This document discusses using gigapixel resolution time-lapse imaging to monitor phenological changes in plants over large landscapes. A new camera system called Gigavision was created that can capture daily 1.5 billion pixel panoramas over 7 hectares from a single vantage point using solar power. Over two growing seasons, the camera captured over 184,000 images totaling 6 terabytes of data. The high-resolution images allow identifying over 500 individual plants and monitoring their growth and changes over time. Such long-term, high-resolution ecological data collection could improve understanding of ecosystem dynamics.
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Gigapixel imaging, ESA Australia, Dec 2012
1. Gigapixel resolution time-lapse imaging for phenological
monitoring of every plant in a landscape.
http://bit.ly/CBR-1
Tim Brown, Postdoctoral Fellow,
Borevitz Lab, Australia National University
www.borevitzlab.anu.edu.au
2. To address the environmental and
management challenges of the 21 st century we
need a substantially better understanding of
how ecosystems work.
– Exponentially more data
– Better models
– Long time-series data sets
2
3. Ecology – Where’s my PCR?
Understanding high-order complexity is hard!
1. The environment is complex and continuous but we typically only
measure limited data over limited snapshots in time
2. Difficult and expensive to track change on the ground at high spatial and
temporal resolution
3. Long term data sets are rare, particularly of images
– Satellite data is good but not high enough resolution for many applications
1. Hard to maintain field-based research over ecologically meaningful time
periods with high enough sample size
To understand ecosystems we need to be tracking “everything” in the
environment at high time-rates for long periods of time.
4. • What if we could watch every plant in our field
sites from our desk?
– Map out population genetics, biotic/abiotic data on
the landscape
– Slide back in time and watch any interaction for as
long as there have been sensors
– Students start new research projects beginning with
all the data previously collected at a site
The technology is here – We need to dream big!
4
5. Gigavision: gigapixel timelapse camera
Collaboration between
Borevitz Lab (U. Chicago, USA) and TimeScience (my company)
The Challenge:
• Build a solar powered, weatherproof gigapixel camera that can record
daily phenology from every plant in a field area.
6. Gigapixel Imaging – How it works
The Gigapan and
Gigavision systems
allow you to capture
hundreds or
thousands of
zoomed-in images in
a panorama.
Images are then
“Stitched” into a
seamless panorama.
(Single 15MP image)
Area: ~7ha
The super-high
resolution of the final
panorama lets you
monitor huge
landscape areas in
great detail.
Area: ~1m2
7. The Gigavision Camera – Specifications
• ~1.5 billion pixels / panorama
• Avg. resolution of ~1 pixel / cm over 7 hectares
– (~600 million times the resolution of MODIS)
• Open-source - Built with off-the-shelf components
• Cellular (3G) or 802.11g wireless access (160MP “thumbnails”)
• Automated capture up to 1 image / hr
• Solar powered (<15w power consumption)
• ~$30,000 -> could be more like $10-15,000
• “Light-phenotyping” of >500 plants for ~$60/plant
For full specs, see Brown et al. 2012.
(Google: “gigavision chapter”
16. Limiting factor is increasingly software
• For example:
– Axis Q-6035e
• $4,000 USD
• Can run on-board software
• ~2 gigapixel image in < 10 min at any focal length
• Temp range: -40 to +50C
• 50W
16
17. GigaPan – Low Cost Gigapixel Imaging
GigaPan (non-timelapse)
• $350-$1,000
• Works with any camera
• Great for documentation and low time-resolution monitoring (e.g. monthly, annual)
Example:
• Alta Ski Area Bark Beetle Project
– Maura Olivos, Alta Environmental Center
– Annual gigapixel survey images
– Identify beetle infested trees for removal
– Online panoramas:
http://gigapan.com/galleries/5582/gigapans
• More examples of gigapans here:
• http://gigapan.com/profiles/TimeScience
• GigaPan hardware: http://www.gigapan.com/
18. Alta Bark Beetle Project – Initial survey path for potential panorama locations
Data collected with EveryTrail smartphone app (http://www.everytrail.com/ )
Panoramas: http://gigapan.org/galleries/6787/gigapans
24. Project summary statistics
Site Name Approximate Area Image Resolution Average Pixel Resolution
(Acres) (Gigapixels) (Pixels per square inch)
Collins Weather Station 697 4.07 0.93
Baldy Shoulder 770 8.84 1.83
Road Shot 211 3.26 2.46
Grizzly Gulch 188 3.65 3.1
Total: 23.5 billion px
TOTALS 830 acres Avg: ~3.2 px/cm2
Avg: 4.7 billion px
(Area Estimates: http://www.earthpoint.us/Shapes.aspx)
25. Funding sources and many thanks to…
TimeScience / www.time-science.com
• Christopher Zimmermann (Data management, image processing, online interface)
University of Chicago
• Justin Borevitz (U. Chicago, not at ANU)
• Nina Noah, Whitney Panneton (University of Chicago)
GigaPan Systems – http://Gigapan.org
Download this talk here:
http://bit.ly/ESA2012