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Underground Space 2023年第2期9卷 186-199页

作者： Yun-Hao Dong Fang-Le Peng Yang Du Yan-Qing Men Research Center for Underground Space and Department of Geotechnical Engineering Tongji UniversityShanghai 200092China Jinan Rail Transit Group Co. LTD.JinanShandong 250101China

Metro-led underground space(MUS)plays a crucial role in modern underground space *** studies have shown its great potential for high-quality urban ***,limited evidence about MUS was available on a national scale,resulting in incomplete and unsystematic knowledge of MUS *** interaction relationship between MUS and the surrounding built environment also remains *** fill the research gap,an automatic method for MUS identification and development features extraction was proposed based on point of interest *** applied the method to identify the MUS in 28 Chinese cities and estimated the development status of MUS in China for the first *** nationwide statistics of MUS and correlation analysis of development features were *** show that complex MUS(CMUS)share is significantly lower than that of simple ***,CMUS development in China is primarily dominated by public transport and does not have a solid functional link to its *** comparative analysis of MUS development in four primary urban agglomerations was also conducted,and their development char-acteristics were *** study aims to expand the planning toolkit and construct the MUS database,which sheds light on the data-driven planning for MUS.

关键词： Development features Metro-led underground space point of interest

Spatial identification of poverty in mountainous cities based on the mountain poverty spatial index:A case study of Ganzhou city in 2018 in China

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Journal of Mountain Science 2022年第11期19卷 3213-3226页

作者： WANG Jin-liang CUI Zhi-chao ZHOU Bing-juan School of Land Resources and Environment Jiangxi Agriculture UniversityNanchang 330045China Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology of Jiangxi Province Jiangxi Agriculture UniversityNanchang 330045China

Poverty is a severe barrier to sustainable human development and a pressing worldwide *** how to accurately assess the spatial distribution of poverty in mountain areas has become crucial for ensuring that governments at all levels take suitable poverty reduction *** this study,the mountain poverty spatial index(MPSI)was created by combining the digital elevation model(DEM),Luojia-1 night-time light imagery,point of interest(POI)data,and vegetation index *** MPSI was then used to identify the spatial characteristics of poverty at different scales in the hilly area of Ganzhou city,Jiangxi Province,*** statistics and Google satellite images were used to verify the reliability of MPSI by constructing a multidimensional poverty index(MPI)at the county *** results showed that MPSI and MPI have a positive correlation with a correlation coefficient of 0.8934(P<0.001),which indicates that MPSI could be used to identify the spatial distribution of poverty ***,the smallest distribution of both MPSI and MPI was in Zhanggong District(1.4555 and 0.1894),which indicates that most of the affluent counties were concentrated in the central region of Ganzhou,and the poor areas were scattered in the surrounding areas of *** addition,MPSI accurately identified poverty in mountainous areas with complex terrain in small administrative units,which can provide a more accurate way to monitor the poverty situation in the mountainous areas of *** study will be useful for providing scientific references for the Chinese government to implement targeted strategies for eradicating poverty with differentiated policies.

关键词： Mountain poverty Night-time light Remote sensing imagery Vegetation index point of interest Synthetic human settlement index

Identifying urban functional zones by capturing multi-spatial distribution patterns of points of interest

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International Journal of Digital Earth 2022年第1期15卷 2468-2494页

作者： Quan Qin Shishuo Xu Mingyi Du Songnian Li School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and ArchitectureBeijingPeople’s Republic of China Key Laboratory of Urban Spatial Informatics Ministry of Natural Resources of the People’s Republic of ChinaBeijingPeople’s Republic of China Department of Civil Engineering Toronto Metropolitan UniversityTorontoCanada

Urban Functional Zone(UFZ)identification is vital for urban planning,renewal,and *** of interest(POI),as one of the most popular data in UFZ studies,is transformed into a geo-corpus under specific sampling strategies,which can be used with Natural Language Processing(NLP)technology to extract geo-semantic features and identify ***,existing studies only capture a single spatial distribution pattern of POIs,while ignoring the other spatial distribution *** this paper,we developed an integrated geo-corpus construction approach to capture multi-spatial distribution patterns of POIs that were represented by different modal POI ***,random forest model was leveraged to classify UFZs based on those embeddings.A set of combination experiments were designed for performance *** results show that our proposed method can effectively identify UFZs with an accuracy of 72.9%,with an improvement of 8.5%compared to the baseline *** outcome of this study will help urban planners to better understand UFZs through investigating the integrated spatial distribution patterns of POIs embedded in UFZs.

关键词： Urban functional zone point of interest spatial distribution pattern natural language processing word2vec

Detection of text in images using SUSAN edge detector

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Journal of Harbin Institute of Technology(New Series) 2005年第1期12卷 34-40页

作者：毛文革张田文王力 Dept. of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Dept. of Mathematics Harbin Institute of Technology Harbin 150001 China

Text embedded in images is one of many important cues for indexing and retrieval of images and videos. In the paper, we present a novel method of detecting text aligned either horizontally or vertically, in which a pyramid structure is used to represent an image and the features of the text are extracted using SUSAN edge detector. Text regions at each level of the pyramid are identified according to the autocorrelation analysis. New techniques are introduced to split the text regions into basic ones and merge them into text lines. By evaluating the method on a set of images, we obtain a very good performance of text detection.

关键词： text detection SUSAN edge detector point of interest projection profile split and merge

The compactness of spatial structure in Chinese cities:measurement,clustering patterns and influencing factors

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Ecosystem Health and Sustainability 2020年第1期6卷 648-661,647页

作者： Fangqi Zhao Lina Tang Quanyi Qiu Gang Wu Key Lab of Urban Environment and Health Institute of Urban EnvironmentChinese Academy of SciencesXiamenChina University of Chinese Academy of Sciences BeijingChina State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijingChina

Rapid urbanization in China has led to an excessive urban expansion of built-up areas,which makes quantitative research on compact city *** adopted density and the degree of mixed land use to measure the compactness of 160 Chinese *** autocorrelation analysis was performed to identify spatial clustering patterns,and the relationships between compactness and five variables were explored through regression *** result shows that in nearly half of the cases,the calculated values of two indices are less than the *** high or low values of density and the degree of mixed land use tend to be spatially *** hot spot regions of density and the degree of mixed land use lie mainly in the south of China,while the north present as cold spots or the insignificant *** compactness can be affected by multifaceted factors and the relationships between compactness and five variables are not consistent throughout the areas of *** GWR model can identify this phenomenon and provides a better fit than the OLS *** study proposed a new approach to measure the compactness,and the results of GWR analysis can conducive to appropriate policy-making based on different local conditions.

关键词： Compact city urban spatial structure point of interest geographically weighted regression

Identifying the uneven distribution of health and education services in China using open geospatial data

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Geography and Sustainability 2023年第2期4卷 91-99页

作者： Shan Hu Rongtian Zhao Yuxue Cui Die Zhang Yong Ge Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China School of Government China University of Labor RelationsBeijing 100048China

Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development *** and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale *** means that such studies lack accessibility metrics for large-scale quantitative *** address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic *** accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 *** the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,*** terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,*** with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological ***,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national ***-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP *** accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG *** analysis of the uneven distribution of health and education services in Ch

关键词： Accessibility Poverty Geospatial data point of interest OpenStreetMap

POI Recommendations Using Self-attention Based on Side Information

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国际计算机前沿大会会议论文集 2020年第2期 62-76页

作者： Chenbo Yue Jinghua Zhu Shuo Zhang Xinxing Ma School of Computer Science and Technology Heilongjiang UniversityHarbin 150080China

point of interest(POI)recommendation is one of the most important tasks in location-based social networks(LBSN).The existing recommendation methods face two challenges:(1)the cold start problem caused by data sparsity;(2)underutilization of the abundant side information besides user-POI interaction in large-scale *** research shows that a user’s social relationship can be used to solve the cold start problem to some *** deep neural network learns users’long term and short term preferences to improve the recommendation ***,this paper proposes a POI recommendation model called SSANet,applying side information(S)and self-attention(SA)to provide the high-satisfaction POI recommendations for ***,first,the user-POI interaction matrix were constructed by users history data to represents the user hidden representation;second,the side information includes rating scores,access frequency,social relationship,and geographic information were used to extract users preference;third,we use self-attention mechanism to learn user long term and short term *** experimental results on the real LBSN datasets show that the recommendation performance of the SSANet model is better than the existing POI recommendation model.

关键词： Location-based social network Smart computing point of interest Location-based services and applications