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From gigapixel timelapse cameras to unmanned aerial vehicles to smartphones: a review of emerging near remote sensing technologies for scaling from organism to ecosystem
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From gigapixel timelapse cameras to unmanned aerial vehicles to smartphones: a review of emerging near remote sensing technologies for scaling from organism to ecosystem


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  • 1. From gigapixel timelapse cameras to unmanned aerial vehicles:A review of emerging near remote sensing technologies for cross-scale monitoring from organism to ecosystem
  • 2. Limits to the rate of knowledge discovery in Ecology…Understanding high-order complexity is hard!1. The environment is complex and continuous but we usually can only measure limited data over limited snapshots in time2. Difficult and expensive to track change on the ground at high spatial and temporal resolution3. Long term data sets are rare, particularly of images – Typically only satellite-based tools and data sets for long term ecosystem monitoringEcosystem science research now is like genetics used to be before PCR and high throughput sequencing (but this is changing)
  • 3. The Future is arriving now By envisioning the future, we can bring it into being and shape it to meet our needs – What kind of hardware/software systems do we need to build? Imagine for any research site… – Live streaming access via laptop, phone, tablet – Multi-billion pixel resolution image feed of any study area – All data is archived for as long as there have been sensors With these tools, what kind of science and education will we do?Capitol Reef Webcam:
  • 4. Conventional ecosystem monitoringSatellite - Remote Sensing• Macro scale / Regional• Multi-spectral cameras – NDVI (Normalized Difference Vegetation Index), “Greenness”• Image Pixel data is georeferenced to a known location• Reliable time-series• But: – Limited resolution – Low sample rate (daily to annually) – Weather dependent
  • 5. Conventional ecosystem monitoringLand based - Field-level sampling• “Micro” scale / local• Stand-level sampling• Short time scales – Infrequent visits – 1 season or a few yearsHow to scale between ground-based sampling and regional-scale satellite sampling“Near remote” Sensing – Intermediate scale• Conventional aerial surveys (good data but expensive and infrequent)• New imaging technologies can bridge the data gap
  • 6. • Numeric data extraction is a challenging problem for image-based datasets• Map pixels from ground-based image sources onto the landscape (just like satellite data)
  • 7. Emerging technologies for ecosystem monitoring• Phenocam networks and towers – Plant Cams / Trail Cams – IP-based cameras• Gigapixel timelapse cameras (gigavision)• Unmanned Aerial Vehicles (UAV/UAS’s)• Kite & balloon photography – –• Socially networked science / Citizen Science – Smartphone applications and geotagged imagesOther enabling technologies• Wireless Internet – Satellite Internet – 802.11 wireless – Cellular: A 4G cell phone has about the same bandwidth as MODIS (and more processing power)• Wireless microclimate sensor arrays• Google Earth
  • 8. Near remote sensing: “Phenocam” Towers• Work well, particularly when coupled with ground-based sensor systems.• Enable capture of visible & infrared images of research areas – Ground-truth satellite data• But limited sampling area: FOV < 150m2
  • 9. Rio Mesa sensor systems• 30’ towers• Solar powered• 5 megapixel network cameras• Infrared cameras (NDVI)• Satellite images• Weather station• Tamarisk & cottonwood sap flux• Wireless network – 802.11  Satellite Internet
  • 10. Camera Systems
  • 11. Tamarisk year timelapse in Vis and IR:
  • 12. Rio Mesa “Gauge Site” - Results NDVI Tamarisk NDVI measured from tower based Infrared cameras at Rio Mesa Field Station, 2008-2009. [Nagler, Brown, Hultine, et al, in prep]Beetle Arrives Sap Flux
  • 13. Online data visualization tools
  • 14. Gigavision: gigapixel timelapse cameraMulti-billion pixel imaging system – Pan/Tilt camera system – Resolution of 1 pixel / cm over 7 hectares • (~600 million times the resolution of MODIS) – Monitor every individual plant within large area – Embed into Google Earth (should be pixel mapped) – Timelapse record of phenology & long term ecosystem changeCamera Specifications – Cellular (3G) or 802.11g wireless access – Automated capture up to 1 image / hr – 180 - 360° degree view – Power consumption: ~12w – Solar powered
  • 15. Image Visualization and Data Collection
  • 16. Area: 6-7 ha v=-_vzxzpJVjc&hd=1
  • 17. Unmanned Aerial Vehicles (UAVs) for Ecosystem Monitoring• GPS Autopilot can repeat sampling with +/- 3m accuracy• Flies @ 400’; 30-40 mph• Survey 1 km2 area in < 10 minutes @ 5 pixels /cm• 12 Megapixel consumer camera + 3MP Infrared Vegetation Camera (NDVI)• Each 12mp image covers 274x366 m2 area [MODIS = 1 pixel / 250x250 m2]• Resolution = ~100 pixels/m2• Commercial version: – $9,000 - $23,000, hardware (Total cost with training, software, etc: $30,000-$50,000)• DIY version: < $1,000 (• In the long term: Automated high resolution aerial imagery at long term sites like NEON• Main current challenge is regulatory RP Flight Systems
  • 18. 76 imagepanorama
  • 19. QuadroCopter Video:
  • 20. High Altitude “Satellite Replacement” systemsNASA Helios project• Prototype long endurance solar powered aircraft• Flies at 15,000 – 22,000m• 6 months flight time (solar + hydrogen cells)• 200 lb payload
  • 21. Kite / Balloon Aerial Photography
  • 22. Kite / Balloon Aerial Photography~40 image panorama of Chandeleur Island, LA, taken from a balloon
  • 23. 3D track of the balloon in the airHigh resolution image layer from balloon’s images, in Google Earth
  • 24. Other tools for data collectionGigapan• Low cost pan-tilt head for gigapixel repeat photography•• Repeat photography• Embed in Google Earth• Example: Early detection of bark beetle infestations at Alta Ski area, Alta, UT• See also: for an amazing example (72 gigapans shot on the same day to build a pixel-accurate 3D model of Yosemite)Game cameras / Plant cams – Wingscapes plant / birdcams – – Buckeye game cameras -- – $300 with solar panel – Smithsonian game camera projects website: CHDK – Convert a $50-$100 Canon into a 8MP timelapse camera – cost GPS• Eye-fi SD card – Add GPS/WiFi capabilities to any camera –• GPS loggers – $100 / Many brands, search amazon for “gps logger”• iPhone / Android apps – EveryTrail –
  • 25. Citizen Science• Picture Post –• Smartphone apps (See OOS22 session, Wed AM) – Virtual picture post – Panorama software (try the “360panorama” app for iPhone) – Phenology apps: • PhenoMap; BudBurst; others• Geo-tagged photos – Flickr: ~4 million images geotagged per month • 6 billion photos, 156 million are geotagged (Aug 2011) – Facebook: • 2.5 billion images uploaded / month – National Parks – 280 million visitors / yr (
  • 26. Geotagged Chicago© Eric Fischer ( )
  • 27. PhotosynthMicrosoft and U. Washington PhotoTourism and Photosynth projects – – –
  • 28. Creating a 3D map of Dubrovnik with 3.5 million flickr photos:
  • 29. Ecology’s PCR moment is coming…• Computers, hard drives and all technologies are getting faster, smaller and cheaper• New monitoring tools – Exponentially increase rates of data collection• Wireless technologies – Live data streams• Long term data collection projects (NEON, LTER, etc.) – Large, long-term standardized data sets – DataONE• Internet based data sharing – Collaborative, open-source science – Multi-disciplinary research – Increases in level of complexity that can be examined – Enhanced science education• Crowd-sourcing / Citizen science – Improved public education – Improved citizen engagement – Improved landscape monitoring – Increase rate of data collection and knowledge discovery• Improved programming and visualization tools – Larger data sets – Enhanced visualization and data management tools – Automated data processing – Easy to use analysis tools
  • 30. The seasons of flickr•
  • 31. Links and CreditsMore Info• Gigavision Gigapixel camera project:• TimeScience:• Interactive online data visualization:• Gigapan pan/tilt camera head: Search TimeScience• Kite photography:• Online mapping/image warping tool:• Hyperblimp:• DIY Drones: and thanks to• Programming and project support: – Christopher Zimmermann, TimeScience• USGS Tamarisk survey project: – Pamela Nagler, USGS – Kevin Hultine, University of Utah / N. Arizona University• Gigavision Project: – Justin Borevitz, University of Chicago
  • 32. CONTACTSCamera System design and Data Visualization Tools Tim Brown TimeScience 801.554.9296 http://www.time-science.comGigavision Camera Project / High Throughput Phenotyping Justin Borevitz University of Chicago / Australian National University borevitz@uchicago.eduTamarisk Sap Flux and Research Projects Pamela Nagler USGS, Sonoran Desert Research Station, Tucson, AZ Kevin Hultine Desert Botanical Garden, Phoenix, AZ
  • 33. • Gigapixel Yosemite –