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Human-perceived thermal comfort (known as human-perceived temperature) measures the combined effects of multiple meteorological factors (e.g., temperature, humidity, and wind speed) and can be aggravated under the influences of global warming and local human activities. With the most rapid urbanization and the largest population, China is being severely threatened by aggravating human thermal stress. However, the variations of thermal stress in China at a fine scale have not been fully understood. This gap is mainly due to the lack of a high-resolution gridded dataset of human thermal indices. Here, we generated the first high spatial resolution (1 km) dataset of monthly human thermal index collection (HiTIC-Monthly) over China during 2003–2020. In this collection, 12 commonly used thermal indices were generated by the Light Gradient Boosting Machine (LightGBM) learning algorithm from multi-source data, including land surface temperature, topography, land cover, population density, and impervious surface fraction. Their accuracies were comprehensively assessed based on the observations at 2419 weather stations across the mainland of China. The results show that our dataset has desirable accuracies, with the mean R2, root mean square error, and mean absolute error of 0.996, 0.693 ∘C, and 0.512 ∘C, respectively, by averaging the 12 indices. Moreover, the data exhibit high agreements with the observations across spatial and temporal dimensions, demonstrating the broad applicability of our dataset. A comparison with two existing datasets also suggests that our high-resolution dataset can describe a more explicit spatial distribution of the thermal information, showing great potentials in fine-scale (e.g., intra-urban) studies. Further investigation reveals that nearly all thermal indices exhibit increasing trends in most parts of China during 2003–2020. The increase is especially significant in North China, Southwest China, the Tibetan Plateau, and parts of Northwest China, during spring and summer. The HiTIC-Monthly dataset is publicly available from Zenodo at https://doi.org/10.5281/zenodo.6895533 (Zhang et al., 2022a).

Human thermal comfort measures the combined effects of temperature, humidity, and wind speed, etc., and can be aggravated under the influences of global warming and local human activities. With the most rapid urbanization and the largest population, China is being severely threatened by aggravating human thermal stress. However, the variations of thermal stress in China at a fine scale have not been fully understood. This gap is mainly due to the lack of a high-resolution gridded dataset of human thermal indices. Here, we generate the first high spatial resolution (1 km1 km) dataset of monthly human thermal index collection (HiTIC-Monthly) over China from 2003 to 2020. In this collection, 12 commonly used thermal indicators are generated by the LGBM machine learning algorithm from multi-source gridded data, including MODIS land surface temperature, topography, land cover and land use, population density, and impervious surface fraction. Their accuracies were comprehensively assessed based on observations at 2419 weather stations across the mainland of China. The results show that our dataset has desirable performance, with mean R2, root mean square error, mean absolute error, and bias of 0.996, 0.693 °C, 0.512 °C, and 0.003 °C, respectively, by averaging the 12 indicators. Moreover, the predictions exhibit high agreements with observations across spatial and temporal dimensions, demonstrating the broad applicability of our dataset. The comparison with two existing datasets also suggests that our high-resolution dataset can describe a more explicit spatial distribution of the thermal information, showing great potentials in fine-scale (e.g., intra-urban) study. Further investigation reveals that nearly all indicators exhibit increasing trends in most parts of China during the year 2003~2020. The increase is especially stronger in North China, Southwest China, the Tibetan Plateau, and parts of Northwest China, and in the spring and summer seasons. The HiTIC-Monthly dataset is publicly available via https://zenodo.org/record/6895533 (Zhang et al., 2022a).

Human-perceived wind chill describes the combined effects of wind velocity and low temperature, strongly related to human health and natural environment. Although long-term trends in the air or ambient temperature over China under global warming have been well studied in the literature, the changes in human-perceived wind chill conditions, especially under possible urbanization effects, are still not completely known. This paper investigates the changes of wind chill over China and quantifies the associated urbanization effect by examining nearly 2000 meteorological stations during 1961–2014 using the generalized additive model (GAM). Results show that the winter wind chill temperature (WCT) in China exhibits more prominent raising trends than the air temperature, i.e., 0.623 and 0.349 °C per decade, respectively. The wind speed (V) and wind chill days (WCD) decreased by 0.149 m/s and 1.970 days per decade, respectively. These trends become more substantial in densely populated and highly urbanized areas such as the North China Plain. The expansion of urban built-up area induces additional warming (reducing) to the increase (decrease) in WCT (WCD). On average, an increase from 0% to 100% in the urban fraction induced 0.290 ± 0.067 °C higher WCT (± denotes the 95% confidence interval), along with a reduction in V and WCD by 0.052 ± 0.014 m/s and 3.513 ± 0.387 days, respectively; whereas, the presence of the grassland and forest significantly diminishes the WCT and increases the WCD and surface V. It is expected that wind chill over China tends to be weakened under glocal warming and local urbanization in the near future. Our results have important implications for climate change mitigation, urban planning, landscape design, and air pollution abatement.

While the changes in air temperature under climate change and urbanization have been extensively examined in the literature, little is known about how human-perceived temperatures change. This study investigates the long-term changes in human-perceived temperatures (e.g., summer heat stress and winter wind chill conditions) over South China and quantifies the possible effects of urbanization. Daily observations at 86 stations during the period of 1961–2014 are collected and analyzed. Analysis results show that heat stress and wind chill temperature increase faster than air temperatures (i.e., daily mean, maximum, and minimum temperatures), and these increases are stronger in winter than in summer. The probabilities of hot extremes increase throughout the study period, whereas those of cold extremes decrease. Compared with those in non-urban areas, the warming trend in both seasons and the increase (decrease) in hot (cold) extremes are even more substantial in highly developed urban areas, such as the Pearl River Delta, indicating a remarkable effect of urbanization. It is estimated that urbanization contributes as much as half of the warming trend in summer and around one-third of the trend in winter. These results are helpful for mitigating climate change and reducing the impacts of extreme events.

This paper analyses the spatial patterns and driving forces of uneven dual-track urbanisation in Fujian province using an approach based on the employment sector. It is found that uneven dual-track urbanisation is driven by four major driving forces, including the administrative force, the general internal market force, the specific internal market force, and the external force. Four area types based on employment structure have different levels of dual-track urbanisation. The relatively balanced levels of state-sponsored and spontaneous urbanisation are found in state-led urbanised areas and less developed areas. However, the levels of two urbanisation tracks in state-led urbanised areas far exceed other areas. Their high level of state-sponsored urbanisation is backed up by a large state-owned sector. There is also significant spontaneous urbanisation owing to the rising private sector and inflow of migrant workers to main urban centres. Coastal developed areas have a high level of spontaneous urbanisation but a relatively low level of state-sponsored urbanisation. Less developed areas have low levels of both state-sponsored and spontaneous urbanisation. The Fujian case shows that the two tracks of urbanisation have beenadvancing despite the relative decline of the employment share of state-owned and collective-owned sectors. The economic sectors other than state-owned and collective-owned sectors have contributed to both tracks of urbanisation. The results shed new light on the relationship between the employment sectors and dual-track urbanisation in China.

Heat waves (HWs) exert increasingly profound effects on public health and ecosystems under global warming and regional urbanization. This study examines the changes in the frequency, duration, magnitude, and timing of HWs in Fujian, Southeast China during 1971–2014 and quantifies the possible effects of urbanization using a dynamical classification scheme for urban and rural stations. Considering that some rural stations could have been converted into urban types during the urbanization process, this scheme dynamically classifies urban and rural stations based on time-varying land use/cover maps in different subperiods, thus giving a better estimation of urbanization effects. Our results show that HWs in Fujian are commencing earlier and ending later, and becoming more frequent, more intense, longer lasting. Particularly, severe (i.e., stronger and longer-lived) HW events have even stronger intensifying trends than regular ones. Moreover, we notice that the intensifying HW activities are especially prominent in densely populated and highly urbanized areas of Fujian. It is estimated that urbanization contributes to approximately half of the increasing HWs. Urbanization induces an additional increase of 0.15 events (3.78 days) per decade to HW frequency (participating days), accounting for 40.3% (57.5%) of the total trend. Meanwhile, 50.4% (60.8%) of the prolonging trend in the average (longest) duration and 27.0% (65.0%) of the intensifying trend in the average (strongest) magnitude are attributable to urbanization, i.e., 1.71 (1.19) days per decade and 0.18 (0.08) °C per decade, respectively. Moreover, urbanization induces further advancing (delaying) trend of 1.37 (1.39) days per decade for the onset (ending) date of HW in the calendar year. The findings presented here uncover the multi-faceted behaviors of HW and advance the existing research by providing a broader picture of this extreme event. It is also recommended to consider these various HW aspects in the research of climate change and extreme climate events.

Determining the timing (i.e. onset and withdrawal) of monsoon season precisely and objectively is an important yet difficult task. Conventional methods mainly define the monsoon timing as the date when the selected atmospheric variables (e.g. rainfall and wind) exceed an arbitrary threshold. These methods present little explicit justification and are subjective and sensitive to the fluctuation of the selected series. In this study, we propose an objective method to determine the onset and withdrawal of the South China Sea summer monsoon (SCSSM) using the cumulative low-level zonal wind. Our proposed approach provides an easy, objective, and applicable method that is recommended for the detection of the timing of monsoon season. On the basis of the proposed definition, the SCSSM onset and withdrawal are determined, and their accompanying processes are also examined in this paper. Both onset and withdrawal of SCSSM exhibit strong variability, and the El Nino–Southern Oscillation plays an important role. Via the modification of the western North Pacific subtropical high, a preceding El Nino (La Nina) event can delay (advance) the monsoon onset and advance (delay) the monsoon withdrawal.

This paper examines unbalanced urbanization process in Fujian province from 1982 to 2010 from the perspective of dual-track urbanization. The analysis is mainly based on 67 county-level units. The spontaneous track of urbanization is a new process of urbanization in China emerged in the reform period. It plays an important role in linking urban and rural areas but also creates problems of rural-urban integration and social cohesion. This paper examines the relative roles of spontaneous and state-sponsored urbanization and their impacts on the spatial pattern and structure of urbanization in Fujian. It is found that rural to urban migration plays the most significant role while state-sponsored urbanization and rural urbanization play equal roles in the process of urbanization. There was a significant shift of state-sponsored urbanization from county-level cities and counties to urban areas of central cities, Fuzhou and Xiamen, and from inland area to coastal area after 1990. There have also been significant shift and growth of temporary population towards the central cities in the reform period. The shift from small towns to large urban areas is clear in both tracks of urbanization.

While previous studies largely focus on extreme events, little is known about the behaviors of mild weather, a positive and pleasant condition occurring frequently, directly associated with outdoor activities, and highly relatable to the public. Here we examine the climatological characteristics and long-term trends of mild weather over China during 1971–2014, as well as the possible linkage with the El Niño−Southern Oscillation. It is found that, on average, China experiences 94.5 days (25.4% of all days) of mild weather in a year, and the annual number of mild days increased by 1.02% per decade (3.73 days per decade) during 1971–2014, especially in summer (1.54% per decade), spring (1.49% per decade), and autumn (1.03% per decade). We also find that most parts of China have been experiencing increasing mild weather in 1971–1998 but decreasing in 1998–2014. Clustering analysis reveals six subregions that exhibit distinct mild weather behaviors. In particular, harsh seasons (i.e., summer of southern China and winter of northern China) are becoming even less pleasant. Besides these secular trends, it is also noticed that El Niño event in the preceding winter is followed by less pleasant spring and summer and more pleasant autumn and winter in most areas of China. The results reported here have significant implications for urban planners and governmental policymakers.

It is well known that urban areas are typically hotter than the surrounding (vegetated) rural areas. However, the contribution of urbanization to the trends of extreme temperature events such as heat waves (HWs) is less understood. Using a homogenized meteorological dataset drawn from nearly 2,000 stations in China, we find that urban and rural areas have different HW trends and the urban-rural contrast of HW trends varies across climate regimes. In wet climates, the increasing trends of HWs in urban areas are greater than those in rural areas, suggesting a positive contribution of urbanization to HW trends. In arid regions, the urbanization contribution to HW trends is smaller and even negative. The stronger urbanization contribution to HW trends in wet climates is linked to the smaller variability of urban heat island intensity. This study highlights the important role of local hydroclimate in modulating the urbanization contribution to extreme temperatures. Plain Language Summary Extreme temperature events commonly known as heat waves (HWs) have profound impacts on human health. While it is well known that urban temperatures are usually higher than their rural counterparts (i.e., the urban heat island effect), whether and how the urbanization contribution to HW trends varies across different climate regimes over a large domain remains unclear. In this study, we explore the urban-rural contrast of HW characteristics over mainland China. Our analysis shows that while both urban and rural HWs are becoming more frequent, longer-lasting, and stronger in most parts of China, their trends are different. Interestingly, we find that the local hydroclimate modulates the variability of daily UHI intensity, thus affecting the contribution of urbanization to the frequency and magnitude of HWs. The stronger contrasts between urban and rural HW trends in wet climates are related to the larger increases in UHI intensity, but more importantly, the smaller variability of UHI intensity. As a result, the eastern, wet climate part of China, with the densest population and highest urbanization, will face severe heat risks in the future due to the combined effects of urbanization and global climate change.

Unprecedented urbanization in China facilitates the rapid development of urban agglomerations (UAs) and may exert prominent effects on regional climate and environment change. By analyzing a set of 27 extreme temperature and precipitation indices, this study examines the changes in extreme climate events in 20 UAs in China and evaluates the urbanization effects using a dynamic classification of urban and rural stations by time-varying land use/cover maps. The regional differences of the urbanization effects on extreme climate events are also investigated by a k-means clustering. It is found that, for both temperature and precipitation extremes, the urban and rural areas exhibit remarkably distinct changes and demonstrate significant urbanization effect, which also varies across different climate backgrounds. Urbanization profoundly contributes to increasing hot extremes and reducing cold extremes in most UAs, while it seems to pose the opposite effects in several UAs of arid and high-latitude regions. On average, the urbanization effect accounts for around 30% of the total change in extreme temperature events over the urban core areas of 20 UAs. On the other hand, the urbanization effects on extreme precipitation indices display stronger regional discrepancies than temperature extremes. Urbanization tends to have weakening effects on extreme precipitation events in UAs over coastal regions and intensifying influences on those in central/west China. It causes more (less) frequent and more (less) intense precipitation in UAs of inland central/west (coastal) areas. Our findings provide a systematic understanding of the urbanization effects on extreme climate and may have important implications for the mitigation of urban disasters.

It is known that rapid expansion in urban area exerts prominent effects on surface or near-surface temperature and the urban heat island effect. However, whether and how urban land expansion influences atmospheric humidity, a key indicator closely relating to human comfort and urban environment, warrant further investigations. By taking Guangdong Province as an example, in this study we examined the change in atmospheric moisture over South China during 1961–2014 and evaluated the urban expansion effects. We found a prominent drying tendency over Guangdong, as characterized by decreasing relative and specific humidities and increasing vapor pressure deficit. The drying trend has a positive correlation with urban expansion speed and exhibited regional differences, with particularly stronger trends in more urbanized and populated areas such as the Pearl River Delta. Using a dynamic classification of urban / rural stations based on time-varying high-resolution land use / land cover maps, we estimated that urbanization contributed to approximately 50% of the total drying trend in the urban areas of Guangdong. Possible mechanisms and processes underlying the urban expansion effect were also discussed. We suggested that the changes in atmospheric moisture and the urban expansion effect should be considered in future climate change mitigation, urban planning, and landscape design to support sustainable development in urban areas.

As an important indicator of sunlight conditions, sunshine duration (SSD) has a close relationship with human health, socio-economic activity, ecosystems, and the environment. This paper examines the long-term changes in SSD over eastern China and evaluates the possible urbanization effect on these changes based on a dynamic classification of urban and rural stations using time-varying land use/land cover maps. Daily SSD observations at nearly 2000 stations during 1961–2014 are collected and analyzed. Results show that SSD in eastern China declines throughout the year at an annual rate of −0.132 h/day per decade, with the largest trend in summer (i.e., −0.218 h/day per decade) and most moderate in spring (−0.066 h/day per decade). The dimming trend is even more profound in the highly urbanized and densely populated areas, such as the North China Plain and the Yangtze River Delta. A significant correlation of −0.48 also exists in the SSD trend and urban area fraction around the station. These results demonstrate an essential influence of local urbanization on SSD changes. It is also estimated that urbanization induces an additional decreasing trend of 0.065 h/day per decade for SSD, contributing to 35.3% of the total dimming trend in eastern China.

The scaling and multifractal properties of drought conditions of different regions in China were explored by employing multifractal detrended fluctuation analysis. Results show that the long-range correlation of the drought series in northern China is stronger than that in southern China, and that scaling properties vary at different time-scales. The scaling behaviors of the drought series in all of the regions are separated by a common crossover time-scale of around 1.5 years. The three regions of north China, southwest China, and the Yangtze River basin exhibited an additional crossover at a 9-year scale. The drought time series are stationary and long-range correlated at a time-scale of 1.5 years in all the regions and at a time-scale longer than 9 years in northern China, southwest China, and the Yangtze River basin. They are however non-persistent at a 1.5-to-9-year scale. Meanwhile, the h(q) curves indicate that the drought series are multifractal.

Application scenarios describe the behavioral execution sequence of system functions using sequence diagrams from the users' point of view; state diagrams give an abstractive illustration of the results of the users' behavior changes from the angle of system. This paper, starting from one application scenario, describing formal definition of sequence diagrams and constraint semantics on objects as the input, studied the automatic conversion from sequence diagrams of the application scenario to state diagrams of objects in the basis of the Unified Modeling Language and the Object Constraint Language. The application scenario instance of an information publishing platform shows that the proposed method can effectively realize the automatic conversion from application scenarios to state diagrams and ensure consistency between models.

The floating population (FP) is a concept in the background of China's particular household registration system. Most of the reported researches on FP were conducted with the census data and few of them concerned the potential value of remotely sensed (RS) data in the area. A methodology was described on how to extract indication information of the spatial distribution of FP using SPOT5 and ground data. The census data and the pollution source were obtained by field survey in Xiamen, P. R. China on the subdistrict scale in 2007. Meanwhile the land use and cover information was extracted from the fused SPOT5 image of the same temporality. According to the distribution of FP and pollution source point data, the built-up area was classified. The correlationships between FP and total population, type of built-up area, distribution of point source pollution respectively, were explored with SPSS (Statistic Package for Social Science).

An employment contract is a contract of human capital property rights transaction between employees and employer. Due to its incompleteness, the employees’ rights can not be fully defined in the employment contract. Therefore, some rights of employees lie in “Public Domain”. Due to the rule of “Power Defining Property” in the prosperity dealing, employers with great power are able to grab at employees’ rights in “Public Domain”. In this paper, the theoretical foundation on the source of violations to employees’ rights, the value of labor contract law and the role of labor union playing in the labor relationship are presented in perspective of property rights.

From local scale to globe one, the spatial distribution of human population is essential to the research in the fields crossing Demography, Humanities and Social Sciences, Environmental Science, etc. The census data of human population traditionally used inevitably have the disadvantage of low spatial and temporal resolution, and it's difficult to integrate the census data with multi-source ones as well due to the different survey units in space dimension. While the spatial distribution of statistical demographic data based on RS can solve these problems, therefore nowadays it has received much attention in the area of spatial distribution of human population. However, previous research work mainly focused on the regional scale, and little was on urban scale. In our work, firstly gathering census data on the subdistrict scale of 2007 year in the study area of Xiamen City, Fujian Province, P. R. China, meanwhile acquiring the information of residential settlements and that of road transportation by interpreting the fused SPOT5 image (with spatial resolution of 2.5m) of the year, we identified the gravity center of human population of subarea in Xiamen, and then calculated the population density of every buffer zone of each district. Using the SPSS software, we built a population density model and simulated the spatial distribution of total population of every district in Xiamen of 2007 year. Additionally, we estimated the precision by the calculated relative error with census data on the subdistrict scale. Finally, we acquired the distribution map of human population density (with grid size of 100 m). Compared with previous research, in the work, we used preferable spatial distribution indicators of human population derived from high resolution remotely sensed image, including buildings and road transportation information. Based on which and according to urban spatial structure, we make the human population simulation much more appropriate for the real world. The integration of RS and GIS can provide useful reference for the research on human population spatial distribution with high precision on the urban subdistrict scale. And the research result can also be referenced by the studies in the areas, such as crime management, economic decision-making, disaster warning, infrastructure construction and so forth.