Photo based Terrain Data Acquisition & 3D Modeling

Transcription

1 Photo based Terrain Data Acquisition & 3D Modeling June 7, 2013 Howard Hahn Kansas State University Partial funding by: KSU Office of Research and Sponsored Programs

2 Introduction: Need Application 1 Monitoring Gully Erosion Field Erosion Progression Source: H. Hahn McPherson County

3 Introduction: Need Application 1 Monitoring Gully Erosion Manual transects performed using GPS (x,y) and laser level (z) Source: H. Hahn McPherson County

4 Introduction: Need Application 1 Monitoring Gully Erosion Manual transects (~15) require one day each major rainfall Source: H. Hahn McPherson County

5 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 Source: H. Hahn McPherson County

6 Introduction: Need Application 2 Micro Drainage Modeling Residential neighborhood being threatened by eroding creek Source: D. Cross Kansas State University

7 Introduction: Need Application 2 Micro Drainage Modeling Analyzing drainage patterns between structures Source: D. Cross Kansas State University

8 Introduction: Need Application 2 Micro Drainage Modeling Proposed water treatment chains and detention areas Source: D. Cross Kansas State University

9 Introduction: Need Application 2 Micro Drainage Modeling Terrain Modeling Needs 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

10 Introduction: Tools (High End) Current Automated Techniques Aerial LiDAR platforms Typical Specifications Lateral placement accuracy: cm Vertical placement accuracy: 7 16 cm Filter first returns for bare earth results Platforms: Plane or helicopter Examples: Leica ALS70 cm /lidar.html

11 Introduction: Tools (High End) Current Automated Techniques Digital Photogrammetry Typical Specifications 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 wikimedia.org/wiki/file:geo Referenced_Point_Cloud.JPG

12 Introduction: Tools (High End) Current Automated Techniques Terrestrial LiDAR Typical Specifications Range: 120 m Target acquisition: up to 50 m Point resolution: 3 mm at 50 m Speed: 1 million pps Examples: Leica ScanStation P20 Commons.wikimedia.org/wiki/file: Lidar_P

13 Introduction: Simpler options Goals Relatively low cost Rapid and easy field operation Sub dm accuracy

14 Software Selection Agisoft PhotoScan Pro Principle Photogrammetric bundle triangulation

15 Software Selection Agisoft PhotoScan Pro Applications Generation of digital elevation models & orthophotos 3D Point Cloud 3D Triangulation Ortho Mosaic Source data by Dr. K. Price Agisoft Model by H. Hahn

16 Software Selection Agisoft PhotoScan Pro Applications Area & volume measurements Stockpile Displacements sample04/sample05.pdf Mining Excavations sample04/sample04.pdf

17 Software Selection Agisoft PhotoScan Pro Applications 3D model reconstruction (archaeology, etc.) Adapted from /kilclooney dolmen/ Kilclooney Dolmen (Scotland) 3D texture mapped model Agisoft model by H. Hahn

18 Photo Collection Terrestrial Standard 35 mm DSLR (Nikon D50) Photographic parameters Camera calibration derived from extracted digital photo info (FOV, FL, etc.) Recommended 5 megapixel or higher Move camera position 60% side overlap; 80% lateral overlap50 80% At least two scale markers Maintain angle to subject

19 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) RiteWing RC Zephyr Flying Wing UAS vehicles and photos by Dr. Kevin Price, KSU DJI S800 Hexacopter

20 Methods Test Site #1 Open Field Purpose: To determine if drainage patterns could be modeled in sufficient detail to replace LiDAR COA certificate Platform: Zephyr wing Images used: 9 Area: ~ 12.9 ha Cover: short grass Ground control: 2m LiDAR and Bing Imagery 16 pts

21 Methods Flight path and composite photo match

22 Results Test Site #1 Open Field Traditional LiDAR yields superior results Open Field Open Field Road trace Defined drainages Control point.(typ) 2m LiDAR Leafless tree patch (typ) Evergreen tree patch (typ) Agisoft PhotoScan 3D Model Inadequate photos per flight speed No bare earth processing (affected by vegetation)

23 Methods Test Site #2 Prairie Gully Purpose: To test if very low altitude aerial imagery/ photomodeling can replace manual transect techniques COA certificate Platform: DJI Hexacopter Images used: 16 Area: ~ 800 m 2 Cover: grass/dirt Ground control: 2m LiDAR and Bing Imagery 3 pts

24 Methods DJI Hexacopter Flight Path

25 Methods 3D Point Cloud Triangulated surface model Texture mapped 3D model

26 Results Test Site #2 Prairie Gully Overall accuracy within 3 cm

27 Methods Test Site #3 Eroded Slope Purpose: To test if Agisoft could resolve minute surface differences enabling erosion volume calculations Handheld camera Images used: 9 Area: ~ 6.7 m 2 Cover: dirt Ground control: 2 markers

28 Methods 3D Point Cloud Triangulated surface model Texture mapped 3D model

29 Results Test Site #3 Eroded Slope Error Control Photographed surface x 2 Photo Series & Surface #1 Photo Series & Surface #2 Change detection noise

30 Results Test Site #3 Eroded Slope Error Control Photographed surface x 2 Photo Series & Surface #1 Scraped Surface Change detection noise

31 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

32 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