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• W3014089499 endingPage "111791" @default.
• W3014089499 startingPage "111791" @default.
• W3014089499 abstract "The impacts of climate change such as extreme heat waves are exacerbated in cities where most of the world's population live. Quantifying urbanization impacts on ambient air temperatures (Tair) has relevance for human health risk, building energy use efficiency, vector-borne disease control and urban biodiversity. Remote sensing of urban climate has been focused on land surface temperature (LST) due to a scarcity of data on Tair which is usually interpolated at 1 km resolution. We assessed the efficacy of mapping hyperlocal Tair (spatial resolutions of 10–30 m) over Oslo, Norway, by integrating Sentinel, Landsat and LiDAR data with crowd-sourced Tair measurements from 1310 private weather stations during 2018. Using Random Forest regression modelling, we found that annual mean, daily maximum and minimum Tair can be mapped with an average RMSE of 0.52 °C (R2 = 0.5), 1.85 °C (R2 = 0.05) and 1.46 °C (R2 = 0.33), respectively. Mapping accuracy decreased sharply with <250 weather stations (approx. 1 station km−2) and remote sensing data averaged within a 100-500 m buffer zone around each station maximized accuracy. Further, models performed best outside of summer months when the spatial variation in temperatures were low and wind velocities were high. Finally, accuracies were not evenly distributed over space and we found the lowest mapping errors in the local climate zone characterized by compact lowrise buildings which are most relevant to city residents. We conclude that this method is transferable to other cities given there was little difference (0.02 °C RMSE) between models trained on open- (satellite and terrain) vs closed-source (LiDAR) remote sensing data. These maps can provide a complement to and validation of traditional urban canopy models and may assist in identifying hyperlocal hotspots and coldspots of relevance to urban planners." @default.
• W3014089499 created "2020-04-03" @default.
• W3014089499 creator A5038829153 @default.
• W3014089499 creator A5040892086 @default.
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• W3014089499 date "2020-06-01" @default.
• W3014089499 modified "2023-10-14" @default.
• W3014089499 title "Hyperlocal mapping of urban air temperature using remote sensing and crowdsourced weather data" @default.
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• W3014089499 cites W1970823284 @default.
• W3014089499 cites W1972855141 @default.
• W3014089499 cites W1973012668 @default.
• W3014089499 cites W1977286958 @default.
• W3014089499 cites W1977618503 @default.
• W3014089499 cites W1981542840 @default.
• W3014089499 cites W1986615132 @default.
• W3014089499 cites W1993064731 @default.
• W3014089499 cites W2006273284 @default.
• W3014089499 cites W2010232131 @default.
• W3014089499 cites W2026942553 @default.
• W3014089499 cites W2030737358 @default.
• W3014089499 cites W2034143857 @default.
• W3014089499 cites W2038774500 @default.
• W3014089499 cites W2042287628 @default.
• W3014089499 cites W2048850076 @default.
• W3014089499 cites W2057314580 @default.
• W3014089499 cites W2063623478 @default.
• W3014089499 cites W2064076411 @default.
• W3014089499 cites W2064951735 @default.
• W3014089499 cites W2067542652 @default.
• W3014089499 cites W2069642449 @default.
• W3014089499 cites W2071611719 @default.
• W3014089499 cites W2075784877 @default.
• W3014089499 cites W2076053298 @default.
• W3014089499 cites W2080995580 @default.
• W3014089499 cites W2081997980 @default.
• W3014089499 cites W2084744129 @default.
• W3014089499 cites W2085747312 @default.
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• W3014089499 cites W2125768885 @default.
• W3014089499 cites W2126859732 @default.
• W3014089499 cites W2147521062 @default.
• W3014089499 cites W2153763028 @default.
• W3014089499 cites W2155553137 @default.
• W3014089499 cites W2156644521 @default.
• W3014089499 cites W2161448838 @default.
• W3014089499 cites W2172120354 @default.
• W3014089499 cites W2173251738 @default.
• W3014089499 cites W2176611691 @default.
• W3014089499 cites W2183844604 @default.
• W3014089499 cites W2198515906 @default.
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• W3014089499 cites W2501814412 @default.
• W3014089499 cites W2538941826 @default.
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• W3014089499 cites W2583977467 @default.
• W3014089499 cites W2626726142 @default.
• W3014089499 cites W2725897987 @default.
• W3014089499 cites W2757079192 @default.
• W3014089499 cites W2757562903 @default.
• W3014089499 cites W2769395281 @default.
• W3014089499 cites W2770156183 @default.
• W3014089499 cites W2770671337 @default.
• W3014089499 cites W2772529881 @default.
• W3014089499 cites W2791956878 @default.
• W3014089499 cites W2792011679 @default.
• W3014089499 cites W2792601978 @default.
• W3014089499 cites W2808184685 @default.
• W3014089499 cites W2809005300 @default.
• W3014089499 cites W2889124453 @default.
• W3014089499 cites W2890733297 @default.
• W3014089499 cites W2895475571 @default.
• W3014089499 cites W2903765445 @default.
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• W3014089499 doi "https://doi.org/10.1016/j.rse.2020.111791" @default.
• W3014089499 hasPublicationYear "2020" @default.
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