Building water dissipation.
Building water dissipation is a process that accompanies water consumption. Based on the principle of bionics, this paper compares building areas to concrete forests composed of urban building trees9-10. Figure 1 shows the main type of water dissipation that occurs inside a building: the conversion of the phase of water from liquid to gaseous. Then, with air circulation, the water vapor inside a building is released into the air through the doors, windows, vents, and other pathways, such as through the leaf pores of trees, participating in the hydrological cycles in urban areas9-10.
The internal water dissipation links of urban buildings mainly include water used for drinking, showering, cooking, flushing, etc. For instance, water vapor evaporation occurs in the process of showering, steam is released in the process of cooking, water vapor evaporation occurs in the process of drying wet clothes, and evaporation occurs from the scrubbing of surfaces such as floors, glass surfaces, walls, desktops, etc.
Correction and Treatment of NTL.
To correct oversaturation in nighttime light (NTL) data, it is necessary to find a suitable lighting threshold value with which to identify and remove oversaturated areas. The more developed a city is, the higher its nighttime light brightness is. In this study, four developed cities, Beijing, Shanghai, Guangzhou and Shenzhen, were chosen to ascertain the maximum lighting values of urban areas in China. The data showed that the maximum lighting values of Beijing, Shanghai, Guangzhou and Shenzhen were 256, 202, 264 and 195, respectively. The nighttime light value of 264 was selected as the maximum lighting value in China. This selected value can almost cover the range of the nighttime lighting in urban areas throughout the whole country. Pixels representing oversaturated light values in other areas of China were removed. The nighttime light image of China was resampled to a pixel size of 500 m × 500 m and then reprojected to the Alberts projection coordinate system. As shown in Figure 2, a lighting value of 15 was chosen as a threshold value to distinguish urban and rural areas; thus, the nighttime lighting range of 15-264 represents urban building areas in China.
The geographic coordinate system of the NPP-VIIRS nighttime light data is GCS_ WGS_ 1984, and the image grid deforms with a change in latitude. First, the global image data were projected to the Alberts projection coordinate system and then resampled to a pixel size of 500 m × 500 m28. Since the NPP-VIIRS sensor has a higher sensitivity than the DMSP-OLS sensor, weak nighttime light appears in some areas in the high-noise images. It is thus necessary to denoise the global nighttime light image. The brightness value of nighttime light data is closely related to the level of urban economic development. In this paper, several developed cities were selected, such as New York, Los Angeles, London, and Beijing; their maximum lighting values were 260, 317, 428 and 256, respectively. As shown in Figure 3, 428 was selected as the global maximum brightness value, and this threshold was used to eliminate the excessive brightness values present in some regions of the world.
Calculation of the building floor area.
To calculate the urban building floor area, the nighttime light comprehensive coefficient α is introduced. It is assumed that the higher the light brightness is, the higher the building density is, i.e., the larger the building floor area is. Moreover, the cumulative value of the building floor area is proportional to the cumulative brightness value. The calculation formula can be expressed as follows:
Artificial water dissipation, also known as enhanced evaporation, mainly refers to the internal water dissipation processes that occur in urban buildings and to artificial water sprinkling on hardened roads. With the acceleration of urbanization, the proportion of building water dissipation is gradually increasing. The higher the degree of economic development is, the greater the building water dissipation is. In this paper, the following formula was used to calculate the building water dissipation: