The document discusses the challenges of monitoring ecological changes in a rapidly warming world with increasing population pressures. It argues that we can no longer rely on low-resolution ecological models and need to track environmental data at high frequencies and spatial resolutions over long periods of time. The TERN/ACEAS network is well-positioned to establish continent-wide monitoring and facilitate collaborative use of large ecological datasets. Advances in remote sensing, sensor networks, and phenomics now allow tracking environmental variables and organism phenotypes in high detail. This level of data collection will be essential to understand and minimize impacts of climate change on ecosystems and food production over the coming century.

1. Networks, pixels and smart devices
Next gen ecology in a changing world
Tim Brown, Postdoctoral Fellow
Research school of biology
Australian National University

2. More than 7 billion people on the planet for the next 100 years
(Figure: Ezeh et al. The Lancet - 14 July 2012

3. At the same time the global climate will warm by 3-6° C
• This will greatly increase variability and severity of weather events
• Growing regions will probably shift by 600 – 900 km (150Km/°C)
• We will need to produce 70% more food by 2050 to feed all these people1
Figure: Moritz & Agudo. 2013. Science 341 (6145), 504-508
1) Tester & LeGrange. 2010. Science:327(818)

4. Global climate will warm by 4-6° C by 2100
• 53% of Eucalyptus species will be out of their native ranges1
(Google Maps )
1) Hughes et al. Climatic range sizes of Eucalyptus species in relation to future climate
change. Global Ecology and Biogeography Letters (1996): 23-29.

5. If we believe what the science is telling us
the next century will not be a pleasant one.
The question is no longer “How do we prevent this?” it is:
“How do we minimize how bad things will get?”

6. If we believe what the science is telling us
the next century will not be a pleasant one.
The question is no longer “How do we prevent this?” it is:
“How do we minimize how bad things will get?”
We no longer have the luxury of using low resolution ecological models

7. If we believe what the science is telling us
the next century will not be a pleasant one.
The question is no longer “How do we prevent this?” it is:
“How do we minimize how bad things will get?”
We no longer have the luxury of using low resolution ecological models
We need to be tracking “everything” in the environment at high
frequency for long periods of time.

8. If we believe what the science is telling us
the next century will not be a pleasant one.
The question is no longer “How do we prevent this?” it is:
“How do we minimize how bad things will get?”
We no longer have the luxury of using low resolution ecological models
We need to be tracking “everything” in the environment at high
frequency for long periods of time.
TERN/ACEAS is uniquely positioned to facilitate this:
– Establishing long term continent-wide monitoring
– Pave the way for collaborative use of big data
– Data standards!

9. If we believe what the science is telling us
the next century will not be a pleasant one.
The question is no longer “How do we prevent this?” it is:
“How do we minimize how bad things will get?”
We no longer have the luxury of using low resolution ecological models
We need to be tracking “everything” in the environment at high
frequency for long periods of time.
TERN/ACEAS is uniquely positioned to facilitate this:
– Establishing long term continent-wide monitoring
– Pave the way for collaborative use of big data
– Data standards!
Near-surface remote sensing can vastly increase the temporal and
spatial resolution of available environmental data.

10. Genotype x Environment = Phenotype
Phenotype (and ecosystem function) emerges as a cross-
scale interaction between genotypes and their environment

11. Genotype x Environment = Phenotype
Phenotype (and ecosystem function) emerges as a cross-
scale interaction between genotypes and their environment
The degree to which we can measure G, E, P is the degree to
which we can understand ecosystem function

12. Genotype x Environment = Phenotype
Phenotype (and ecosystem function) emerges as a cross-
scale interaction between genotypes and their environment
The degree to which we can measure G, E, P is the degree to
which we can understand ecosystem function
• Phenomics lets us we split out
– Traits – the genetically heritable component of
phenotype
– Plasticity – the environmental component phenotype

13. Genotype x Environment = Phenotype
Phenotype (and ecosystem function) emerges as a cross-
scale interaction between genotypes and their environment
The degree to which we can measure G, E, P is the degree to
which we can understand ecosystem function
• Phenomics lets us we split out
– Traits – the genetically heritable component of
phenotype
– Plasticity – the environmental component phenotype
• What is the scale and rate of local adaptation?

14. Genotype x Environment = Phenotype
Phenotype (and ecosystem function) emerges as a cross-
scale interaction between genotypes and their environment
The degree to which we can measure G, E, P is the degree to
which we can understand ecosystem function
• Phenomics lets us we split out
– Traits – the genetically heritable component of
phenotype
– Plasticity – the environmental component phenotype
• What is the scale and rate of local adaptation?
• GxE=P lets us predict climate change impacts
– How “brittle” are specific ecosystems?

15. Current Work
How do we capture what is going on in the
environment, quantify it and provide it to scientists
(and the public) in a format that they can use?

16. Current Work
How do we capture what is going on in the environment,
quantify it and provide it to scientists (and the public) in a
format that they can use?
(1) Lab phenomics
– Identifying the genetic basis of plant growth and
development

17. Current Work
How do we capture what is going on in the environment,
quantify it and provide it to scientists (and the public) in a
format that they can use?
(1) Lab phenomics
– Identifying the genetic basis of plant growth and
development
(2) Field ecology
– High resolution monitoring of ecosystems

18. Current Work
How do we capture what is going on in the environment,
quantify it and provide it to scientists (and the public) in a
format that they can use?
(1) Lab phenomics
– Identifying the genetic basis of plant growth and
development
(2) Field ecology
– High resolution monitoring of ecosystems

19. Current Work
How do we capture what is going on in the environment,
quantify it and provide it to scientists (and the public) in a
format that they can use?
(1) Lab phenomics
– Identifying the genetic basis of plant growth and development
(2) Field ecology
– High resolution monitoring of ecosystems
How do we phenotype thousands of plants at high spatial and
temporal resolution at low cost.

20. Lab phenotyping
High precision measurements but low realism
In the lab we can control environment and measure phenotype with high precision
And we have to develop data pipelines to phenotype 2-3,000 plants continuously

21. Field phenotyping
Realistic environment but low precision measurements
In the field we have real environments but the complexity (and bad lighting!) reduces
our ability to measure things with precision

22. NextGen Ecology – Where’s my PCR?
• Ecology is like genetics before PCR and high throughput sequencing
• Remember back in the ’80s & early 90s when people would get a
PhD just sequencing a single gene?

23. NextGen Ecology – Where’s my PCR?
• Ecology is like genetics before PCR and high throughput sequencing
• Remember back in the ’80s & early 90s when people would get a
PhD just sequencing a single gene?
• Humane Genome Project cost $2.7billion USD and took 13 years
• Now (20 years in) we buy sequencing machines on ebay and light
sequence whole genomes for <$50 a plant in just a few weeks

24. Genetics -> Genomics -> Phenomics
20 years of technical advances have turned genetics into genomics into
phenomics and yielded the ability to address fundamental and very
complex questions

25. Genetics -> Genomics -> Phenomics
20 years of technical advances have turned genetics into genomics into
phenomics and yielded the ability to address fundamental and very
complex questions
Now state of the art phenomics is almost able to track “everything all the time”
• CSIRO High Resolution Plant Phenomics Center Glasshouse Capacity:
– Time-series hyperspectral and 3D imaging including Thermal & LIDAR

26. Genetics -> Genomics -> Phenomics
20 years of technical advances have turned genetics into genomics into
phenomics and yielded the ability to address fundamental and very
complex questions
Now state of the art phenomics is almost able to track “everything all the time”
• CSIRO High Resolution Plant Phenomics Center Glasshouse Capacity:
– Time-series hyperspectral and 3D imaging including Thermal & LIDAR
– Generates:
• 3D time-lapse models of every plant growing with each pixel in all spectra
mapped to the 3D “data cube” model of each plant

27. Genetics -> Genomics -> Phenomics
20 years of technical advances have turned genetics into genomics into
phenomics and yielded the ability to address fundamental and very
complex questions
Now state of the art phenomics is almost able to track “everything all the time”
• CSIRO High Resolution Plant Phenomics Center Glasshouse Capacity:
– Time-series hyperspectral and 3D imaging including Thermal & LIDAR
– Generates:
• 3D time-lapse models of every plant growing with each pixel in all spectra
mapped to the 3D “data cube” model of each plant
– Precision environmental controls

28. Genetics -> Genomics -> Phenomics
20 years of technical advances have turned genetics into genomics into
phenomics and yielded the ability to address fundamental and very
complex questions
Now state of the art phenomics is almost able to track “everything all the time”
• CSIRO High Resolution Plant Phenomics Center Glasshouse Capacity:
– Time-series hyperspectral and 3D imaging including Thermal & LIDAR
– Generates:
• 3D time-lapse models of every plant growing with each pixel in all spectra
mapped to the 3D “data cube” model of each plant
– Precision environmental controls
– Genome sequence for every plant

29. Genetics -> Genomics -> Phenomics
20 years of technical advances have turned genetics into genomics into
phenomics and yielded the ability to address fundamental and very
complex questions
Now state of the art phenomics is almost able to track “everything all the time”
• CSIRO High Resolution Plant Phenomics Center Glasshouse Capacity:
– Time-series hyperspectral and 3D imaging including Thermal & LIDAR
– Generates:
• 3D time-lapse models of every plant growing with each pixel in all spectra
mapped to the 3D “data cube” model of each plant
– Precision environmental controls
– Genome sequence for every plant
– Automated bioinformatics pipeline for trait extraction

30. Genetics -> Genomics -> Phenomics
20 years of technical advances have turned genetics into genomics into
phenomics and yielded the ability to address fundamental and very
complex questions
Now state of the art phenomics is almost able to track “everything all the time”
• CSIRO High Resolution Plant Phenomics Center Glasshouse Capacity:
– Time-series hyperspectral and 3D imaging including Thermal & LIDAR
– Generates:
• 3D time-lapse models of every plant growing with each pixel in all spectra
mapped to the 3D “data cube” model of each plant
– Precision environmental controls
– Genome sequence for every plant
– Automated bioinformatics pipeline for trait extraction
But ecosystems are more complex than plants in growth chambers…
We need significantly higher resolution capacity in the field

31. TERN will be a multi-decade project
NEON is 30-year project
• 30 years ago was ~1980 (everything was analog)
New technology will enable NextGen ecology too
1.http://www.popsci.com/node/31716
2.http://modis.gsfc.nasa.gov/about/specifications.php
3.https://www.lte.vzw.com/AboutLTE/VerizonWirelessLTENetwork/tabid/6003/Default.aspx

32. TERN will be a multi-decade project
NEON is 30-year project
• 30 years ago was ~1980 (everything was analog)
– The first space shuttle (1981) 1MB of RAM1 (your phone has 1000x this)
New technology will enable NextGen ecology too
1.http://www.popsci.com/node/31716
2.http://modis.gsfc.nasa.gov/about/specifications.php
3.https://www.lte.vzw.com/AboutLTE/VerizonWirelessLTENetwork/tabid/6003/Default.aspx

33. TERN will be a multi-decade project
NEON is 30-year project
• 30 years ago was ~1980 (everything was analog)
– The first space shuttle (1981) 1MB of RAM1 (your phone has 1000x this)
– 4G is the same bandwidth that MODIS uses to download a full satellite image of the
earth every day (MODIS: 6.1Mbps avg; Verizon 4G: 5-12Mbps 2,3)
New technology will enable NextGen ecology too
1.http://www.popsci.com/node/31716
2.http://modis.gsfc.nasa.gov/about/specifications.php
3.https://www.lte.vzw.com/AboutLTE/VerizonWirelessLTENetwork/tabid/6003/Default.aspx

34. TERN will be a multi-decade project
NEON is 30-year project
• 30 years ago was ~1980 (everything was analog)
– The first space shuttle (1981) 1MB of RAM1 (your phone has 1000x this)
– 4G is the same bandwidth that MODIS uses to download a full satellite image of the
earth every day (MODIS: 6.1Mbps avg; Verizon 4G: 5-12Mbps 2,3)
• When our kids grow up, what datasets can we have ready for
them to use?
New technology will enable NextGen ecology too
1.http://www.popsci.com/node/31716
2.http://modis.gsfc.nasa.gov/about/specifications.php
3.https://www.lte.vzw.com/AboutLTE/VerizonWirelessLTENetwork/tabid/6003/Default.aspx

35. Current capacity is very limited in most field work
“Typical” field site:
• One weather station (temp, humidity, rain
gauge, maybe soil moisture, sunlight)

36. Current capacity is very limited in most field work
“Typical” field site:
• One weather station (temp, humidity, rain
gauge, maybe soil moisture, sunlight)
• Much work is manual: hand measurements,
subjective observations, etc.
– Manual measurements are often only for
short time periods (e.g. 1-2 yrs)
– Repeat experiments to verify results are
often at a different site by different
observers

37. Current capacity is very limited in most field work
“Typical” field site:
• One weather station (temp, humidity, rain
gauge, maybe soil moisture, sunlight)
• Much work is manual: hand measurements,
subjective observations, etc.
– Manual measurements are often only for
short time periods (e.g. 1-2 yrs)
– Repeat experiments to verify results are
often at a different site by different
observers
• Some more advanced long term sites (e.g.
TERN, NEON, fluxnet), but little phenotyping

38. Field site of the future…
Within 10 years we could have:

39. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site

40. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site
• Daily hyperspectral and thermal data layered over every plant with cm accuracy

41. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site
• Daily hyperspectral and thermal data layered over every plant with cm accuracy
• Every long lived species is sequenced so population genetics is known

42. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site
• Daily hyperspectral and thermal data layered over every plant with cm accuracy
• Every long lived species is sequenced so population genetics is known
• Microclimate mesh sensor networks provide growth and environmental data for every tree

43. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site
• Daily hyperspectral and thermal data layered over every plant with cm accuracy
• Every long lived species is sequenced so population genetics is known
• Microclimate mesh sensor networks provide growth and environmental data for every tree
• Advanced visualization tools let you fly into any site to look around, grab data from any location
– Slide back in time and watch any interaction for as long as there have been sensors
– Query field sites globally for matching or contrasting environments with the same data and all
genetics available
– Back-end bioinformatics pipelines for automated data mining (cloud computing solutions)
– Generate snapshot and comparisons of data on the fly to share with colleagues

44. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site
• Daily hyperspectral and thermal data layered over every plant with cm accuracy
• Every long lived species is sequenced so population genetics is known
• Microclimate mesh sensor networks provide growth and environmental data for every tree
• Advanced visualization tools let you fly into any site to look around, grab data from any location
– Slide back in time and watch any interaction for as long as there have been sensors
– Query field sites globally for matching or contrasting environments with the same data and all
genetics available
– Back-end bioinformatics pipelines for automated data mining (cloud computing solutions)
– Generate snapshot and comparisons of data on the fly to share with colleagues
• Start new research projects beginning with all the data previously collected at a site

45. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site
• Daily hyperspectral and thermal data layered over every plant with cm accuracy
• Every long lived species is sequenced so population genetics is known
• Microclimate mesh sensor networks provide growth and environmental data for every tree
• Advanced visualization tools let you fly into any site to look around, grab data from any location
– Slide back in time and watch any interaction for as long as there have been sensors
– Query field sites globally for matching or contrasting environments with the same data and all
genetics available
– Back-end bioinformatics pipelines for automated data mining (cloud computing solutions)
– Generate snapshot and comparisons of data on the fly to share with colleagues
• Start new research projects beginning with all the data previously collected at a site
• In the field tablets, Google glass or similar augmented reality tools let you view high precision data
mapped onto the actual plants you are looking at

46. Field site of the future…
Within 10 years we could have:
• Time-series 3D model of every field site
• Daily hyperspectral and thermal data layered over every plant with cm accuracy
• Every long lived species is sequenced so population genetics is known
• Microclimate mesh sensor networks provide growth and environmental data for every tree
• Advanced visualization tools let you fly into any site to look around, grab data from any location
– Slide back in time and watch any interaction for as long as there have been sensors
– Query field sites globally for matching or contrasting environments with the same data and all
genetics available
– Back-end bioinformatics pipelines for automated data mining (cloud computing solutions)
– Generate snapshot and comparisons of data on the fly to share with colleagues
• Start new research projects beginning with all the data previously collected at a site
• In the field tablets, Google glass or similar augmented reality tools let you view high precision data
mapped onto the actual plants you are looking at
So how do we do this?

47. Gigapixel Imaging

48. Gigapixel Imaging
-
Golfer, 7km distant

49. (Single 15MP image)
Area: ~7ha
Area: ~1m2
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.
The super-high
resolution of the final
panorama lets you
monitor huge
landscape areas in
great detail.
Gigapixel Imaging – How it works

50. Gigavision: Gigapixel time-lapse camera
• 2008 - TimeScience (my company) & U Chicago (Borevitz Lab)
• Capture timelapse of every leaf on every tree within a few hectares

51. Gigavision: Gigapixel time-lapse camera
• 2008 - TimeScience (my company) & U Chicago (Borevitz Lab)
• Capture timelapse of every leaf on every tree within a few hectares
• ~1-2 billion pixels / panorama = Avg. resolution of ~1-2 pixel / cm over 7 hectares
– (~600 million > MODIS resolution)
• Solar powered; wireless/cellular
• Data management and extraction are a challenge

52. Gigavision: Gigapixel time-lapse camera
• 2008 - TimeScience (my company) & U Chicago (Borevitz Lab)
• Capture timelapse of every leaf on every tree within a few hectares
• ~1-2 billion pixels / panorama = Avg. resolution of ~1-2 pixel / cm over 7 hectares
– (~600 million > MODIS resolution)
• Solar powered; wireless/cellular
• Data management and extraction are a challenge
The Future
• Standardized control software (AXIS VAPIX protocols and PelcoD) would enable
almost ANY cheap PTZ camera to become a gigapixel timelapse camera
• Cloud solution for data processing -> Just buy a camera and plug it in and post-
processing is automatic  < $6,000 for complete wifi, solar gigapixel system

53. Unmanned Aerial Systems (UAV/UAS)
• Tech is very new
– Getting much easier & cheaper VERY quickly
• Current regs are restrictive
• But anyone can get started now for <$1,000
• Typically weekly or monthly repeat flights

54. Unmanned Aerial Systems (UAV/UAS)
• Tech is very new
– Getting much easier & cheaper VERY quickly
• Current regs are restrictive
• But anyone can get started now for <$1,000
• Typically weekly or monthly repeat flights
Gatewing (Trimble), ~$90,000 Sensefly.com, ~$15-30K
Custom built, Chris Gough
CanberraUAV (2KG payload)
Pocket Drone: $450
20min flight time
GoPro Mount
Control with tablet
Phantom 2
$700 on eBay
GoPro gimbal ptz
Control w/ phone

55. 3D Reconstruction from UAV images
• 5cm resolution 3D point cloud from UAV images
(DEM/orthorectified, etc).
– Software Cost: <$10K or $400/mo. Rental: pix4d.com
• UAV-ready 360 degree video (hardware + software): < $6,000 AUD
(kolor.com/video)
http://www.sphericalimages.com/

56. http://www.youtube.com/watch?v=-11Sb531lPs
Building a 6mm resolution 3D mesh from UAV images

57. Sequencing and microclimate sensors
Sequencing:
• Reduced representation plant genome sequence costs < $50/ plant
– Should be $10/plant within a few years, then ever cheaper

58. Sequencing and microclimate sensors
Sequencing:
• Reduced representation plant genome sequence costs < $50/ plant
– Should be $10/plant within a few years, then ever cheaper
Microclimate Sensors
• Currently expensive: ~$700/node. Will be <$100/node soon

59. Sequencing and microclimate sensors
Sequencing:
• Reduced representation plant genome sequence costs < $50/ plant
– Should be $10/plant within a few years, then ever cheaper
Microclimate Sensors
• Currently expensive: ~$700/node. Will be <$100/node soon
National Arboretum Phenomic Sensor Array (Funded!)
• 30 wireless mesh sensors measure microclimate
– Above ground: Temp/HG/Par
– Below Ground: Soil Temp / Moisture
• Micro-resolution wifi dendrometers
– 20 trees
• Two gigavision cameras
• All data live online in realtime
• Sequence all trees in study site
• Track phenology and survivorship along w/ microclimate
• UAV overflights (probably monthly) via CanberraUAV

60. Developing an International Phenocam Network
Everyone is installing cameras now because they
are cheap
Cheap IP cameras on eBay

61. Developing an International Phenocam Network
Everyone is installing cameras now because they
are cheap
The challenge:
• Get everyone on board using the same
cameras and protocols
Cheap IP cameras on eBay

62. Developing an International Phenocam Network
Everyone is installing cameras now because they
are cheap
The challenge:
• Get everyone on board using the same
cameras and protocols
• Standardization of camera type
– And rigorous testing protocols for new models
Cheap IP cameras on eBay

63. Developing an International Phenocam Network
Everyone is installing cameras now because they
are cheap
The challenge:
• Get everyone on board using the same
cameras and protocols
• Standardization of camera type
– And rigorous testing protocols for new models
• Build automated data extraction tools that can
be widely used
Cheap IP cameras on eBay

64. Developing an International Phenocam Network
Everyone is installing cameras now because they
are cheap
The challenge:
• Get everyone on board using the same
cameras and protocols
• Standardization of camera type
– And rigorous testing protocols for new models
• Build automated data extraction tools that can
be widely used
• What about QA/QC?
Cheap IP cameras on eBay

65. TERN is uniquely suited to help facilitate an international phenocam network
TERN can lead in:
• Collecting long-term datasets phenocam from all of its sites
– Good long term data
– Ground truth

66. TERN is uniquely suited to help facilitate an international phenocam network
TERN can lead in:
• Collecting long-term datasets phenocam from all of its sites
– Good long term data
– Ground truth
• Providing support and authority to the development of
standardized protocols

67. TERN is uniquely suited to help facilitate an international phenocam network
TERN can lead in:
• Collecting long-term datasets phenocam from all of its sites
– Good long term data
– Ground truth
• Providing support and authority to the development of
standardized protocols
• Building and promoting collaboration with other national and
international phenocam efforts
– NEON phenocam workshop (October 2013)
– ACEAS phenocam workshop (March 2014)
– Asia, Europe?

68. TERN is uniquely suited to help facilitate an international phenocam network
TERN can lead in:
• Collecting long-term datasets phenocam from all of its sites
– Good long term data
– Ground truth
• Providing support and authority to the development of
standardized protocols
• Building and promoting collaboration with other national and
international phenocam efforts
– NEON phenocam workshop (October 2013)
– ACEAS phenocam workshop (March 2014)
– Asia, Europe?
• Developing methods for handling big data and data
interoperability

69. Enabling Phenocam networks: How do we get everyone on board?
• Reduce barriers to participation at all levels
– Google method…
• Make using their tools cheaper and easier than anyone other
• Provide significant value-added for users at low or no cost

70. Enabling Phenocam networks: How do we get everyone on board?
• Reduce barriers to participation at all levels
– Google method…
• Make using their tools cheaper and easier than anyone other
• Provide significant value-added for users at low or no cost
• Provide turn-key hardware systems
– Lots of cameras available, but not all cameras are created equally
– Work with vendors to create turnkey hardware options?
– Pre-configured
– Robust
– Easy to install, use and maintain

71. Enabling Phenocam networks: How do we get everyone on board?
• Reduce barriers to participation at all levels
– Google method…
• Make using their tools cheaper and easier than anyone other
• Provide significant value-added for users at low or no cost
• Provide turn-key hardware systems
– Lots of cameras available, but not all cameras are created equally
– Work with vendors to create turnkey hardware options?
– Pre-configured
– Robust
– Easy to install, use and maintain
• Provide free tools for
– Free or low cost data storage
– Consensus data products with QC/QA
– Desktop and web playback and analysis tools that are free or low cost if data complies with
standards

72. Enabling Phenocam networks: How do we get everyone on board?
• Reduce barriers to participation at all levels
– Google method…
• Make using their tools cheaper and easier than anyone other
• Provide significant value-added for users at low or no cost
• Provide turn-key hardware systems
– Lots of cameras available, but not all cameras are created equally
– Work with vendors to create turnkey hardware options?
– Pre-configured
– Robust
– Easy to install, use and maintain
• Provide free tools for
– Free or low cost data storage
– Consensus data products with QC/QA
– Desktop and web playback and analysis tools that are free or low cost if data complies with
standards
• Data can be hosted anywhere as long as it is standardized and discoverable

73. Let’s build a phenocam network where it takes 1 minute to sign up

74. Let’s build a phenocam network where it takes 1 minute to sign up

75. Let’s build a phenocam network where it takes 1 minute to sign up

76. Let’s build a phenocam network where it takes 1 minute to sign up
• Archives are automatically and stored in
permanent archive solution
• User gets instant embed codes for
putting the timelapse and data on their
site
• Timelapse and data can be embedded
anywhere on any other sites
• Users can create bookmarks of datasets
to send to others

77. Let’s build a phenocam network where it takes 1 minute to sign up
• Archives are automatically and stored in
permanent archive solution
• User gets instant embed codes for
putting the timelapse and data on their
site
• Timelapse and data can be embedded
anywhere on any other sites
• Users can create bookmarks of datasets
to send to others
Funded !
(NCRIS phenomics
infrastructure)

78. http://www.uvu.edu/crfs/livefeed/http://phenocam.sr.unh.edu/webcam/sites/bartlettir/
Data/Image visualization
http://www.doublejackauctions.com/pheno/2012/
Visualization needs to:
• Enhance research usability
• Improve collaboration
• Enhance education and
outreach opportunities

79. Final questions
• I always focus on things from a “capacity” perspective
because I think more data is always better so When we
are no longer limited by data or interfaces what science
would we do?

80. Final questions
• I always focus on things from a “capacity” perspective
because I think more data is always better so When we
are no longer limited by data or interfaces what science
would we do?
• All the pieces exists to build these systems how do we
get from here to there? What can we do first?

81. Final questions
• I always focus on things from a “capacity” perspective
because I think more data is always better so When we
are no longer limited by data or interfaces what science
would we do?
• All the pieces exists to build these systems how do we
get from here to there? What can we do first?
• How can we best enable collaborations that enhance our
collective ability to advance near-surface remote
sensing?

82. Final questions
• I always focus on things from a “capacity” perspective
because I think more data is always better so When we
are no longer limited by data or interfaces what science
would we do?
• All the pieces exists to build these systems how do we
get from here to there? What can we do first?
• How can we best enable collaborations that enhance our
collective ability to advance near-surface remote
sensing?
• End users – what do you need?

83. Final questions
• I always focus on things from a “capacity” perspective
because I think more data is always better so When we
are no longer limited by data or interfaces what science
would we do?
• All the pieces exists to build these systems how do we
get from here to there? What can we do first?
• How can we best enable collaborations that enhance our
collective ability to advance near-surface remote
sensing?
• End users – what do you need?
• What are the core science questions near-remote
sensing can better answer?

84. The pace of change is accelerating
Panono (panono.com)
• 108MP instant panoramas
• $600AUD
• Indiegogo: $1.2 M USD
Oculus Rift (oculusvr.com)
• Immersive 3D VR goggles
• $350AUD
• Kickstarter: $2.4 Million USD
Structure 3d scanner (structure.io/)
• 2mm res 3D scanner for ipads
• Fully hackable with open SDK
• $350AUD
• Kickstarter: $1.3M USD
Some new crowd funded tech from just last year
Kickstarter has raised $1 billion USD in donations since 2009

85. media.pixelcase.com/360video/huntervalley/index.html

86. How do we process all this stuff?!
• In < 5 years Google has created 360 deg panoramas of 5 million
miles of streets (20 petabytes of geo referenced data) 1
Images
• Facebook
– 350 million (mostly georeferenced) images uploaded / day
• A picture a minute, 15hrs a day from 60 NEON sites for 18 years is < 350 million
– 250 billion images stored (with backup and instant retrieval)
(1) http://www.engadget.com/2012/06/06/google-street-view-20-petabytes/
(2) http://www.google.com/maps/about/behind-the-scenes/streetview/

87. Credits & Thanks
Justin Borevitz and the Borevitz Lab, ANU
borevitzlab.anu.edu.au
Gigavision Camera Project
Justin Borevitz, U. Chicago, Now ANU
Christopher Zimmermann, (Time-Science.com)
Phenocam Projects
Utah & Nevada Phenocams:
- Pamela Nagler, USGS; Kevin Hultine, DBG
FNQ phenocam: Mike Liddell, TERN / Supersite Network
US Phenocam Network (Hardware and protocols):
- Andrew Richardson, Harvard
Funding
- ACEAS: Phenocam workshop
- FNQ Camera (who funded the FNQ camera?)
- NEON/NSF: US Phenocam Workshop
- NCRIS: Phenocam camera admin server
- ANU Major Equipment Grant: National Arboretum sensor array
Find me here: bit.ly/Tim_ANU
WEB: borevitzlab.anu.edu.au
Find me here: http://bit.ly/Tim_ANU
Or Google: Tim Brown anu