2011
DOI: 10.1016/j.landurbplan.2011.08.010
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Development of an urban landcover classification scheme suitable for representing climatic conditions in a densely built-up Asian megacity

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Cited by 24 publications
(14 citation statements)
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“…However, these values are set based on urban structure characteristics of average German cities. Therefore, the present study applied coefficient of friction and cold air generation rate reflected the characteristics of Korean city structures [11,33]. As for temperature difference and zero-plane displacement height, the values provided in the KALM model were used.…”
Section: Analysis Of the Cold Airflow And Altitude Of The Cold Air Layermentioning
confidence: 99%
“…However, these values are set based on urban structure characteristics of average German cities. Therefore, the present study applied coefficient of friction and cold air generation rate reflected the characteristics of Korean city structures [11,33]. As for temperature difference and zero-plane displacement height, the values provided in the KALM model were used.…”
Section: Analysis Of the Cold Airflow And Altitude Of The Cold Air Layermentioning
confidence: 99%
“…To rapidly and efficiently map urban areas, various kinds of automatic classification methods are used, that are usually adopted [39,40]; however, they are more difficult to apply in large urban areas because of the massive amount of adjustments required for the parameters as opposed to the visual interpretation method. Moreover, the visual interpretation method has advantages in scientifically recognizing how other land use types convert to urban lands [41,42].…”
Section: Data Processingmentioning
confidence: 99%
“…The powerful functions of GIS technology provide convenient means to analyze urban expansion data and relevant auxiliary data (Wu et al, 2006;Ram and Kolarkar, 2007;Ma and Xu, 2009). Local and international remote sensing monitoring of urban expansion mostly adopt the automatic classification method (Jacquin et al, 2007;Doxania et al, 2011;Eum et al, 2011). However, the influences of the self-characteristics of remote sensing data, the information complexity of urban land, and the limited image processing techniques currently available lead to the poor universality of this method in extracting information on urban land at the regional scale.…”
Section: Introductionmentioning
confidence: 99%