Lowering the difficulty of mesoscale sky view factor mapping using satellite products

With the intensification of climate change, outdoor thermal comfort has become an increasingly crucial topic. Therefore, in this paper, a cost-effective and convenient method of data preparation is proposed for calculation of large-scale sky view factors (SVFs) with the Urban Multi-scale Environmental Predictor (UMEP). Land surface features, including buildings and tree canopies, were extracted from satellite products and used with the UMEP to determine the distribution of the SVF. Once the SVF distributions had been calculated, these distributions were validated using the GSV2SVF tool by considering 68 validation points. The lowest mean error (ME) and mean absolute error (MAE) achieved with the proposed method were 0.009 and 0.130, respectively, which are small and acceptable values. The SVF calculated on the basis of the features extracted from the satellite products had a similar distribution to that calculated on the basis of an official building data set. When the SVF was extracted from satellite products only, the ME and MAE of the proposed method only increased by 0.089 and 0.038, respectively, which indicates the feasibility and applicability of the proposed method. The collected data sets and obtained results were then used in thermal environmental assessment, and suitable results were obtained. The proposed method reduces the difficulties involved in research on outdoor thermal comfort, and researchers from developing countries can use this method to perform thermal assessments in a convenient and cost-effective manner for improving the thermal environment in their countries.