Simulation emergency evacuation is an important part in the field of safety engineering, affective computing plays a vital role in the popularization of artificial intelligence, computer simulation and human-computer interaction. Inspired by this field, this paper proposes a method for simulating group interactions during emergency evacuation. First, each individual is assigned with dynamic survival needs and psychological quality based on urgent event and the external influence. Second, the emotional interaction of the group is realized based on OCEAN (Openness, Conscientiousness, Extroversion, Agreeableness, Neuroticism) personality trait and the improved CA-SIRS (Cellular Automaton-Susceptible Infected Recovered Susceptible) model. Third, after the perception of the external environment changes, the accident experience and panic level are used as factors of emotion update. At last, the environmental familiarity and nearby flow factors are introduced to path planning process. Based on emotion contagion, this method explores individual's emotional changes in different scenarios and situations. Combined with personality traits and emotional contagion, the experimental results show that the proposed method can simulate dynamic emotional changes in emergency situations in both efficient and reasonable way and provide guidance for emergency evacuation.INDEX TERMS Emergency evacuation, OCEAN personality traits, CA-SIRS model, emotion contagion.

Rapid urbanization is an important factor leading to the rise in surface temperature. How to effectively reduce the land surface temperature (LST) has become a significant proposition of city planning. For the exploration of LST and the urban heat island (UHI) effect in Zhengzhou, China, the LST was divided into seven grades, and the main driving factors of LST change and their internal relations were discussed by correlation analysis and gray correlation analysis. The results indicated that LST showed an upward trend from 2005 to 2020, and a mutation occurred in 2013. Compared with 2005, the mean value of LST in 2020 increased by 0.92 °C, while the percentage of LST-enhanced areas was 22.77. Furthermore, the spatial pattern of UHI was irregularly distributed, gradually spreading from north to south from 2005 to 2020; it showed a large block distribution in the main city and southeast in 2020, while, in the areas where woodlands were concentrated and in the Yellow River Basin, there was an obvious “cold island” effect. In addition, trend analysis and gray correlation analysis revealed that human factors were positively correlated with LST, which intensified the formation of the UHI effect, and the influence of Albedo on LST showed obvious spatial heterogeneity, while the cooling effect of vegetation water was better than that of topography. The research results can deepen the understanding of the driving mechanism of the UHI effect, as well as provide scientific support for improving the quality of the urban human settlement environment.

The Yellow River is the second largest river in China, and the provinces and cities affected by the Yellow River are called the Yellow River Basin influence area. The relationship between land use and surface thermal effects in the influence area of the Yellow River Basin from 2000 to 2015 was analyzed using MODIS remote sensing data and an energy balance algorithm. The results showed that: (1) net radiation and latent heat flux both increased, and the high value areas were located in the urban expansion areas and natural and seminatural areas, respectively; (2) net surface energy intake showed a upward trend, and increased as the intensity of human influence increased, indicating that human activities had strengthed the positive trend of net surface energy intake and increased the warming effect; (3) net radiation had a greater impact on surface energy intake than latent heat flux, and this relationship was more obvious in land use types that were greatly affected by human activities. This study emphasizes the difference in energy budgets of different land use types under the influence of human activities. It provides a theoretical basis for judging the climate change trend and urban heat island effect in the influence area of the Yellow River Basin from the perspective of biogeophysics.

With social changes and economic development, human activities inevitably lead to significant changes in land use types. Land use and land cover change (LUCC) leads to a series of changes in energy balance and surface temperature, which has an impact on the regional climate. In this study, MODIS remote sensing data were used to quantify the results of the biological and geophysical effects caused by LUCC in four typical cities in the Yellow River Basin of China: Jinan, Zhengzhou, Lanzhou and Xining. The results showed the following: (1) The latent heat flux and the net radiation of the four cities were both increasing on the whole. The latent heat flux of water and forest was higher, which played a key role in energy consumption on the ground. The net radiation value of the old urban and urban expansion areas was higher, while that of the forest was lower, which indicated that human activities increased the input of surface energy. (2) The differences between latent heat flux and net radiation in areas greatly affected by human activities were much smaller than those in natural areas such as forest and grassland. This indicted that human activities increased the warming trend. In addition, most of the differences between latent heat flux and net radiation in the four cities showed a downward trend. (3) Different cities have different regulating factors for land surface temperature (LST). In Jinan and Zhengzhou, the regulation of LST by net radiation was more obvious, while in Lanzhou and Xining, the regulation of LST by latent heat flux was more pronounced. By comparing LUCC and the forced balance between energy intake and consumption in four typical cities along the Yellow River Basin, this study emphasizes the difference of energy budgets under different land use types, which has important reference value for judging the spatial difference of urban thermal environments.

As one of the main driving forces for the change in surface energy balance, land use and cover change affects the ecological climate through different levels of biogeochemical and physical processes. However, many studies on the surface energy balance are conducted from the perspective of biogeochemistry, ignoring biogeochemical processes. By using core methods such as the surface energy balance algorithm and Mann–Kendall trend test, we analyzed the surface energy balance mechanism and ecological climate effects of five land use types in the Huang-Huai-Hai Basin in China. The results showed that: (1) the net radiation and latent heat flux in the five land use types increased significantly, and their highest values were located in cropland areas and urban expansion areas, respectively. (2) The influence of net radiation on surface energy absorption was greater than latent heat flux. This relationship was more obvious in land use types that were greatly influenced by human activities. (3) The net surface energy intake in the Huang-Huai-Hai River Basin showed a decreasing trend and decreased with the increase in human influence intensity, indicating that human activities weakened the positive trend in net surface energy intake and increased the warming effect. This study reveals the difference in energy budgets of different land use types under the influence of human activities. It is helpful for understanding how to formulate sustainable land management strategies, and it also provides a theoretical basis for judging the climate change trends and urban heat island effects in the Huang-Huai-Hai River Basin from a biogeophysical perspective.