Computers Environment and Urban Systems最新文献

{"title":"Estimating the density of urban trees in 1890s Leeds and Edinburgh using object detection on historical maps","authors":"Eleanor S. Smith ,&nbsp;Christopher Fleet ,&nbsp;Stuart King ,&nbsp;William Mackaness ,&nbsp;Hannah Walker ,&nbsp;Catherine E. Scott","doi":"10.1016/j.compenvurbsys.2024.102219","DOIUrl":"10.1016/j.compenvurbsys.2024.102219","url":null,"abstract":"<div><div>We present a new end-to-end methodology for extracting symbols from historical maps and demonstrate an application of the method to extract details of the urban forests of Leeds and Edinburgh in the UK using Ordnance Survey maps from the 1890s. The methods presented allow tree symbols on 1:500 scale maps to be efficiently extracted, with our object detection model achieving an <em>F</em>_<em>1</em>-score of 0.945. The results for each city are presented on the National Library of Scotland website and have been used to generate an estimate of 37 ± 1 tree symbols per hectare for Leeds in 1888–90 and 40 ± 1 tree symbols per hectare for Edinburgh in 1893–94. This is the first time that quantitative data has been obtained for historical urban tree counts in these two cities. The method presented can be expanded to other UK towns and cities and is a valuable tool for learning about the past, and changes to both the natural and built environment over time, aiding decisions on future tree planting. We discuss the process used to automate the generation of training data and to train a machine learning model to extract the symbols, comparing it with other possible models. This discussion provides context on how best to tackle similar problems of symbol extraction from historical maps and the issues that may arise in such automated analysis, alongside factors that must be considered when using historical maps as a data source.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"115 ","pages":"Article 102219"},"PeriodicalIF":7.1,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658804","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":"The role of data resolution in analyzing urban form and PM2.5 concentration","authors":"Ziwei Zhang ,&nbsp;Han Zhang ,&nbsp;Xing Meng ,&nbsp;Yuxia Wang ,&nbsp;Yuanzhi Yao ,&nbsp;Xia Li","doi":"10.1016/j.compenvurbsys.2024.102214","DOIUrl":"10.1016/j.compenvurbsys.2024.102214","url":null,"abstract":"<div><div>Despite the global concern about the chronic toxic effects of fine particulate matter (PM2.5) on human health, particularly in urban areas, the impact of urban form on PM2.5 pollution remains incompletely understood. This study established panel regression models for two resolutions (1 km and 30 m), covering 320 cities in China from 2000 to 2015, using landscape metrics and natural and socioeconomic variables to explore the urban form-PM2.5 relationship. The findings suggest that while the effects of fragmentation and agglomeration are opposite, the impact of urban scale on PM2.5 remains consistent across different resolutions. To unveil its mechanism, we compared authentic urban land use data under varying resolutions in detail and discovered that the coarse-resolution data lacked certain small patches, in addition to exhibiting edge deformation. As a result, we conducted counterfactual experiments on high-resolution land use data (30 m), simulating changes to urban patches, including removing small urban patches, dilating urban patch edges, and eroding urban patch edges. The implication of the findings is that the loss of information on small patches is more common in coarse resolution data than the deformation of patch edges, which in turn ultimately alters the results. Therefore, one of the major contributions of this study is exploring the mechanism of how spatial resolution impacts the relationship between urban form and PM2.5 concentration. The results can provide recommendations for sustainable urban development, emphasizing the significance of the scale effect in studies. This recommends urban planners to adopt a satellite urban development approach in which large cities are evenly distributed and minor ones are clustered together, with the aim of reducing PM2.5 pollution and human exposure.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"115 ","pages":"Article 102214"},"PeriodicalIF":7.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658803","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":"Causal discovery and analysis of global city carbon emissions based on data-driven and hybrid intelligence","authors":"Xiaoyan Li ,&nbsp;Wenting Zhan ,&nbsp;Fumin Deng ,&nbsp;Xuedong Liang ,&nbsp;Peng Luo","doi":"10.1016/j.compenvurbsys.2024.102206","DOIUrl":"10.1016/j.compenvurbsys.2024.102206","url":null,"abstract":"<div><div>The unclear causal links of carbon emissions among global cities challenge policy development. This study develops two causal discovery algorithms to aid in this understanding. The first, scalable causal discovery, excels in unraveling complex causal relationships within extensive non-Euclidean networks encompassing thousands of nodes. The second, knowledge-injection causal discovery, merges expert expertise with artificial intelligence's data mining capabilities, employing a human-computer interaction approach for precise causal analysis. The proposed algorithms outperform leading causal discovery methods in the Granger causality test and causal structural consistency. This study investigates the emission causal networks across global cities and key international organizations, including the Organization for Economic Cooperation and Development, the Commonwealth, G20, the Belt and Road Initiative, and the Asia-Pacific Economic Cooperation. The analysis encompasses networks, countries, cities, and emission sources, providing insights for developing collaborative urban emission reduction policies. It underscores the tightly interconnected nature of the worldwide emission network, where the effects are rapidly disseminated. Furthermore, sub-networks reveal consistency and variability in their causal patterns, with core cities exerting significant influence over various dynamics. It is essential to leverage the unique structural characteristics inherent in each sub-network to enhance the effectiveness of coordinated emission reduction initiatives.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"115 ","pages":"Article 102206"},"PeriodicalIF":7.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658798","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":"Exploring the built environment impacts on Online Car-hailing waiting time: An empirical study in Beijing","authors":"Jianhui Lai,&nbsp;Yanyan Wang,&nbsp;Yang Yang,&nbsp;Xiaojie Wu,&nbsp;Yue Zhang","doi":"10.1016/j.compenvurbsys.2024.102205","DOIUrl":"10.1016/j.compenvurbsys.2024.102205","url":null,"abstract":"<div><div>Waiting time is a critical metric for evaluating the quality of online car-hailing services, with studies indicating a close association between Online Car-hailing waiting time (CWT) and the urban built environment (BE). Points of interest (POI) data is widely utilized to characterize the built environment. However, quantifying the proper combination or spatial relationships between different types of POIs to capture the functional features of the built environment within a region poses a challenge. This paper proposes a framework for analyzing built environment characteristics based on a semantic probabilistic topic model utilizing Latent Dirichlet Allocation, demonstrating that integrating the building area of POIs along with the travel activity intensity at their respective locations enables a more precise identification of regional functions. Moreover, while some studies have explored the correlation between the built environment and waiting time, few have evaluated the nonlinear interactions between them. On this foundation, employing the machine learning technique XGBoost model in conjunction with online car-hailing order data, we probe the relationship between the built environment and waiting time. The research indicates that CWT is comprehensively affected by multiple factors. Taking weekday evening peak period as an example, the CWT of Central-urban area, where has dense commercial and office land use, positively correlated with commercial and office topics, while negatively correlated with educational, residential, leisure and healthcare topics, leading to a longer CWT in the Central-urban. In addition, the interaction between BEs can weakens their individual effects on CWT. A higher degree of job-residence balance can mitigate the negative impact of residential and office topics on increasing CWT, particularly in Intermediate-urban areas. Additionally, BE topics may also suppress the positive effect of road density on reducing CWT. The relationship between the BE and CWT exhibits threshold effects and a V-shaped relationship, indicating that the BE is significantly associated with CWT only within specific ranges. This correlation also exhibits a gradient pattern from the Central-urban to the Sub-urban, especially concerning office and residential topics. These outcomes elucidate the salient ranges of the built environment that exert substantial impacts on waiting time, informing strategic planning for online car-hailing dispatch and urban development to augment passenger travel satisfaction.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"115 ","pages":"Article 102205"},"PeriodicalIF":7.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586472","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":"Spatiotemporal dynamics of ethnoracial diversity and segregation in Los Angeles County: Insights from mobile phone data","authors":"Rongxiang Su ,&nbsp;Niall Newsham ,&nbsp;Somayeh Dodge","doi":"10.1016/j.compenvurbsys.2024.102203","DOIUrl":"10.1016/j.compenvurbsys.2024.102203","url":null,"abstract":"<div><div>Ethnoracial segregation persists as a pressing issue in American cities. Understanding these issues is crucial for promoting social equity and justice, and planning more inclusive cities. Prior research has predominantly emphasized residential ethnoracial diversity but has often overlooked or inadequately addressed ethnoracial diversity and segregation in individuals' daily activities and places they visit, due in part to data limitations. This study leverages a dynamic measure of ethnoracial diversity and dominance at the finest spatial scale, specifically at the Points of Interest (POI) level and various temporal contexts. Using one month of privacy-enhanced mobile phone location data in Los Angeles County, California, this study explores ethnoracial diversity and spatial segregation simultaneously in POI visits in LA County. Our findings confirm that individuals' daily mobility in urban areas enhances ethnoracial mixing at activity locations. Empirical results indicate that the diversity of visitors to a POI is significantly higher than the neighborhood diversity where the same POI is located. A significant positive linear relationship was found between the neighborhood diversity of POIs and the diversity of visitors. About 34 % of the variance in the diversity of visitors to POIs can be explained by the neighborhood diversity of POIs. Our results also suggest significant spatial clusters of isolated/integrated areas regarding ethnoracial mixing in people's daily activity locations. Notably, the Hispanic or Latino population tends to stay in their own communities and experiences a higher level of segregation in their daily activity locations. The findings have significant implications for urban planners and policymakers to design targeted solutions and policies to promote social equity, integration, and equal access to public amenities and opportunities in urban spaces.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"114 ","pages":"Article 102203"},"PeriodicalIF":7.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539459","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":"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}