2013 21st International Conference on Geoinformatics最新文献_第6页

Massive image data management using HBase and MapReduce 使用HBase和MapReduce进行海量图像数据管理

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626187

Yuehu Liu, Bin Chen, Wenxi He, Yu Fang

引用次数: 19

Emergency cartographic system based on national fundamental geographic data 基于国家基础地理数据的应急制图系统

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626067

Zhijun Zhang, Junwu Qiu, Jiong Li

引用次数: 0

Progressive attribute editing for geological interpretation of remote sensing images 遥感影像地质解译的渐进式属性编辑

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626108

Hu Shao, Lun Wu, Yuan Tian, Yong Gao, W. Kang

引用次数: 0

The spatio-temporal characteristics analysis on new-urbanization level of CPER in China 中国CPER新型城镇化水平时空特征分析

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626075

Zhiwei Ding, Gaisu Zhang, Fazeng Wang

{"title":"The spatio-temporal characteristics analysis on new-urbanization level of CPER in China","authors":"Zhiwei Ding, Gaisu Zhang, Fazeng Wang","doi":"10.1109/Geoinformatics.2013.6626075","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2013.6626075","url":null,"abstract":"According to the connotation explanation of new-urbanization, this paper gives an analysis of temporal and spatial characteristics of new-urbanization level by gray correlation model and spatial autocorrelation method. The results show that: (1) From temporal characteristics, the overall new-urbanization level of CPER is in a relatively stable rising state in addition slight waved, the sub-system level of social harmony and urban-rural is in a fluctuant rising state, the sub-system level of economic cost-effectiveness is in a good growth trend like overall level, the sub-system level of environment health is in a weak growth state by waved decrease in some years. (2) From spatial characteristics, the new-urbanization of each city in CPER is quite different. From the distribution pattern of overall level, Zhengzhou, Jiyuan are in first and second class respectively, Jiaozuo, Luoyang, Sanmenxia and some other cities near to Mountain Taihang are concentrated in third class mainly, the fourth and fifth class cities are mainly distributed in the south and southeast region of CPER. From the distribution pattern of economic cost-effective development and social harmony development, the distribution characteristics of first three class cities are similar to overall level to some certain extent, but different from the latter two class. From the distribution pattern of urban-rural coordination development and environment healthy development, the former is similar to the overall pattern;the latter is quite different from the overall pattern. Based on the analysis results, this paper gives a simple cause analysis and puts forward some development measures.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"1 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":"128706678","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

The eco-zoning of Huaihe River Basin based on multi-source data and spatial analysis 基于多源数据和空间分析的淮河流域生态区划

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626041

Qing Wang, Xuehua Liu

引用次数: 0

Assessment of vulnerability to sea-level rise for China's Coast 中国沿海对海平面上升的脆弱性评估

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626181

Shoufen Wang, Weian Wang, M. Ji, Wen Chen, Shuying Xu

{"title":"Assessment of vulnerability to sea-level rise for China's Coast","authors":"Shoufen Wang, Weian Wang, M. Ji, Wen Chen, Shuying Xu","doi":"10.1109/Geoinformatics.2013.6626181","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2013.6626181","url":null,"abstract":"Coastal systems are characterized by high geophysical and biophysical sensitivity due to their special environment. The ecosystems along China's coast are especially vulnerable to the accelerated sea-level rise and associated multi-hazards such as storm surges and coastal flooding due to their low-lying topography, highly developed economy, and high-density population. To ensure a better management of China's coastal areas, it is crucial to develop adequate nationwide coastal vulnerability assessment models. This paperpresents our design and procedure of assessing the vulnerability of China's entire coast using eight factors. Techniques of geographic information systemand remote sensing were used to integrate the best available, spatially-disaggregated national data on critical impact elements. A comprehensive coastal vulnerability index(CVI) was then calculated by integrating the differentially weighted rank values of the variables. In the finalstep, the coastline was segmented into 4vulnerability levels: low, moderate, high and very high. The results generated from the segmentation show that 35% of the entire coast has high or very high vulnerability, mostly along Bohai Bay, the North Jiangsu coastal plain, the Yangtze River and the Yellow River Delta, and the western coast of Taiwan. The geographical distribution of the vulnerability grade proves to be reasonable. Findingsfurtherreveal that large amounts of land and population wouldbe vulnerable to inundation by coastal flooding from sea level rise and storm surge without effective measures. Finally, some suggestions are presented for decision makers and other concerned stakeholders to develop appropriate coastal zonemanagement and mitigation measures.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"61 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":"116978723","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

The simulation of land use and land change in Erhai lake basin based on CA-Agent 基于CA-Agent的洱海流域土地利用与土地变化模拟

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626096

Yulian Yang, Kun Yang, Chao Meng, Cen Li, Xudong Zhao

{"title":"The simulation of land use and land change in Erhai lake basin based on CA-Agent","authors":"Yulian Yang, Kun Yang, Chao Meng, Cen Li, Xudong Zhao","doi":"10.1109/Geoinformatics.2013.6626096","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2013.6626096","url":null,"abstract":"The complexity of LUCC (Land Use / Cover Change, LUCC) determines that it is important to conduct the study of LUCC using complex system theories, in particular by the establishment of a mathematical model for complex systems. In this paper, the LUCC model was built based on GIS technology, CA (cellular automata) and Agent technology. Firstly, Landsat TM data of 2000 and 2010 are used to obtain the land use map. Based on the maps, land use change patterns can be determined as references for the LUCC model. GIS is used to obtain the spatial variables. ANN (Artificial neural network) instead of complex transformation rules is used to obtain the parameters. This method significantly simplifies the structure of the CA model and the definition of transformation rules. Cellular interactions are entirely based on spatial proximity, which cannot move. However, ABM (Agent Based Modeling) has great advantages for complex “human-land relationship analog” and therefore, it is applied in this study. Land use change of each grid cell is determined and marked by CA model, and Agent makes the change of land use type according to the marks. The model is realized by Repast and Matlab. The LUCC model uses the land use type of 2002 initially to simulate land use type of 2010 and evaluates the accuracy of the simulation results by the Lee-Sallee index. After repeated debug processes and parameter adjustments, the optimal dynamic LUCC evolution model is determined. Based on initial land use of 2010, future land use types in 2020 of the Erhai region are predicted.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"38 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":"117272245","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

GIS-based landslide susceptibility mapping using analytical hierarchy process in Wenchuan 基于gis的汶川滑坡易感性制图

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626068

Changjiang Gou, R. Liu, Ce Feng

引用次数: 3

Exploring carbon emissions, economic growth, energy and R&D investment in China by ARDL approach 用ARDL方法探讨中国的碳排放、经济增长、能源和研发投资

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626205

Shiyan Zhai, Genxin Song

{"title":"Exploring carbon emissions, economic growth, energy and R&D investment in China by ARDL approach","authors":"Shiyan Zhai, Genxin Song","doi":"10.1109/Geoinformatics.2013.6626205","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2013.6626205","url":null,"abstract":"This paper examines the causal relationship among economic growth, energy structure, R&D investment and carbon emission in China by using autoregressive distributed lag bounds testing approach of cointegration during the period of 1990-2011. In order to examine this linkage, the authors use the two-step procedures. Firstly, the authors conducted the unit root tests to measure whether the single integrated of time series is not more than 1. Secondly, the authors explore the long-run relationships between the variables by using ARDL bounds testing approach complemented by Johansen-Juselius maximum likelihood procedure in a multivariate framework. The findings are as follows:when carbon emissions and economic growth, respectively, are the dependent variable, the other independent variables show the long-term stability cointegration relationship of the dependent variable. Whether in the short-run or long-run relationship, the impact of economic growth and R&D investment on carbon emission is not statistically significant. In the long term and short term relationships, carbon emissions have a positive impact on the economic growth. However, energy structure has a negative impact on the economic growth. The decrease in energy structure will cause carbon emissions reduction and boost economic growth in both the long-run and short-run period. Therefore, China's government should give more attention to the optimization of energy structure and make a reasonable and feasible energy saving policy.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"95 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":"114289245","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: 13

A model for heterogeneous quality evaluation of Geographic web service 地理网络服务异构质量评价模型

2013 21st International Conference on Geoinformatics Pub Date : 2013-06-20 DOI: 10.1109/Geoinformatics.2013.6626188

Li Liu, Jinyun Fang, Dui Liang

引用次数: 5