Urban Sci. 2020, 4(4), 66; https://doi.org/10.3390/urbansci4040066 - 27 Nov 2020
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Urban 3D surface reflectance is a critical parameter for the modeling of surface biophysical processes. It is of great significance to enhance the accuracy of reflectance in urban areas. Based on the urban solar radiative transfer (USRT) model, this study presents a methodology [...] Read more.
Urban 3D surface reflectance is a critical parameter for the modeling of surface biophysical processes. It is of great significance to enhance the accuracy of reflectance in urban areas. Based on the urban solar radiative transfer (USRT) model, this study presents a methodology for estimating urban reflectance using the sky view factor (SVF) derived from airborne LiDAR data. Then, the USRT model was used to retrieve urban 3D surface reflectance from Landsat 8 data over the typical area of Beijing. The reflectance from USRT model was compared with the estimated value obtained from the model without considering the impact of morphological characteristics of the urban underlying surface (flat model). The results showed that the urban sample reflectance estimated by the USRT model was close to the sample reflectance of the suburban underlying surface which was less affected by morphological characteristics. The research summaries are as follows: (1) The definite physical meaning is presented in the USRT model, and can be applied to estimate the physical parameters of the urban underlying surface. (2) The reflectance from the USRT model is slightly larger than the reflectance derived from the flat model, which indicates that the accuracy of urban 3D surface reflectance is improved by the USRT model. (3) The effects of the SVF and building reflectance are different. The SVF presents a strong sensitivity to the estimation of the urban 3D surface reflectance, and the variations of building reflectance setting have little impact on urban reflectance, which is characterized by low sensitivity. Generally, the methodology of estimating urban reflectance proposed in this study can better clarify the impact mechanism of urban geometry on the radiative transfer processes and further promote the application and development of urban quantitative remote sensing. Full article