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In the process of rapid urbanization, urban heat island (UHI) effect has been showing more and more significant impacts on human well-being. Therefore, a more detailed understanding of the impact of three-dimensional (3D) building morphology on UHI effect across a continuum of spatial scales will be necessary to guide and improve the human settlement.This study selected 31 provincial capital cities of mainland China to analyze the impacts of the 3D building morphology, including the number, area, height, volume, and the surface area of the buildings, on the land surface temperature (LST). By exploring how the influence of 3D building morphology on LST changes with the increase of spatial scale (between 0 and 600 m radii), this study finally recognized which 3D building morphology index is the most significant index affecting LST in different cities, and which spatial scale these 3D building morphology indexes have the most significant impact on LST. The results showed that the building area is the most important 3D building morphology parameter affecting the LST, while the building height has the slightest influence on the LST. These effects are more significant in the spatial scale of 150 m–540 m, and the spatial scale increases with the increase of building areas in developed cities. These results highlight the necessity of considering fine-grained management in the governance and alleviating of the urban thermal environment through urban planning and urban renewal strategies.

The growing demographic dividend is declining worldwide due to global population shrinkage. However, with the enhancement of spatial connection, industry-oriented population flow is becoming more and more active. The floating demographic dividend will bring new opportunities to regional development. Population flow has become an important field of urban research. We selected the Beijing-Tianjin-Hebei urban agglomeration as the study area and conducted the study of the interaction relationship between population flow and industry space supply. Considering that it takes time for space supplies to be industrial entities and then to affect population flow, this study built a fixed-effects model with annual space supply and “t + 1” population flow to perform regression analysis. The main findings of the research can be concluded as below. The regional population flow was mainly rural population and floated mainly to rural areas. It is difficult to complete the urbanization of floating population through land urbanization due to China’s household registration system. The population flow is sensitive to industry space supply and its spatial development conditions. As the study area is an important global urban agglomeration and China’s political, economic, and cultural center, its regional population flow is representative and typical. Guiding its population flow to form a coordinated spatial and social network can provide scientific support for regional industry space supply and allocation, and can provide a reference for the development of other urban agglomerations.

When a public health emergency occurs, a potential sanitation threat will directly change local residents’ behavior patterns, especially in high-density urban areas. Their behavior pattern is typically transformed from demand-oriented to security-oriented. This is directly manifested as a differentiation in the population distribution. This study based on a typical area of high-density urban area in central Tianjin, China. We used Baidu heat map (BHM) data to calculate full-day and daytime/nighttime state population aggregation and employed a geographically weighted regression (GWR) model and Moran’s I to analyze pre-epidemic/epidemic population aggregation patterns and pre-epidemic/epidemic population flow features. We found that during the COVID-19 epidemic, the population distribution of the study area tended to be homogenous clearly and the density decreased obviously. Compared with the pre-epidemic period: residents’ demand for indoor activities increased (average correlation coefficient of the floor area ratio increased by 40.060%), traffic demand decreased (average correlation coefficient of the distance to a main road decreased by 272%), the intensity of the day-and-night population flow declined significantly (its extreme difference decreased by 53.608%), and the large-living-circle pattern of population distribution transformed to multiple small-living circles. This study identified different space utilization mechanisms during the pre-epidemic and epidemic periods. It conducted the minimum living security state of an epidemic-affected city to maintain the operation of a healthy city in the future.

Urban Heat Island (UHI), a phenomenon characterized by significantly higher air and land surface temperatures (LSTs) in urban areas than in suburban areas, results in land use change from non-urban to urban land and is accompanied by increases in anthropogenic heat release. A variety of land use contribution indexes have been proposed to quantitatively calculate the impact of land use types on UHI. However, these indexes can only show the impact of specific land use types on UHI. In fact, the area and the intensity (which also can be considered as the average temperature) of land use change jointly determine the regional UHI. The purpose of this paper is to develop an algorithm to quantitatively reveal the influence of the area and the intensity of land use change on regional UHI. MODIS LST products and 1:1,000,000 land use data sets were used to quantitatively calculate the seasonal and interannual contributions of land use change on regional UHI between 2005 and 2018 in China. These results have theoretical and practical significance for further understanding the formation mechanism of urban thermal environment and its mitigation measures.

Tourism development activities affect the structure and functions of ecosystems directly triggering changes in the thermal environment of tourism destinations and raising a need for sustainable development of the tourism industry. Using the 2005–2015 moderate resolution imaging spectroradiometer (MODIS) data on the land surface temperature combined with the land use data, the urban thermal environment contribution index (CI) of prefecture-level cities and ecosystem types corresponding to the study area in Sichuan-Chongqing region were quantitatively calculated under various seasonal and diurnal conditions in terms of the scales of administrative divisions and ecosystem types. The characteristics of the roles played by different cities and ecosystem types to contribute to the thermal environment of the metropolitan region were summarized, and the differences and changes in the corresponding contribution intensity of various ecosystem types were measured. The results indicate the following: (1) Different cities play different roles as the sources and sinks with respect to the thermal environment in the daytime and nighttime. Based on the diurnal differences of the contribution indices, cities can be divided into three types: the day-night heat source type, the day-sink and night-source type, and the day-night heat sink type. (2) The farmland and the grassland ecosystems are the most important source and sink landscapes in the thermal environment of the Sichuan-Chongqing Region, respectively. (3) The region is affected by the spatial arrangement of the internal ecosystems and its own development conditions, and, consequently, there are significant temporal-spatial variations and role transitions between heat source and heat sink regarding the contribution of different ecosystem types to the thermal environment of individual cities. It is important to scientifically regulate the thermal environment effect on tourism destinations and maintain the comfort and sustainable development through identifying the source and sink ecosystems of the thermal environment, controlling the quantity and spatial arrangement of the heat source ecosystems, and fully enabling the cooling effect of the heat sink ecosystems.

An understanding of the spatio-temporal structure of the urban thermal environment (UTE) is important for determining the formation mechanism of the urban heat island (UHI) effect. The empirical or...

Production–Living–Ecological Space (PLES) is the functional projection of sustainable development in territory spatial planning. Its rational layout has become the most important task for developing countries to enhance ecological awareness and achieve sustainable goals. This study took the rural areas of Beijing-Tianjin-Hebei (BTH) as an example to analyze the relationship by means of quantitative cumulation between regional endowments (natural factors, location and facilities) and PLES to figure out the preference mechanism. The Boosted Regression Tree model (BRT) was used to obtain the contribution rate of factors and the internal marginal effect between 1980~2018. Our conclusions are as follows: Living space (LS) enjoyed the highest advantage of regional endowment level, followed by production space (PS). Except for the distance to water, other indicators were significantly different in the PLES, and the suitable range of various types was expanded from LS to PS and ecological space (ES). During the transfer, elevation had a universal effect. The process of increasing naturalness was affected by the distance of high-level urban areas, which verified the continuous effect of Chinese ecological civilization. This study clarified the selectivity of regional endowments to PLES, which will greatly guide the direction of regional territory spatial planning and the next step of regional sustainable development.

China has experienced extreme urban heat island effects and air pollution associated with rapid urbanization. Optimizing urban ventilation environment could relieve these environmental problems. In this study, an Urban Ventilation Network Model (UVNM) was developed to explore the impact of urban morphology and building height on the urban ventilation condition. The study calculated the ventilation resistance coefficient of building height according to fluid mechanics, and then determined the least cost path among the air inlets and outlets considering the direction and frequency of wind. Eventually, corridors at several different levels of ventilation were extracted by classifying the line densities of least cost paths, which were effectively verified through land surface temperature retrieved from the Landsat Thematic Mapper. The new model is more scientific and convenient than traditional urban construction environmental assessment software in terms of data acquisition and hardware support. The results suggest that urban design based on urban morphology and building height and considering the direction and frequency of wind would be effective for optimizing ventilation to regulate urban environmental problems.

Studies of the spatial extent of surface urban heat island (SUHI or UHISurf) effects require precise determination of the footprint (FP) boundary. Currently available methods overestimate or underestimate the SUHI FP boundary, and can even alter its morphology, due to theoretical limitations on the ability of their algorithms to accurately determine the impacts of the shape, topography, and landscape heterogeneity of the city. The key to determining the FP boundary is identifying background temperatures in reference rural regions. Due to the instability of remote sensing data, these background temperatures should be determined automatically rather than manually, to eliminate artificial bias. To address this need, we developed an algorithm that adequately represents the decay of land surface temperature (LST) from the urban center to surrounding rural regions, and automatically calculates thresholds for reference rural LSTs in all directions based on a logistic curve. In this study, we applied this algorithm with data from the Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS) 8-day level 3 (L3) LST global grid product to delineate precise SUHI FPs for the Beijing metropolitan area during the summers of 2004–2018 and determine the interannual and diurnal variations in FP boundaries and their relationship with SUHI intensity.

For urban climatic environments, the urban heat island (UHI) effect resulting from land use and land cover change (LUCC) caused by human activities is rapidly becoming one of the most notable characteristics of urban climate change due to urban expansion. UHI effects have become a significant barrier to the process of urbanization and sustainable development of the urban ecological environment. Predicting the spatial and temporal patterns of the urban heat environment from the spatial relationship between land use and land surface temperature (LST) is key to predicting urban heat environment risk. This study established an Urban Heat Environment Risk Model (UHERM) as follows. First, the urban LST was normalized and classified during three different periods. Second, a Markov model was constructed based on spatio-temporal change in the urban heat environment between the initial year (2005) and middle year (2010), and then a cellular automata (CA) model was used to reveal spatial relationships between the urban heat environments of the two periods and land use in the initial year. The spatio-temporal pattern in a future year (2015) was predicted and the accuracy of the simulation was verified. Finally, the spatio-temporal pattern of urban heat environment risk was quantitatively forecasted based on the decision rule for the urban heat environment risk considering both the present and future status of the spatial characteristics of the urban heat environment. The MODIS LST product and LUCC dataset retrieved from remote sensing images were used to verify the accuracy of UHERM and to forecast the spatio-temporal pattern of urban heat environment risk during the period of 2015&ndash, 2020. The results showed that the risk of urban heat environment is increasing in the Chongqing metropolitan area. This method for quantitatively evaluating the spatio-temporal pattern of urban heat environment risk could guide sustainable growth and provide effective theoretical and technical support for the regulation of urban spatial structure to minimize urban heat environment risk.