2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM)最新文献_第4页

Extracting map information from trajectory and social media data 从轨迹和社交媒体数据中提取地图信息

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298018

Jun Li, Huayang Dai, Yuan Zhang, Q. Qin, Hong-bo Jiang

引用次数: 0

Comparing multilevel modelling and artificial neural networks in house price prediction 多层模型与人工神经网络在房价预测中的比较

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298035

Yingyu Feng, K. Jones

引用次数: 23

Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments 复杂城市环境下多视点激光扫描点云自动配准

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298041

Bisheng Yang, Z. Dong, Wenxia Dai, Yuan Liu

引用次数: 0

Toward a new approach for massive LiDAR data processing 迈向大规模激光雷达数据处理的新方法

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298040

V.-H. Cao, K.-X. Chu, Nhien-An Le-Khac, Mohand Tahar Kechadi, D. Laefer, L. Truong-Hong

{"title":"Toward a new approach for massive LiDAR data processing","authors":"V.-H. Cao, K.-X. Chu, Nhien-An Le-Khac, Mohand Tahar Kechadi, D. Laefer, L. Truong-Hong","doi":"10.1109/ICSDM.2015.7298040","DOIUrl":"https://doi.org/10.1109/ICSDM.2015.7298040","url":null,"abstract":"Laser scanning (also known as Light Detection And Ranging) has been widely applied in various application. As part of that, aerial laser scanning (ALS) has been used to collect topographic data points for a large area, which triggers to million points to be acquired. Furthermore, today, with integrating full wareform (FWF) technology during ALS data acquisition, all return information of laser pulse is stored. Thus, ALS data are to be massive and complexity since the FWF of each laser pulse can be stored up to 256 samples and density of ALS data is also increasing significantly. Processing LiDAR data demands heavy operations and the traditional approaches require significant hardware and running time. On the other hand, researchers have recently proposed parallel approaches for analysing LiDAR data. These approaches are normally based on parallel architecture of target systems such as multi-core processors, GPU, etc. However, there is still missing efficient approaches/tools supporting the analysis of LiDAR data due to the lack of a deep study on both library tools and algorithms used in processing this data. In this paper, we present a comparative study of software libraries and new algorithms to optimise the processing of LiDAR data. We also propose new method to improve this process with experiments on large LiDAR data. Finally, we discuss on a parallel solution of our approach where we integrate parallel computing in processing LiDAR data.","PeriodicalId":404001,"journal":{"name":"2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127057345","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}

引用次数: 12

A method based on spatial analyst to detect hot spot of urban component management events 基于空间分析的城市构件管理事件热点检测方法

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298025

Peipei Dai, Changfeng Jing, Mingyi Du, Wensheng Zhou

{"title":"A method based on spatial analyst to detect hot spot of urban component management events","authors":"Peipei Dai, Changfeng Jing, Mingyi Du, Wensheng Zhou","doi":"10.1109/ICSDM.2015.7298025","DOIUrl":"https://doi.org/10.1109/ICSDM.2015.7298025","url":null,"abstract":"Rapid growth of urban public facilities increased the important impact on urban component management in case number and hotspot space distribution. Many urban component management events such as huddle of wastes and illegal ads have been frequently hot issues. To support the government decision, methods and flows based on spatial analyst are put forward to explore the hot spot of urban component management event. Illegal ads event is taken as case study. The event's spatial correlation is decided by using exploratory spatial data analysis and Global Moran's I. Ripley's K is used to explore its spatial distribution pattern, which provides the basis for urban management events data mining. To identify the spatial border of hot spots, the spatial hot spot analysis is employed. Finally, the overlay spatial analyst between hot spot and business area layer and/or residential building layer is used to validate the feasibility and rationality of the hot spot analysis. It is concluded that illegal ads event has obvious spatial clustering and coincides exactly with the existing business area and places where population flows more frequently. According to the result, the urban management administrators can make decision more conveniently and reasonably. Comparing with time series analysis methods, this method has advantage in space information, good visualization and dynamic monitor which are useful for government decision.","PeriodicalId":404001,"journal":{"name":"2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125585185","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}

引用次数: 2

Spatial patterns of retail stores using POIs data in Zhengzhou, China 基于poi数据的郑州市零售商店空间格局研究

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298031

Caihui Cui, Zhigang Han

{"title":"Spatial patterns of retail stores using POIs data in Zhengzhou, China","authors":"Caihui Cui, Zhigang Han","doi":"10.1109/ICSDM.2015.7298031","DOIUrl":"https://doi.org/10.1109/ICSDM.2015.7298031","url":null,"abstract":"Identifying spatial patterns of geographic entities such as retail stores is important in city for understanding how they behave. The pattern formed by the distribution of points can be measured by some quantitative methods. In Big Data era, the data sets for spatial patterns analysis are various including traditional street network data and points of interest (POIs) data in LBS (Location based services) application. This paper analyzed the spatial pattern of retail stores and its correlations with street centrality using POIs data in Zhengzhou, China. Firstly, the paper provided an exploratory analysis of spatial patterns using the centrographic methods including Standard Deviational Ellipse and Average Nearest Neighbor. Secondly, the paper uncovered the spatial distribution of retail stores using the kernel density estimation (KDE). Finally, the paper calculated the street centrality of Zhengzhou using three centrality assessment indexes and converted all nodes centrality index values to raster pixel using KDE for correlation analysis. Results show that the retail stores are clustering pattern and mainly elongated along the west-east direction. The street centralities are correlated with the retail store location in Zhengzhou, and there is a different level of correlation between them. The paper reveals that the spatial pattern analysis and street centralities index are valuable in location analysis or urban planning.","PeriodicalId":404001,"journal":{"name":"2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133803180","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}

引用次数: 8

Machine learning based social media recommendation 基于社交媒体推荐的机器学习

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298020

Tai-Ku Lai, Xianghan Zheng

引用次数: 2

Research and realization on integrated management of multisource heterogeneous satellite data based on spatial database 基于空间数据库的多源异构卫星数据综合管理研究与实现

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298049

Fanghong Gao, P. Jiang, Xiangxiang Li, Hongqiang Wang

引用次数: 0

Depth estimation from a single outdoor image based on scene classification 基于场景分类的单幅户外图像深度估计

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-08 DOI: 10.1109/ICSDM.2015.7298050

Liu Dan, Wang Meizhen, L. Xuejun

引用次数: 1

Detecting and analysis of coast changes of Xiamen Island by RS & GIS 基于RS & GIS的厦门岛海岸变化探测与分析

2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM) Pub Date : 2015-07-01 DOI: 10.1109/ICSDM.2015.7298053

Fengqin Sun, L. Hua, Hui Li, Yanting Wang, Yaqi Chen

{"title":"Detecting and analysis of coast changes of Xiamen Island by RS & GIS","authors":"Fengqin Sun, L. Hua, Hui Li, Yanting Wang, Yaqi Chen","doi":"10.1109/ICSDM.2015.7298053","DOIUrl":"https://doi.org/10.1109/ICSDM.2015.7298053","url":null,"abstract":"Multi-temporal Landsat images in 1999, 2006 and 2013 were used to reveal the spatial-temporal changes of the coastal locations and types of Xiamen Island. The high tide water levels were extracted as coastline approximations and the coastal types were made by manual interpretation based on Google earth high resolution images in this study. The results indicated that the coast changes mainly happened at the northern and eastern parts of the island. The artificial coast came up to 46.4 km with an increment about 8.8 km due to sea reclamation while the mudflat coast decreased about 18.1 km and faded away from 1999 to 2006. Then there was another increase of artificial coast due to returning ponds back to sea, and the sand coast also increased due to sand supply project from 2006 to 2013. Thus the artificial coast increased to 48.0 km and the sand coast increased from 10.1 km to 16.9 km. The total coastline decreased from 66.4 km to 57.0 km first but then increased back to 65.5 km during the whole period while the island area had a persistent growth from 128.5 km2 to 140.0 km2. The coastlines moved northward and seaward with less curves due to local constructions except the parts returning ponds back to sea. The rapid social and economic development raised great demand of land use as well as the environmental quality, which made sea reclamation and returning ponds back to sea the main causes of coast changes of Xiamen Island.","PeriodicalId":404001,"journal":{"name":"2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115134855","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}

引用次数: 1