2013 21st International Conference on Geoinformatics最新文献_第2页

Spatial structure of the economic network of Central Plains Economic Zone 中原经济区经济网络的空间结构

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626021

Shaoqi Pan, Yating Li, Jianhua Gao

{"title":"Spatial structure of the economic network of Central Plains Economic Zone","authors":"Shaoqi Pan, Yating Li, Jianhua Gao","doi":"10.1109/Geoinformatics.2013.6626021","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2013.6626021","url":null,"abstract":"This paper will focus on the spatial structure of the economic network of Central Plains Economic Zone, 231 nodes which are at county level and above in this area are considered, their intensity of economic connection were computed based on gravity model in 1996 and 2010. Then, spatial pattern and evolution characteristics of the economic network of Central Plains Economic Zone are analyzed. The result shows: (1) There is significant difference among the node's cyber power in the economic network of Central Plains Economic Zone. Node's degree has a fat-tailed distribution to the right. Zhengzhou is the absolute center of the economic network and Luoyang is the subcenter as well as Handan. (2) According to the spatial structure of the economic network, the whole network can be divided into five communities. (3) The network is in a period of polarization. The hub node's cyber power is increasing such as Zhengzhou and Luoyang, etc. (4) Most hub nodes of the economic network are located in Central Plains City Group, so the development of Central Plains City Group is critical to enhance the connected ability of the economic network.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129668923","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: 0

UAV image mosaic based on adaptive SIFT algorithm 基于自适应SIFT算法的无人机图像拼接

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626167

Shujuan Sun, Zhe Zeng

引用次数: 6

The application of the MODHMS in contaminant transport simulation MODHMS在污染物迁移模拟中的应用

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626050

Qiannan Li, Jing Zhang, Yin Wu, H. Gong, Xiaoguang Cheng

引用次数: 0

MODIS infrared (IR) water vapor calibration model and assessment MODIS红外(IR)水汽定标模型及评价

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626197

Liang Chang, Shuanggen Jin

引用次数: 2

Building Topological Flow-path Networks based on scale-adaptive DEM 基于尺度自适应DEM的拓扑流道网络构建

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626134

Yumin Chen, X. Bi, Yajuan Li, Qiao Wan

引用次数: 0

An automatic coastline extraction method based on active contour model 一种基于活动轮廓线模型的海岸线自动提取方法

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626130

Hongwei Zhang, Baoming Zhang, Haitao Guo, Jun Lu, Hong He

引用次数: 13

Analysis of accurately estimating infiltration rate of river's flow routing model 河流路线模型入渗率的准确估算分析

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626150

H. Tong, Zongzhi Wang, Ruonan Hao, Shixiong Hu

引用次数: 0

Study on Grain for Green Project implementation effect monitoring based on high resolution image — A case study in Ansai County, Shanxi Province, China 基于高分辨率图像的退耕还林工程实施效果监测研究——以山西省安塞县为例

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626210

Junxiang Zhu, Juanle Wang

{"title":"Study on Grain for Green Project implementation effect monitoring based on high resolution image — A case study in Ansai County, Shanxi Province, China","authors":"Junxiang Zhu, Juanle Wang","doi":"10.1109/Geoinformatics.2013.6626210","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2013.6626210","url":null,"abstract":"China has implemented the Grain for Green Project (GGP) since 1999 and up until today. It is emergent to search for smart methods utilizing remote sensing to learn the states of GGP. This research studied a method for land cover information extraction based on automatic interpretations of high resolution satellite images, which could obtain local GGP information efficiently and timely. The method was used in the land cover change monitoring in Ansai County, where is the priority area for GGP implementation. Land cover change information from 2004 to 2010 was revealed based on SPOT5 and Rapideye high resolution images. The results showed that the farmland reduced overall with a decrease in percentage from 18.12% in 2004 to 13.58% in 2010, an area of 133.91km2 was lost. The proportion of forest increased from 14.60% to 37.95% with area raised by 688.18km2. As with the forest, the grassland showed a trend of growing, its ratio increased to 28.83% from 19.16%, the area raised by 564.47km2. The classification accuracy of SPOT5 is 90.73%, and the Rapideye is 92.19%, the corresponding Kappa coefficients are 0.87 and 0.89, respectively. This study can provide date support and technical reference for GGP implementation's remote sensing monitoring in the study area and other related areas in China.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127066663","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

Mining spatial association rules from LBS anonymity dataset for improving utilization 从LBS匿名数据集中挖掘空间关联规则，提高利用率

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626160

Haitao Zhang, Liang Xu, Huihui Huang, Shasha Gao

{"title":"Mining spatial association rules from LBS anonymity dataset for improving utilization","authors":"Haitao Zhang, Liang Xu, Huihui Huang, Shasha Gao","doi":"10.1109/Geoinformatics.2013.6626160","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2013.6626160","url":null,"abstract":"With the development of Location-Based Services system (LBS), privacy protection of LBS is becoming a hotspot topic in GIS and mobile communication domains. Among series of LBS users' privacies protection techniques, Spatial-Temporal K-Anonymity has become a prominent method for its easy implementation and extension. While, this method and its variants suffer from a common drawback that they decrease utilization of LBS anonymity datasets because of adopting the common principle that reduces spatial temporal resolution of LBS query. However, improving utilization of LBS anonymity datasets is very important for LBS providers. The reason is that it can benefit for many LBS applications. In this paper, we format basic concepts of mining spatial association rules from LBS anonymity datasets and design the implemented algorithms. In experiments we present the detailed process of mining spatial association rules which includes three phases: generating LBS anonymity datasets by adopting Spatial-Temporal K-Anonymity to GPS trajectories; preprocessing LBS anonymity datasets by spatial joining with geographic background GIS layers to achieve a spatial transaction database; mining spatial association rules from the spatial transaction database by adopting the proposed method. The experimental results show that utilization of the mined spatial association rules can assist intelligent traffic management.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117188671","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: 3

Tourism CO2 emissions measure and temporal and spatial differences study — A case of Henan Province in China 旅游CO2排放测度及时空差异研究——以河南省为例

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626140

Xu Li, Hongxia Sun, Yaochen Qin

引用次数: 0