2010 U.S. Geological Survey (USGS) Topographic LiDAR: San Francisco Bay, California

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This graphic shows the lidar coverage for the San Francisco Bay Area, California.

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LiDAR data representing the USGS San Francisco Coastal LiDAR Task Order to be used for various analysis and research purposes. | Source Geospatial Form: map | Type of Source Media: Hard Drive

- Establishment of survey points to support the LiDAR data collection.

Three existing published CGPS stations (CHAB, P181, P222) were observed in a GPS control network and used to establish three new points for the primary control for this site. 101U01,101U02, 101U04,AY0887 and AY1499 were observed and used to control all flight missions and static ground surveys. The following are the final coordinates of the control points used for this project:

Station Id;Latitude;Longitude;Easting;Northing;Ellipsoidal_Height;

1010601; 37 30 52.26391; -122 29 41.86434; -16.6617

1010602; 37 27 16.57733; -122 06 37.48309; -29.7404

1010603; 37 39 48.24857; -122 07 23.10831; -23.1470

1010604; 37 59 35.03464; -122 03 44.26783; -26.2030

1010605; 37 59 49.29391; -122 45 33.01378; 50.3610

- Airborne acquisition of Lidar

Terrapoint used one Optech ALTM 3100EA system to collect the data.

The Optech System was configured in the following method:

Aircraft Speed 150 knots

Data Acquisition Height 1300 m AGL

Swath Width 755 m

Distance between Flight Lines 377 m

Overlap 50 %

Scanner Field Of View 19.2 +/- degrees

Pulse Repetition Rate 70 KHz

LiDAR Scan Frequency 38.7 Hz

Number of Returns per Pulse 4 Discrete returns

Beam Divergence 0.3 mRad

Flight Line Length <30km

Base Station Distance <35km

Resultant Raw Point Density ~2 point pt/m2 with overlap

2 missions (o110292a, o110293a) were flown at higher altitude with different parameters to accommodate air traffic control restrictions

Aircraft Speed 125 knots

Data Acquisition Height 2300 m AGL

Overlap 50 %

Scanner Field Of View 15 +/- degrees

Pulse Repetition Rate 50 KHz

LiDAR Scan Frequency 25.5 Hz

Number of Returns per Pulse 4 Discrete returns

Beam Divergence 0.3 mRad

Resultant Raw Point Density ~2 point pt/m2 with overlap

Aircraft platforms were used in the collection of this project:

A Piper Navaho aircraft, registered as FVTL was used to conduct the aerial survey. The Navaho is a fixed wing aircraft that have an endurance of approximately 6-7 hours.

-GPS-IMU: High accuracy IMU and GPS information concerning the attitude and position of the sensor were acquired at the same time as the Laser data. Ground based GPS stations also acquired consecutive GPS information for the duration of the flights. A combination of Sokkia GSR 2600 and NovAtel DL-4+ dual-frequency GPS receivers were used to support the airborne operations of this survey.

-Number of Flights

A total of 14 missions were flown total under good meteorological and GPS conditions to provide complete coverage.

The LiDAR data were collected under tidal restrictions at or below Mean Lower Low Water. 10 missions were acquired during spring 2010 (between June 11, 2010 and June 30, 2010) and 4 missions were acquired during fall (between October 19, 2010 and November 7, 2010)

- Airborne GPS Kinematic processing

Airborne GPS kinematic data was processed on-site using GrafNav kinematic On-The-Fly (OTF) software. Flights were flown with a minimum of 6 satellites in view (13o above the horizon) and with a PDOP of better than 4. Distances from base station to aircraft were kept to a maximum of 30 km, to ensure a strong OTF (On-The-Fly) solution. For all flights, the GPS data can be classified as excellent, with GPS residuals of 3cm average but no larger than 10 cm being recorded.

The Geoid09 geoid model, published by the NGS, was used to transform all ellipsoidal heights to orthometric.

- Generation and Calibration of laser points

Laser data points are generated using Terrapoint's proprietary

laser post-processing software for Midrange data and using Optech's software Dashmap for data acquired with Optech systems. Those software combine the raw

laser range and angle data file with the finalized GPS/IMU trajectory

information. Each mission is evaluated in Terrasolid's Terramatch software to correct any residual roll pitch heading misalignments, if necessary those values are to the data. The resulting point cloud is projected into

the desired coordinate system and created in LAS

format. One file per swath.

On a project level, a coverage check is carried out to ensure no slivers

are present.

- Mission to mission adjustments of Lidar data

All missions are validated and adjusted against the adjoining

missions for relative vertical biases and collected GPS kinematic

ground truthing points for absolute vertical accuracy purposes.

The following adjustments were applied to the data (vertical shifts in meters, + means raise the Lidar points and - means lower the Lidar points)

o110163a, Dz= 0.05

o110164a, Dz= 0.15

o110173a, Dz= -0.25

o110178a, Dz= -0.1

o110179a, Dz= 0.05

o110292a, Dz= 0.2

o110293a, Dz= 0.2

o110305a, Dz= 0.2

o110306a line 30608 - 30615, Dz= 0.15

o110306a line 30616 - 30623, Dz= 0.2

o110306a line 30602 - 30607, Dz= 0.05

- Data Classification and Editing

The data was processed using the software TerraScan, and following the methodology described herein. The initial step is the setup of the TerraScan project, which is done by importing project defined tile boundary index encompassing the entire project areas. The acquired 3D laser point clouds, in LAS binary format, were imported into the TerraScan project and divided into file size optimized tiles. Once tiled, the laser points were classified using a proprietary routine in TerraScan. This routine removes any obvious outliers from the dataset following which the ground layer is extracted from the point cloud. The ground extraction process encompassed in this routine takes place by building an iterative surface model.

This surface model is generated using three main parameters: building size, iteration angle and iteration distance. The initial model is based on low points being selected by a "roaming window" with the assumption is that these are the ground points. The size of this roaming window is determined by the building size parameter. The low points are triangulated and the remaining points are evaluated and subsequently added to the model if they meet the iteration angle and distance constraints. This process is repeated until no additional points are added within iteration.

A second critical parameter is the maximum terrain angle constraint, which determines the maximum terrain angle allowed within the classification model.

-Deliverable Product Generation

>Tiling Index

Classified point cloud products were delivered in 695 tiles based on provided a tile scheme given by the client.

>Raw LIDAR Point Cloud

Raw LiDAR point cloud, was provided in the following formats/parameters:

- LAS V1.2, point record format 1, georeferencing information populated in header

- The following fields are included in the LAS file:

1. Adjusted GPS time reported to the nearest microsecond

2. Flight line ID

3. Easting (reported to the nearest 0.01m)

4. Northing (reported to the nearest 0.01m)

5. Elevation (reported to the nearest 0.01m)

6. intensity

7. Echo number

8. Classification

9. Scan angle

10. Edge of scan

11. Scan direction

- Full swaths, all collected points delivered (except planned cut-off and discarded flightline)

- 1 file per swath, 1 swath per file (except when swath had to be divided in section for size or calibration)

>Classified LIDAR Point Cloud, tiled

Classified LiDAR point cloud, was provided in the following formats/parameters:

- LAS V1.2, point record format 1, georeferencing information populated in header

- The LAS files adhere to the ASPRS classification scheme as outlined below:

1 : Unclassified,

2 : Ground,

7 : Noise,

- The following fields are included in the LAS file:

1. Adjusted GPS time reported to the nearest microsecond

2. Flight line ID

3. Easting (reported to the nearest 0.01m)

4. Northing (reported to the nearest 0.01m)

5. Elevation (reported to the nearest 0.01m)

6. intensity

7. Echo number

8. Classification

9. Scan angle

10. Edge of scan

11. Scan direction

Dewberry utilizes a variety of software suites for inventory management, classification, and data processing. All LiDAR related processes begin by importing the data into the GeoCue task management software. GeoCue allows the data to retain its delivered tiling scheme (1500 m by 1500 m). After the a review of the Terrapoint ground classification was completed, the dataset was processed through a water classification routine that utilizes breaklines compiled by Dewberry to automatically classify hydrographic features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. During this water classification routine, points which are in close proximity (0.5 m) to the hydrographic features are moved to class 10, an ignored ground. In addition to classes 1, 2, 9, and 10, the project allows for a Class 7, noise points. This class was only used if needed when points could manually be identified as low/high points.

The fully classified dataset is then processed through Dewberry's comprehensive quality control program.

The data was classified as follows:

Class 1 = Unclassified. This class includes vegetation, buildings, noise etc.

Class 2 = Ground

Class 7= Noise

Class 9 = Water

Class 10= Ignored Ground

The LAS header information was verified to contain the following:

Class (Integer)

GPS Week Time (0.0001 seconds)

Easting (0.001 m)

Northing (0.001 m)

Elevation (0.001 m)

Echo Number (Integer 1 to 4)

Echo (Integer 1 to 4)

Intensity (8 bit integer)

Flight Line (Integer)

LiDAR Scan Angle (Integer degree)

The NOAA Office for Coastal Management (OCM) received topographic files in LAS format. The files contained lidar elevation and intensity measurements.

The data were received in UTM Zones 10 coordinates and were vertically referenced to NAVD88 using the Geoid09 model. The vertical

units of the data were meters. OCM performed the following processing for data storage and Digital Coast provisioning purposes:

1. The topographic las files were converted from orthometric (NAVD88) heights to ellipsoidal heights using Geoid09.