Satellite observations are used to monitor the August 2003 heat wave in Paris, and their applications to environmental risk assessment and to health alert systems are discussed. Fifty NOAA-AVHRR satellites images were processed to retrieve the diurnal variations of surface temperature. Land cover classification of the Paris basin was mapped from a multi-spectral SPOT-HRV image. Geographic Information Systems were used to merge SPOT-HRV and NOAA-AVHRR data. Results indicate large surface temperature gradients and contrasted warming patterns. Contrary to prevailing concepts, the magnitudes of temperature anomalies are larger in daytime than at night. Surface temperature gradients between urban parks and industrial areas are largest in daytime, the negative correlation between surface temperature and normalized vegetation index showing the cooling effect of vegetation. The temperature difference between downtown and suburban areas is largest at night, revealing the strong relationship of nighttime temperature anomaly with built density inferred from the classified SPOT image. Comparison between time-series for August 1998, a normal summer, and the anomalous August 2003, indicates a large difference in diurnal temperature amplitude, confirming the impact of high nighttime temperatures on the heat wave process. The areas of the Paris region most vulnerable to heat stress were identified. Thermal indices can be constructed for assimilation into logistic models, to assess the urban variability of risk factors and implement health alert systems. The method is general and applicable to other cities.

Application of satellite Remote Sensing for Urban Risk Analysis: a case study of the 2003 extreme heat wave in Paris

MAURI E
2007

Abstract

Satellite observations are used to monitor the August 2003 heat wave in Paris, and their applications to environmental risk assessment and to health alert systems are discussed. Fifty NOAA-AVHRR satellites images were processed to retrieve the diurnal variations of surface temperature. Land cover classification of the Paris basin was mapped from a multi-spectral SPOT-HRV image. Geographic Information Systems were used to merge SPOT-HRV and NOAA-AVHRR data. Results indicate large surface temperature gradients and contrasted warming patterns. Contrary to prevailing concepts, the magnitudes of temperature anomalies are larger in daytime than at night. Surface temperature gradients between urban parks and industrial areas are largest in daytime, the negative correlation between surface temperature and normalized vegetation index showing the cooling effect of vegetation. The temperature difference between downtown and suburban areas is largest at night, revealing the strong relationship of nighttime temperature anomaly with built density inferred from the classified SPOT image. Comparison between time-series for August 1998, a normal summer, and the anomalous August 2003, indicates a large difference in diurnal temperature amplitude, confirming the impact of high nighttime temperatures on the heat wave process. The areas of the Paris region most vulnerable to heat stress were identified. Thermal indices can be constructed for assimilation into logistic models, to assess the urban variability of risk factors and implement health alert systems. The method is general and applicable to other cities.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.14083/827
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