The trend of urbanization nowadays has caused a lot of changes that related to climate. One of the most important issues is that of Urban Heat Island (UHI) and occurs in major cities in worldwide scale. Surface urban heat island (SUHI) and canopy urban heat island (CUHI) are the most commonly studied UHI categories. The current study was held during both spring and summer period of 2021, in the city of Milan. The methodology includes in-situ measurements and remote sensing techniques. For the examination of CUHI effect, meteorological data were also acquired from a nearby meteorological station. The outcomes showed differences of in-situ measurements in terms of both air temperature (Tair) and relative humidity (RH), by 3.8 oC and by 7.6 % accordingly higher than that acquired from the meteorological station. Concerning remote sensing, the results showed that the root mean square error (RMSE) of surface temperature concerning the downscaled values from MODIS (1.000m) to Landsat8 (30m) found to be equal to 2.71 oC. On the other hand, the downscaled values from MODIS to Sentinlel-2 (10m) found to be equal to 3.42 oC

Remote Sensing and In-situ Data Analysis for the Urban Heat Island and Land Surface Temperature in the Vertical Forest area (“Bosco Verticale”), in Milan city

Tzortzi N;
2023-01-01

Abstract

The trend of urbanization nowadays has caused a lot of changes that related to climate. One of the most important issues is that of Urban Heat Island (UHI) and occurs in major cities in worldwide scale. Surface urban heat island (SUHI) and canopy urban heat island (CUHI) are the most commonly studied UHI categories. The current study was held during both spring and summer period of 2021, in the city of Milan. The methodology includes in-situ measurements and remote sensing techniques. For the examination of CUHI effect, meteorological data were also acquired from a nearby meteorological station. The outcomes showed differences of in-situ measurements in terms of both air temperature (Tair) and relative humidity (RH), by 3.8 oC and by 7.6 % accordingly higher than that acquired from the meteorological station. Concerning remote sensing, the results showed that the root mean square error (RMSE) of surface temperature concerning the downscaled values from MODIS (1.000m) to Landsat8 (30m) found to be equal to 2.71 oC. On the other hand, the downscaled values from MODIS to Sentinlel-2 (10m) found to be equal to 3.42 oC
2023
2023 Joint Urban Remote Sensing Event (JURSE)
canopy urban heat island effect, surface urban heat island effect, remote sensing, downscaling LST, in-situ measurements, surface temperature
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1247699
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