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With the global economy increasingly dependent on innovation, urban discourse has shifted to consider what kinds of spatial designs may best nurture innovation. We examined the relationship between the built environment and the spatial heterogeneity of regional innovation productivity (RIP) using the example of China’s Pearl River Delta (PRD). Based on a spatial database of 522 546 patent data from 2017, this study proposed an innovation-based built environment framework with the following five aspects: healthy environment, daily interaction, mixed land use, commuting convenience, and technology atmosphere. Combining negative binomial regression and Geodetector to examine the impact of the built environment on RIP, the results show that the spatial distribution of innovation productivity in the PRD region is extremely uneven. The negative binomial regression results show that the built environment has a significant impact on the spatial differentiation of RIP, and, specifically, that healthy environment, mixed land use, commuting convenience, and technology atmosphere all demonstrate significant positive impacts. Meanwhile, the Geodetector results show that the built environment factor impacts the spatial heterogeneity of RIP to varying degrees, with technology atmosphere demonstrating the greatest impact intensity. We conclude that as regional development discourse shifts focus to the knowledge and innovation economy, the innovation-oriented design and updating of built environments will become extremely important to policymakers.

The aims of the present study were to determine the pH variation and chemical feature of atmospheric precipitation during the research period. We also investigated the redistribution characteristics of rainfall while passing through the canopy layer, leaf-litter layer and soil layer, successively to quantify the acid rain buffering capacity of these spatial levels in the evergreen broadleaved forest (EBF), deciduous broadleaved forest (DBF) and coniferous forest (CF) in Guangzhou urban area, China. Results showed that the rainfall was typically acidic, and the acid rain type in Guangzhou urban area is converted from sulfuric acid type to mixed type of sulfuric acid and nitric acid. The major ions from the canopy to the forest floor differed within the three forest types. However, the enrichment phenomenon of base cations in soil leachate in EBF and DBF implied that nutrient loss was more serious in the broadleaved forest than in the coniferous forest. Variability of ionic concentration and pH in the vertical sequence of different tree species showed that the net ion concentration variation index has a significant conic relationship with ne pH change rate. We also built an acid rain buffering index, which combines the neutralization and interception effects of vegetation to acid rainfall. The present results indicated that the three forest types in urban Guangzhou all have certain buffering capacity to acid rain, and following the order: DBF > EBF > CF. In the meanwhile, the forest canopy is the biggest acid rain buffer in urban Guangzhou, following by the soil.

In the aftermath of the global financial crisis of 2008, China witnessed gradual shrinkage of cities in the Pearl River Delta (PRD). In this study, we introduce the concept of economic resilience to analyse urban growth and shrinkage in the context of a rapidly-urbanising region. Multiple regression analysis is performed to explore the determinants of economic resilience in the PRD. By measuring resistance in the shrinking phase and re-coverability in the growing phase in a group of cities in the PRD, this study distinguishes four scenarios and investigates their characteristics from a spatial perspective. The results demonstrate that the financial crisis had a severe and asymmetric influence on this area, indicating more than 15% of cities are faced with shrinking. The spatial distribution of economic resilience indicates a centre-periphery pattern, that is, high economic resilience in the inner ring and low economic resilience in the outer ring of the PRD. The service economy is found to play a significant role in promoting urban economic resilience. Results imply that sound economic policies for enhancing resilience: both poor local financial status and a high degree of export concentration adversely impact resistance, while upgrading the manufacturing economy and stimulating of industrial innovation are conducive to improve recoverability.

This study explores how firm heterogeneity affects the geographic agglomeration and location choice of foreign direct investment (FDI) based on micro -evidence from 3558 new foreign manufacturing firms in the Pearl River Delta, China. Kernel density and categorical multivariate linear regression are integrated to examine FDI location choices. The empirical results confirm that firm location choices are jointly influenced by location factors and firm heterogeneity. Specifically, we find that a firm's location decisions and agglomeration behavior are determined by the interaction between firm heterogeneity and location factors. Although location factors reveal a significant impact on the entry decisions of firms, the location effects are adjusted to some extent, or even change direction, when firm heterogeneity factors are taken into consideration. Investment from different origins via different entry modes and different sectoral composition in the same host location exhibits different nature of clustering, which may be interpreted as different characteristics of interaction between home and host regions in the context of the global economy. Such insights into the heterogeneity of firms with their divergent ways in choosing their locations also echo with the previous discussion on ‘divergent capitalism’. We believe that a better understanding of the impact of firm heterogeneity on FDI location choices at the micro-level can help policymakers formulate more appropriate firm-based policies. Such policies could address the specific preferences of different types of firms.

Cities are regarded as the main areas for conducting strategies for energy sustainability and climate adaptation, specifically in the world&rsquo, s top energy consumer&mdash, China. To uncover dynamic features and main drivers for the city-level energy consumption, a comprehensive and systematic city-level total energy consumption accounting approach was established and applied in China&rsquo, s megacity, which has the highest industrial electricity consumption. Compared with previous studies, this study systematically analyzes drivers for energy consumption based on industrial and residential perspectives. Additionally, this study analyzes not only the mechanisms by which population size, economic growth, and energy intensity affect energy consumption but also the effects of population and industry structural factors. According to the extended Logarithmic mean Divisia index (LMDI) method, the main conclusions drawn from this research are as follows: (1) The total energy consumption of Suzhou presented an overall increasing trend, with 2006&ndash, 2012 as a rapid growth stage and 2013&ndash, 2016 as a moderate growth stage. (2) The energy consumption structure was mainly dominated by coal, which was followed by outsourced electricity and natural gas. (3) Scale-related factors have dominated changes in energy consumption, and structural and technological factors have had profound effects on energy consumption in different development periods. (4) Population size and economic output were the main drivers for increments in industrial energy consumption, whereas energy intensity and economic structure performed the important curbing effects. The income effect of urban residents was the biggest driver behind the increase in residential energy consumption, whereas energy intensity was the main limiter. These findings provide a scientific basis for an in-depth understanding of the determinants of the evolution of urban energy consumption in China&rsquo, s megacity, including similar cities or urban areas in the developing world.

With the development of deep neural network (DNN), many DNN-based super-resolution (SR) models have achieved state-of-the-art (SOTA) performance. But the applications of these SOTA models are limited by the high computational and memory costs. We observed that different image regions have different difficulties in the process of SR reconstruction. However, current DNN-based SR models process different types of regions equally, and thus involve much redundant computation in the regions with low SR difficulty. To address this limitation, this paper proposes a general acceleration framework for SR networks, which first distinguishes the SR difficulty of image regions, and then applies large model and light model for difficult regions and easy regions respectively. Experimental results demonstrated that the proposed acceleration framework can accelerate SOTA SR networks with 2–4 times without reducing of quality performance.

Population migration, especially population inflow from epidemic areas, is a key source of the risk related to the coronavirus disease 2019 (COVID-19) epidemic. This paper selects Guangdong Province, China, for a case study. It utilizes big data on population migration and the geospatial analysis technique to develop a model to achieve spatiotemporal analysis of COVID-19 risk. The model takes into consideration the risk differential between the source cities of population migration as well as the heterogeneity in the socioeconomic characteristics of the destination cities of population migration. It further incorporates a time-lag process based on the time distribution of the onset of the imported cases. In theory, the model will be able to predict the evolutional trend and spatial distribution of the COVID-19 risk for a certain time period in the future and provide support for advanced planning and targeted prevention measures. The research findings indicate the following: (1) The COVID-19 epidemic in Guangdong Province reached a turning point on January 29, 2020, after which it showed a gradual decreasing trend. (2) Based on the time-lag analysis of the onset of the imported cases, it is common for a time interval to exist between case importation and illness onset, and the proportion of the cases with an interval of 1–14 days is relatively high. (3) There is evident spatial heterogeneity in the epidemic risk; the risk varies significantly between different areas based on their imported risk, susceptibility risk, and ability to prevent the spread. (4) The degree of connectedness and the scale of population migration between Guangdong’s prefecture-level cities and their counterparts in the source regions of the epidemic, as well as the transportation and location factors of the cities in Guangdong, have a significant impact on the risk classification of the cities in Guangdong. The first-tier cities — Shenzhen and Guangzhou — are high-risk regions. The cities in the Pearl River Delta that are adjacent to Shenzhen and Guangzhou, including Dongguan, Foshan, Huizhou, Zhuhai, Zhongshan, are medium-risk cities. The eastern, northern, and western parts of Guangdong, which are outside of the metropolitan areas of the Pearl River Delta, are considered to have low risks. Therefore, the government should develop prevention and control measures that are specific to different regions based on their risk classification to enable targeted prevention and ensure the smooth operation of society.

Lack of either spatial or temporal coverage in city-level carbon emissions analysis might curb our understanding of historical drivers and make future forecasting uncertain. To fill these gaps, we analyzed time-series energy-related industrial carbon emissions (EICEs) from manufacturing in over 99 cities nationwide in China during the period 2000–2015. We estimated these cities’ EICEs reduction potential up until 2030 by improving scenario design, which imposed constraints separately on different city groups based on historical drivers. Results indicated distinct changes of EICEs around 2013 for the heavy manufacturing [HM], light manufacturing [LM] and high-tech development [HD] city groups and of emissions intensity for the energy production [EP] city group. The slowing economic growth would partly explain these transformations since 2013. Energy efficiency and industrial structure contributed most to these switches for the EP and HD city groups, respectively, while energy mix and energy efficiency were also major contributors for the HM and LM city groups. Given economic growth at a normal speed, EICEs will increase by 59%, 78%, 90% and 95% for the EP, HM, LM and HD city groups, respectively, from 2015–2030. Our scenarios show that energy efficiency improvement and industrial structure optimization will spur the EICEs to peak before 2030 and limit future EICEs increase by 6.4% and 33.4% in 2030 for the EP and HD city groups, respectively. This implies that energy efficiency improvement and industrial structure optimization are key emissions mitigation factors for the EP and HD cities. Equally important, our study found more unclean fuel structure with higher coal share in the HM and LM city groups than in the other groups. It is therefore imperative to improve their energy efficiency and optimize energy and industrial structures in the HM and LM cities. Results highlight the need to impose different constraints in scenario design and provide mitigation strategies at city level.

Analysis of driving factors of energy related carbon emissions from the regional perspective is necessary and helpful for China to achieve its reduction targets. An extended STIRPAT model based on the classical IPAT identity was used to determine the main driving factors for energy related carbon emissions in Xinjiang. In order to get the best understanding of driving factors on carbon emissions during 1952–2012, we divided the process into 3 stages, such as “Before Reform and Opening up” (1952–1978), “After Reform and Opening up” (1978–2000), and “Western Development” (2000–2012). Research results show that the impacts and influences of various factors on carbon emissions are different in the three different development stages. Before the Reform and Opening up (1952–1977), carbon intensity and population size are the two dominant contributors to the carbon emissions increments, while energy consumption structure is the important influencing factor in curbing carbon emissions. After the Reform and Opening up (1978–2000), economic growth and population size are the two dominant contributors to the carbon emissions increments, while carbon intensity plays the important negative effect on carbon emissions. During the Western Development (2001–2012), fixed assets investment and economic growth are the two dominant contributors to the carbon emissions increments, while carbon intensity plays the important negative effect on carbon emissions. Solving these problems effectively will be of great help for Xinjiang to harmonize economic growth and carbon emissions reduction, even environmental damage reduction.

With the transition in the regional development discourse to knowledge- and innovation-based economics, the cultivation of innovation capacity has gained importance as an initiative to enhance regional sustainability and has emerged as a policy goal. An understanding of the formation of innovation clusters is critical to the cultivation of regional innovation capabilities. Except for the location and regional development conditions&rsquo, factors, researchers emphasize a built environment&rsquo, s role in the formation of innovation clusters. Based on the spatial database of 12,516 high-tech firms in 2017 in the Pearl River Delta (PRD), this study developed a conceptual framework for the built environment. The framework comprises living, service, perceptual, industrial, and physical aspects. The direction and intensity of the correlation between built environment factors and high-tech firms are discussed using the spatial regression model and geographical detector (GD) technique. The results show a highly concentrated spatial distribution pattern of high-tech firms in the PRD. A significant county-level spatial autocorrelation is revealed through Moran&rsquo, s I. According to the model, we determine the positive impacts of technology support, transport infrastructure, and living service levels on the agglomeration of high-tech firms as well as the negative impact of the public service level. The GD&rsquo, s result demonstrates different levels of impact intensity of built environmental factors. We argue that a comprehensive understanding of the influence of built environment factors on innovation agglomeration will help policymakers develop targeted policies to foster local innovation capabilities and promote sustainable regional development.

Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions increments both at the industrial sector and the residential sector. Research results are listed as follow: (1) Carbon emissions embodied in the imported electricity played a significant important role in emissions mitigation in Guangzhou. (2) The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10th five-year plan period (2003-2005), the 11th five-year plan period (2005-2010), and the 12th five-year plan period (2010-2013). The main reasons underlying these influencing mechanisms were different policy measures announced by the central and local government during the different five-year plan periods. (3) The affluence effect (g-effect) was the dominant positive effect in driving emissions increase, while the energy intensity effect of production (e-effect-Production), the economic structure effect (s-effect) and the carbon intensity effect of production (f-effect-Production) were the main contributing factors suppressing emissions growth at the industrial sector. (4) The affluence effect of urban (g-effect-AUI) was the most dominant positive driving factor on emissions increment, while the energy intensity effect of urban (e-effect-Urban) played the most important role in curbing emissions growth at the residential sector.

The effective coupling of poverty alleviation and carbon emission reduction goals is an important requirement for sustainable economic development in the present day. In this paper, we utilized socioeconomic data to construct a multiregional input-output (MRIO) table for 27 industries in 30 provinces of China. Multiregional input-output analysis and carbon emission intensity analysis were applied to analyze the effects of poverty alleviation investment on carbon emissions. We found that an investment in poverty alleviation has produced an increase in China's economic aggregate growth from 2010 to 2017. During this time period, the fastest economic growth occurred in 2012 and the regions with the greatest economic drivers were Yunnan and Guizhou. Regarding the industry sector, the construction industry and non-metal products industries had the highest contribution to economy. The economic contribution of the agricultural and food processing industries was insufficient. Poverty alleviation in 26 provinces effectively reduced carbon emission intensity, and the effects were continuously optimized from 2010 to 2017. However, this effect in Inner Mongolia and other 3 provinces was weak. In addition, the effect of carbon emission reduction in the energy production and mining industries was not ideal. This study focuses on the effect of poverty alleviation investment on carbon emissions, which can provide policy guidance for poverty alleviation and green economic growth in China.

In the globalization era, shrinking cities have emerged as a widespread phenomenon and become a new buzzword in regional and urban research discourse. The Pearl River Delta (PRD), one of the most representative areas of rapid urbanization in China, is characterized by export-oriented economy and “exo-urbanization.” Induced by the financial crisis of 2008, new spatial symptoms related to urban shrinkage, such as factory collapses, job losses, and vacant dwellings, were observed in this area. To investigate spatial-temporal characteristics of the crisis-induced shrinkage in the PRD, this paper proposes a theoretical approach to interpret urban growth and shrinkage in combination with economic, population, and land dimensions. Moreover, through an analysis of statistical data and in-depth interviews in the case of Dongguan, three primary influences (i.e., global financial crisis, demographic dividend diminishment, and change in institutional arrangement) on urban shrinkage in town-level cities are evaluated. This study not only contributes to the literature by analyzing the short-term urban shrinkage influenced by sudden economic shock in globalization but also demonstrates the complexity and multiplicity of urban shrinkage that emerged in the rapidly urbanizing area of the Global South.

The location selection mechanism and effect of industrial transfer have been widely considered in academia, but the influence of institutional factors on cross-regional industrial transfer and regional differences still need further investigation. Based on theories of economic geography as well as new economic geography (NEG) and its&rsquo, institutional transformation, this paper studies the form, mechanism, and effect of the &ldquo, core&ndash, periphery&rdquo, regional relationship between the Pearl River Delta (PRD) and non-Pearl River Delta (NPRD) areas in Guangdong Province from the micro perspective of industrial spatial organization. Based on a case study on the change of the cross-regional production spatial organization of ceramics enterprises between Foshan and Qingyuan, it is found that after three rounds of spatial reorganization, the production spatial organization of Foshan&rsquo, s and Qingyuan&rsquo, s ceramics industries has changed significantly, forming a multifactory, multilocation production spatial structure and regional production network, which further drives to form the regional functional division of &ldquo, Institution factors, especially environmental regulation and industrial transfer institutional arrangements, have become an important driving force for the current industrial transfer, but its impact on regional relations is still not a decisive factor. The path locking of the &ldquo, mode has not been fundamentally broken through. Although the form of spatial inequality has greatly changed, in fact, it produces a new form of inequality. The economic, geographical, and political theoretical framework from the micro-perspective of enterprises will provide a possible theoretical explanation for the phenomenon of &ldquo, pollution moving to the West, high-tech industry moving to the East, industrial output gathering to the East&rdquo, in China.

Since the 1980s, the rapid, extensive, and dispersed urban expansion in the Pearl River Delta megalopolis (PRDM) has led to landscape fragmentation and the inefficient use of construction land. Like other developed regions in China that are subject to the dual challenges of shortages of construction land and deterioration of the ecological environment, it is becoming increasingly important in the PRDM to improve the land-use efficiency of urban construction. However, current methods for assessing land-use efficiency do not meet the emerging needs of land-use planning and policymaking. Therefore, using the American Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) nighttime light imagery and Landsat TM data, this study aims to develop a timely and efficient approach to model the high-resolution economic efficiency of construction land (EECL). With this approach, we mapped the reliable EECL of the PRDM at township level and with a one-kilometer grid. Next, the study compared the temporal changes and revealed the spatial-temporal dynamics in order to provide a scientific reference for informed land-use planning and policymaking. The results show that since 1998, the economic efficiency of construction land in the PRDM increased in general but varied significantly throughout the area. Further, these disparities widened from 1998 to 2012 between the PRDM’s inner and peripheral circles. Only one-fifth of the towns and subdistricts were categorized as fast-growth or ultrafast-growth, with the majority located in the most developed areas of the PRDM’s inner circle. In order to improve the efficiency of construction land in the PRDM and realize sustainable development, differentiated land-use policies for the inner and peripheral circles were proposed. The inner circle should focus on promoting the efficiency of existing construction land and encourage urban renewal, while the peripheral circle should enhance the control of new construction land and improve its efficiency.

Optimising the spatial structure of cities to promote low-carbon travel is a primary goal of urban planning and construction innovation in the low-carbon era. There is a need for basic research on the structural characteristics that help to reduce motor traffic, thereby promoting energy conservation. We first review the existing literature on the influence of urban spatial structure on transport carbon dioxide emissions and summarise the influence mechanisms. We then present two low-carbon transportation oriented patterns of urban spatial structure including the traditional walking city and the modern transit metropolis, illustrated by case studies. Furthermore, we propose an improved model Green Transportation System Oriented Development (GTOD), which is an extension of traditional transit-oriented development (TOD) and includes the additional features of a walking city and an emphasis on the integration of land use with a green transportation system, consisting of the public transportation and non-auto travel system. A compact urban form, effective mix of land use and appropriate scale of block are the basic structural features of a low-carbon transportation city. However, these features are only effective at promoting low-carbon transportation when integrated with the green traffic systems. Proper integration of the urban structural system with the green space system is also required. The optimal land use/transportation integration strategy is to divide traffic corridors with wedge-shaped green spaces and limit development along the transit corridors. This strategy forms the basis of the proposed urban structural model to promote low-carbon transportation and sustainable urban growth management.

The nighttime stable light (NSL) images on board the Operational Line-scan System (OLS) of the Defense Meteorological Satellite Program (DMSP) are useful for extracting large-scale built-up urban areas. However, most NSL-based studies are presently empirical threshold-based approaches. They always overestimate the areas of built-up land in urban regions because of the ‘blooming’ effect of NSL; and overlook small patches in developing towns where the NSL is much lower. In this study, a neighborhood statistics analysis (NSA) method is developed on the basis of the relative spatial variations between neighboring built-up and non-built-up pixels in DMSP-OLS images. It is applied to extract the built-up areas of eight cities in the Pearl River Delta in 1996, 2000, 2005, and 2009. The validations indicate that the total areas of the NSA-mapped results are highly correlated with those from Landsat TM/ETM+ data (R2 = 0.94; p

Urban expansion models are useful tools to understand urbanization process and have been given much attention. However, urban expansion is a complicated socio-economic phenomenon that is affected by complex and volatile factors involving in great uncertainties. Therefore, the accurate simulation of the urban expansion process remains challenging. In this paper, we make an attempt to solve such uncertainty through a reversal process and view urban expansion as a process wherein the urban landscape overcomes resistance from other landscapes. We developed an innovative approach derived from the minimum cumulative resistance (MCR) model that involved the introduction of a relative resistance factor for dif- ferent source levels and the consideration of rigid constraints on urban expansion caused by ecological barriers. Using this approach, the urban expansion ecological resistance (UEER) model was created to describe ecological resistance surfaces suitable for simulating urban expansion and used to simulate urban expansion in Guangzhou. The study results demon- strate that the ecological resistance surface generated by the UEER model comprehensively reflects ecological resistance to urban expansion and indicates the spatial trends in urban expansion. The simulation results from the UEER-based model were more realistic and more accurately reflected ecological protection requirements than the conventional MCR-based model. These findings can enhance urban expansion simulation methods.

提升区域可达性能显著促进地区经济发展,可达性分析成为评估交通网络建设效益及制定决策的重要内容。针对传统可达性分析模型的不足,本文采用模拟精度更高的矢量—栅格集成法,以厦深高铁为例,分析高铁开通前后广东省东部区域可达性变化程度和空间分布,探讨高铁对研究区域不同尺度发展的影响。结果显示:厦深高铁显著提升区域交通可达性,但不同站点间提升程度有所差异;高铁对区域可达性影响具有显著的隧道效应,可达性变化较高的空间分布方向与厦深高铁一致;厦深高铁对区域交通可达性的公平性和区域产业发展都将产生一定影响,高铁对中小站点地区发展的刺激作用将是长期的过程。

Provincial carbon emissions research is necessary for China to realize emissions reduction targets. Two-level decomposition model based on the Kaya identity was applied to uncover the main driving forces for the energy related carbon emissions in Shandong province from 1995 to 2011, an important energy base in China. Coal consumption is still the biggest contributor to the increased carbon emissions in Shandong. Decomposition results show that the affluence effect is the most important contributors to the carbon emissions increments. The energy intensity effect is the dominant factor in curbing carbon emissions. The emission coefficient effect plays an important negative but relatively minor effect on carbon emissions. Based on the local realities, a series of environment-friendly mitigation policies are raised by fully considering all of these influencing factors. Sustainable mitigation policies will pay more attention to the low-carbon economic development along with the significant energy intensity reduction in Shangdong province.

Due to the lack of city-level energy consumption statistics and the inconsistency between national, provincial and city-level data, we developed a normalized approach for assessing China׳s city-level CO 2 emissions of energy consumptions using DMSP/OLS nighttime light imageries and explored major driving forces for proposing feasible mitigation policies. China׳s CO 2 emission process was always consistent with its economic development and was classified into two rapid periods (1999–2002 and 2007–2010) and two slow periods (1992–1999 and 2002–2007). Most cities in Western, Central and Northern China belonged to the slow growth type, while most cities in Eastern China belonged to the rapid growth type. Cities with huge CO 2 emissions mainly congregated in southern and eastern coastal areas. Contrarily, cities with small amount of CO 2 emissions were mainly located in southwestern inlands. The CO 2 emission per capita (PCCE) in Northeastern and Eastern China was higher than that of Western and Central China. While the CO 2 emission per GDP (PGCE) of Northeastern and Western China was higher than that of Eastern and Central China. GDP increment was the major factor determining the carbon-emission growth rate, while industry structures and energy efficiencies were the major factors influencing regional CO 2 emission intensities. Therefore, in order to decrease the growth rate of China׳s CO 2 emissions but not hinder its economic development, major efforts should be focused on optimizing the industrial structures in Eastern and Central China where industries mainly belonged to technology-intensive, labor-intensive and light industry types, and guiding companies to increase the energy efficiencies in Northeastern and Western China, where industries mainly belonged to heavy and energy-related types. In particular, more attention should be paid to prevent the CO 2 emissions per energy consumption (PECE) of underdeveloped cities or provinces from increasing rapidly rather than only focusing on reducing the PECE of developed regions.

Landsat TM images of the Pearl River Delta taken in 1988, 1998 and 2006 are used to explore the site factors that influence the construction land expansion in this study. Several site factors, including landscape types and the distances to roads, coastlines, or city centers, had significant impacts on the expansion of construction land, influencing the direction, scale and intensity of the expansion. The site factors serve as important natural and spatial indicators of the preferable locales for construction land expansion, describing tendencies to expand to locations in suburbs, plains and areas near roads or coastlines.

Understanding the factors that affect residents’ environmental conservation behaviors help in managing the environment of tourist sites. This research provides an integrative understanding of how residents near tourist sites form their environmental conservation behaviors by merging the norm-activation model and cognitive-affective model into one theoretical framework. Results of the structural analysis from a sample of 642 residents showed that this study’s proposed composite model includes a satisfactory level of predictive power for environmental conservation behaviors. The findings identify the following two dimensions of awareness of environmental consequences as having a key role in predicting environmental conservation behaviors: (1) awareness of positive consequences of environmental protection; and (2) awareness of disaster consequences. Results also show that environment attachment and personal norms about environmentalism played a mediating role between awareness of environmental consequences and environmental conservation behaviors, and that personal norms about environmentalism were the most powerful factor in predicting behaviors. Several practical implications were derived from the research findings that can contribute to environment management policy both within and outside the field of tourism, mostly notably: (1) how the effective promotion of these factors can encourage environmental conservation behaviors for residents; and (2) how governments can develop and implement environmental management measures to improve locals’ awareness of positive consequences of environmental protection.

The hub-and-spoke network has been applied in the maritime transport since 1980s. To realize the economy of scale, transoceanic containerships optimize their liner routes to call only a limited number of hub ports. This paper develops a non-Symmetrical Proportional Model to calculate the origin-destination (O-D) container matrix of the port system. Then a Hub-and-Spoke Maritime Container Transport model is applied in the China-Western Europe liner route, which is under the rapid expansion of container shipping, to determine the hub ports that the liners stop and call. To solve real-sized instances, the heuristic algorithm is proposed and the solution is optimized by comparing the alternative results from the model computation. For the hub location, Hamburg, Rotterdam, Zeebrugge, Hong Kong, Kaohsiung and Shanghai are the optimal hubs in the China-Western European container liner's route. At last, further research direction is predicted to simulate under the real scenario.

Landsat TM images of the Pearl River Delta taken in 1988, 1998 and 2006 are used to explore the Construction land Expansion and the Influence of Site Factors. The expansion shows the characteristics of gathering on plains and along major roads and coastlines in both periods from 1988 to 1998 and from 1998 to 2006. Several site factors, including landscape types and the distance from roads, coastlines, or the city center, had significant impacts on the expansion of construction land, influencing the direction, scale and intensity of the expansion. The site factors serve as important natural and spatial indicators of construction land expansion, describing tendencies to expand to locations in suburbs, plains and areas near roads or coastlines.