A Myopic History of Great Lakes Remote Sensing - PowerPoint PPT Presentation

a myopic history of great lakes remote sensing n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
A Myopic History of Great Lakes Remote Sensing PowerPoint Presentation
Download Presentation
A Myopic History of Great Lakes Remote Sensing

play fullscreen
1 / 115
A Myopic History of Great Lakes Remote Sensing
125 Views
Download Presentation
naomi
Download Presentation

A Myopic History of Great Lakes Remote Sensing

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. A Myopic History of Great Lakes Remote Sensing Dr. John R. Schott Digital Imaging and Remote Sensing Laboratory (DIRS) Center for Imaging Science Rochester Institute of Technology schott@cis.rit.edu

  2. Lake Ontario Comparison of Temperature & Transmission Temperature % Transmission

  3. Ontario Mid-lakeTemperature Sections late April mid May early June late June

  4. May 25, 1978ITOS

  5. Skylab Photos: chlorophyll maps

  6. AVHRR Lake Ontario Thermal Bar

  7. HCMM Lake Ontario Thermal Bar

  8. IFYGL Aerial Photos Off Ginna May 22, 1978

  9. Landsat Evolution Number of Bands Spot Size Year 1972 4 80 m 1982 7 30 m 1999 7 15 m Rochester false color infrared true color

  10. Landsat TM

  11. Landsat TM Ontario Thermal Bar

  12. LANDSAT: April 23, 1991 Lakes Ontario & Erie Cold center Warm ring True Color Composite Thermal Channel

  13. Landsat TM April 23, 1991

  14. LANDSAT: May 11, 1992 Lakes Ontario & Erie Cold center Warm ring True Color Composite Thermal Channel

  15. Landsat June 12, 1992 True Color Composite Thermal Channel

  16. Landsat TM Braddock Bay to Irondequoit Bay True Color Composite (Enhanced) Thermal band warm cold June 23, 1996

  17. Linking Hydrodynamic Models with Remotely Sensed Data

  18. AGLE Simulation including Niagara Inflow 22C 0C 4C 11C

  19. Hyperspectral Imagery

  20. MISIRIT’s Modular Imaging Spectrometer Instrument Ginna Nuclear Power Plant

  21. MISIRIT’s Modular Imaging Spectrometer Instrument West Roch Embayment Russell Power Plant July 5, 2000 Altitude=4000ft East Roch Embayment Genesee River Plume July 5, 2000 Altitude=4000ft MISI thermal image of Russell Power Plant Effluent

  22. MODIS Moderate Resolution Imaging Spectroradiometer Resolution Trades: Temporal: Global Coverage in 1- 2 days Spatial: 1 km pixels (low) Spectral: 36 bands .4-14.4um

  23. MODIS March 5, 2005

  24. SeaWiFS April 12, 1998

  25. SeaWiFS September 3, 1999

  26. Hyperspectral Imagery: AVIRIS solar glint AVIRIS Flightlines May 20, 1999 11:45 AM Digital Imaging and Remote Sensing Laboratory

  27. Hyperspectral Concentration Maps AVIRIS Image Cube: Lake Ontario Shoreline • Provide user community with water quality maps derived from hyperspectral data to address environmental issues. Dr. Rolando Raqueno

  28. Spectral Bottom Type Mapping Dr. Anthony Vodacek AVIRIS May 20, 1999

  29. Spectral Bottom Type Mapping RIT’s MISI October 1, 2002 Dr. Anthony Vodacek

  30. Comparison ofEO-1 and Landsat 7

  31. Airborne Hyperspectral Imagery Analysis Assessing Near Shore Water Quality Modeling Strategy • Solar Spectrum Model (MODTRAN) • Atmospheric Model (MODTRAN) • Air-Water Interface (DIRSIG/Hydrolight) • In-Water Model (HYDROMOD= • Hydrolight/OOPS + MODTRAN) • Bottom Features(HYDROMOD/DIRSIG) Airborne Hyperspectral Imagery Analysis Assessing Near Shore Water Quality MODTRAN ALGE Model Agriculture Urban bacteria phytoplankton CDOM macrophytes HydroLight… particles & algae Bottom Type A Bottom Type B

  32. Model of Land/Water Interface What the Future Holds TopoBathymetry required

  33. Where are we going? • GIS with satellite derived temporal history of Landuse/Landcover • Hydrological models • precipitation • stream flow • materials transport • Environmental forcing functions • insolation • cloud cover • wind speed • precipitation • air temperature GL GIS

  34. Where are we going? • Lakewide Hydrodynamic models with local • and regional inputs • temperature and flow models • material transport models • bio-optical models • productivity models driven by temperature, flow, transport, and optical models • bio-optical models to predict remotely sensed observables • Use of thermal and reflective remote sensing and surface measurements in feedback loops to calibrate models GL GIS HydroMod

  35. Future Remote Sensing Trends: • commercial satellites • more than just pretty pictures / actual • physical earth measurements • higher spatial resolution • increased spectral resolution/ • hyperspectral imaging • RS links to models: • inputs to climate models • verification and validation of models • more products available to public IKONOS MODIS AVIRIS MISI

  36. ENJOY!!!

  37. Airborne Hyperspectral Imagery Analysis Assessing Near Shore Water Quality Agriculture Urban bacteria CDOM phytoplankton macrophytes particles & algae Bottom Type A Bottom Type B

  38. Remote Sensing Platforms: Airborne compared to Satellite • Advanced Very High Resolution Radiometer (1km) • Landsat 5 (120m) Landsat 7 (60m) • MISI (2-10ft) LANDSAT AVHRR MISI

  39. Coverage vs. Spatial, Spectral, Temporal Resolutions AVHRR ~1km 1 day Landsat7 30m (vis) 16 day

  40. Chlorophyll Concentration CZCS Winter

  41. Chlorophyll Concentration CZCS Spring

  42. Chlorophyll Concentration CZCS Summer

  43. Chlorophyll Concentration CZCS Fall

  44. Global Biosphere Ocean - CZCS Land - AVHRR

  45. Chernobyl, Russia Landsat April 29, 1986

  46. Thermal Patterns in Reactor Cooling Pond April 22, 1986 plant in normal use, pond is warm May 8, 1986 pond in ambient, no activity April 29, 1986 pond cooling, little or no activity

  47. Gulf Stream Composite Thermal Patterns Great Lakes and Western Atlantic