Eastern West Virginia LiDAR Acquisition

Josh NovacProject Manager

Dewberry (Tampa, FL)jnovac@dewberry.com

Project Overview

Project Overview

• LiDAR Acquisition Scheduled for Winter/Spring 2012• LiDAR Acquisition is 100% Complete• Products are currently being delivered as they are completed• Collection designed to meet FEMA needs and USGS V13

Specifications for LiDAR

Project Overview- Specifications

• Nominal Pulse Spacing < 1 meter• Vertical Accuracy

– RMSEZ 12.5 cm– Fundamental Vertical Accuracy (FVA): 24.5 cm– Consolidated Vertical Accuracy (CVA): 36.3 cm– Supplemental Vertical Accuracy (SVA): 36.3 cm

• Relative Accuracy– Within an Individual Swath ≤ 7 cm– Between Swaths ≤ 10 cm

Project Overview- Specifications

• Spatial Reference System– Horizontal

• North American Datum of 1983• UTM Zone 18N• Meters

– Vertical• North American Vertical Datum of 1988• Geoid 2009• Meters

Project Overview – Specifications

• Breaklines– Inland Ponds and Lakes:

• 2 acres or greater• Flat and level (each vertex must have the same elevation)• Water surface must be at or just below adjacent ground

– Inland Streams and Rivers:• 100’ nominal width• Flat and level bank to bank• Should flow continuously downhill (monotonic)

Project Overview - Specifications

• LiDAR Classification– LAS format (v1.2) with ASPRS classification scheme

• Class 1 – Processed, Unclassified• Class 2 – Bare-Earth, Ground• Class 7 – Noise (High/Low Points)• Class 9 – Water (Classified Using Breaklines)• Class 10 – Ignored Ground (Breakline Proximity)

Project Overview – Deliverables

• Raw Point Cloud– LAS V1.2– Georeference Information in Header Files– GPS times recorded as Adjusted GPS Time– Intensity Values– Full Swaths– Size not to exceed 2GB per swath

Project Overview - Deliverables

• Classified Point Cloud– LAS V1.2– Meet V13 Specifications for Classification (The new V1 specs are now

out)– Tiled at 1500 m x 1500 m to U.S. National Grid

• Bare Earth Surface (Raster DEM)– Cell Size of 1 meter– ERDAS .IMG format (32-bit floating point)– Depressions/Sinks not filled (Hydro-flattened DEM not Hydro-enforced

DEM)

Project Overview - Deliverables

• Control– Supplemental Ground Control – Used to control the LiDAR collection

and processing– Ground Control Quality Checkpoints

• Minimum of 20 points across 5 land cover types– Bare Earth/ Open Terrain– Urban– Tall Weeds/Crops – Brush and Trees– Forested

• Must be on flat or uniformly sloping terrain

Project Overview - Deliverables

• Metadata– FGDC Compliant– Overview of processing steps and procedures

• Project Report– Detailed records of collection, production, and quality assurance

processes

Project Overview - Schedule

Deliverable Description Due Date Status

Mobilization 12/16/2012 Complete

LiDAR Acquisition 03/09/2012 Complete

Survey (QA/QC Points) 02/10/2012 Complete

LiDAR Calibration 05/11/2012 Complete

Pilot Deliverable 05/25/2012 Complete

Full Deliverable 11/15/2012 In Progress

Final Acceptance 12/15/2012

Project Overview - Contacts

• USGS State Liaison – Craig A. NeidigCharleston, WV

304-347-5130 x237cneidig@usgs.gov

• USGS Project Manager – Patrick EmmettRolla, MO

573-308-3587pemmett@usgs.gov

• Dewberry – Josh NovacTampa, FL

813-421-8632jnovac@dewberry.com

LiDAR Technology

What is LiDAR

• Light Detection and Ranging• Active Scanning System

– Uses its own energy source to produce pulses of laser (light) which are emitted, reflected and then received from surfaces

• Measures range distances– Based on time between emission, reflection and receive

time

• Direct terrain measurements, unlike photogrammetry which is inferred

• Day or night operation except when coupled with digital camera

• In addition to ranging, LiDAR systems can provide:– Additional information about the target (for classification)– Information about the transmission path (e.g. DIAL to

measure concentration of elements in the atmosphere)

What LiDAR is NOT

• The answer to all your elevation requirements• All-weather

– Target must be visible within the selected EM spectrum– No rain or fog– Must be below clouds

• Able to “penetrate vegetation”– LiDAR can penetrate openings in the vegetation cover but

cannot see through closed canopies

Airborne LiDAR System Components

LiDAR Transmitter, Scanner, and Receiver

Aircraft Positioning – Differential GPS (with post-processing)

Aircraft Attitude – Pitch, Roll, Yaw – Inertial Navigation System (GPS-Aided)

Data System

Operating Wavelengths

In theory, any light source can be used to create a LiDAR instrument Near-Infrared wavelength

Used by most airborne terrestrial LiDAR systems Easily absorbed at the water surface (unreliable water surface reflections). Wavelengths utilized: 1000 – 1500 nm

Blue-Green Wavelength Used by all airborne bathymetric and “topobathymetric” systems (532 nm) Can penetrate water, but signal strength attenuates exponentially through the

water column

GammaRays

VisibleUltraviolet Infrared Microwave TV/RadioX-Rays

100µm0.1cm

0.7Wavelength (not to scale)

0.30.2µm0.01µm 0.4 1.5 5.6µm 10cm1cm0.0001µm 1m100µm20µm

FilmElectro-optical Sensors

Thermal IR

Passive MicrowaveActive RADAR

Laser system characteristics

• Pulse width (or duration) is usually defined as the time during which the laser output pulse power remains continuously above half its maximum value (FWHM).

Pul

se w

idth

pulse width

“long” pulse

“short” pulse

time (ns)

inte

nsity

Multiple Scanning Patterns (two most common)

It is common to withhold the data for a few percent at the tips of the zig-zags where elevations are less accurate

Various LiDAR Formats

DigitizedBackscatterWaveform

Threshold

Discrete Return

Leading-Edge

PhotonCounting

Pulse-Width

Short DurationLaser Pulse

Image courtesy Dave Harding, NASA

Discrete return vs. waveform-resolving and the “dead zone” effect

Discrete-return LiDAR Waveform-resolving LiDAR most discrete-return systems require a minimum vertical object separation to

register consecutive returns from the pulse separately, thereby being blind to canopy material within this dead zone

Flight Planning Considerations

Maximum scan angle? Leaf-on or leaf-off?

Laser Penetration

Discrete Return LiDAR systems

All returns (16,664 pulses)

1st returns (11,460 pulses, 69%)

2nd returns (4,385 pulses, 26%)

3rd returns (736 pulses, 4%)

4th returns (83 pulses, <1%)

Image courtesy Hans-Erik Anderson

LiDAR Systems Manufacturers

• Leica Geosystems• Optech Inc.• Riegl

Enabling Technologies: Aircraft Position and Attitude Determination

Lidar System Components

• Lidar Transmitter, Scanner, and Receiver

• Aircraft Positioning – Differential GPS (with post-processing)

• Aircraft Attitude – Pitch, Roll, Yaw – Inertial Navigation System (GPS-Aided)

Differential GPS

• Positions the aircraft every one second

• Integrates with IMU – blends the GPS position fixes and the IMU orientation fixes for a complete record of the aircraft motion

• Largest source of positional error!

• Minimize baseline length for best accuracy

Inertial Measurement Unit - IMU

• Position and Orientation systems utilizes a combination of gyros and accelerometers

• Outputs position, roll, pitch and heading of airborne sensors real time and post processing

• Capable of 0.005˚pitch/roll, 0.008˚ heading accuracies (POS AV 510 post processed)

• 5-10 cm sensor positioning (post-processed)

• 200 Hz data rates

IMU - Orientation

Pitch Yaw Roll

LiDAR Data Processing

LiDAR Data Processing Workflow

DGPS Data

IMU Data

Lidar range

Scan Angles

Calibration and mounting

parameters

Point Cloud Data X, Y, Z data

Post-processed GPS trajectory and INS solutions

Data Processing Steps

• Initial processing done in field• Process GPS/IMU• Process calibration data• Process waveform data (if available)• Process full point cloud to calibration• Verify data (i.e. flight line comparison, coverage,

accuracy, etc.)• Post Processing – Classification; auto and manual

filtering

LiDAR: Raw Data Processing

• Data collected by flight• Monitored during collection

– Sensor operation– Flight line holidays– Data voids– Gross data errors

• Calibration flight at start and end of flight for adjustment of system and systematic drift

• GPS Data processing (kinematic post-processing aircraft GPS to reference station)

• Results in X Y Z, Scan Angle, Intensity, Return# ASCII or Binary files – Typically LAS

LiDAR post-processing creates a point cloud

LiDAR: Post Processing - Classification

• Separating ground from non-ground– Automated Processing– Manual Processing

Post Processing - Classification

• Automated scripts– Classifies approximately 80 – 85% and takes 20% of the time– Algorithm must be balanced to classify correctly - May cut into slopes too

much, or leave too much artifacts– Color coding orange = ground, green = other

Post Processing - Classification

• Manual Classification– Impossible to classify to the 100% level– Manual classification takes 80% of the post processing time (to get that last

20%)– Color coding orange = ground, green = other

ASPRS Standard LiDAR Point Classes

Classification Value (bits 0:4)

Meaning

0 Created, never classified

1 Unclassified

2 Ground

3 Low Vegetation

4 Medium Vegetation

5 High Vegetation

6 Building

7 Low Point (noise)

8 Model Key-point (mass point)

9 Water

10 Reserved for ASPRS Definition

11 Reserved for ASPRS Definition

12 Overlap Points

LAS Classified by Class

Elevation Data Challenges

• Large number of elevation records can require long processing times

• Exploitation of LiDAR has typically required specialized software such as• GeoCUE

• QT Modeler

• Terrascan/Terramodeler

• Many new LiDAR programs are being introduced which will allow more users access to the data

• ArcGIS – Version 10.1

• FugroViewer – Free

• LAS Reader for ArcGIS – Free

• PointView LE - Free

LiDAR Software Tools

• ArcGIS (10.1)• Geocue (Geocue)• LP 360 (GeoCue)• Quick Terrain Modeler (Applied Imagery)• Terrascan (Terrasolid)• LASTools• FugroViewer

Sample list – no endorsement is inferred or implied

Data Verification & Quality Control (QA/QC)

Data Verification & Quality

Three fundamental questions MUST BE ASKED

1. Did the LiDAR system work2. Are the data classified properly and free of

artifacts to support the intended product?3. Is the dataset complete?

Types of Analysis

• Quantitative Analysis– Utilize survey checkpoints to verify TIN accuracy– FEMA only “requires” quantitative analysis

• Qualitative Analysis– Subjective analysis to assess the quality which can include

cleanliness, usefulness for the intended product etc.• Completeness

– Are tiles complete with no voids, correct location, projection information, classified to the correct classes etc.

Dewberry’s Approach to QA/QC

Dewberry’s Approach to QA/QC

• Inventory (completeness)• Quantitative• Qualitative• Reporting

Quantitative Verification

• Ground truth surveys– Utilize GPS and conventional survey checkpoints (cp)– Place checkpoints in strategic locations based on flight line pattern– Verify data in varied land cover categories– Compare CP with interpolated TIN value

Qualitative Assessment - Techniques

• Utilize different software and tools • Use imagery• Create pseudo imagery• Combine images or techniques

• Bare-earth DTM• Full point cloud• Intensity Images• TIN’s• DEM’s• Hillshades• Contours• Slope Map• Speciality Maps• Survey Checkpoints/cross

sections

Derivative Products

Intensity Images

• Measures the amount of light returning to the sensor

• Useful for QA/QC & Research– Identify conditions at time of

collection

• Can be used for stereo-compilation to generate 3D breaklines (“LiDARgrammetry) or 2D features

Breaklines

• Linear features that control surface behavior• Can be 2D or 3D• Traditionally derived from stereo photogrammetry or from

surveys• Can use LiDAR and Intensity to create breaklines• 2D breaklines with assigned elevations for hydro-flattening are

typically used.

Terrain Dataset

A Terrain Datasets is a multi-resolution TIN-based surface build on-the-fly from feature classes stored in a feature dataset of a geodatabase.

Terrain Datasets are more effective for storing and visualizing large point data sets.

A Terrain Datasets resides in the same feature dataset where the feature classes (used to construct it) reside.

Terrain Datasets can be used to obtain TINs and grids.

Terrain Dataset

In a Terrain Dataset, feature classes include: Mass points (e.g., LiDAR); Breaklines (hard and soft); Clipping polygons (hard and soft); Erase polygons (hard and soft); Replace polygons (hard and soft).

A Terrain Dataset is composed of a series of TINs, each of which is used within a map-scale range. For each map-scale range, a level of detail (i.e., z resolution) and pyramid level are defined.

Different Treatments of LiDAR DTMs and DEMs

• Traditional Stereo DTM (Topographic Surface)

• Pure LiDAR (Topographic Surface)

• Hydro-Flattened (Topographic Surface)

• Full Breaklines (Topographic Surface)

• Hydro-Enforced (Hydrologic Surface)

• Hydro-Conditioned (Hydrologic Surface)

Traditional Stereo DTM (Topographic Surface)

• Reference image of the traditional stereo-compiled DTM

• Built from Masspoints and Breaklines

• Much coarser resolution than LiDAR

• Demonstrates the familiar and usually expected character of a topographic DEM

• Most notably, the “flat” water surfaces

Stream Waterbody

Pure LiDAR (Topographic Surface)

• DEM created only using bare-earth LiDAR points

• Surface contains extensive triangulation artifacts (“TINning”).

• Cause by the absence of:– LiDAR returns from water – Breakline constraints that

would define buildings, water, and other features (as in the Stereo DTM).

• Aesthetically and cartographically unacceptable to most users

TINning in Water Areas

Hydro-Flattened (Topographic Surface)

• The goal of the v13 Spec• Intent is to support the development of

a consistent, acceptable character within the NED

• Removes the most offensive pure LiDAR artifacts: those in the water.

– Constant elevation for waterbodies.– Wide streams and rivers are flattened

bank-to-bank and forced to flow downhill (monotonic).

• Carries ZERO implicit or explicit accuracy with regards to the represented water surface elevations – It is ONLY a cartographic/aesthetic enhancement.

• Building voids are not corrected due to high costs

• Most often achieved via the development and inclusion of hard breaklines.Stream Waterbody

Full Breaklines (Topographic Surface)

• A further possible refinement of the hydro- flattened surface

• Removes artifacts from building voids

• Refines the delineation of roads, single-line drainages, ridges, bridge crossings, etc.

• Requires the development of a large number of additional detailed breaklines

• A higher quality topographic surface, but significantly more expensive.

• Not cost effective for the NED.Buildings Roads

Hydro-Enforced (Hydrologic Surface)

• Surface used by engineers in Hydraulic and Hydrologic (H&H) modeling.

• Similar to Hydro-Flattened with the addition of Single Line Breaklines: Pipelines, Culverts, Underground Streams, etc…

• Terrain is then cut away at bridges and culverts to model drain connectivity

• Water Surface Elevations (WSEL) are often set to known values (surveyed or historical).

Culverts Cut Through Roads

Hydro-Conditioned (Hydrologic Surface)

• Another type of surface used by engineers for H&H modeling.

• Similar to the hydro- enforced surface, but with sinks filled

• Flow is continuous across the entire surface – no areas of unconnected internal drainage

• Often achieved via ArcHydro or ArcGIS Spatial Analyist

Common Data Upgrades to USGS V13 Spec.

1. Independent 3rd party QA/QC2. Higher Nominal Pulse Spacing (NPS)3. Increased Vertical Accuracy4. Full waveform or topo/bathy collection with red/green lasers5. Tide coordination, flood stage, plant growth cycle, shorelines6. Top-of-canopy (1st return) Digital Surface Model (DSM)7. More detailed LAS classification for vegetation, buildings8. Hydro enforced and/or hydro conditioned DEMs9. Single-line hydro feature breaklines; other breaklines10. Building footprints with elevations/heights11. Additional data products such as contours

Generating Contours from LiDAR

Contours are produced from LiDAR mass points and breaklines

Not aesthetically pleasing

ASPRS’ “DEM Users Manual”

1. Intro to DEMs, 3-D Surface Modeling, Tides

2. Vertical Datums3. Accuracy Standards4. National Elevation Dataset5. Photogrammetry6. IFSAR7. Topographic & Terrestrial Lidar8. Airborne Lidar Bathymetry9. Sonar10. Enabling Technologies11. DEM User Applications12. DEM Quality Assessment13. DEM User Requirements14. Lidar Processing & Software15. Sample Elevation Datasets

Final Report for NEEA Study available at www.dewberry.com

http://www.dewberry.com/Consultants/GeospatialMapping/FinalReport-NationalEnhancedElevationAssessment

THANK YOU

Josh NovacProject ManagerRemote Sensing Services LineDewberry (Tampa, FL)jnovac@dewberry.comPh: 813.421.8632