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An Assessment of Satellite Thermal Imagery for Estimating Road Surface Temperatures Stennis Space Center Objective •Conduct exploratory assessment of ASTER thermal imagery for estimating road surface temperature –Key parameter for Winter Road Maintenance –Primarily proof-of-concept to demonstrate applicability of NASA data to surface transportation What is Maintenance Decision Support Systems •The MDSS is a complex prototype system that merges state-of- the-art weather forecasting with computerized roadway maintenance rules of practice. Output from the system consists of a series of optimized road treatment guidance geared specifically for winter road maintenance managers. •Road Weather Impacts: –800,000 Injuries, 7,000 Fatalities –Estimated Annual Cost Of $42 Billion –544 Million Vehicle-Hours of delay from Snow, Ice, And Fog Weather Information for Surface Transportation Hypothesis Testing Goal: Is not to use ASTER as a weather prediction tool, but to characterize road thermal properties between RWIS stations, thereby enabling thermal-model enhancement Assumptions: 95% Confidence Interval Land surface variation within a 90-meter ASTER Temperature pixel can be explained by 3 dominant thermal types: – pavement – non-pavement: vegetation, soil – water ASTER reflectance and radiance models to remove atmospheric effects are fully effective Summary •Iowa results demonstrate that ASTER 90-meter thermal data can estimate road surface temperature. •Portability and seasonality of the model remains undetermined 280.0 285.0 290.0 295.0 300.0 305.0 310.0 315.0 320.0 325.0 330.0 280.0 285.0 290.0 295.0 300.0 305.0 310.0 315.0 320.0 325.0 330.0 ASTER Observed Temperature (K ) RWIS Measured Temperature (K) 290.0 295.0 300.0 305.0 310.0 315.0 320.0 325.0 330.0 290.0 295.0 300.0 305.0 310.0 315.0 320.0 325.0 330.0 ASTER & S olar Azimuth M odeled Tem perature (K) RWIS Measured Temperature (K ) 290.0 295.0 300.0 305.0 310.0 315.0 320.0 325.0 330.0 0 5 10 15 20 25 30 S tation N um ber R oad Surface Tem perature (K ) rwis regress y = 215.96 -0.54*solar_az+0.58*aster R2 = 0.98 F-test = 339.12 Statistical Results Stepwise Multiple Linear Regression RWIS Stepwise Regression Plot ASTER vs. RWIS Scatterplot Research Study Site IA005 IA003 IA017 IA016 60 km 60 km IA005 IA003 IA017 IA003 ASTER Imagery – VNIR 15m ASTER Thermal Imagery – 90 m Applied Science Directorate Crosscutting Solutions: Surface Transportation

Weather Information for Surface Transportation

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ASTER Imagery – VNIR 15m. Research Study Site. 60 km. y = 215.96 -0.54*solar_az+0.58*aster R 2 = 0.98. IA005. IA003. 60 km. IA017. IA016. ASTER Thermal Imagery – 90 m. IA005. IA003. IA003. IA017. Objective. - PowerPoint PPT Presentation

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Page 1: Weather Information for Surface Transportation

An Assessment of Satellite Thermal Imagery for Estimating Road Surface Temperatures

Stennis Space Center

Objective

• Conduct exploratory assessment of ASTER thermal imagery for estimating road surface temperature–Key parameter for Winter Road Maintenance

–Primarily proof-of-concept to demonstrate applicability of NASA data to surface transportation

What is Maintenance Decision Support Systems

• The MDSS is a complex prototype system that merges state-of-the-art weather forecasting with computerized roadway maintenance rules of practice. Output from the system consists of a series of optimized road treatment guidance geared specifically for winter road maintenance managers.

• Road Weather Impacts:–800,000 Injuries, 7,000 Fatalities–Estimated Annual Cost Of $42 Billion–544 Million Vehicle-Hours of delay from Snow, Ice, And Fog

Weather Information for Surface Transportation

Hypothesis Testing

• Goal: Is not to use ASTER as a weather prediction tool, but to characterize road thermal properties between RWIS stations, thereby enabling thermal-model enhancement

Assumptions:• 95% Confidence Interval• Land surface variation within a 90-

meter ASTER Temperature pixel can be explained by 3 dominant thermal types: – pavement– non-pavement: vegetation, soil– water

• ASTER reflectance and radiance models to remove atmospheric effects are fully effective

Summary

• Iowa results demonstrate that ASTER 90-meter thermal data can estimate road surface temperature.

• Portability and seasonality of the model remains undetermined

280.0

285.0

290.0

295.0

300.0

305.0

310.0

315.0

320.0

325.0

330.0

280.0 285.0 290.0 295.0 300.0 305.0 310.0 315.0 320.0 325.0 330.0

ASTER Observed Temperature (K)

RW

IS M

easu

red

Tem

per

atu

re (

K)

290.0

295.0

300.0

305.0

310.0

315.0

320.0

325.0

330.0

290.0 295.0 300.0 305.0 310.0 315.0 320.0 325.0 330.0

ASTER & Solar Azimuth Modeled Temperature (K)

RW

IS M

easu

red

Tem

per

atu

re (

K)

290.0

295.0

300.0

305.0

310.0

315.0

320.0

325.0

330.0

0 5 10 15 20 25 30

Station Number

Ro

ad S

urf

ace

Tem

per

atu

re (

K)

rwis

regress

y = 215.96 -0.54*solar_az+0.58*asterR2 = 0.98

F-test = 339.12

Statistical Results

Stepwise Multiple Linear Regression

RWIS Stepwise Regression Plot

ASTER vs. RWIS Scatterplot

Research Study Site

IA005

IA003

IA017

IA016

60 km

60 k

m

IA005

IA003

IA017

IA003

ASTER Imagery – VNIR 15m

ASTER Thermal Imagery – 90 m

Applied Science DirectorateCrosscutting Solutions: Surface Transportation