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Sensor Networks & Sensor Systems NEON CAO Chris Field & Greg Asner Department of Global Ecology Carnegie Institution Stanford, CA 94305 www.global-ecology.org.

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Presentation on theme: "Sensor Networks & Sensor Systems NEON CAO Chris Field & Greg Asner Department of Global Ecology Carnegie Institution Stanford, CA 94305 www.global-ecology.org."— Presentation transcript:

1 Sensor Networks & Sensor Systems NEON CAO Chris Field & Greg Asner Department of Global Ecology Carnegie Institution Stanford, CA

2 NEON: a continental scale ecological observation platform Understanding and forecasting the impacts of climate change, land use change on continental-scale ecology

3 NEON Science Vision Provide the capacity to forecast future states of continental-scale ecological systems for the advancement of science and the benefit of society.

4 NEON Education Vision Prepare society and the scientific community to use NEON data, information, and forecasts in order to understand and effectively manage Grand Challenge ecological issues.

5 NEON Fundamental Science Challenges Challenge #1 How will ecosystems and their components respond to changes in natural- and human- induced forcings spatial and temporal scales? And, what is the pace and pattern of the responses?

6 NEON Fundamental Science Challenges Challenge #2 How do the internal responses and feedbacks of biogeochemistry, biodiversity, hydroecology and biotic structure and function interact with changes in climate, land use, and invasive species?

7 Grand Challenge Areas in the Environmental Sciences Biodiversity Biodiversity Biogeochemical cycles Biogeochemical cycles Climate change Climate change Hydroecology Hydroecology Infectious disease Infectious disease Invasive species Invasive species Land use Land use

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12 Developing the NEON strategy What to measure? What to measure? How to make the measurements? How to make the measurements? How to scale? How to scale? How to synthesize? How to synthesize? How to move from analysis to forecasting? How to move from analysis to forecasting?

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14 Laser Detection and Ranging (LIDAR)

15 Derivation of quantitative requirements: Spatial stratification and scaling strategy

16 Spatial Scaling Strategy LUAP AOP Sites/Exps Ecological Forecast models

17 Temperature Trends

18 Precipitation Trends

19 Hargrove representativeness analysis within NEON domains red=soil/landform; green= current veg; blue=climate 20% of full resolution Water bodies masked to black G. Henebry 1/25/2007

20 NEON Domains and Deployment

21 NEON Domains and Deployment (Con’t)

22 Derivation of quantitative measurement requirements by Observing System Simulation flux PAR Hanta

23 Temporal Scaling Strategy

24 NEON Facilities for Science and Education 20 Core sites (FIU and FSU) 20 Core sites (FIU and FSU) 40 Relocatable sites (FIU and FSU) 40 Relocatable sites (FIU and FSU) 18 Mobile laboratories 18 Mobile laboratories 2 Airborne Observing Packages 2 Airborne Observing Packages 10 STREON experiments 10 STREON experiments 4-5 Global change experiment sites 4-5 Global change experiment sites Land Use Analysis Package Land Use Analysis Package QA/QC Lab QA/QC Lab Data and forecast product production facility Data and forecast product production facility

25 Mapping of Grand Challenge Areas to Network Design D 01 D 02 D 03 D 04 D 05 D 06 D 07 D 08 D 09 D 10 D 11 D 12 D 13 D 14 D 15 D 16 D 17 D 18 D 19 D 20 E1E2 INVASV BIODIV LAND USE BIOGEO ECO- HYDRO CLIMATE D01-D20: Domains 1-20 E1 = STREON Experiment E2 = Global Change Experiment

26 Mapping of Grand Challenge Areas to Network Design: Core Sites D 01 D 02 D 03 D 04 D 05 D 06 D 07 D 08 D 09 D 10 D 11 D 12 D 13 D 14 D 15 D 16 D 17 D 18 D 19 D 20 E1E2 INVASV BIODIV LAND USE BIOGEO ECO- HYDRO CLIMATE D01-D20: Domains 1-20 E1 = STREON Experiment E2 = Global Change Experiment = addressed by Core sites. = not addressed

27 Mapping of Grand Challenge Areas to Network Design: Relocatables D 01 D 02 D 03 D 04 D 05 D 06 D 07 D 08 D 09 D 10 D 11 D 12 D 13 D 14 D 15 D 16 D 17 D 18 D 19 D 20 E1E2 INVASV BIODIV LAND USE BIOGEO ECO- HYDRO CLIMATE D01-D20: Domains 1-20 E1 = STREON Eperiment E2 = Global Change Eperiment = addressed by relocatable systems

28 Mapping of Grand Challenge Areas to Network Design: Experiments D 01 D 02 D 03 D 04 D 05 D 06 D 07 D 08 D 09 D 10 D 11 D 12 D 13 D 14 D 15 D 16 D 17 D 18 D 19 D 20 E1E2 INVASV BIODIV LAND USE BIOGEO ECO- HYDRO CLIMATE D01-D20: Domains 1-20 E1 = STREON Experiment E2 = Global Change Experiment = addressed by national experiments

29 NEON System Architecture

30 NEON Budget NEON budget still being negotiated with NSF and Congress. NEON budget still being negotiated with NSF and Congress. Construction budget will be $ million over ten years Construction budget will be $ million over ten years MREFC account.MREFC account. M&O: ~ 15% of construction M&O: ~ 15% of construction 12 million in MREFC dollars are currently appropriated for NEON 12 million in MREFC dollars are currently appropriated for NEON

31 NEON Timeline Construction - MREFC Planning plus R&D Maintenance and Operations Research

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33 Access to impacts of land-use and climate change At a spatial scale compatible with high accuracy, and with sensitivity to a wide range of drivers, plus direct and indirect responses Aircraft measurements very inexpensive, relative to satellites Aircraft platforms simple to maintain and upgrade Ironically, US governmental support has been waning, even as the opportunities incease The Need for Regional-scale Observations

34 Land Cover Landsat MSS Landsat TM Landsat ETM+ TIROS NASA EOS Land Cover Global Physiology NOAA 1970s 1980s 1990s 2000s 2010s L and Cover SatelliteMultispectralSensing 1970s 1980s 1990s 2000s 2010s Low-fidelity High-fidelity imaging spectroscopy Early Ecosystem Chemistry Ecosystem Chemistry Aircraft Full Spectral Sensing Evolution of ecological remote sensing systems -- hyperspectral High Resolution Land Cover NOAA

35 Passive Remote Sensing Basics From 1970s to present, satellites only take a sample of these reflectance ‘signatures’. Now we can see the entire signature…

36 The Imaging Spectroscopy Concept

37 Airborne Hyperspectral Sensing

38 Leaf and canopy studies

39 Kilauea Caldera Canopy Chemistry  Invasive Species Hedychium in forest understory (high canopy water) Myrica invasion front (high leaf nitrogen) Myrica infestations (high leaf nitrogen and high canopy water)

40 Carnegie Invasive Species Program in Hawaii Hedychium Miconia calvensens African grasses Myrica faya Psidium cattleianum

41 Land Cover Landsat MSS Landsat TM Landsat ETM+ TIROS NASA EOS Land Cover Global Physiology NOAA 1970s 1980s 1990s 2000s 2010s L and Cover SatelliteMultispectralSensing 1970s 1980s 1990s 2000s 2010s Low-fidelity High-fidelity imaging spectroscopy Early Ecosystem Chemistry Ecosystem Chemistry Aircraft Full Spectral Sensing and Laser Evolution of ecological remote sensing systems – hyperspectral plus LIDAR LIDAR Ecosystem Structure High Resolution Land Cover NOAA

42 Laser Detection and Ranging (LIDAR) + Imaging Spectroscopy The Carnegie Airborne Observatory What does this system deliver? Detailed chemical, structural and biological information on ecosystem health on land and in coastal environments, and at a spatial resolution commensurate with conservation, management, and planning

43 Spectrometer + LIDAR In-flight Data Fusion Hilo, Hawai’i 0.5 m spatial resolution, full-waveform, 70,000 hz

44 Example CAO LiDAR waveforms for forest canopy profiling and forest floor detection Subset image of waveform height (m) Sample waveforms Single tree crown (30-60 waveforms)

45 CAO instrument control system fully operational

46 CAO Instrument Sensor Head Assembly

47 3-D Forest and Topographic Imaging – Rainforest and cattle pasture, Laupahoehoe Forest Reserve 1.0 m spatial resolution, 100,000 htz

48 Spectrometer – 1/3 of swath, 1.0 m spatial resolution, 7 nm spectral resolution

49 Spectrometer – 1/3 of swath, 1.0 m spatial resolution, canopy carotenoid pigments

50 Spectrometer + LIDAR In-flight Data Fusion Laupahoehoe Forest Reserve, Hawai’i 1.0 m spatial resolution Canopy pigment retrieval at sub-tree crown spatial resolution

51 High Car:Chl Ratio Low Car:Chl Ratio Car:Chl ratio inversely proportional to carbon uptake efficiency (LUE) CAO Test Flight – Nov 12, 2006 Laupahoehoe Rainforest Reserve, Hilo, Hawai’i Top-of-canopy Carotenoid Pigments  Light-use Efficiency Analysis crown-by-crown (sunlit vs. shaded sides of crowns)

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53 Concluding thoughts Continental scale ecology creates vast challenges (& opportunities) Huge numbers of sensors Large distances Little or no power Diverse kinds of data Diverse kinds and levels of users New opportunities for aircraft Increased need for validation and auxiliary data Grand challenge questions will require grand challenge creativity


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