Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557187
De-Shun Yang, Jianhou Gan, Yi Luo
Urban road image segmentation is an important technology of intelligent city management and pilotless driving. In order to improve the effect of image segmentation, direct at the deficiency of single seed point and fixed threshold of traditional region growing algorithm, a seed selection method based on the gray level of two-dimensional histogram and local variance is proposed, and the dynamic threshold is used to change the region growing rule. The experimental results show that the seeds selected by this method can be highly representative, and realize the complete segmentation of the image. Based on the dynamic threshold region growth rule, the image segmentation has a better effect.
{"title":"Urban Road Image Segmentation Algorithm Based on Statistical Information","authors":"De-Shun Yang, Jianhou Gan, Yi Luo","doi":"10.1109/GEOINFORMATICS.2018.8557187","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557187","url":null,"abstract":"Urban road image segmentation is an important technology of intelligent city management and pilotless driving. In order to improve the effect of image segmentation, direct at the deficiency of single seed point and fixed threshold of traditional region growing algorithm, a seed selection method based on the gray level of two-dimensional histogram and local variance is proposed, and the dynamic threshold is used to change the region growing rule. The experimental results show that the seeds selected by this method can be highly representative, and realize the complete segmentation of the image. Based on the dynamic threshold region growth rule, the image segmentation has a better effect.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124003985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557083
Jie Han, Songlin Zhang, Yali LilZhenghuaDong, Xin Zhang
Weighted total least-squares for condition equation (WTLSC) is a method to solve the problem that random errors exist in both observation vector and coefficient matrix of condition equation. WTLSC takes into account the case that the elements in the observation vector and coefficient matrix are independent. But in some problems, the coefficient matrix and the observation vector have common elements. Therefore, this study extends the WTLSC into IWTLSC (improved WTLSC), to deal with the case that the elements in the observation vector and coefficient matrix are dependent. The derivation process of solutions, variance-covariance matrices and bias-corrections of IWTLSC are given. A simulated experiment is applied to illuminate the proposed IWTLSC method. Considering the dependent and independent condition respectively, two group simulated data are implemented. The results show that the IWTLSC method can obtain stable solution. The bias can be corrected effectively, and the IWTLSC method is an alternative strategy to solve the nonlinear problems without linearizing.
{"title":"An Improved Weighted Total Least-Squares for Condition Equation and Corresponding Bias-Corrected Method","authors":"Jie Han, Songlin Zhang, Yali LilZhenghuaDong, Xin Zhang","doi":"10.1109/GEOINFORMATICS.2018.8557083","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557083","url":null,"abstract":"Weighted total least-squares for condition equation (WTLSC) is a method to solve the problem that random errors exist in both observation vector and coefficient matrix of condition equation. WTLSC takes into account the case that the elements in the observation vector and coefficient matrix are independent. But in some problems, the coefficient matrix and the observation vector have common elements. Therefore, this study extends the WTLSC into IWTLSC (improved WTLSC), to deal with the case that the elements in the observation vector and coefficient matrix are dependent. The derivation process of solutions, variance-covariance matrices and bias-corrections of IWTLSC are given. A simulated experiment is applied to illuminate the proposed IWTLSC method. Considering the dependent and independent condition respectively, two group simulated data are implemented. The results show that the IWTLSC method can obtain stable solution. The bias can be corrected effectively, and the IWTLSC method is an alternative strategy to solve the nonlinear problems without linearizing.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124683977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557062
Xingran Ao, Hangbin Wu, Zhengwen Xu, Zhiqiang Gao
Structural damages on the surface of metro tunnel will affect service time and traffic safety seriously. Therefore, it is of great significance to study the method of damage detection. Based on roughness map, a new method for tunnel damage detection is proposed, which is mainly to determine the location of disease. Firstly, this paper uses central axis denoising algorithm to eliminate ancillary facilities. Then, based on the theory of Poisson reconstruction, an irregular triangulated grid of point cloud is constructed in order to calculate the area of polygons of first-order neighborhood for each point as surface area. Next, given that the standard cylinder of tunnel design shape, point cloud, which is projected onto the fitted cylinder, will be constructed grid to calculate projection area around each point. Finally, with the definition of the ratio between the surface area and the projected area, tunnel surface roughness can be extracted under the set threshold. Through experimental analysis for actual tunnel data, the feasibility and accuracy of the method is confirmed.
{"title":"Damage Extraction of Metro Tunnel Surface from Roughness Map Generated by Point Cloud","authors":"Xingran Ao, Hangbin Wu, Zhengwen Xu, Zhiqiang Gao","doi":"10.1109/GEOINFORMATICS.2018.8557062","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557062","url":null,"abstract":"Structural damages on the surface of metro tunnel will affect service time and traffic safety seriously. Therefore, it is of great significance to study the method of damage detection. Based on roughness map, a new method for tunnel damage detection is proposed, which is mainly to determine the location of disease. Firstly, this paper uses central axis denoising algorithm to eliminate ancillary facilities. Then, based on the theory of Poisson reconstruction, an irregular triangulated grid of point cloud is constructed in order to calculate the area of polygons of first-order neighborhood for each point as surface area. Next, given that the standard cylinder of tunnel design shape, point cloud, which is projected onto the fitted cylinder, will be constructed grid to calculate projection area around each point. Finally, with the definition of the ratio between the surface area and the projected area, tunnel surface roughness can be extracted under the set threshold. Through experimental analysis for actual tunnel data, the feasibility and accuracy of the method is confirmed.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129463504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557043
Shanzhen Yi, Wenhao Xie, Wenxia Yu
Near land surface atmospheric water vapor content is an import factor for land-atmosphere exchange, evapotranspiration and environment assessment. Currently it is lack of effective method for estimation of near land surface atmospheric water vapor content with a high spatial resolution and a large coverage area. This paper has proposed methods combining MODIS, NCEP/NCAR reanalysis data and DEM data for estimation of the near surface water vapor content. The proposed methods take advantage of NCEP/NCAR stratified pressure level data, MODIS high spatial resolution data, and DEM terrain analysis data for the estimation of near surface water vapor content. The methods are effectiveness and viable for water vapor estimation in high spatial resolution and large coverage area. An example is given for the illustration of the methods.
{"title":"Combining MODIS, NCEP/NCAR and DEM Data for Near Land Surface Atmospheric Water Vapor Estimation","authors":"Shanzhen Yi, Wenhao Xie, Wenxia Yu","doi":"10.1109/GEOINFORMATICS.2018.8557043","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557043","url":null,"abstract":"Near land surface atmospheric water vapor content is an import factor for land-atmosphere exchange, evapotranspiration and environment assessment. Currently it is lack of effective method for estimation of near land surface atmospheric water vapor content with a high spatial resolution and a large coverage area. This paper has proposed methods combining MODIS, NCEP/NCAR reanalysis data and DEM data for estimation of the near surface water vapor content. The proposed methods take advantage of NCEP/NCAR stratified pressure level data, MODIS high spatial resolution data, and DEM terrain analysis data for the estimation of near surface water vapor content. The methods are effectiveness and viable for water vapor estimation in high spatial resolution and large coverage area. An example is given for the illustration of the methods.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128449054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557184
Fankai Sun, Jin Zhang
The spatial distribution of 1300 coal mines in Shanxi Province are researched using the nearest neighbor index, L(d) function, nearest neighbor hierarchical spatial clustering, and kernel density estimation. The results show that the coal mines in Shanxi Province present the aggregated distribution, and with the increases of spatial scale, the degree of aggregation increases first and then decreases, and reaches maximum with a spatial scale of 35 km. There are three small-scale and high-density coal mines cluster areas in Xishan Mining Area, Liliu Mining Area and Huodong Mining Area respectively and four large-scale banded cluster areas in Datong-Pingshuo Mining Area, Yangquan Mining Area, Xiangning-Huozhou Mining Area, Jincheng-Lu'an Mining Area, and a large-scale planar cluster area in Fenxi-Huozhou Mining Area. The cluster areas present the spatial distribution features of “overall dispersion and partial agglomeration”, small-scale high-intensity aggregation areas and large-scale aggregation areas coexisting. It is basically consistent with the existing division of coal resources in Shanxi Province.
{"title":"Scale Features of Spatial Aggregation and Cluster Analysis of Coal Mines","authors":"Fankai Sun, Jin Zhang","doi":"10.1109/GEOINFORMATICS.2018.8557184","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557184","url":null,"abstract":"The spatial distribution of 1300 coal mines in Shanxi Province are researched using the nearest neighbor index, L(d) function, nearest neighbor hierarchical spatial clustering, and kernel density estimation. The results show that the coal mines in Shanxi Province present the aggregated distribution, and with the increases of spatial scale, the degree of aggregation increases first and then decreases, and reaches maximum with a spatial scale of 35 km. There are three small-scale and high-density coal mines cluster areas in Xishan Mining Area, Liliu Mining Area and Huodong Mining Area respectively and four large-scale banded cluster areas in Datong-Pingshuo Mining Area, Yangquan Mining Area, Xiangning-Huozhou Mining Area, Jincheng-Lu'an Mining Area, and a large-scale planar cluster area in Fenxi-Huozhou Mining Area. The cluster areas present the spatial distribution features of “overall dispersion and partial agglomeration”, small-scale high-intensity aggregation areas and large-scale aggregation areas coexisting. It is basically consistent with the existing division of coal resources in Shanxi Province.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128494854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557129
Jinyan Cai, Zeng Rui, Gang Ya
The Internet of things is to identify, locate, track, monitor and manage the perceiving objects through sensing devices. As a part of smart city, the combination of Internet of things and geographic information system will be used more and more widely, such as intelligent traffic network, intelligent environment detection network, forest fire prevention network and so on. These application networks feature single node generating small data packets and massive nodes connecting. Network energy supply and data effective transmission have become the objectives of the research. In this paper, a model of Adaptive Wireless Power Internet of things is proposed. The optimize methods of adaptive clustering based on space information of sensor nodes, data relay transmission and adaptive wireless energy supply are proposed to reduce network energy consumption. The simulation results indicate that the proposed methods can effectively overcome Near-Far Effect of network, ensure the transmission of node data and reduce the network energy consumption.
{"title":"Research of Adaptive Wireless Power Internet of Things","authors":"Jinyan Cai, Zeng Rui, Gang Ya","doi":"10.1109/GEOINFORMATICS.2018.8557129","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557129","url":null,"abstract":"The Internet of things is to identify, locate, track, monitor and manage the perceiving objects through sensing devices. As a part of smart city, the combination of Internet of things and geographic information system will be used more and more widely, such as intelligent traffic network, intelligent environment detection network, forest fire prevention network and so on. These application networks feature single node generating small data packets and massive nodes connecting. Network energy supply and data effective transmission have become the objectives of the research. In this paper, a model of Adaptive Wireless Power Internet of things is proposed. The optimize methods of adaptive clustering based on space information of sensor nodes, data relay transmission and adaptive wireless energy supply are proposed to reduce network energy consumption. The simulation results indicate that the proposed methods can effectively overcome Near-Far Effect of network, ensure the transmission of node data and reduce the network energy consumption.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127123530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557042
Yongyang Xu, Yaxing Feng, Zhong Xie, A. Hu, Xueman Zhang
The road network plays an important role for traffic management, GPS navigation and many other applications. Extracting the road from a high remote sensing (RS) imagery has been a hot research topic in recent years. The road structure always changing as the terrain, thus, how to extract the features of road network and identify the roads from RS imagery efficiently still a challenging. In this paper, we propose a road extraction method for RS imagery using the deep convolutional neural network, which is designed based on the deep residual networks and take full advantages of the U-net. Road network data form Las Vegas, America, are used to validate the method, and experiments show that the proposed model of deep convolutional neural network can extract road network accurately and effectively.
{"title":"A Research on Extracting Road Network from High Resolution Remote Sensing Imagery","authors":"Yongyang Xu, Yaxing Feng, Zhong Xie, A. Hu, Xueman Zhang","doi":"10.1109/GEOINFORMATICS.2018.8557042","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557042","url":null,"abstract":"The road network plays an important role for traffic management, GPS navigation and many other applications. Extracting the road from a high remote sensing (RS) imagery has been a hot research topic in recent years. The road structure always changing as the terrain, thus, how to extract the features of road network and identify the roads from RS imagery efficiently still a challenging. In this paper, we propose a road extraction method for RS imagery using the deep convolutional neural network, which is designed based on the deep residual networks and take full advantages of the U-net. Road network data form Las Vegas, America, are used to validate the method, and experiments show that the proposed model of deep convolutional neural network can extract road network accurately and effectively.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127391795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the establishment of Xiong'an New Area, the process of urbanization in Xiong’ an will further accelerate, and the water area of Baiyang Lake will also be increasingly influenced by man-made and natural factors. In this study, thirty-six Landsat remote sensing images from 1982 to 2017 were used to extract the visible waters of Baiyang Lake, the construction land and rural residential land in Xiong'an New Area. Furthermore, the temporal and spatial changes of visible waters, construction land and rural residential land, as well as precipitation in Xiong'an New Area were analyzed. The results showed that: (1) The expansion rate of construction land in urban and rural residential areas was very different before and after 2000, but they all regularly increased year by year, only slightly different in magnitude and increase speed. (2) The fluctuation of the visible water area of Baiyang Lake gradually decreased, and it experienced three various stages: from the continuous decrease by a wide margin of the visible water area to the dramatic fluctuation, and to a relative stabilization gradually. After the year of 2003, the water area of Baiyang Lake had basically stabilized. (3) The annual precipitation in Xiong'an New Area gradually decreased and the fluctuation was obvious. Currently, the Baiyang Lake has become an urban wetland under artificially controlled, and the establishment of Xiong'an New Area will further promote the urban expansion. In the future, it is still necessary to explore and clarify the internal relations between Baiyang Lake and Xiong'an New Area.
{"title":"The Study of Interannual Change of Urban Expansion, Precipitation and Water Area of Baiyang Lake in Xiong'an New Area","authors":"Sujie Liu, Yaoping Cui, Nan Li, Xiaoqing Deng, Xinyu Shi, Xiaomeng Liu, Fang Zhao","doi":"10.1109/GEOINFORMATICS.2018.8557084","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557084","url":null,"abstract":"With the establishment of Xiong'an New Area, the process of urbanization in Xiong’ an will further accelerate, and the water area of Baiyang Lake will also be increasingly influenced by man-made and natural factors. In this study, thirty-six Landsat remote sensing images from 1982 to 2017 were used to extract the visible waters of Baiyang Lake, the construction land and rural residential land in Xiong'an New Area. Furthermore, the temporal and spatial changes of visible waters, construction land and rural residential land, as well as precipitation in Xiong'an New Area were analyzed. The results showed that: (1) The expansion rate of construction land in urban and rural residential areas was very different before and after 2000, but they all regularly increased year by year, only slightly different in magnitude and increase speed. (2) The fluctuation of the visible water area of Baiyang Lake gradually decreased, and it experienced three various stages: from the continuous decrease by a wide margin of the visible water area to the dramatic fluctuation, and to a relative stabilization gradually. After the year of 2003, the water area of Baiyang Lake had basically stabilized. (3) The annual precipitation in Xiong'an New Area gradually decreased and the fluctuation was obvious. Currently, the Baiyang Lake has become an urban wetland under artificially controlled, and the establishment of Xiong'an New Area will further promote the urban expansion. In the future, it is still necessary to explore and clarify the internal relations between Baiyang Lake and Xiong'an New Area.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132073737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557121
Wenzheng Yang, J. Ma, Yujun Pan, Meilin Li
This paper took urban agglomeration in the middle of Yunnan Province as a research object, using fractal theory and fractal dimension methods, including aggregation dimension, grid dimension and correlation dimension. ArcGIS and the big data platform of Baidu-Map API were also used to calculate fractal dimension, in order to identify the spatial structure of urban system. There are some findings discovered in this study. Firstly, the density of urban agglomeration in the middle of Yunnan Province is decreasing while taking Kunming as the center. The urban system has a large number of blanks in the coverage of the region, and the potential spatial development of urban agglomeration is huge. Secondly, the capacity dimension is much larger than the information dimension, which shows that the topography of Yunnan High-mountain and Flat-dam restricts the spatial distribution of the urban agglomeration in central Yunnan Province, and the urban agglomeration is still in the primary stage of development. Thirdly, the cow-crow dimension is generally low, showing that the urban agglomeration in central Yunnan Province is limited by natural factors such as topography and water system. The level of traffic correlation needs to be improved. This study provides a reference for the healthy and orderly development of the urban agglomeration in central Yunnan Province, from the degree of aggregation, equilibrium and correlation to identify the spatial structure of urban agglomeration.
{"title":"Study on Spatial Structure Identification of Urban Agglomeration in Central Yunnan Province Based on Fractal Theory","authors":"Wenzheng Yang, J. Ma, Yujun Pan, Meilin Li","doi":"10.1109/GEOINFORMATICS.2018.8557121","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557121","url":null,"abstract":"This paper took urban agglomeration in the middle of Yunnan Province as a research object, using fractal theory and fractal dimension methods, including aggregation dimension, grid dimension and correlation dimension. ArcGIS and the big data platform of Baidu-Map API were also used to calculate fractal dimension, in order to identify the spatial structure of urban system. There are some findings discovered in this study. Firstly, the density of urban agglomeration in the middle of Yunnan Province is decreasing while taking Kunming as the center. The urban system has a large number of blanks in the coverage of the region, and the potential spatial development of urban agglomeration is huge. Secondly, the capacity dimension is much larger than the information dimension, which shows that the topography of Yunnan High-mountain and Flat-dam restricts the spatial distribution of the urban agglomeration in central Yunnan Province, and the urban agglomeration is still in the primary stage of development. Thirdly, the cow-crow dimension is generally low, showing that the urban agglomeration in central Yunnan Province is limited by natural factors such as topography and water system. The level of traffic correlation needs to be improved. This study provides a reference for the healthy and orderly development of the urban agglomeration in central Yunnan Province, from the degree of aggregation, equilibrium and correlation to identify the spatial structure of urban agglomeration.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/GEOINFORMATICS.2018.8557067
Chuanjia Gong, Sha Xu, Ziyu Tong
Modern urban highway entrances and exits are the first perceptual interface for people entering into cities from outside, and play a very important role in exhibiting a city's image. Erecting symbolic sculptures at optimal positions at highway on ramps and off ramps is a significant step in showcasing a city's image and is critical for a city's overall sculpture planning. At present, the locations of such sculptures still lack sufficient scientific analyses and judgment in terms of specific site selection. By using the ARCGIS viewshed analysis method and verifying new methods developed through the implementation of actual projects, this paper has studied and put forth a new method for determining sculpture locations at urban highway on and off ramps. Results indicate that this method can actually provide a more effective and scientific way to consider and plan sculpture locations and designs, bringing about convenience for utilizing portal spaces and promoting various cities' image.
{"title":"Study on the Potential Location of Sculptures at Urban Highway Entrances and Exits","authors":"Chuanjia Gong, Sha Xu, Ziyu Tong","doi":"10.1109/GEOINFORMATICS.2018.8557067","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557067","url":null,"abstract":"Modern urban highway entrances and exits are the first perceptual interface for people entering into cities from outside, and play a very important role in exhibiting a city's image. Erecting symbolic sculptures at optimal positions at highway on ramps and off ramps is a significant step in showcasing a city's image and is critical for a city's overall sculpture planning. At present, the locations of such sculptures still lack sufficient scientific analyses and judgment in terms of specific site selection. By using the ARCGIS viewshed analysis method and verifying new methods developed through the implementation of actual projects, this paper has studied and put forth a new method for determining sculpture locations at urban highway on and off ramps. Results indicate that this method can actually provide a more effective and scientific way to consider and plan sculpture locations and designs, bringing about convenience for utilizing portal spaces and promoting various cities' image.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126550397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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