## 1 Introduction
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\begin{tabular}{c c c c} \hline \hline
**Research Idea** & **Research Content** & **Relevant Data** & **Literature** \\ \hline Fixed or moving observations from the ground (meteorological stations and meteorological monitoring equipment). & Urban albedo & Area of the city & Oka [6] \\  & Cloud cover and wind speed & Twenty years of data from 40 weather stations in Melbourne. & [PERSON] [7] \\  & Temperature and wind speed & Barrow meteorological data. & [PERSON] [8] \\  & & Data from 77 weather stations in & [PERSON] an [9] \\  & Wind & London. & \\  & Temperature & Meteorological data for Athens from & Found [10] \\ \hline  & Surface radiant temperature & Remote sensing data for U.S. coastal areas & [PERSON] [11] \\  & Single window algorithm & Landsat TM data for Egypt and Israel & [PERSON] [12] \\  & Surface radiant temperature & NOAA thermal infrared data of four & Author [13] \\  & & coastal cities in Greece & \\  & Gaussian approximation method & Remote sensing data for 8 cities & [PERSON] [14] \\  & thermal data) & Building density and roofing & Landsat-7 EMT+ data and SPOT & [PERSON] [15] \\  & materials. & imaging data from Seoul, Korea & \\  & Level of commercialization & Landsat-7 EMT+ satellite image data & [PERSON] [16] \\ \hline  & Three-dimensional mesoscale & Meteorological and geographic data & [PERSON] [17] \\  & model & for Brisbane & \\  & (the data model) & Three-dimensional flow model & Emissivity, albedo, and thermal & \\  & & inertia data for London city & [PERSON] [18] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Related research. the whole life cycle of buildings, of which 1.1 billion tons of equivalent coal was consumed in building material production, accounting for 51.3 percent of the total energy consumption. The figures for the construction phase and operation phase were 47 million TCE (2.2%) and 1 billion TCE (46.6%), respectively. [PERSON] et al. [26] analyzed the existing information on building energy consumption, especially the information related to high-voltage air conditioning systems. On the basis of a detailed investigation of the availability of building information, considering the commercial buildings between different countries, the situation in offices can elicit more in-depth analysis. [PERSON] et al. [27] found that due to the different opening times of air conditioning, the energy consumption of different buildings varies greatly. Through building energy simulation, the behavior of residents is classified. These typical behavior patterns of residents can be used as the background of community building energy profile and the evaluation standard of building energy saving technology. [PERSON] et al. [28] measured the energy consumption of refrigeration in a residential building in Beijing, China, in summer. The results show that the running time of air conditioning has a significant effect on building energy consumption. Based on the Gini coefficient of air conditioning energy consumption, the operation mode of air conditioning is regarded as the most important factor affecting the energy consumption of residential buildings. At the same time, it is found that China's residential building refrigeration energy consumption has great potential for growth and decline. [PERSON] et al. [29] conducted a comparative analysis of different building cases, and the results showed that under the urban heat island effect, the cooling load of buildings located in the city center was 13% higher than that of buildings located in the suburbs. At the same time, [PERSON] also points out that the instantaneous power consumption of buildings increases by 4.6% and the total power consumption increases by 8.5% when the temperature increases by 1 \({}^{\circ}\)C [30]. Temperature rise has a significant impact on building energy consumption in different climate zones in China.