistent with the horizontal units. Data were also converted to cloud optimized geotiff format and given vertical georeferencing in the same step.

This point cloud lidar data can be obtained on-line at the following URL:

https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6256.

This data can be obtained on-line at the following URL:

https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6270.

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