This article compares the land surface temperature (LST) and sky view factor (SVF) as indicator of the impact of urban morphology on the urban heat island effect. For this purpose, the work investigates the dependence of this relationship to spatial resolutions varying from coarse to very fine and related scaling effect. For this purpose, several daytime Landsat 8, Advanced Spaceborne Thermal Emission and Reflection Radiometer and airborne TASI-600 images acquired in different months of the year were used to retrieve LST. Moreover, a three-dimensional building vector database was used to produce SVF maps at different spatial resolutions, according to the thermal ones. The results show a positive relationship between LST and SVF; these trends are almost superimposable for same-sensor images, but vary for images at different resolutions. This is likely due to the interference on the SVF and LST values of micro-scale factors, e.g. thermal properties of building materials, anthropogenic heat, humidity and pollutants, and others, which in a macro-scale analysis are smoothed becoming irrelevant. Therefore, a digital database able to represent urban features at suitable spatial scale is a requirement for a reliable analysis. In particular, when airborne thermal data are used, the lack of a reliable cartographic digital data could represent a limiting factor. Specifically, the data set used in the computation of SVF and other geographical parameters involved in the LST assessment should be consistent with the resolution of airborne thermal data.
|Data di pubblicazione:||2017|
|Titolo:||Assessing the relationship between sky view factor and land surface temperature to the spatial resolution|
|Autore/i:||Scarano, M; Mancini, F.|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1080/01431161.2017.1368099|
|Codice identificativo ISI:||WOS:000412545900024|
|Codice identificativo Scopus:||2-s2.0-85054263948|
|Citazione:||Assessing the relationship between sky view factor and land surface temperature to the spatial resolution / Scarano, M; Mancini, F.. - In: INTERNATIONAL JOURNAL OF REMOTE SENSING. - ISSN 1366-5901. - 38:23(2017), pp. 6910-6929.|
|Tipologia||Articolo su rivista|
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