Wireless Sensor Networks and Drones for Measuring Forest Photosynthetic Biophysics
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Talk I gave at the University of Alberta GIS DAY 2015
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Wireless Sensor Networks and Drones for Measuring Forest Photosynthetic Biophysics
- 1. Synergistic Use of Ground Sensor Networks and ‘Drones’ for Measuring Forest Photosynthetic Biophysics Cassidy Rankine, PhD Candidate Arturo-Sanchez-Azofeifa (PI) U of A’s Center for Earth Observation Sciences
- 2. Presentation Overview • What is a wireless sensor network and why use them for GIS and geomatics? • Optical WSNs for forest photosynthetic monitoring • What are lightweight UAVs (aka civilian drones) and how can they be used for GIS? • Combining WSNs and UAVs for remote sensing of forest productivity (health and resilience)
- 5. Satellite Remote Sensing & Earth Observation Sciences
- 7. Assessments of global change impacts have identified phenology as a key indicator of ecosystem alteration (IPCC 2007; Morisette et al. 2009) Breathing Earth – IDV Solutions. From NASA satellite imagery
- 8. 45% of solar radiation in visible & photosynthetic spectrum 400-700nm Photosynthetic Active Radiation =
- 9. f raction of A bsorbed P hotosynthetically A ctive R adiation
- 10. Light Use Efficiency Model of Plant Productivity Gross Primary Productivity = iPAR x FPAR x LUE • iPAR = Incident Photosynthetically Active Radiation – Depends on atmospheric conditions • FPAR = Fraction of Photosynthetically Active Radiation Absorbed – Depends on canopy structure (ie. Leaf Area) • LUE (ε)= Light Use Efficiency = εmax x STair x SVPD
- 11. Biospheric Process Modelling requires integration of multi-scale observations to relate ecosystem structure to function
- 13. The air above dense forests is often hard to see through!
- 14. Near-Surface Remote Sensing • Remote observations (touchless/non- destructive) of physical features or processes below the majority of the atmospheric air mass, typically within 100m of the target • Emerging approach to investigate whole ecosystem dynamics Examples - LTER, TERN, FLUXNET, NEON
- 15. NSRS Methods • Manual Measurements • Tripod/Tower Mounted • Canopy Cranes • Balloons • Ultra-Low Aircraft • Ground Sensors • Unmanned Aerial Vehicles
- 17. Tropi-Dry Phenology Tower, Sanchez et al. (2008) Downwelling Light Upwelling Light Shortwave Solar Radiation PAR
- 18. Wireless Sensor Networks (WSNs) Expanding Our Observational Senses in Ecology and Earth Sciences NODESNETWORKS
- 19. WSN Advantages • Real-time data retrieval capabilities • Increased spatial coverage with distributed sensing • Synchronized sampling across sensors • Landscape scale remote sensing validation • Non-intrusive!
- 20. Mobile / Scalable deployments Readily deployed, less intrusive
- 21. Broadband PAR Sensors • Photosynthetically Active Radiation (PAR = 400-700nm) • Hemispherical sensors (180° FOV)
- 22. Synchronized PAR sensors above and below canopy FAPAR = 1 - t - r t = fraction of PAR transmitted through canopy r = fraction of PAR reflected by canopy FAPAR
- 23. 3D Understory Light Contours (canopy transmitted light in deciduous tropical forest at 1m height)
- 24. 0.2 0.4 0.6 0.8 1 FractionofInterceptedPAR Tropical Dry Forest In-Situ WSN Canopy FIPAR 2008-2012 ʃfPAR = Forest Productivity Rankine et al, 2012 - IEEE International Geoscience and Remote Sensing Symposium 2012 Canopy Biophysics
- 25. auscover.org Near-Surface Remote Sensing of Ecosystems Using Sensor Networks
- 26. auscover.org Remote Sensing of Ecosystems
- 27. Lightweight UAVs
- 28. Mapping Forests with UAVs OrthoMosaics
- 29. Modelling Forests with UAVs Photogrammetry
- 30. Mapping & Modelling Forests with UAVs Allows us to see the forest for the trees!
- 31. 1.9 x 1.9 km n = 115 TM 2011 Location A Location B Case Study: Coal Valley Alberta LandSat Imagery Optical Wireless Sensor Networks
- 33. WSN - UAV Synergies
- 34. Initial Results Methods: • Optical ground WSN (fAPAR) • PAR albedo UAV Figure: Overlaid UAV albedo flight path on Spot Satellite Imagery with WSN daily mean fAPAR values. Composed in ESRI ArcMap.
- 38. Thank You!
- 39. Photo/Video Credits • Livescience.com • Diydrones.com • Carbomap.wordpress.com • Conservationdrones.org • Heliguy.com • Dronemapper.com • Uasvision.com • Videohive.net • Aeryon.com • Droneblog.com • Photogrammetricpractica.org • Carleton.edu • Nasa.edu
Editor's Notes
- As ecosystem phenology changes, so does primary productivity
- PAR_VIS light life on earth evolved to utilize these wavelengths not coincident we see and plants use these same wavelengths, very useful band energetically for life
- Gross primary production (GPP) is the amount of chemical energy as biomass that primary producers create in a given length of time. (GPP is sometimes confused with Gross Primary productivity, which is the rate at which photosynthesis or chemosynthesis occurs.) Some fraction of this fixed energy is used by primary producers for cellular respiration and maintenance of existing tissues (i.e., "growth respiration" and "maintenance respiration").[2] The remaining fixed energy (i.e., mass of photosynthate) is referred to as net primary production (NPP).
- Scaling Up – ground up remote sensing quantum flux, 8-10 photons to fix 1 CO2 molecule how to quantify at larger scales? We work from meso scale – canopy to pixel and image scale
- Examples include photography, meteorological sensors, infrared carbon flux, scintillometers, laser trace gases, lidar systems
- The marriage of satellite/airborne data with accurate ground based measurements
- The sun produces light with a distribution similar to what would be expected from a 5525 K (5250 °C) blackbody, which is approximately the sun's surface temperature
- Cables are expensive, time and money, significantly limits coverage distance, and can interfere with plot. Non-intrusive! Synchromization is important Enter the EOSL...
- SQ-110 response: 4 http://www.apogeeinstruments.co.uk/sq-110-sun-calibration-quantum-sensor/09-659nm
- Transmitted par is averaged across the entire understory sensor network FAPAR more robust to changes in spatial resolution of observation. Compared to LAI, fPAR is a flux ratio, advantage being that retrieval accuracy less dependent on canopy 3D structural knowledge – Meroni et al., 2012
- ----- Meeting Notes (13-04-09 10:11) ----- MODIS resolution not as good integrated fAPAR linearly related the GPP for the period of observation Burts of Carbon Sequestration!
- Collaborations with computer sciences, electrical engineering, physics, and industry enables rapid advancement of research capabilities in earth system monitoring Sensor cloud demo anyone? http://sensorcloud.com/