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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 [email protected]
Lake Ontario Comparison of Temperature & Transmission
Ontario Mid-lakeTemperature Sections
late Aprilmid May
early June
late June
May 25, 1978ITOS
Skylab Photos: chlorophyll maps
AVHRR Lake Ontario Thermal Bar
HCMM Lake Ontario Thermal Bar
IFYGL Aerial Photos
Off Ginna May 22, 1978
Landsat Evolution
Rochester
true color
1972 4 80 m1982 7 30 m1999 7 15 m
YearNumber of Bands
Spot Size
false color infrared
Landsat TM
Landsat TM
Ontario Thermal Bar
LANDSAT: April 23, 1991 Lakes Ontario & Erie
True Color Composite Thermal Channel
Cold center
Warm ring
Landsat TM April 23, 1991
Thermal ChannelTrue Color Composite
Cold center
Warm ring
LANDSAT: May 11, 1992 Lakes Ontario & Erie
Landsat June 12, 1992
True Color Composite Thermal Channel
Landsat TM
True Color Composite(Enhanced)
Thermal band
warmcold
Braddock Bay to Irondequoit Bay
June 23, 1996
Linking Hydrodynamic Models with Remotely Sensed Data
AGLE Simulation including Niagara Inflow
0C 4C 11C 22C
Hyperspectral ImageryHyperspectral Imagery
MISIRIT’s Modular Imaging Spectrometer Instrument
Ginna Nuclear Power Plant
MISIRIT’s Modular Imaging Spectrometer Instrument
West Roch EmbaymentRussell Power PlantJuly 5, 2000Altitude=4000ft
East Roch EmbaymentGenesee River PlumeJuly 5, 2000Altitude=4000ft
MISI thermal image of Russell Power Plant Effluent
MODISModerate Resolution
Imaging Spectroradiometer
Resolution Trades:Temporal: Global Coverage in 1- 2 daysSpatial: 1 km pixels (low)Spectral: 36 bands .4-14.4um
MODISMarch 5, 2005
SeaWiFS
April 12, 1998
SeaWiFSSeptember 3, 1999
AVIRIS FlightlinesMay 20, 1999
11:45 AM
Digital Imaging and Remote Sensing Laboratory
solar glint
Lake Ontario
Hyperspectral Imagery: AVIRIS
Hyperspectral Hyperspectral Concentration MapsConcentration Maps
• Provide user community with water quality maps derived from hyperspectral data to address environmental issues.
AVIRIS Image Cube: Lake Ontario Shoreline
Dr. Rolando Raqueno
AVIRIS May 20, 1999
Spectral Bottom Type Mapping
Dr. Anthony Vodacek
Spectral Bottom Type Mapping
RIT’s MISIOctober 1, 2002
Dr. Anthony Vodacek
Comparison ofEO-1 and Landsat 7
Airborne Hyperspectral Imagery Analysis Assessing Near Shore Water Quality
ALGE Model
Bottom Type A Bottom Type B
particles & algae
CDOM phytoplankton
MODTRAN
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)
HydroLight…
Agriculture Urban
macrophytes
bacteria
Airborne Hyperspectral Imagery Analysis Assessing Near Shore Water Quality
TopoBathymetryTopoBathymetry
requiredrequired
Model of Land/Water InterfaceWhat the Future Holds
•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
Where are we going?
GL GIS
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
HydroMod
GL GIS
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
MODIS
IKONOS
AVIRIS MISI
ENJOY!!!
Bottom Type A Bottom Type B
particles & algae
CDOMphytoplankton
Agriculture Urban
macrophytes
bacteria
Airborne Hyperspectral Imagery Analysis Assessing Near Shore Water Quality
• Advanced Very High Resolution Radiometer (1km)• Landsat 5 (120m) Landsat 7 (60m)• MISI (2-10ft)
Remote Sensing Platforms: Remote Sensing Platforms: Airborne compared to SatelliteAirborne compared to Satellite
AVHRRLANDSAT
MISI
Coverage vs. Spatial, Spectral, Temporal Resolutions
AVHRR ~1km1 day
Landsat730m (vis)16 day
CZCSWinter
Chlorophyll ConcentrationChlorophyll Concentration
CZCSSpring
Chlorophyll ConcentrationChlorophyll Concentration
CZCSSummer
Chlorophyll ConcentrationChlorophyll Concentration
Chlorophyll Concentration
CZCSFall
Global Biosphere
Ocean - CZCSLand - AVHRR
LandsatApril 29, 1986
Chernobyl, Russia
April 22, 1986plant in
normal use, pond is warm
Thermal Patterns in Reactor Cooling Pond
April 29, 1986pond cooling,
little or no activity
May 8, 1986pond in
ambient, no activity
Gulf Stream Composite Thermal Patterns
Great Lakes and Western
Atlantic
Gulf Stream
New York CityPhiladelphiaBaltimoreWashington
HCMM thermal
Urban heat islands
Understanding & Monitoring water quality & flow
Great Lakes Hydrodynamics
52Digital Imaging and Remote Sensing LaboratoryRR..II..TT
RR..II..TT
Maximum Density of Water
Colors of Light
• Humans can see in the visible region
– These are mostly reflected photons from the Sun, Moon or lights.• Some animals can see in the near infrared (NIR) region
– This gives them improved contrast of prey against vegetation.• Some sensors can “see” in the long-wave infrared (LWIR)
– This allows them to measure temperatures without touching it.
: Radiant Exitance of EarthTransmission of the : Earth’s Atmosphere
Solar Irradiance Outside Earth’s Atmosphere:
Great Lakes of the World
Great Lakes Profile(Bathymetry & Flow)
Sea Level
282 m229 m
64 m
244 m
Superior Michigan Huron Erie Ontariomodified from The Great Lakes Atlas, 1995
406 m
183.2 m 176 m 176 m 173.5 m
74.2 m
Laurentian Great Lakes
• Hold 18% of the world’s fresh waterHold 18% of the world’s fresh water
• US coast line exceeds US Atlantic coastUS coast line exceeds US Atlantic coast
• About 10% of US and 32% of Canadian About 10% of US and 32% of Canadian population (about 35 million people) live in population (about 35 million people) live in the Laurentian Basinthe Laurentian Basin
• Large fraction of the industrial northeastLarge fraction of the industrial northeast
Seasons of a Dimictic Lake
Thermal Stratification & Mixing in a Dimictic Lake
winter stratification
summerstratification
springmixing
fallmixing
Thermal Bar Process
Summer Stratification
WinterStratification
Lake cross-section
Den
sity
Temperature (Celsius)0 2 4 6
max
imum
den
sity
Thermal Bar
Thermal Bar Spring Progression Lake Ontario Cross-Sections
Late April
Mid May
Early June
Late June
Lake Ontario Comparison of Temperature & Transmission
Can Remote Sensing Help?
Can we ‘see’ :
•Water quality
•Hydrodynamic processes that impact water quality and materials transport
•Impact of global / regional forcing functions
Questions
• When does the thermal bar occur?
• How long does it last?
• What functions drive the start, progression
and end?
• Can we predict these occurrences?
• How does it effect water quality?
Hydrodynamic Model to Predict this Thermal Bar Phenomenon
Digital Imaging and Remote Sensing Laboratory
N
S
N S
Thermal Bar at 4 Celsius
Temperature Maps from Hydrodynamic Model
vertical cross-section
ALGE Simulation without Niagara inflow
0C 4C 11C 22C
Niagara River: localized plume study
6 hours 12 hours 18 hours 24 hours
ALGE simulation including variable inflow at Niagara (March-August 1998)
ALGE simulation including variable inflow at Niagara (March-August 1998)
ALGE simulation including variable inflow at Niagara (March-August 1998)
ALGE simulation including variable inflow at Niagara (March-August 1998)
ALGE simulation including variable inflow at Niagara (March-August 1998)
ALGE simulation including variable inflow at Niagara (March-August 1998)
ALGE simulation including variable inflow at Niagara (March-August 1998)
ALGE simulation including variable inflow at Niagara (March-August 1998)
4D Hydrodynamic Modeling
Reference: Reference: Schott, de Alwis, Raqueno, Barsi. “Calibration of a Great Lake Hydrodynamic Model Using Remotely Sensed Imagery,” presented at the International Association for Great Lakes Research 43 rd Conference on Great Lakes and St. Lawrence River Research, Cornwall, Ontario, May, 2000
Thesis:Thesis: de Alwis. Simulation of the formation and propagation of the thermal bar on Lake Ontario. RIT, M.S. Thesis, 1999.
Landsat TM April 7, 1991