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• W3138474015 abstract "Typical urban and rural temperature records are essential for the estimation and comparison of urban heat island effects in different regions, and one of the key issues is how to identify the typical urban and rural stations. This study tried to analyze the similarity of air temperature sequences by using dynamic time warping algorithm (DTW) to improve the selection of typical stations. We examined the similarity of temperature sequences of 20 stations in Beijing, and the results indicated that DTW algorithm could identify the difference of temperature sequence, and clearly divide them into different groups according to their probability distributions. DTW algorithm could create more rigorous and reasonable classification for typical urban and rural stations in Beijing by comparing with remote sensing and cluster analysis method. We also found that some traditional rural stations did not represent temperature variation in rural areas because their surrounding environments have been highly modified by urbanization process in last decades, and this might lead to an underestimate of the urban climate effect by 1.24℃. The study suggests that DTW algorithm is a simple and efficient method for selecting appropriate temperature records and analyzing temperature sequences with a good potential in improving urban heat island estimation." @default.
• W3138474015 created "2021-03-29" @default.
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• W3138474015 date "2021-08-13" @default.
• W3138474015 modified "2023-09-25" @default.
• W3138474015 title "Urban heat island estimation from improved selection of urban and rural stations by DTW algorithm" @default.
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• W3138474015 doi "https://doi.org/10.1007/s00704-021-03749-z" @default.
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