Estimating Urban Heat Island Effects on the Temperature Series of Uccle (Brussels, Belgium) Using Remote Sensing Data and a Land Surface Scheme

In this letter, the urban heat island effects on the temperature time series of Uccle (Brussels, Belgium) during the summers months 1960–1999 was estimated using both ground-based weather stations and remote sensing imagery, combined with a numerical land surface scheme including state-of-the-art urban parameterization, the Town Energy Balance Scheme. Analysis of urban warming based on remote sensing method reveals that the urban bias on minimum temperature is rising at a higher rate, 2.5 times (2.85 ground-based observed) more, than on maximum temperature, with a linear trend of 0.15 °C (0.19... Mehr ...

Verfasser: Rafiq Hamdi
Dokumenttyp: Artikel
Erscheinungsdatum: 2010
Reihe/Periodikum: Remote Sensing, Vol 2, Iss 12, Pp 2773-2784 (2010)
Verlag/Hrsg.: MDPI AG
Schlagwörter: urban heat island / remote sensing imagery / urbanization / climate record / climate change / Science / Q
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27004416
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.3390/rs2122773

In this letter, the urban heat island effects on the temperature time series of Uccle (Brussels, Belgium) during the summers months 1960–1999 was estimated using both ground-based weather stations and remote sensing imagery, combined with a numerical land surface scheme including state-of-the-art urban parameterization, the Town Energy Balance Scheme. Analysis of urban warming based on remote sensing method reveals that the urban bias on minimum temperature is rising at a higher rate, 2.5 times (2.85 ground-based observed) more, than on maximum temperature, with a linear trend of 0.15 °C (0.19 °C ground-based observed) and 0.06 °C (0.06 °C ground-based observed) per decade respectively. The results based on remote sensing imagery are compatible with estimates of urban warming based on weather stations. Therefore, the technique presented in this work is a useful tool in estimating the urban heat island contamination in long time series, countering the drawbacks of a ground-observational approach.