photo based terrain data acquisition 3d modeling · photo‐based terrain data acquisition & 3d...

DLA CONFERENCE 20136‐8 June | Bernburg, Germany

June 7, 2013

Photo‐based Terrain Data Acquisition & 3D Modeling

Howard Hahn Kansas State University

Partial funding by:KSU Office of Research and Sponsored Programs


Introduction: Need

Application 1 – Monitoring Gully Erosion

Source: H. HahnMcPherson County

• Field Erosion Progression


Introduction: Need

Application 1 – Monitoring Gully Erosion • Manual transects performed using GPS (x,y) and laser level (z)



Introduction: Need

Application 1 – Monitoring Gully Erosion • Manual transects (~15) require one day each major rainfall



Introduction: Need

Application 1 – Monitoring Gully Erosion Terrain Modeling Needs

• Reduce time to perform transect measurements

• Preserve a photographic and 3D model record for periodic field monitoring

• Estimate the volume of erosion taking place

• Integrate the 3D model in a GIS environment to correlate with soil, slope, and drainage patterns



Introduction: Need

Application 2 – Micro Drainage Modeling

Source: D. CrossKansas State University

• Residential neighborhood being threatened by eroding creek


Introduction: Need



• Analyzing drainage patterns between structures


Introduction: Need

Application 2 – Micro Drainage Modeling• Proposed water treatment chains and detention areas



Introduction: Need


• Terrain map post construction sites for design of stormwater best management practices (BMPs)

• Schedule flexibility to fly anytime, anywhere (not currently possible without COA)

• Aerial photo acquisition for small area sites where it is not cost effective to fly LiDAR

• Map drainage networks at potentially higher resolution than what is available through county 2m LiDAR data

Terrain Modeling Needs


Introduction: Tools (High End)

Current Automated Techniques

http://www.wy.nrcs.usda.gov/wygis/lidar.html

• Aerial LiDAR platforms

Typical Specifications

‐ Lateral placement accuracy: 10‐30 cm‐ Vertical placement accuracy: 7‐16 cm‐ Filter first returns for bare earth results‐ Platforms: Plane or helicopter

Examples: Leica ALS70‐cm



Current Automated Techniques• Digital Photogrammetry


‐ Optical/sensor: DTM and ortho from same source‐ RGB color, color infrared, & panchromatic‐ On‐the‐fly L1 image rectification‐ Triangulation for DTM: Vert +/‐ 8 cm; contour 15 cm‐ Ground sample distance (GSD): 5‐25 cm

Examples: Leica ADS80, Aerometrex UltraCam

http://commons. wikimedia.org/wiki/File:Geo‐Referenced_Point_Cloud.JPG



Current Automated Techniques• Terrestrial LiDAR

Commons.wikimedia.org/wiki/file:Lidar_P1270901


‐ Range: 120 m‐ Target acquisition: up to 50 m‐ Point resolution: 3 mm at 50 m‐ Speed: 1 million pps

Examples: Leica ScanStation P20


Introduction: Simpler options

• Relatively low cost• Rapid and easy field

operation• Sub‐dm accuracy

Goals


Software Selection

Agisoft PhotoScan Pro ‐ Principle• Photogrammetric bundle triangulation


Software Selection

Agisoft PhotoScan Pro Applications• Generation of digital elevation models & orthophotos

3D Point Cloud 3D Triangulation Ortho Mosaic

Source data by Dr. K. PriceAgisoft Model by H. Hahn


Software Selection

Agisoft PhotoScan Pro Applications• Area & volume measurements

Stockpile Displacements Mining Excavations

http://downloads.agisoft.ru/photoscan/sample04/sample04.pdf

http://downloads.agisoft.ru/photoscan/sample04/sample05.pdf


Software Selection

Agisoft PhotoScan Pro Applications• 3D model reconstruction (archaeology, etc.)

Agisoft model by H. Hahn

Adapted from http://www.voicesfromthedawn.com

/kilclooney‐dolmen/

Kilclooney Dolmen (Scotland) 3D texture mapped model


Photo Collection

Terrestrial • Standard 35 mm DSLR (Nikon D50)

• Photographic parametersCamera calibration derived from extracted digital photo info (FOV, FL, etc.) Recommended 5 megapixel or higherMove camera position60% side overlap; 80% lateral overlap50‐80%At least two scale markersMaintain 45‐90°angle to subject


Photography Collection

Airborne Systems • In the USA, subject to regulation by the Federal Aviation

Administration and requires Certificate of Operation (COA)• Unmanned Aerial Systems (UAS) standards by 2015• Camera: Lightweight Canon Powershot S100 (wide angle)

UAS vehicles and photos by Dr. Kevin Price, KSU

RiteWing RC Zephyr Flying Wing

DJI S800 Hexacopter


Methods

Test Site #1 – Open Field• Purpose: To determine if drainage patterns could be

modeled in sufficient detail to replace LiDAR

COA certificatePlatform: Zephyr wingImages used: 9Area: ~ 12.9 haCover: short grassGround control: 2m LiDARand Bing Imagery – 16 pts


Methods

Flight path and composite photo match


Results

Test Site #1 – Open Field• Traditional LiDAR yields superior results

Open Field Open Field

Road trace

Defined drainages

Leafless tree patch (typ)

Evergreen tree patch (typ)

Control point.(typ)

• Inadequate photos per flight speed• No bare earth processing (affected by vegetation)

2m LiDAR Agisoft PhotoScan 3D Model


Methods

Test Site #2 – Prairie Gully• Purpose: To test if very low altitude aerial imagery/

photomodeling can replace manual transect techniques

COA certificatePlatform: DJI HexacopterImages used: 16Area: ~ 800 m2

Cover: grass/dirtGround control: 2m LiDARand Bing Imagery – 3 pts


Methods

DJI Hexacopter Flight Path


Methods

3D Point Cloud

Triangulated surface model

Texture mapped 3D model


Results

Test Site #2 – Prairie Gully• Overall accuracy within 3 cm


Methods

Test Site #3 – Eroded Slope• Purpose: To test if Agisoft could resolve minute surface

differences enabling erosion volume calculations

Handheld cameraImages used: 9Area: ~ 6.7 m2

Cover: dirtGround control: 2 markers


Methods

Triangulated surface model

3D Point Cloud

Texture mapped 3D model


Results

Photo Series & Surface #1 Photo Series & Surface #2

Test Site #3 – Eroded Slope• Error Control – Photographed surface x 2

Change detection noise


Results

Photo Series & Surface #1 Scraped Surface

Test Site #3 – Eroded Slope• Error Control – Photographed surface x 2

Change detection noise


Conclusions• TS 1‐ Field

• Matched GIS control points within +/‐ 1.5 m

• Terrain produced via Zephyr flying wing and PhotoScan did not yield better results than 2m LiDAR

• Too few photos acquired due to long photo interval relative flight speed (~ 60 km/hr) contributed to lower quality

• Vegetation, which could not be filtered from point cloud, contributed to lower quality compared to LiDAR results

• TS 2 – Prairie Gully• Imagery acquired from hexacopter flying at low 16m altitude

used to generate 3D terrain model with a mean error of 3.53 cm compared against manual measurements


Conclusions• TS 3 ‐ Eroded Slope

• At close photo ranges, PhotoScan is capable of resolving minute terrain changes (+/‐ 5 mm)

• For a small area test, Initial investigations demonstrated that accuracy of at least 85% can be achieved when estimating erosion quantities.

• Future Research• Re‐test drainage network mapping for improved accuracy. For

smaller fields, switch to a hexacopter aerial platform at slower flight speed. Attempt to filter vegetation from point clouds

• Create field gully models over an extended monitoring period, align models, and estimate erosion quantities

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