utilizing low-cost unmanned vehicle (uav) to build orthophotos and digital surface models

@bricker USGS Brownbag 1

Utilizing low-cost unmanned vehicle (UAV) to build orthophotos and Digital Surface Models

Britta Ricker, PhDAssistant Professor

5/16/15

http://faculty.washington.edu/bricker0/uav.html




About my research

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Outline

1. Context - the problem/opportunity Unmanned Aerial Vehicles (UAV) Paradigm shift: digital globes! &

Citizen Science2. How to generate your own

imagery3. Additional considerations4. Future Research

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Landscape is evolving

Constant need to monitor this

change

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5

Gaspar Felix TournachonAKA Nadar, Paris 1858

KitesBalloonsPigeons

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Early aerial photo of a

Boston shoreline

1860

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"Boston, as the Eagle and the Wild Goose See It"by James Wallace Black


3rd Balloon CompanyFort Lewis 1938

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Tacoma Narrows 1959

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Photogrammetry is the use of photography in surveying and mapping to measure distances

between objects.

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The science applied, technique and art of collecting reliable information from stereoscopic models to determine the shape, position and size of objects in space.

The word Photogrammetry, is derived from three words of Greek origin:

"Photon" - light; "Graphos" – written or description; "Metron" – to measure.


Remote Sensing Applications

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Environmental monitoringNatural Resource ManagementEpidemiology Geology – Hazard monitoring and mitigationLand use – Agriculture, soil moistureSearch and Rescue Animal tracking

(Colomina & Molina, 2014; Everaerts, 2008; Forance et al., 2014; Upton et al, 2015)


Traditional Geographic Information Systems and Science

Technical TrainingDifficult to use

ExpensivePrecise & Accurate

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Geoweb and Digital Globes

• Geoweb: Interconnected tools and data available on the web that span multiple geographic regions and are geographically associated (Lake & Farley, 2007; Haklay et al., 2008)

• Revolutionized spatial data (Sui, 2008)

• but not democratized (Haklay, 2013; Sui et al, 2013)

• What is significant = access to satellite imagery! (Goodchild, 2007; Harvey, 2014; Kingsbury & Jones, 2009)

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Geoweb + Citizen Science

Citizen Science “scientific work

undertaken by members of the general public,

often in collaboration with or under the direction of

professional scientists and scientific

institutions.” (Haklay, 2015)

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Challenges in Citizen Science

• Getting and keeping people evolved, excited and to keep coming back…

• Enthusiasm…emotional intensity • Hardware accessibility and extensibility• Software and data standards • Privacy/Anonymity• Authentication + Trust

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@bricker USGS Brownbag 155/16/15

Tell me, I forget.Show me, I remember.

Involve me, I understand.

-Chinese Proverb(Paulos et al., 2009)


drones and enthusiasm

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469,000 results on google

http://www.slashgear.com/nasas-drone-airspace-expert-clamps-down-on-enthusiasm-01343803/

http://www.slashgear.com/nasas-drone-airspace-expert-clamps-down-on-enthusiasm-01343803/

http://time.com/3053003/martha-stewart-drone/

http://chicagoinno.streetwise.co/2015/02/08/drone-regulation-drone-enthusiasm-up-despite-profit-restrictions/


YouTube search “drone”=

3,440,000 (March 2015)5,900,000 (Dec. 2015)

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How drones are being used

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How/Can enthusiasm be harnessed and incorporated into (participatory) mapping and citizen science?

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Drones!

Evoke negative connotation (Sandvik & Lohne, 2014)

– Militarization– Surveillance (Crampton et al.,

2013)

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Drones for Good“Humanitarian weapon” (Sandvik & Lohne, 2014)“Predators for Peace” (Chow, 2012)HumanitarianSearch and Rescue

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Drones and Enthusiasm and Citizen Science #dronesforgood

Meyer (2015) Digital Humanitarianism Ch. 4 “Crowd Computing Satellite and Aerial Imagery”

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Knowledge sharing communities

• Micro Mappers• UAViators - Humanitarian• DIYDrones

• OpenDroneMap

• droneAdventures• Drone Mapper• Conservation Drones• Drone code• …

http://irevolution.net/2014/09/09/piloting-micromappers-in-namibia/


Potential benefits of using Unmanned Aerial Vehicles (UAV) for mapping and

Citizen Science?

Temporal ResolutionSpatial ResolutionIncreased coverage

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Could complement or augment existing data collection methods (Crampton et al., 2013)

Big Raster DataUAV image

Google Earth


Research Aim:Identify a feasible workflow to create maps from aerial

imagery captured from dronesfor citizen science initiatives (= cheap + easy)

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Img- pix4D

Where to begin? Project Goals

Sensor (Payload)

End mapping product

Software Spatial Scale


Partnering with local scientists

to monitor gradual changes

1. noxious algal blooms 2. eel grass beds

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Monitor acute change Landslide Spring 2015Des Moines WA


Key Considerations

1. Pre-Flight2. Flight3. Image Processing4. Post-processing

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Pre-flight: What type of UAV do I need?UAV classifications

• Flight characteristics• Takeoff and landing methods• Source of Power• Weight (including payload)

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Drone classifications

Takeoff and landing methods

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Fixed Wing (Airplane) Rotor Wing (Helicopter)

Which Drone to buy?Drone Specs

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Eisenbeiss, 2008 http://www.igp-data.ethz.ch/berichte/blaue_berichte_pdf/105.pdf


DJI Phantom Vision 2 +

• Flight time ~25 min• Return to “home”

when battery is low• Compass and GPS• No fly zone• Camera and gimble• 14 megapixel

camera• http://www.dji.com/product/phantom-2-vision-pl

us/spec

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http://www.dji.com/product/phantom-2-vision-plus/spec

http://www.dji.com/product/phantom-2-vision-plus/spec


MapBox ESRI

Are you in a “No Fly Zone”?

https://www.mapbox.com/drone/no-fly/

http://story.maps.arcgis.com/apps/MapSeries/?appid=79798a56715c4df183448cc5b7e1b999


Pre Flight:Read the manual!

Plan your flight.(Autopilot versus free flight)

Have a back up plan.

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(Nex & Remondino, 2013)


Flight

• Angle of Nadir

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Try to Avoid this…

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Cost of the drone is not the only cost

Key Considerations

1. Pre-Flight2. Flight3. Image Processing4. Post-processing

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$ $$


Processing Images

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Share Online

Software selction

Stitch Imagery

Capture imageryDrone Flying Fun!

Manually

PS/GIMPArcGIS/QGIS

Automatically

Pix4DAgisoft

OpenDroneMap

Map Knitter, Google Earth, PDF, MapBox, GeoServer + OpenLayers, ESRI Online…


Manual correction and stitching

Correct Fisheye using GIMP Filters→Distorts→Lens distortion → In the new window change Main to -55 & Edge to 10 modify as needed

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Stitch imagery

• ArcGIS – Georeference• QGIS• MapKnitter

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Needed AutomationNeeded Measurements

Needed Photogrammetry!

Influenced metadata associated with the photos

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Software Options

Proprietary • Pix4D• Agisoft• Other

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Open Source• Visual Structure from

Motion System (VisualSFM)

• Clustering Views for Multi-view Stereo (CMVS)

• OpenDroneMap


Computer Vision

• field that includes methods for acquiring, processing, analyzing, and understanding images and, in general, high-dimensional data from the real world in an effort to produce numerical or symbolic information, e.g., in the forms of decisions.

• Applications: – Recognition– Motion Analysis– Scene reconstruction– Image restoration– Artificial intelligence

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Structure from Motion“a range imaging technique; it refers to the process of estimating three-dimensional structures from two-dimensional image sequences which may be coupled with local motion signals. It is studied in the fields of computer vision and visual perception. In biological vision, SfM refers to the phenomenon by which humans (and other living creatures) can recover 3D structure from the projected 2D (retinal) motion field of a moving object or scene.” Wikipedia

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https://en.wikipedia.org/wiki/Range_imaging

https://en.wikipedia.org/wiki/Motion_perception

https://en.wikipedia.org/wiki/Computer_vision

https://en.wikipedia.org/wiki/Visual_perception


Structure from Motion basics

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1. Detection of feature points in view2. Tracking feature points from one frame to the next frame3. Robust estimation of 3D position of these points, based on their motion

http://www.invision-news.de/artikel/104202.htm

http://www.invision-news.de/artikel/104202.htm


Structure from Motion basicsEpipolar Geometry

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perspective projection model

http://www.cs.columbia.edu/~jebara/htmlpapers/SFM/sfm.html




Free and Open Source Software (FOSS)

• Free as in speech • Free as in beer

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Created and Run by Steven Matherhttps://github.com/OpenDroneMap/OpenDroneMap

http://opendronemap.github.io/odm/

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Point CloudDigital Surface Model (DSM)

Textured DSMDigital Elevation Models (DEM)

Orthophotography

https://github.com/OpenDroneMap/OpenDroneMap




AgiSoft

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Pix4D


Pix4D Mobile App – for camera

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Flight PathAuto PilotFree flight

https://support.pix4d.com/hc/en-us/articles/202557269--Android-Pix4Dmapper-Capture-App-Getting-started

DJI offers three Software Development Kits (SDK)Mobile: Aerial Imagery, Live Video, NavigationOnboard: Flight data, flight control, data transmissionGuidance: Hardware, ports, velocity, filters, depth


Pix4D: Autopilot App

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Federal Way Twin Lakes July 2015

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Lake Loreene Lake Jean

Individual photos


Water is difficult to renderand sometimes ugly

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Lake Jean Lake Loreen


But Not Impossible

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http://faculty.washington.edu/bricker0/google_tiles/Mission_00002_mosaic.html






errors


Lake Wapato

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Eel grass images

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Acute ChangeLandslide

Des Moines, WA

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Landslide in Des Moines, WA

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Pix4D Online processed 34 images in 4 minutes


2012 2015


Digital Surface Model (DSM)


Pix4D

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Digital Surface Model (DSM)

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Interactive models

• https://sketchfab.com/models/62bf2c2b531e4e8680fed3897b36b622

• https://sketchfab.com/models/ca1846e7863c405b9eee14f63b278c61

• https://sketchfab.com/models/d561e5cb65b941c98566ae18bb1bc1f0

• My website http://faculty.washington.edu/bricker0/uav.html

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https://sketchfab.com/models/62bf2c2b531e4e8680fed3897b36b622




https://sketchfab.com/models/ca1846e7863c405b9eee14f63b278c61



https://sketchfab.com/models/d561e5cb65b941c98566ae18bb1bc1f0






Relative AccuracyAbsolute Accuracy

support.pix4d.com/hc/en-us/articles/202557489

http://faculty.washington.edu/bricker0/report_DJI/

http://faculty.washington.edu/bricker0/report_DJI/


Lessons Learned• UAVs take practice to fly.• Proprietary Software is expensive but easy to use!• Open Source Software is an option if you have time and

technical knowhow.• Water is difficult to georeferenced.• Citizen science is an opportunity to continue to explore.

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Additional Considerations• Legal• Ethical

– Surveillance – Critical Cartography

• Data processing and sharing• Practical

– weather – other obstacles (trees, buildings, birds,

people)

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Future Research Dream:Develop an online platform for

1. UAV flyers and owners to share/donate photos2. Provide a cloud based platform for image processing3. Volunteers (citizen scientists) classify imagery4. Expert Scientists verify results?5. Share new knowledge!

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Other project ideas: 3D print a model rendered with UAV

Algal Boom full season – 1 week intervals

Multispectral sensor


Outline

Context - the problem/opportunity Unmanned Aerial Vehicles (UAV) Paradigm shift: digital globes! &

Citizen ScienceHow to generate your own imageryAdditional considerationsFuture Research

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Thank you!

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Acknowledgements: Kris Seymer, Andrew James, Ali Modarres


References

Balletti, C., Guerra, F., Tsioukas, V., & Vernier, P. (2014). Calibration of action cameras for photogrammetric purposes. Sensors (Basel, Switzerland), 14(9), 17471–90. doi:10.3390/s140917471Chow, J. (2012, April). Predators for Peace. Foreign Policy. Retrieved from http://foreignpolicy.com/2012/04/27/predators-for-peace/Crampton, J. W., Graham, M., Poorthuis, A., Shelton, T., Stephens, M., Wilson, M. W., & Zook, M. (2013). Beyond the geotag: situating “big data” and leveraging the potential of the geoweb. Cartography and Geographic Information Science, 40(2), 130–139. Retrieved from http://dx.doi.org/10.1080/15230406.2013.777137Eisenbeiss, H., & Grün, A. (2009). UAV Photogrammetry. Institute of Photogrammetry and Remote Sensing (Vol. Doctor of). doi:doi:10.3929/ethz-a-005939264Everaerts, J. (2008). The use of unmanned aerial vehicles (uavs) for remote sensing and mapping. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII, 1187–1192. Retrieved from http://www.isprs.org/proceedings/XXXVII/congress/1_pdf/203.pdfFornace, K. M., Drakeley, C. J., William, T., Espino, F., & Cox, J. (2014). Mapping infectious disease landscapes: unmanned aerial vehicles and epidemiology. Trends in Parasitology, 30(11), 514–519. doi:10.1016/j.pt.2014.09.001Haklay, M. (2013). Neogeography and the delusion of democratisation. Environment and Planning A, 45(1), 55–69. Retrieved from http://www.envplan.com/abstract.cgi?id=a45184Haklay, M. (2015). Citizen Science and Policy: A European Perspective.Kingsbury, P., & Jones, J. (2009). Walter Benjamins Dionysian Adventures on Google Earth. Geoforum, 40(4), 502–513.Lake, R., & Farley, J. (2007). Infrastructure for the Geospatial Web. In A. Scharl & K. Tochterman (Eds.), The geospatial web: How geobrowsers, social software, and Web 2.0 are shaping the network society (pp. 15–26). London: Springer.Meier, P. (2015). Digital Humanitarians: How Big Data is changing the face of humanitarian response. Boca Raton, FL: CRC Press Taylor & Francis Group.Nex, F., & Remondino, F. (2013). UAV for 3D mapping applications: a review. Applied Geomatics, 6(1), 1–15. doi:10.1007/s12518-013-0120-xPaulos, E., Foth, M., Satchell, C., Kim, Y., Dourish, P., & Choi, J. (2008). Ubiquitous Sustainability: Citizen Science and Activism. In Workshop at the 10th International Conference on Ubiquitous Computing (UbiComp 2008).Sandvik, K. B., & Lohne, K. (2014). The Rise of the Humanitarian Drone: Giving Content to an Emerging Concept. Millennium - Journal of International Studies, 43(1), 145–164. doi:10.1177/0305829814529470Sui, D., Goodchild, M., & Elwood, S. (2013). Volunteered Geographic Information, and the Growing Digital Divide. In D. Sui., S. Elwood, & M. Goodchild (Eds.), (pp. 1–12). Dordrecht: Springer.Sui, D. Z. (2008). The wikification of GIS and its consequences: Or Angelina Jolie’s new tattoo and the future of GIS. Computers, Environment and Urban Systems, 32(1), 1–5.Upton, V., Ryan, M., O’Donoghue, C., & Dhubhain, A. N. (2015). Combining conventional and volunteered geographic information to identify and model forest recreational resources. Applied Geography, 60, 69–76. doi:10.1016/j.apgeog.2015.03.007

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utilizing low-cost unmanned vehicle (uav) to build orthophotos and digital surface models

Technology