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  • Orginal Article
    Chaolin GU, Yue ZHANG, Wei ZHAI, Weihua GUAN, Qiang LI, Na ZHAO, Chen LIU
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    This article systematically reviews some quantitative research methods about urbanization, including mathematical and simulation models of the process of urbanization, single urban growth models (cellular automata, agent and multi-agent), system dynamics model and simulation of urbanization, spatial computable general equilibrium model of urbanization, and integrated multi-model system of urbanization. The article concludes that before 1950, the main method of urbanization forecast was time series model that predicts urbanization trend based on historical data. During the 1960s, the main method was mathematical statistics model and population statistics model; regression model was also applied in urbanization research. During the 1970s, with the development of system science, system analysis method contributed to the creation of transportation, population, and land use models, which all facilitated in-depth analysis of urbanization. Since 1990, access to urbanization data has been greatly improved and data-intensive simulation models expanded the scope and depth of urbanization research. In recent years, integrated multi-model system becomes a popular research area because of the breakthrough in spatial data mining, big data, cloud computing, and large-scale model system.

  • Orginal Article
    Jian FENG, Hongbo CHAI
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    Qualitative Geographic Information System (GIS) is one of the important methodologies of qualitative research in Western human geography. Integrating qualitative data and spatial elements, qualitative GIS enables researchers to further illustrate how a spatial background is constructed and influenced by social elements. Equipped with this system, researchers may reorganize multiple elements, and therefore demonstrate the diversity and complexity of people's living space. Based on this, a three-dimensional visualization can be conducted to depict the very detail of daily life path, thus realizing the visualization of processes of social space. This article reviews current methodologies of qualitative GIS in the West, summarizes the application of these methods in urban social space research, as well as examines the prospect of similar studies in China. There are mainly four methodologies in qualitative GIS: participatory GIS, geo-ethnography combined with grounded visualization, geo-narrative, and sketch maps. These methods are respectively certain combination of various academic fields, such as critical Geographic Information System, anthropology, computer-aided qualitative data analysis, and mental maps. The above mentioned methodologies are mainly applied in three aspects: individual data collection and analysis based on emotion expression, activity space visualization based on hybrid approach, and social space study based on qualitative GIS. Generally, qualitative GIS, as a relatively new academic concept, contains multiple meanings in both micro and macro scales, making it possible for researchers to observe and participate in social processes from various perspectives, which is beneficial for theoretical innovation and further research of urban social space. Although there exist technical obstacles to the widespread use of qualitative GIS in current studies, there is still plenty of space for researchers to move further and build on this approach in the future.

  • Orginal Article
    Xueting HONG, Hongmei ZHANG
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    As the concept of sustainability becomes widely adopted, research on environmentally responsible behavior receives broad attention. In order to examine the knowledge base, hotspots, and tend of development of environmentally responsible behavior research, this article analyzes 4675 papers related to environmentally responsible behavior from the Web of Science database between 1990 and 2016 to map knowledge domains of co-citation journals, authors, and papers and co-current key words and burst key words by the aid of CiteSpace—a free Java application for visualizing and analyzing trends and patterns in scientific literature. The results show that: the knowledge bases in the field of responsible environmental behavior include "value-belief-norm theory," "theory of planned behavior," "norm activation model," "model of responsible environmental behavior," "multi-factor integration model," and the "new ecological paradigm." The research mainly focused on environmental concern, social basis of environmental concern, influencing factors of environmentally responsible behavior, measurement, and the construction of theoretical models. The research trends mainly include strategies for coping with global climate change and sustainable development, shifting trend of predictive indices of environmentally responsible behavior, development of factors that influence environmentally responsible behavior, construction of theoretical models of environmentally responsible behavior, and guiding practice through environmental policy development and design. The article concludes by summarizing and providing a glimpse into the future direction of Chinese research on environmentally responsible behavior, including a review of the existing theory, developing theories suitable for China's cultural background, studying in different scientific fields and with different perspectives, studies focusing on situational factors, intervention policy making, studying the subdivisions of environmental behavior and its influencing factors, development of measurements, as well as research methods innovation, so as to lay a foundation for further research on environmentally responsible behavior in China.

  • Orginal Article
    Jianglong CHEN, Pingxing LI, Jinlong GAO
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    In recent years, the spatial and temporal patterns of regional carbon emissions and their influencing factors were a key research focus by researchers from various fields. Taking the Pan-Yangtze River Delta region— one of the most economically developed and fast changing regions in China—as case area, we analyzed the spatiotemporal patterns of carbon emissions in six representative years of 1990, 1995, 2000, 2005, 2010, and 2014. Employing scree plot analysis and a nonlinear polynomial model, we also investigated the major influencing factors of carbon emissions in 2010. Results indicate that the total amount of carbon emissions has increased rapidly, but the spatial pattern has been largely stable since 1990. Sixteen cities of the core area dominated the carbon emissions in the Pan-Yangtze River Delta region, and they accounted for more than 50% of the total at most stages. However, the amount and rate of growth of the carbon emissions of all cities showed significant spatial differences. With 2005 as the turning point, the share of carbon emissions of most peripheral cities declined gradually before, but grew faster than the core cities after this point. The total share of the peripheral cities increased to 47% in 2014 from 33% in 2005. The spatial agglomeration degree first increased and then decreased. The spatial heterogeneity of regional carbon emissions was affected by various factors including economic development and energy consumption. Industrialization, urbanization, and population agglomeration are the major factors of carbon emissions. Fixed asset investment and foreign direct investment also had effects on carbon emissions. The relationship between economic development and carbon emissions shows an inverted U shape. The results indicate the environmental effect of change in economic development pattern and can provide some reference for energy saving and carbon emission reduction policy making.

  • Orginal Article
    Wei SUN, Xiaobin JIN, Zhihong ZHANG, Juan HAN, Xiaomin XIANG, Yinkang ZHOU
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    China has experienced rapid industrial development, especially in manufacturing. Formation of China's emerging urban agglomerations has relied on this development along with the expansion of manufacturing land. In order to explore the structure and layout conditions of new manufacturing land as well as functional division status, based on the data of manufacturing land transaction collected from China's land market from 2009 to 2013, this study analyzes the characteristics and development of new manufacturing land in five major urban agglomerations—the Yangtze River Delta, the Pearl River Delta, the Beijing-Tianjin-Hebei region, the middle reach of the Yangtze River, and the Chengdu-Chongqing area. The location entropy method was used to explore land distribution characteristics at the city level. Coupled with urban system, three evaluation indicators—price level, level of activity, and scale were selected to analyze the development discrepancies at the county level. Pearson correlation coefficient method was further adopted for quantitative analysis. The results show that: (1) New manufacturing land differed significantly among the urban agglomerations. Development in the Yangtze River Delta and the Pearl River Delta is balanced. The Beijing-Tianjin-Hebei region, the middle reach of the Yangtze River, and the Chengdu-Chongqing area showed poor coordination. (2) Each industrial category presents the characteristics of spatial clustering in all urban agglomerations. The raw materials industry is mostly concentrated in the peripheral cities of urban agglomerations and the low-grade land areas within cities, while electronic information industry tends to distribute in the core cities of urban agglomeration and the high-grade land areas within cities. (3) Market mechanism is present in new manufacturing land acquisition, where land price follows the value (grade) of land. There has been very limited manufacturing land transaction in the core urban areas, and the most active market transaction generally occurred immediately outside the core urban areas. The conclusions could provide some references for adjusting and optimizing industrial layout, and coordinate development strategies in regions of different industrial development levels.

  • Orginal Article
    Kejing WANG, Hongyan CAI, Xiaohuan YANG
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    Population distribution data are essential for socioeconomic and environmental studies, such as population estimation, spread of disease, natural disaster relief, and environmental protection. Existing research has proved that spatialized population grid data can precisely delineate the spatial pattern of population distribution, while model selection and size of grids may influence the accuracy of population distribution modeling. It is therefore important to estimate population distribution using appropriate models and at a proper spatial scale. This study mainly focused on the spatialization modeling of Anhui Province county-level population census data in 2010 at three grid scales. Anhui Province was selected for the study due to its complex landforms and significant difference of population distribution within its area. Population regionalization was carried out as a preprocessing step: 78 counties in Anhui Province were divided into four groups. Combining with land-use data and nighttime light (DMSP/OLS), urban residential areas were reclassified to reflect regional differences. Based on the population regionalization, multi-factor linear regression (MFLR) and geographically weighted regression (GWR) models were employed to integrate the reclassified urban residential land-use data with the rural residential land-use data. This study established three population spatial datasets at 1 km, 5 km, and 10 km gird scales. Comparing the two models’ precision at each scale, the results show that the modeling and grid scale have much influence on the accuracy of the spatialization result, which increased with the grid scale by using the MFLR model and the highest accuracy was achieved in the 10 km grid datasets. For the GWR model, the accuracy decreased as the grid scale increased, and the highest model accuracy was obtained at the 1 km scale. Overall, the GWR model had a higher accuracy (22.31%) than the MFLR model when taking into account the geographic location and local modeling. This study may provide a scientific basis for the production and application of population spatial data and provide a reference of spatialization for other types of statistical data in the future.

  • Orginal Article
    Hongbo CHAI, Jian FENG
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    The suburbs are an important part of urban space. Through the analysis of the formation and change of behavior space of suburban residents, we can understand the interactive relationship between behavior space and urban space. Existing studies about behavior space of suburban residents pay much attention to aggregated data based on individuals but little attention is paid to family units. This study used family as a basic unit to explain the micro-level behavior space of suburban residents. It chose three different types of families as cases, which all lived between the fifth and the sixth ring roads of Beijing. By using qualitative research methods, we analyzed the important life events in their life courses and the influence on their behavior. The results show that there's a dialectical relationship between the life course and the daily behavior of each individual in these families. Migration and changes of individuals' employment, social role in a family, and family structure are all important life events of a family. The influences of these events are in two aspects. On the one hand, the interaction of home-work space constrains the daily activities of family members. On the other hand, the changes of job-housing relationship and family structure influence family division of labor. Different family division of labor also affects the daily activities of male and female parents. Although gender differences are still existing and different among different families, a family can influence and coordinate the daily activities of the family members through different strategies. Suburban space expands the gender differences in activity and mobility of individuals, but family, as a coordination mechanism, can help individuals to cope better.

  • Orginal Article
    Duo YIN, Junxi QIAN, Hong ZHU
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    Recent cultural geographical research on the home reflects engagements not only with the material form of residential space but also the embodied, emotional and performative nature of home in different geographical scales. This article takes Kangbashi, a typical new town in Ordos, as a case area to analyze the contradictory representation and construction of "new town" and the ways in which different social actors construct, practice, and negotiate with the new town's subjective identity as home. The result indicates that: On the one hand, the discourse of popular media outside the Kangbashi New Town, BBC and Times in particular, describes it as a "Ghost City", a weird and unhealthy home space with largely the quality of desolated and abandoned landscape. In contrast, the local government endeavors to re-shape the image of Kangbashi New Town as a vigorous and livable space of the city that is filled with ecological and cultural landscape. On the other hand, residents living in Kangbashi New Town tend to negotiate the meanings of home through their own everyday practices beyond the social representation and authorized discourses. First, daily life mobility enables residents to overcome the spatial constraints of the new town, permits them to break out the social isolation and integrate into the broad urban society. Second, local residents' identity of city-as-home is gradually fostered through re-mapping of the emotional boundary of their living place. In this sense, local residents are not passive recipients of the representation imposed by either the government or the media. We argue that home making is a dynamic negotiation process instead of a fixed and dominant one, which opens a diversified and contradictory image for continuous negotiation by different social actors in everyday life. We hope our findings can provide some insights for further studies on critical geographies of home, and provides some useful ideas on the development of new town research in China.

  • Orginal Article
    Yueer GAO, Shuting CHEN, Chengyu ZHENG, Jingwei BIAN
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    With the rapid development of tourism, there has been a sharp increase in traffic demand in tourist cities during public holidays, which results in various traffic problems. This article examines the traffic characteristics of Xiamen using floating car data (FCD) on 1 October (a public holiday) and 14 October 2014 (a normal working day). The spatial scope of the study was determined by the spatiotemporal differences between the number of trips on the public holiday and the normal working day using the origin and destination's kernel density estimation method. Road network capacity was estimated by analyzing the change of traffic volume near the tourist sites using kernel density estimation based on FCD, and comparing with road facility attributes such as the grade of the road section, and the number of lanes. Finally, the study validates the feasibility of the method by estimating the traffic speed of the road sections in the road network. The results show that there exist spatiotemporal differences between the tourist traffic on the public holiday and commuting traffic on the normal working day, and the method for road network capacity study near the tourist sites is effective based on FCD. The road capacity near Xiamen University and Nanputuo Temple cannot meet the traffic demand during the public holiday. The estimation of road network capacity near tourist sites can provide a basis for reasonable planning and management of the tourism road network during the tourist season.

  • Orginal Article
    Jingchao JIANG, Junzhi LIU, Chengzhi QIN, Yamin MIAO, A-Xing ZHU
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    The lapse rate of near-surface air temperature is a critical parameter for obtaining high-precision air temperature products, especially in mountainous areas. The average lapse rate for the troposphere is 0.65℃/100 m, which cannot depict the seasonal and type differences in near-surface air temperature. This study used data from 839 Chinese national-level meteorological stations in 2000-2013 to calculate the lapse rates of seasonal mean air temperature (lrmeanT), seasonal mean minimum air temperature (lrminT), and seasonal mean maximum air temperature (lrmaxT) based on a multiple regression method at the national and regional scales, respectively. A spatial interpolation algorithm was used to validate the reliability of these lapse rates, and the seasonal and type differences were analyzed. The following results were obtained: (1) At the national scale, all the lapse rates are smaller than 0.65℃/100 m. The seasonal differences of lrminT, lrmeanT, and lrmaxT are 0.05, 0.13, and 0.24℃/100 m, respectively. Generally, the lapse rates of the summer are greater than those of the winter. The differences among the three types of lapse rates of air temperature are 0.12, 0.05, 0.11, and 0.26℃/100 m, respectively, in spring, summer, fall and winter. Generally, lrminT is the largest, while lrmaxT is the smallest. (2) At the regional scale by the comprehensive physical geographical regionalization, the lapse rates are also mostly smaller than 0.65℃/100 m. There are spatial differences for each type of lapse rate—the spatial ranges of annual lrminT, lrmeanT, and lrmaxT are 0.27-1.66℃/100 m, 0.22-1.03℃/100 m, and-0.10-0.83℃/100 m, respectively. The seasonal differences of lapse rates are mostly greater than or equal to 0.10℃/100 m, and the lapse rates of the summer are mostly greater than those of the winter. The differences among the three types of lapse rates in half of the regions are greater than 0.10℃/100 m. lrmaxT is larger than lrminT and lrmeanT for half of the regions in spring, summer, and fall, while lrminT is usually the largest in winter. Because of the seasonal differences, spatial differences, and differences among the three types of temperature lapse rates, temperature lapse rate should be determined for each season, region, and temperature type.