Computers Environment and Urban Systems最新文献

{"title":"Machine-based understanding of noise perception in urban environments using mobility-based sensing data","authors":"Liuyi Song ,&nbsp;Dong Liu ,&nbsp;Mei-Po Kwan ,&nbsp;Yang Liu ,&nbsp;Yan Zhang","doi":"10.1016/j.compenvurbsys.2024.102204","DOIUrl":"10.1016/j.compenvurbsys.2024.102204","url":null,"abstract":"<div><div>An accurate understanding of noise perception is important for urban planning, noise management and public health. However, the visual and acoustic urban landscapes are intrinsically linked: the intricate interplay between what we see and hear shapes noise perception in the urban environment. To measure this complex and mixed effect, we conducted a mobility-based survey in Hong Kong with 800 participants, recording their noise exposure, noise perception and GPS trajectories. In addition, we acquired Google Street View images associated with each GPS trajectory point and extracted the urban visual environment from them. This study used a multi-sensory framework combined with XGBoost and Shapley additive interpretation (SHAP) models to construct an interpretable classification model for noise perception. Compared to relying solely on sound pressure levels, our model exhibited significant improvements in predicting noise perception, achieving a six-classification accuracy of approximately 0.75. Our findings revealed that the most influential factors affecting noise perception are the sound pressure levels and the proportion of buildings, plants, sky, and light intensity. Further, we discovered non-linear relationships between visual factors and noise perception: an excessive number of buildings exacerbated noise annoyance and stress levels and diminished objective noise perception at the same time. On the other hand, the presence of green plants mitigated the effect of noise on stress levels, but beyond a certain threshold, it led to worsened objective noise perception and noise annoyance instead. Our study provides insight into the objective and subjective perception of noise pressure, which contributes to advancing our understanding of complex and dynamic urban environments.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102204"},"PeriodicalIF":7.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inclusive accessibility: Analyzing socio-economic disparities in perceived accessibility","authors":"Armita Kar ,&nbsp;Ningchuan Xiao ,&nbsp;Harvey J. Miller ,&nbsp;Huyen T.K. Le","doi":"10.1016/j.compenvurbsys.2024.102202","DOIUrl":"10.1016/j.compenvurbsys.2024.102202","url":null,"abstract":"<div><div>Existing accessibility measures mainly focus on the physical limitations of travel and ignore travelers' perceptions, behavior, and socio-economic differences. By integrating approaches in time geography and travel behavior, this study introduces a bottom-up inclusive accessibility concept that aggregates individual-level travel perceptions across socio-economic groups to evaluate their multimodal access to opportunities. We classify accessibility constraints into hard constraints (physical space-time limitations to travel) and soft constraints (perceptual factors influencing travel, such as safety perceptions, comfort, and willingness to travel). We categorize travelers into 12 mutually exclusive socio-economic groups from a mobility survey dataset of 477 travelers. We apply a support vector regressor-based ensemble algorithm to estimate network-level walking perception scores as soft constraints for each social group. We derive group-specific inclusive accessibility measures that consider space-time limitations from transit and sidewalk networks as hard constraints and minimize the group-specific soft constraint to a certain threshold. Finally, we demonstrate the effectiveness of group-specific inclusive accessibility by comparing it with the classic access measure. Our study provides scientific evidence on how people of varying socio-economic statuses perceive the same travel environment differently. We find that socio-economically disadvantaged communities experience higher mobility barriers and lower accessibility while walking and using transit in Columbus, OH. Our study demonstrates a transition from person- to place-based accessibility measures by sequentially quantifying mobility perceptions for individual travelers and aggregating them by social groups for a large geographic scale, making this approach suitable for equity-oriented need-specific transportation planning.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102202"},"PeriodicalIF":7.1,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A graph-based modelling approach for the representation and analysis of urban conflicts","authors":"Catherine Trudelle ,&nbsp;Christophe Claramunt","doi":"10.1016/j.compenvurbsys.2024.102201","DOIUrl":"10.1016/j.compenvurbsys.2024.102201","url":null,"abstract":"<div><div>The many human interactions within cities inevitably generate relations between different places, civic and political organisations, authorities, and eventually conflictual events. Among all conflicts occurring in urban environments, if some are isolated events, many are connected by strong dependencies that generate networks in space and time. The research presented in this paper introduces a graph-based approach whose objective is to track the intertwined relations and dependencies that are associated with registered conflicts. The approach is experimented with and implemented using a combination of a graph-based database and visual graphics that together provide a series of data query capabilities and analysis specifically adapted to the context of our study. An experimental application to a series of conflicts reported in local media from 1985 to 2007 in the urban area of Montréal in Canada is presented and discussed.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102201"},"PeriodicalIF":7.1,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Satisfying transport needs with low carbon emissions: Exploring individual, social, and built environmental factors","authors":"Michał Czepkiewicz ,&nbsp;Filip Schmidt ,&nbsp;Dawid Krysiński ,&nbsp;Cezary Brudka","doi":"10.1016/j.compenvurbsys.2024.102196","DOIUrl":"10.1016/j.compenvurbsys.2024.102196","url":null,"abstract":"<div><div>The article studies the relationships between daily travel greenhouse gas (GHG) emissions and self-rated satisfaction with transport needs. It also investigates the conditions that satisfy one's transport needs at emission levels compatible with internationally agreed reduction targets by 2030 to keep warming below 1.5 degrees. It uses a representative geo-questionnaire survey from Poznan, a functional urban area in Poland (ca 800 thousand inhabitants), with 550 study participants answering questions used in the study. Four built environmental (BE) and accessibility measures are calculated using geospatial methods and used as predictors of low/high emission levels, low/high need satisfaction levels, and their combinations (i.e., <em>social-ecological quadrants</em>), along with socio-demographic characteristics and transport-related resources, competences, and responsibilities. The relationship between transport need satisfaction and GHG emissions is positive but weak and non-linear. In line with previous studies on well-being and energy or carbon footprints, the relationship appears to saturate (i.e., need satisfaction most steeply increasing at low emission levels). The saturation point is at the emission level lower than the 2030 1.5-degree compatible target (∼300 kg CO₂/year/person). A sizeable group (∼30 %) satisfies their transport needs at low emission levels (i.e., sufficiency condition). Exploratory spatial data analysis reveals that members of this group cluster in Poznan city center. All BE characteristics significantly and strongly influence the outcome variables, with central, densely populated, and walkable locations increasing the odds of having one's needs met at low emission levels. Retirees comprise about half of the sufficiency group, but there are also many workers. Specific transport needs that negatively impact the ability to meet one's needs at low emission levels, including multiple locations and doing errands on the way from or to work. The results support land use policies that reduce travel distances (i.e., densification, preventing sprawl, promoting walkable street designs) as they support low-carbon access to necessary activities for all social groups. Suburban residential locations, in turn, are associated with low need satisfaction and high emissions. The results also highlight that the ability to meet one's transport needs within the emission threshold is spatially and individually differentiated, with implications for climate policies in the mobility domain.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102196"},"PeriodicalIF":7.1,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling nonlinear and spatial non-stationary effects of urban form on surface urban heat islands using explainable spatial machine learning","authors":"Yujia Ming ,&nbsp;Yong Liu ,&nbsp;Yingpeng Li ,&nbsp;Yongze Song","doi":"10.1016/j.compenvurbsys.2024.102200","DOIUrl":"10.1016/j.compenvurbsys.2024.102200","url":null,"abstract":"<div><div>Under global warming, surface urban heat islands (SUHI) threaten human health and urban ecosystems. However, scant research focused on exploring the complex associations between urban form factors and SUHI at the county scale, compared with rich studies at the city scale. Therefore, this study simultaneously examined the nonlinear and spatial non-stationary association between SUHI and urban form factors (e.g., landscape structure, built environment, and industrial pattern) across 2321 Chinese counties. An explainable spatial machine learning method, combining the Geographically Weighted Regression, Random Forest, and Shapley Additive Explanation model, was employed to deal with nonlinearity, spatial non-stationary, and interpretability of modeling. The results indicate the remarkable spatial disparities in the relationship between urban form factors and SUHI. Landscape structure contributes the most in southern counties, while the built environment is more important in northeastern counties. The impact of building density and building height increases with the county size and becomes the main driver of urban heat in mega counties. Most urban form factors exhibit nonlinear impacts on SUHI. For example, urban contiguity significantly affects SUHI beyond a threshold of 0.93, while building density does so at 0.17. By comparison, the influence of shape complexity remains stable above a value of 7. Factors such as industrial density and diversity have a varied influence on SUHI between daytime and nighttime. The results of local explanations and nonlinear effects provide targeted regional mitigation strategies for urban heat.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102200"},"PeriodicalIF":7.1,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A specialized inclusive road dataset with elevation profiles for realistic pedestrian navigation using open geospatial data and deep learning","authors":"Reza Hosseini ,&nbsp;Samsung Lim ,&nbsp;Daoqin Tong ,&nbsp;Gunho Sohn ,&nbsp;Seyedehsan Seyedabrishami","doi":"10.1016/j.compenvurbsys.2024.102199","DOIUrl":"10.1016/j.compenvurbsys.2024.102199","url":null,"abstract":"<div><div>Built environment characteristics can greatly influence pedestrians' route choices with factors beyond distance, such as accessibility, convenience, safety, and aesthetics, playing crucial roles. Although current navigation apps, such as Google Maps and Waze, have successfully provided driving directions, their navigation services are insufficient and sometimes unrealistic for addressing pedestrians' needs, largely due to the lack of dedicated pedestrian networks and the associated navigation algorithms. To address the research gaps, this paper proposes a novel approach that integrates freely available geospatial data and computer vision technology to create a specialized inclusive network dataset for outdoor pedestrian navigation. Moreover, a pedestrian navigation algorithm is developed to generate more practical “shortest” and “alternative” paths by incorporating various sidewalk attributes. We applied the method to create a pedestrian navigation network in Las Vegas. SpaceNet's open imagery dataset was used to extract Las Vegas's road networks. A virtual audit process assessed the visual and operational properties of the sidewalk networks using Google street-level images, evaluating factors including sidewalk presence, widths, surface types and conditions, missing curb ramps, greenery, protection from weather conditions, and lighting. Google Earth's open elevation data were used to analyze road elevation profiles as meaningful 3D indicators of sidewalk accessibility for wheelchair users. Further, additional geometric properties of the network, including road curviness, proximity to road intersections, and directional changes, were detected and analyzed. A navigation experiment conducted with individuals having varying mobility abilities, including regular pedestrians, older adults, and wheelchair users demonstrated the effectiveness of the newly developed network and algorithm in meeting the diverse needs of pedestrians.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102199"},"PeriodicalIF":7.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategic allocation of landmarks to reduce uncertainty in indoor navigation","authors":"Reza Arabsheibani ,&nbsp;Jan-Henrik Haunert ,&nbsp;Stephan Winter ,&nbsp;Martin Tomko","doi":"10.1016/j.compenvurbsys.2024.102198","DOIUrl":"10.1016/j.compenvurbsys.2024.102198","url":null,"abstract":"<div><div>Indoor navigation systems often rely on verbal, turn-based route instructions. These can, at times, be ambiguous at complex decision points with multiple paths intersecting under angles that are not well distinguished by the <em>turn grammar</em> used. Landmarks can be included into turn instructions to reduce this ambiguity. Here, we propose an approach to optimize landmark allocation to improve the clarity of route instructions. This study assumes that landmark locations are constrained to a pre-determined set of slots. We select a minimum-size subset of the set of all slots and allocate it with landmarks, such that the navigation ambiguity is resolved. Our methodology leverages computational geometric analysis, graph algorithms, and optimization formulations to strategically incorporate landmarks into indoor route instructions. We propose a method to optimize landmark allocation in indoor navigation guidance systems, improving the clarity of route instructions at complex decision points that are inadequately served by turn-based instructions alone.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102198"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A tale of many cities: Mapping social infrastructure and social capital across the United States","authors":"Timothy Fraser ,&nbsp;Osama Awadalla ,&nbsp;Harshita Sarup ,&nbsp;Daniel P. Aldrich","doi":"10.1016/j.compenvurbsys.2024.102195","DOIUrl":"10.1016/j.compenvurbsys.2024.102195","url":null,"abstract":"<div><div>Research has underscored the role that social infrastructure - the places and spaces that help build and maintain social ties - plays in improving quality of life, lowering crime, and creating connection. Little work to date has shown how, across multiple urban environments, these parks, community centers, cafes, mosques, libraries, and other facilities correlate with bonding, bridging, and linking social capital. Our paper seeks to better understand the relationship between social infrastructure and bonding, bridging, and linking social capital along with inter-city differences in social facilities. We use Google map data from 25 urban centers in North America along with information from census-tract level Social Capital Index (SoCI) scores to map out these connections. We find that, controlling for other factors, social infrastructure positively correlates with bridging social capital - the weak or thin ties that build heterogeneous groups. As intended, many forms of social infrastructure help people engage with broader and more diverse networks, that is, provide a structure for connective democracy. Further, some cities' residents have extensive access to social infrastructure - such as those of Washington DC - while in others, such as Los Angeles, have far less. These findings bring with them policy recommendations for communities, NGOs, and decision makers alike.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102195"},"PeriodicalIF":7.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PRIME: A CyberGIS Platform for Resilience Inference Measurement and Enhancement","authors":"Debayan Mandal ,&nbsp;Lei Zou ,&nbsp;Rohan Singh Wilkho ,&nbsp;Furqan Baig ,&nbsp;Joynal Abedin ,&nbsp;Bing Zhou ,&nbsp;Heng Cai ,&nbsp;Nasir Gharaibeh ,&nbsp;Nina Lam","doi":"10.1016/j.compenvurbsys.2024.102197","DOIUrl":"10.1016/j.compenvurbsys.2024.102197","url":null,"abstract":"<div><div>In an era of increased climatic disasters, there is an urgent need to develop reliable frameworks and tools for evaluating and improving community resilience to climatic hazards at multiple geographical and temporal scales. Defining and quantifying resilience in the social domain is relatively subjective due to the intricate interplay of socioeconomic factors with disaster resilience. To broaden upon it, the choice of indicators and their subsequent ranking for the aggregation into an index is subjective in nature. This aggregation is not empirically validated and is prone to omit the nuances of localized resilience changes and causal factors affecting it, while leading to oversimplified conclusions. Meanwhile, there is a lack of scientifically and computationally rigorous, user-friendly tools that can support customized resilience assessment with consideration of local conditions. This study addresses these gaps through the power of CyberGIS with three objectives: 1) To develop an empirically validated disaster resilience model - Customizable Resilience Inference Measurement (RIM), designed for multi-scale community resilience assessment and influential socioeconomic factors identification; 2) To implement a Platform for Resilience Inference Measurement and Enhancement (PRIME) module in the CyberGISX platform backed by high-performance computing, enabling users to apply and customize RIM to compute and visualize disaster resilience; 3) To demonstrate the utility of PRIME through a representative study to understand the geographical disparities of county-level community resilience to natural hazards in the United States and identifying the driving factors of resilience in the social domain. Customizable RIM generates vulnerability, adaptability, and overall resilience scores derived from empirical parameters—hazard threat, damage, and recovery. Computationally intensive Machine Learning (ML) methods are employed to explain the intricate relationships between these scores and socioeconomic driving factors. PRIME provides a web-based notebook interface guiding users to select study areas, configure parameters, calculate and geo-visualize resilience scores, and interpret socioeconomic factors shaping resilience capacities. A representative study showcases the efficiency of the platform while explaining how the visual results obtained may be interpreted. The essence of this work lies in its comprehensive architecture that encapsulates the requisite data, analytical and geo-visualization functions, and ML models for resilience assessment. This setup provides a foundation for assessing resilience and strategizing enhancement interventions.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102197"},"PeriodicalIF":7.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experiencing the future: Evaluating a new framework for the participatory co-design of healthy public spaces using immersive virtual reality","authors":"Gamze Dane ,&nbsp;Suzan Evers ,&nbsp;Pauline van den Berg ,&nbsp;Alexander Klippel ,&nbsp;Timon Verduijn ,&nbsp;Jan Oliver Wallgrün ,&nbsp;Theo Arentze","doi":"10.1016/j.compenvurbsys.2024.102194","DOIUrl":"10.1016/j.compenvurbsys.2024.102194","url":null,"abstract":"<div><div>Urban densification is promoted for sustainable urban growth, yet it also generates concerns about negative health impacts on local citizens. Engaging local citizens in the co-design of densification projects is therefore crucial to address their needs and concerns. The use of immersive Virtual Reality (VR) technologies creates potential for advancing the participatory co-design of healthier urban spaces by allowing citizens to not only visualize but also experience the impacts of future designs or “what-if” scenarios. Theoretically grounded in an extended version of Sheppard's approach, which we call the Experiencing the Future Framework (EFF), we developed a study to create and evaluate an immersive VR application called CoHeSIVE. This application was designed to facilitate participatory co-design processes for healthy public spaces. CoHeSIVE, as the technological manifestation of our framework, was created through iterative workshops with end-user input. During the final workshop with 41 participants, both qualitative and quantitative data were collected, including user behavior and experiences with CoHeSIVE, especially regarding its experiential and interactive components. The vast majority of participants had positive experiences and recommended CoHeSIVE for participatory co-design processes. Participants felt confident in their design outcomes and found the user interface easy to use and effective for making and communicating design decisions. The most preferred design attributes were found to be many and clustered trees, several benches, large grass areas, high-rise buildings, more lampposts and the presence of a fountain, showing that the design outcomes were meaningful for the selected local context. Future enhancements of CoHeSIVE might include adding more design attributes, enhancing visual representations, adding multi-user capabilities, integrating generative AI and expanding CoHeSIVE's applicability to other contexts.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102194"},"PeriodicalIF":7.1,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0198971524001236/pdfft?md5=74d928f2aee7149cf037f706d9aabcd3&pid=1-s2.0-S0198971524001236-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}