Case Study Of Guangzhou Research Articles

Effect of urban green infrastructure on pedestrian exposure to ultrafine particles: A case study of Guangzhou, China

Traffic emissions, as the dominant source of urban Ultrafine Particles (UFP), pose great potential health risks to pedestrians who commute near busy roads. Green infrastructure is regarded as an effective measure for urban particulate pollution abatement. In this study, two weeks of mobile measurements of pedestrian UFP exposure were performed during morning and evening rush hours, along greenway and sidewalk with and without vegetation barrier near an arterial road. UFP concentration was observed to be 28.7% lower with weakened fluctuations on vegetation barrier sidewalk than on open sidewalk in average, while UFP lung-deposited surface area concentration decreased by 21.1% accordingly. Vegetation mitigated UFP concentration in general, however, locally intense heavy-duty vehicles activities might weaken this effect occasionally. The weekly and diurnal variations of UFP concentration and the greenery effect performance were attributable to the combined effect of practical traffic situations, meteorological conditions, and crowd activities. Gray relational analysis indicated that temperature (γ = 0.814), relative humidity (γ = 0.787), traffic volume (γ = 0.764) and heavy-duty vehicles count (γ = 0.741) were the top four impact factors on roadside UFP concentration during observation.

Uneven impacts of COVID-19 on residents' utilization of urban parks: A case study of Guangzhou, China

As COVID-19 increased people's dependency on urban parks for physical and psychological well-being, it also has uncertain impacts on park utilization. Understanding these impacts and how the pandemic has contributed to them is an issue that warrants urgent attention. We used multi-source spatio-temporal data to examine urban park use before and during COVID-19 in Guangzhou, China, and constructed a set of regression models to evaluate the associated factors. We found that COVID-19 has significantly reduced the overall utilization of urban parks while also exacerbating spatial unevenness. This was due to residents' limited movement distance, and the diminished role of urban transportation affecting the efficient citywide use of parks. Meanwhile, residents' increased demand for nearby parks amplified the importance of community parks, which exacerbated the consequences caused by the uneven distribution of park resources. We propose that city administrators improve the efficiency of existing parks and prioritize the adequate placement of community parks at urban fringes to improve access. Furthermore, cities with similar layouts as Guangzhou should plan for urban parks from a multi-perspective and consider the sub-city level differences to address unevenness during the current pandemic and in the future.

Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series

Climate change has led to the increased intensity and frequency of extreme meteorological events, threatening the drainage capacity in urban catchments and densely built-up cities. To alleviate urban flooding disasters, strategies coupled with green and grey infrastructure have been proposed to support urban stormwater management. However, most strategies rely largely on diachronic rainfall data and ignore long-term climate change impacts. This study described a novel framework to assess and to identify the optimal solution in response to uncertainties following climate change. The assessment framework consists of three components: (1) assess and process climate data to generate long-term time series of meteorological parameters under different climate conditions; (2) optimise the design of Grey-Green infrastructure systems to establish the optimal design solutions; and (3) perform a multi-criteria assessment of economic and hydrological performance to support decision-making. A case study in Guangzhou, China was carried out to demonstrate the usability and application processes of the framework. The results of the case study illustrated that the optimised Grey-Green infrastructure could save life cycle costs and reduce total outflow (56–66%), peak flow (22–85%), and TSS (more than 60%) compared to the fully centralised grey infrastructure system, indicating its high superior in economic competitiveness and hydrological performance under climate uncertainties. In terms of spatial configuration, the contribution of green infrastructure appeared not as critical as the adoption of decentralisation of the drainage networks. Furthermore, under extreme drought scenarios, the decentralised infrastructure system exhibited an exceptionally high degree of removal performance for non-point source pollutants.

Assessing hydrological performance for optimized integrated grey-green infrastructure in response to climate change based on shared socio-economic pathways

Integrated grey-green infrastructure (IGGI) is considered as a promising facility for mitigating urban flooding during extreme rainfall events. However, most IGGI strategies rely heavily on historical precipitation data, while ignoring the long-term effects of dynamic and non-stationary climate change. This study explored a novel approach to assess the hydrological performance under Shared Socio-economic Pathways (SSPs) based on long-term rainfall time series, facilitating the exploration of the optimal solution to urban runoff alleviation in response to climate change. A case study of Guangzhou, China, was applied for model validation. The results indicated that through non-stationarity analysis and stage division, the future time series of the three SSPs were identified with an abrupt point and divided into two stages. By assessing the hydrological performance of the optimal solutions at various historical and future stages, both fully centralized IGGI and decentralized IGGI are found vulnerable to long-term climate change. Based on a certain extent of trade-off between centralization and decentralization, an appropriate degree of decentralization was observed to significantly enhance the hydrological performance of the whole IGGI system, particularly for reducing peak flow following extreme rainfall events. The authors believe that the findings could provide a novel perspective on hydrological performance assessment for IGGI in response to non-stationary and multi-scenario climate change in urban catchments with high built-up density.

Drivers or Pedestrians, Whose Dynamic Perceptions Are More Effective to Explain Street Vitality? A Case Study in Guangzhou

As an important indicator of urban development capacity, vitality can be affected by the human perception of street views, which is a dynamic sensory process that can differ greatly according to different transportation modes, due to their different travel speeds, distances, and routes. However, few studies have evaluated how the dynamic spatial perceptions differ between different travel modes and how these differences can affect vitality differently, due to the limitation of city-scale quantitative data on the dynamic perception of urban scenes. To fill the gap, we propose a “dynamic through-movement perception” (DTMP) measure which integrates a streetscape quality evaluation model with a network-based movement potential model. We measure the streetscape qualities from Baidu street-view images (SVI) and compare the spatial perceptions of drivers and pedestrians in central Guangzhou, China. First, more than twenty visual elements were classified from SVIs to predict human perceptions collected from visual surveys. Second, the through-movement probability of driving and walking were calculated based on classic natural movement theory in space syntax and measured as the angular betweenness for the two travel modes. Third, we accumulate the multipliers of visual perception and through-movement probability of driving and walking as the DTMP for both modes. Lastly, the DTMPs of both modes were fitted into linear regression models to explain street vitality, which is measured using Baidu mobile phone check-in data, when other control variables such as functional density, functional diversity and amenity clustering reachability are accounted for. The results show that the dynamic perception of driving overall shows a stronger correlation with street vitality, while perceived richness is significantly positive in both travel modes. This study provides the first quantitative evidence to reveal how the movement probability of different travel modes can significantly influence people’s sense of place, while in turn increasing street vitality. Our results can explain how different types of street commerce (i.e., pedestrian-oriented, and auto-oriented) aggregate spontaneously due to the dynamic movement potential, which provides an important reference for urban planners and decision makers for improving street vitality when making urban revitalization policies.

Impact of landscape patterns on herb-layer diversity and seed size of Schima superba in urban remnant vegetation: A case study in Guangzhou, Southern China

In order to explore which ecological strategies the remnant vegetation is taken to adapt to urbanization, we investigated three kinds of typical remnant vegetation (grassland, plantation, and secondary forest) in 16 sample sites along the urban–rural gradient in the city of Guangzhou. In this study, we examined plant species composition, and plant diversity, and analyzed the seed of the dominant tree species Schima superba (S. superba) in the secondary forest sites. Those indicators are strongly related with ecological strategies. Eighteen landscape pattern characteristics were determined to reveal the extent of landscape fragmentation. Geographic Information System (GIS), linear regression, and Canonical Correspondence Analysis (CCA) were conducted to analyze the influence of landscape pattern characteristics on plant communities. Results showed that (1) Fragmentation of landscape patterns caused by urbanization has a negative impact on the diversity of herb-layer plants, the dominant species of grassland in the city center are mainly weeds, such as Bidens pilosa and Neyraudia reynaudiana. (2) In order to adapt to the pressure of landscape fragmentation, seeds of S. superba have developed into a larger size, with a competitive advantage over smaller ones. (3) Two different ecological strategies of plant communities adapting to urbanization: The pioneer weeds in grasslands, with high reproductive and dispersal ability, have adopted a r-selection strategy and the dominant tree species with higher survival rates, larger individuals, and longer life spans, have adopted a K-selection strategy to resist disturbance, as well as with a larger seed size to increase viability and settlement ability.

The spatial distribution of NIMBY facilities and housing prices in surrounding areas: A case study of Guangzhou

The spatial distribution of NIMBY facilities and housing prices in surrounding areas: A case study of Guangzhou

Spatial structure and driving pathways of the coupling between ecosystem services and human well-beings:A case study of Guangzhou

Spatial structure and driving pathways of the coupling between ecosystem services and human well-beings:A case study of Guangzhou

Information Services as a Method to Evaluate the Sustainability of Intangible Dimensions of a Historic Urban Landscape: A Case Study in Guangzhou, China

The historic urban landscape (HUL) is the result of the continuous dynamic process of production, interaction, and accumulation. It is full of information from bygone years and remains to this day as a living witness of antiquity and a benefit to the contemporary public, both in mind and spirit. These intangible benefits, however, are easier to overlook than the tangible ones in conservation and management efforts that aim at sustainability. Therefore, we return to the prototype of the category “cultural services” in the ecosystem classification “information service” to evaluate these intangible benefits. The objectives of this study are: (1) to provide a methodological framework to assess the ability of the landscape to continuously provide information services in the historical process; (2) to analyze the drivers affecting HUL’s ability to continuously deliver information services, and then discuss the governance experience of HUL’s intangible dimensions for sustainability. First, we regard HUL as an object to learn from the experience of urban heritage governance: using the methods and tools of ecosystem service evaluation, this paper evaluates the intangible services that the public receives from the landscape over several consecutive historical periods, summarizes the dynamic changes in these services, and analyzes their drivers. Furthermore, we consider that the aforementioned intangible services are brought about in part by the spread of heritage information stored in HUL among specific people, and the continuous provision of information services is considered the sustainability of HUL in intangible dimensions. We use Yuexiu Hill in the center of Guangzhou, China, as a case study to verify the feasibility of our methodological framework by evaluating the information services provided by this ancient area with a construction history of 2000 years over five historical periods. The data needed for the evaluation of the information service was obtained through text mining by retrieving 1063 ancient Chinese poems related to Yuexiu Hill from the poetry database. The results obtained through this evaluation framework will provide a quantitative basis for planning, design, and decision making in small and medium-sized landscapes.

A whale optimization algorithm–based cellular automata model for urban expansion simulation

• A whale optimization algorithm-based cellular automaton (WOA-CA) model for simulating urban expansion is innovatively proposed in this research. • A new objective function is designed in this research to help mining the transition rules. • The comparison results show that our proposed model outperforms five commonly used representative models in terms of the accuracy and computational efficiency. Cellular automata (CA) has proved to be effective and efficient in conducting urban expansion simulation. The generation of cell transition rules is a crucial step for a CA model. In this research, a whale optimization algorithm–based CA (WOA-CA) model was innovatively proposed. In the proposed model, a WOA was adapted to help mining the transition rules of the CA model, which was also evaluated and utilized in the case study of Guangzhou, simulating urban expansion from the year of 2000 to 2010. The experiment results demonstrated that the proposed model is effective and the simulation result is able to reach an overall accuracy of 92.16% with a Kappa coefficient of 0.744, and the value of Moran’s I is also quite close to that of the actual urban expansion. In addition, the proposed model has also been compared with a few representative CA models, including multi-criteria evaluation-based CA (MCE-CA), artificial neural network-based CA (ANN-CA), bat algorithm-based CA (BA-CA), convolution neural network for united mining-based CA (UMCNN-CA), and gray wolf optimizer-based CA (GWO-CA). The comparison results showd that our proposed model outperforms all these models in terms of overall accuracy and computational efficiency.

Comparing satellite image and GIS data classified local climate zones to assess urban heat island: A case study of Guangzhou

Cities are frontlines to tackle climate change challenges including the urban heat island (UHI) effect. The classification and mapping of local climate zones (LCZs) can effectively and consistently describe the urban surface structure across urban regions. This study pays attention to two mainstream methods in classifying LCZs, namely, by using geographic information system (GIS) data such as building footprints or remote sensing (RS) satellite images. Little has been done to compare the divergence and coherence of the abovementioned two methods in modeling UHI. Thus, by comparing pairwise LCZ classes of different urban form characteristics in Guangzhou, this study investigated how GIS- and RS-based approaches complement or conflict with each other in explaining the variance of UHI measured by land surface temperature (LST). First, while both GIS-based (R2 0.724) and RS-based (R2 0.729) approaches can effectively explain heat risks measured by LST, the RS-based method slightly outperforms the GIS counterpart. Second, the sizes of LCZs classified by two methods in urban core districts tend to converge but diverge in urban outskirts with disparities in low-rise urban forms. Both approaches found that LCZs with higher heights are all cooler among compact forms. LCZ E is always related to the highest average LST, and LCZ 7, 8, and 10 contribute significantly to heat islands from both GIS and RS results. This study has developed a comparable framework that is evident based for city planners, architects, and urban policy makers to evaluate which approaches can more accurately reveal relations between UHI and urban geometry with land cover.

Construction of a COVID-19 Pandemic Situation Knowledge Graph Considering Spatial Relationships: A Case Study of Guangzhou, China

The outbreak of COVID-19 (coronavirus disease 2019) has generated a large amount of spatiotemporal data. Using a knowledge graph can help to analyze the transmission relationship between cases and locate the transmission path of the pandemic, but researchers have paid little attention to the spatial relationships between geographical entities related to the pandemic. Therefore, we propose a method for constructing a pandemic situation knowledge graph of COVID-19 that considers spatial relationships. First, we created an ontology design of the pandemic data in which spatial relationships are considered. We then constructed a non-spatial relationships extraction model based on BERT and a spatial relationships extraction model based on spatial analysis theory. Second, taking the pandemic and geographic data of Guangzhou as an example, we modeled a pandemic corpus. We extracted entities and relationships based on this model, and we constructed a pandemic situation knowledge graph that considers spatial relationships. Finally, we verified the feasibility of using this method as a visualization exploratory tool in the analysis of spatial characteristics, pandemic development situation, case sources, and case relationships analysis of pandemic-related areas.

An Improved Publicness Assessment Tool Based on a Combined Spatial Model: Case Study of Guangzhou, China

By 2021, the urbanization rate of China had reached as high as 64.72%. At the same time, the efficiency-driven urban planning paradigm had shifted to that of an efficiency-and-fairness intent. Fairness refers to the publicness of public open spaces (POS) as an indicator of an inclusive and fair city. The authors are interested in the measure of POS. However, few studies evaluated POS by effective assessment frameworks and tools. Based on this critique, the authors propose to integrate a qualitative assessment tool—the Star Model, with that of a quantitative assessment tool—the Space Syntax, for assessing publicness and enhancing the understanding of POS (streets and squares). There are two conclusions: (1) The combined use of the quantitative and qualitative tools provides accuracy and enables a comprehensive understanding of public spaces, namely, the mechanism of publicness—of both bottom-up POS and top-down POS. On the one hand, bottom-up POS is an outcome of the spatial system enabled by a networked structure of space. On the other, the publicness of top-down POS can be largely twisted by the government and urban designers rather than the residents. (2) This research has introduced an improved combined tool for the benefits of both policymakers and planners.

Urban construction land demand prediction and spatial pattern simulation under carbon peak and neutrality goals: A case study of Guangzhou, China

Urban construction land demand prediction and spatial pattern simulation under carbon peak and neutrality goals: A case study of Guangzhou, China

Heterogonous buyers and housing transaction prices: a case study of Guangzhou, China

We investigate whether and the extent to which buyer’s characteristics affect housing transaction prices. Using the transaction data of existing apartments from 2014 to 2017 in Guangzhou, China, our results show that buyer’s locality, motivation and financial ability affect the transaction prices. Non-local buyers pay a premium. First-time buyers gain a discount. Experienced repeat buyers for upgrading pay a premium. We also find that buyer’s financial ability affects purchasing power and transaction prices. The buyers paying the acquisition with mortgage gain a higher discount or pay a lower premium than their counterparts paying in cash. Internet use itself won’t affect transaction price. When it is combined with buyer’s other characteristics, the buyers using the internet to obtain the property information have an information advantage over the ones using the traditional method and gain a higher discount or pay a lower premium than their counterparts using the traditional method, especially for the non-local. This finding is important for market participants and regulators to improve market efficiency and transparency by improving the accuracy of the information disclosed on the Internet.

Influences of Differentiated Residence and Workplace Location on the Identification of Spatiotemporal Patterns of Dengue Epidemics: A Case Study in Guangzhou, China.

The location of the infections is the basic data for precise prevention and control of dengue fever (DF). However, most studies default to residence address as the place of infection, ignoring the possibility that cases are infected at other places (e.g., workplace address). This study aimed to explore the spatiotemporal patterns of DF in Guangzhou from 2016 to 2018, differentiating workplace and residence. In terms of temporal and spatial dimensions, a case weight assignment method that differentiates workplace and residence location was proposed, taking into account the onset of cases around their workplace and residence. Logistic modeling was used to classify the epidemic phases. Spatial autocorrelation analysis was used to reveal the high and early incidence areas of DF in Guangzhou from 2016 to 2018. At high temporal resolution, the DF in Guangzhou has apparent phase characteristics and is consistent with logistic growth. The local epidemic is clustered in terms of the number of cases and the time of onset and outbreak. High and early epidemic areas are mainly distributed in the central urban areas of Baiyun, Yuexiu, Liwan and Haizhu districts. The high epidemic areas due to commuting cases can be further identified after considering the workplaces of cases. Improving the temporal resolution and differentiating the workplace and residence address of cases could help to improve the identification of early and high epidemic areas in analyzing the spatiotemporal patterns of dengue fever in Guangzhou, which could more reasonably reflect the spatiotemporal patterns of DF in the study area.

The Impact of Rail Transit on Accessibility and Spatial Equity of Public Transit: A Case Study of Guangzhou, China.

The urban rail transit network provides the possibility for people to shift from car to public transit for travel. This paper clarified the relationships among public transit, accessibility, and equity and studied the impact of rail transit on public transit accessibility that incorporates the measure of travel time and transit fare and the impacts’ spatial equity. The results show that rail transit contributes to the similar distribution between high rate of changes of time-based accessibility communities and fare-based accessibility communities, which are located nearby the rail transit lines. The degree of inequity in travel time is higher than the degree in transit fare in two scenarios. Due to the well-connected bus transit in the city center, absolute changes in travel time are slight, while relative changes are high. The rail transit has promoted the improvement of public transit equity in some areas. The difference between the time-based accessibility of Conghua District, northern and southern Baiyun District, Huadu District, Nansha District and southern Panyu District, and other communities is getting smaller, which is conducive to the improvement of spatial equity. The results provide theoretical support for the development of an integrated multimodal public transit system.

Impact of spatial discretization resolution on the hydrological performance of layout optimization of LID practices

• Four SWMM models with various spatial discretization resolutions were constructed. • The scale effects on the LID layout optimization are discussed. • Solutions optimized by the finest model performed best under small rainfall events. • Modelling scale had little impact on the layout optimization under a heavy rainstorm. • Layouts optimized by a coarse model overshadowed some types of LID practices. Climate change and increasing urbanization have worsened urban floods and other water problems, and it is generally accepted that the optimization of the spatial layout of low impact development (LID) practices is a promising solution. Existing studies have focused on coupling the hydrological model with optimization methods, but little is known about the effects of the spatial discretization of the model on the optimization results. In this study, the scale effects were examined in a case study in Guangzhou, China. Four models at various spatial discretization levels, namely models R1, R2, R3, and R4, with an average unit size of 0.022*10 4 , 0.405*10 4 , 2.43*10 4 , and 4.865*10 4 m 2 , respectively, were constructed to investigate the performance difference caused by delineation scales. The results show that the highest-resolution model R1 (one unit represented one type of land cover) provides more cost-effective layout schemes, but during a heavy rainstorm, the solution set provided by a coarser model are very similar to that generated by the finest model R1. A coarser model can provide wider solution sets, but most of these schemes overshadow some types of LID practices such rain garden and bio-retention cell, which also have a critical role in urban heat mitigation, air quality improvement, and so on. Due to the cumbersome work of catchment subdividing and time-consuming optimization process, a coarse model would be a good substitute to a large area. These findings provide new insights on how to achieve better performance by subdividing the catchment at a proper scale when optimizing the spatial layout of LID practices.

Environmental Risk Assessment of Polycyclic Aromatic Hydrocarbons in Farmland Soils near Highways: A Case Study of Guangzhou, China.

Recently, the rapid growth in vehicle activity in rapidly urbanized areas has led to the discharge of large amounts of polycyclic aromatic hydrocarbons (PAHs) into roadside soils and these compounds have gradually accumulated in the soil, which poses a serious threat to national food security and public health. However, previous studies did not clearly investigate the seasonal differences in PAH pollution of roadside soil by different highways. Therefore, based on field investigations, this study collected 84 soil surface samples to compare the pollution characteristics of 16 PAHs in farmland soils located near different roads in different seasons in Guangzhou, China. The results showed that the concentration of Σ16PAHs in farmland soils in spring (with a mean value of 258.604 μg/kg) was much higher than that in autumn (with a mean value of 157.531 μg/kg). There are differences in the PAH compositions in spring (4 ring > 3 ring > 5 ring > 6 ring) and autumn (4 ring > 5 ring > 6 ring > 3 ring). The proportion of 4–6 ring PAHs was much higher than 2–3 ring PAHs in both seasons. The spatial differences were significant. The sampling areas with higher concentrations of 16 PAHs were Tanbu Town, Huadu District (TB), Shitan Town, Zengcheng District (ST), and Huashan Town, Huadu District (HS), while the lowest concentration was in Lanhe Town, Nansha District (LH). The results of the diagnostic ratios showed that the main source of soil PAHs consists of a mixed source from petroleum and biomass combustion. The results from the total pollution assessment method and Nemerow index method indicated that the pollution levels of PAHs in the farmland soils indicated weak contamination. Our study provides a scientific basis for the prevention and control of soil pollution in farmlands near highways.

Research on the Operation Management and Optimization Path of Quarantine Hotels During Disasters from the Perspective of Emergency Shelters: a Case Study of Guangzhou, China

In order to meet the demand for large-scale temporary centralized medical observation of public security emergencies, China has launched large-scale hotels as centralized quarantine places. The disaster operation mechanism of quarantine hotels needs to be optimized. Based on the constructivism perspective, this study selects quarantine hotels in Guangzhou, China as a case study. In-depth interviews and text analysis were used to explore the operation mechanism, risk and optimization path of quarantine hotels through dialogue with research literature on emergency shelters. The study adds to the story of urban resilience.