light detection and ranging (lidar) introduction some ... · pdf filelight detection and...

Light Detection And Ranging (LiDAR) introduction Some applications of Aerial LiDAR imagery

Dr. Venkat Devarajan Professor, Electrical Engineering, UTA

Director, Virtual Environment Lab (VEL) Email: [email protected]

10/29/2014 VEL Lab, UT Arlington 1

Airborne LiDAR


Target is illuminated by laser and distance is measured by analyzing reflected beam

Courtesy:USGS

Range R = v.t/2

LiDAR data acquisition


1) Aircraft 2) Scanning Laser Emitter -Receiver Unit 3) Differential GPS 4) IMU 5) Computer

Available information • X,Y, Z of the reflecting points • Reflected beam intensity • Return count from a point • Time stamp of each pulse

Image source: Imaging Notes Magazine, Volume 26 Number 2

Aerial LiDAR Systems and Scanning Mechanism


Courtesy: Claus Brenner, Institute of Cartography and Geoinformatics University of Hannover, Germany

Range of commercial Lasers


Courtesy: J. Stoker, USGS

LiDAR Footprint


Accuracy and Resolution in laser Ranging


Courtesy: Amar Nayegandhi

Terrestrial LiDAR


Image Courtesy: Sanborn and Fargo

Terrestrial LiDAR collected from a vehicle (left) and a boat (right)

LiDAR Bathymetry


Sonar and LiDAR complement each other when making nautical charts.

Courtesy: Optech

LiDAR Data Point Cloud


Courtesy: USGS

NPD: Nominal Point Density is the number of returns per square meter

LiDAR intensity image


Baltimore Harbor 1st return LiDAR and corresponding intensity image

Courtesy: NRCS DEM whitepaper

Reflectivity of various surface/materials @ 0.9μm


Highly reflective objects sometimes saturates some laser detector and return signal from low-reflective object might be too weak to register as valid.

Spectral Reflectance of vegetation, water and soil


Multiple LiDAR Return


Courtesy: J. Stoker USGS

Contemporary LiDAR systems are capable of giving at least three returns per pulse

Multiple LiDAR Return


Courtesy: Hans-Eric Anderson

LiDAR Deliverables: Digital Elevation Model (DEM)


Source: USGS NED overview

Higher resolution source migration

LiDAR Deliverables: Digital Surface model (DSM) and Digital Terrain Model (DTM)


Source: NRCS DEM Whitepaper

LiDAR Deliverables: Triangulated Irregular Network (TIN)


Source: Valerie Garcia, NCSU

LiDAR Deliverables: Hillshaded, Color-Ramped DEM


Courtesy: LiDAR 101, NOAA

LiDAR Applications: Feature Extraction using LiDAR


Courtesy: LiDAR 101, NOAA

LiDAR Applications: LiDAR data used to asses damage caused by fire


Courtesy: J. Stoker

LiDAR Applications: LiDAR data used to asses damage cased by

Hurricane Isabel


Courtesy: J. Stoker

LiDAR Applications: LiDAR for Urban Modeling


Courtesy: J. Stoker, USGS

LiDAR Applications: Power Line Mapping with LiDAR


Courtesy: Reigl USA

LiDAR rapidly provides most comprehensive and accurate assessment of power lines and their surroundings

TIN along the side of a ridge with/without break line


The dam is successfully modeled with break line

TIN without/with Hydro Breaklines


Source: Furgo earth data

Water body with unenforced boundary and after breakline enforcement


Source: PE&RS mar 2012

Contours entering the water body is not desirable. So breakline enforcement is necessary

Importance of Intensity Image for water body detection


Source: Dewberry LiDAR QA report, Sabine/Shelly Counties, Tx

Intensity image confirms a large riverbank area is ground not water

Jagged Shoreline from Manual Delineation


Source: Dewberry LiDAR QA report, Sabine/Shelly Counties, Tx

Insufficient number of vertices makes islands and shorelines appear jagged

Flow Chart of VEL/UTA Auto Hydro Breakline Generation


2m DEM and 2m pixel intensity image of a test area in L’Anguille river basin


Water surface is relatively smooth


Three 40000 m2 area were chosen inside three water bodies and the water surface elevation variation was found to be 1.9233 in2, 1.6721 in2 and 1.3482 in2

Flow Chart for water body detection in Method 1


Histogram Generation and Peak Detection


0 200 400 600 800 1000 1200-0.5

0

0.5

1

1.5

2

2.5x 10

4

138 140 142 144 146 148 150 152 154

4200

4250

4300

4350

4400

4450

4500

4550

4600

X: 146.1Y: 4590

X: 142.3Y: 4239

Detecting areas associated with one particular peak


Detected water bodies after removing all the false detection using method 1


Steps in detecting water bodies using method 2


2m pixel Intensity Image

Detect all the pixels which Falls below 20 percentile

Keep areas greater than ½ acre in size

Compare elevation with surrounding area

Reject some areas as false detection Continuity test

Compare intensity with surrounding area

Final detection in method 2

Overall Philosophy: Small water bodies might remain undetected by method 1 as those might not appear as a sharp peak in the elevation histogram and hence method 2 is used

Water bodies detected using method 2


Water body detected after merging detection from elevation and intensity data


LIDAR Strip Adjustment and Mosaicking


Biased Strip

Reconstructed Strip

Ground Detection


Original Image Elevation map in 9m by 9m resolution Ground detection is necessary to create bare earth model

Ground Detection


Ground mask detection using ground filtering Generated DEM

Ground Detection


Ground mask with more precise resolution Original image

Comparison with other technologies


Photogrammetric technology and Manual survey are other available technologies Pros

• LiDAR provides higher accuracy and faster data collection • Data acquisition is possible both day and night. • Cloud shadow, mountain and building shadow is not a problem • Bare earth modeling is also possible in dense forest region • Lower cost. Significantly low for large project • Can be integrated with other technology

Cons • New technology. Algorithms and procedures are under development • High spatial resolution and very large dataset. So high computation time

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