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2012 20th International Conference on Geoinformatics最新文献

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The application of fractal theory in assessing chlorophyll content using hypersectral data 分形理论在利用超光谱资料评估叶绿素含量中的应用
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270349
Yanfang Xiao, Luxiang Li, H. Gong, Demin Zhou
{"title":"The application of fractal theory in assessing chlorophyll content using hypersectral data","authors":"Yanfang Xiao, Luxiang Li, H. Gong, Demin Zhou","doi":"10.1109/Geoinformatics.2012.6270349","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270349","url":null,"abstract":"The variance in leaf chlorophyll concentration can cause the comprehensive variation of spectral curve in geometry and characteristics. Fractal is an appropriate mathematical tool to explain the comprehensive variation. In this paper, the fractal dimension of segmented reflectance spectral curves was used to assess the leaf chlorophyll concentration by the moving window technique. Firstly, the size of moving window was defined in 10nm, 20nm, 30nm, 50nm, 75nm, 100nm and the best window size was chose by comparing the correlation between fractal dimension and chlorophyll content. Secondly, the fractal dimension with the best window was used to build the estimation model of chlorophyll content, and the estimation result was compared with various spectral VIs. The research result showed that (1) the window with the length of 50nm was the best for chlorophyll content assessment. (2) For different chlorophyll content, the variation of fractal dimension was mainly found in 475nm~650nm of visible light spectra and 720nm~770nm of near-infrared spectra, with the trend of changes conforming to the reflectance. (3) Comparing with several spectral VIs, the fractal dimension was better related with chlorophyll content. So, the fractal dimension of segmented reflectance spectral curve can be served as a new comprehensive parameter to estimate the chlorophyll content of vegetation.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124805373","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
Research research on on parallel algorithm for polygon rasterization 多边形栅格化并行算法的研究
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270274
Yafei Wang, Manchun Li, Shuai Zhang, Lihua Tong, Jinbiao Wei, Zhenjie Chen
{"title":"Research research on on parallel algorithm for polygon rasterization","authors":"Yafei Wang, Manchun Li, Shuai Zhang, Lihua Tong, Jinbiao Wei, Zhenjie Chen","doi":"10.1109/Geoinformatics.2012.6270274","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270274","url":null,"abstract":"Vector to raster conversion has always been one of the foundational research topics in the field of Geographical Information System. With the development of processing for massive geospatial data, traditional serial algorithms can not satisfy the need of effective rastering of large amounts of vector data. This paper proposes a parallel algorithm of rasterization for vector polygon based on data parallel which is improved on the basis of scanline algorithm of polygon rasterization, and implements the parallel algorithm using the C++ programming language and the Message Passing Interface(MPI). We test the parallel algorithm by experiments and analyses the parallel efficiency. Results show that the parallel algorithm proposed in this paper achieves high parallel speedup and efficiency.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130208701","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
Risk analysis of city emergency evacuation based on multi-agent simulation 基于多智能体仿真的城市应急疏散风险分析
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270303
Zhiyong Lin, Zhao Yan, Changqing Huang
{"title":"Risk analysis of city emergency evacuation based on multi-agent simulation","authors":"Zhiyong Lin, Zhao Yan, Changqing Huang","doi":"10.1109/Geoinformatics.2012.6270303","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270303","url":null,"abstract":"City emergency is one of the top threatens to the public safety. To devise appropriate schemes for emergency response, effective risk analysis of emergency evacuation is almost a necessity. In light of this, we propose a model for city emergency evacuation based on the multi-agent simulation framework, which has found successful applications in various areas and in specific is very suitable for the emergency evacuation problem. Through extensive simulation results the effectiveness of our proposed model is verified.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130344807","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
Parallelized remote sensing classifier based on rough set theory algorithm 基于粗糙集理论算法的并行遥感分类器
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270295
Xin Pan, Shuqing Zhang
{"title":"Parallelized remote sensing classifier based on rough set theory algorithm","authors":"Xin Pan, Shuqing Zhang","doi":"10.1109/Geoinformatics.2012.6270295","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270295","url":null,"abstract":"Supervised classification in remote sensing imagery is receiving increasing attention in current research. In order to improve the classification accuracy, a lot of spatial-features (e.g., texture information generated by GLCM) are often utilized. Unfortunately, too many spatial-features usually reduce the computation speed of remote sensing classification, that is, the time complexity may be increased due to the high dimensionality of the data. It is thus necessary to improve the computational performance of traditional classification algorithms which are single process-based, by making use of multiple CPU resources. This study presents a novel parallelized remote sensing classifier based on rough set (PRSCBRS). Feature set is firstly split sub-feature sets into in PRSCBRS; a sub-classifier is then trained with a sub-feature set; and multiple sub-classifier's decisions ensemble are finally utilized to avoid the instable performance a single classifier. The experimental results show that both the classification accuracy and computation speed are all improved in remote sensing classification, compared with the traditional ANN and SVM method.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127160504","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
Research on sensitivity evaluation of soil erosion based on GIS in Jixi County 基于GIS的鸡西县水土流失敏感性评价研究
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270276
Jing Zhang, Manchun Li, Chaowen Yang, Chen Yang, Yongxing Wang, Feixue Li
{"title":"Research on sensitivity evaluation of soil erosion based on GIS in Jixi County","authors":"Jing Zhang, Manchun Li, Chaowen Yang, Chen Yang, Yongxing Wang, Feixue Li","doi":"10.1109/Geoinformatics.2012.6270276","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270276","url":null,"abstract":"Sensitivity of soil erosion is the representative of the possibility of occurring soil erosion under natural conditions. Sensitivity evaluation of soil erosion is the reliable method to identify the highly sensitivity areas and evaluate the sensitivity degree in a particular area. This paper uses the revised universal soil loss equation (RUSLE) and GIS technique which has powerful space analysis functions for extracting the factors of soil erosion, making thematic maps and building the model to research the sensitivity of soil erosion in Jixi County. According to the characteristics of geography in study area, the key sensitivity factors of the soil erosion were defined, which include rainfall erosivity factor, soil erodibility factor, slope factor and vegetation cover factor. The aim of the article is to explore the space distribution characteristics of soil erosion in Jixi County.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122500185","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
A parallel index supprorting concurrent queries for finding relevant remote sensing images 一个并行索引，支持查找相关遥感图像的并发查询
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270313
Huizhong Chen, Yongguang Chen, N. Jing, Luo Chen
{"title":"A parallel index supprorting concurrent queries for finding relevant remote sensing images","authors":"Huizhong Chen, Yongguang Chen, N. Jing, Luo Chen","doi":"10.1109/Geoinformatics.2012.6270313","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270313","url":null,"abstract":"Nearest neighbor (NN) query in multi-dimensional space is one of the key problems for searching relevant remote sensing images from a large gallery. Facing the concurrent queries, we propose a Parallel Compressed Vector Approximation Hashing (PCVAH) index in this paper. The PCVAH keeps the pointers to approximated vectors in a hashing style structure, uses neighboring masks for filtering. The neighboring masks are sets of mask vectors indicating grids close to the query point. And then access the accurate vectors to calculate the final NN results. It handles several concurrent queries in parallel when filtering and access the accurate vectors together. Theoretical analysis and experiments confirm that the PCVAH parallel query method is of high parallel efficiency and time efficiency. And more important it is simple for practical implement in real applications.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115213541","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 comprehensive evaluation and spatial analysis of Jiangsu's population quality 江苏省人口素质综合评价与空间分析
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270321
Mengmeng Yang, Zhibing Jin
{"title":"The comprehensive evaluation and spatial analysis of Jiangsu's population quality","authors":"Mengmeng Yang, Zhibing Jin","doi":"10.1109/Geoinformatics.2012.6270321","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270321","url":null,"abstract":"Population quality is an integrated performance of the population's physical fitness, cultural and scientific quality, and ideological moral quality in a nation or a region. The population quality of Jiangsu varies from one area to another with the differences in history and resource endowment, economic development level and geographical conditions. This paper uses the SPSS (Statistical Product and Service Solutions) software to construct the evaluation index system of population quality and decides the factors related to population quality with PCA (Principal Component Analysis) method; then calculates every factor score and gets the population integrated index; finally categorizes the related factors and population integrated evaluation indexes with SPSS clustering method, and makes evaluation graphics of integrated population quality of Jiangsu with ArcGIS software. The spatial distribution characteristics of Jiangsu's population quality can be seen from these graphics. Some suggestion is presented in order to further improve the population quality of Jiangsu in the future.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132006566","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
An image fusion method based on region segmentation and wavelet transform 一种基于区域分割和小波变换的图像融合方法
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270260
P. Sun, L. Deng
{"title":"An image fusion method based on region segmentation and wavelet transform","authors":"P. Sun, L. Deng","doi":"10.1109/Geoinformatics.2012.6270260","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270260","url":null,"abstract":"An image fusion method based on region segmentation and wavelet transform for multi-scale remote sensing image fusion is proposed. Firstly, the multiscale decomposition of source images is carried out with the wavelet transform. Then region segmentation based on area standard deviation is done for the low-frequency coefficients, the low-frequency coefficients is decomposed two parts: target information and background information. The target information is fused with larger absolute value operator, and the background information is fused with gray error value operator. The high-frequency coefficients are fused with image definition. Finally the fused coefficients are reconstructed to obtain the fusion image. Using this method and comparison with several traditional methods, the results show that the fused image by the presented algorithm can not only hold spectrum information of the multispectral image, but also improve the high resolution of the fusion image.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130735359","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: 4
Determinations of low breast screening uptake using geographically weighted regression model 使用地理加权回归模型确定低乳腺筛查吸收率
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270323
Cheng Chen, Yu Wang, Huabing Wan, T. Cheng
{"title":"Determinations of low breast screening uptake using geographically weighted regression model","authors":"Cheng Chen, Yu Wang, Huabing Wan, T. Cheng","doi":"10.1109/Geoinformatics.2012.6270323","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270323","url":null,"abstract":"In recent years, the overall breast screening uptake rate in South West London is lower than national average figure. It is well acknowledged that population turnover, minutes for travel time to screening units, deprivation and culture factors impact on breast screening uptake from previous research. This paper focuses on the relationship between breast screening uptake and its determinant factors: Index of Multiple Deprivation score in 2007, percentage of African and Muslim, minutes for travel time to nearest breast screening unit in South West London through a traditional global model. Moreover, using a local regression model, Geographically Weighted Regression explores the specific reasons of the low figures of breast screening uptake and examines the most significant variables in each lower supper output area. The Geographically Weighted Regression model is used in testing the spatial dependency and spatial non-stationary of each variable, which reveals the influence across the region uniform or variable.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130648305","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
Rapid extraction of Pakistan floods from TM images 从TM图像中快速提取巴基斯坦洪水
2012 20th International Conference on Geoinformatics Pub Date : 2012-06-15 DOI: 10.1109/Geoinformatics.2012.6270352
Rui Zhang, Yonghua Sun
{"title":"Rapid extraction of Pakistan floods from TM images","authors":"Rui Zhang, Yonghua Sun","doi":"10.1109/Geoinformatics.2012.6270352","DOIUrl":"https://doi.org/10.1109/Geoinformatics.2012.6270352","url":null,"abstract":"This paper take the catastrophic floods of Pakistan in August 2010 as research object, based on the spectral characteristic of the water body. This paper takes the water extraction experiment on TM images which contain a large number of confounding factors. We compared and analyzed the results obtained by the methods such as Single-band threshold value method, Spectral Relations Act and Normalized water index etc. The results show that MNDWI is the best method about extracting the flood information from TM images. This paper provides the methodological guidance for water extraction in remote sensing images.","PeriodicalId":259976,"journal":{"name":"2012 20th International Conference on Geoinformatics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114156613","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
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