Pub Date : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378582
Shudan Zheng, Jianghua Zheng, C. Mu, Y. Ni, Bahetiyaer Dawuti, Jianguo Wu
Locusts are a kind of primary pests that cause severe damage to the agriculture in Xinjiang, northwest of China. Early forecasting probable sites of locust outbreaks are very important for rangeland management and agricultural protection. This study promoted a GIS-based model combining with multi-criteria analysis to predict the possible area where locust might outbreak. Factors including monthly average temperature, monthly relative humidity, elevation, slope, NDVI and soil PH value were used in this model. The results showed that the locusts were mainly distributed in the north and west part of Xinjiang, which was highly consistent with the actual locust distribution. The average accuracy was 84.37%, and the highest accuracy that appeared in Urumqi reached 97.25%. The average empowering weight method is more suitable for this study as the accuracies are both higher than 90% in 2011 and 2012. Hence, this model was able to predict the probable sites of locust outbreak in Xinjiang, which would provide valuable information to locust control and prevention authorities.
{"title":"GIS-based multi-criteria analysis model for identifying probable sites of locust outbreak in Xinjiang, China","authors":"Shudan Zheng, Jianghua Zheng, C. Mu, Y. Ni, Bahetiyaer Dawuti, Jianguo Wu","doi":"10.1109/GEOINFORMATICS.2015.7378582","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378582","url":null,"abstract":"Locusts are a kind of primary pests that cause severe damage to the agriculture in Xinjiang, northwest of China. Early forecasting probable sites of locust outbreaks are very important for rangeland management and agricultural protection. This study promoted a GIS-based model combining with multi-criteria analysis to predict the possible area where locust might outbreak. Factors including monthly average temperature, monthly relative humidity, elevation, slope, NDVI and soil PH value were used in this model. The results showed that the locusts were mainly distributed in the north and west part of Xinjiang, which was highly consistent with the actual locust distribution. The average accuracy was 84.37%, and the highest accuracy that appeared in Urumqi reached 97.25%. The average empowering weight method is more suitable for this study as the accuracies are both higher than 90% in 2011 and 2012. Hence, this model was able to predict the probable sites of locust outbreak in Xinjiang, which would provide valuable information to locust control and prevention authorities.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122470488","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378610
Fengzhi Wu, Jinliang Wang, Xingyao Zhong, M. Dao, Zijiao Zhao
One of the most effective ways to improve the quality of the nature reserve management is to integrate all information resources in depth based on modern spatial geographic information technology and build digital information management platform of nature reserve. (1) Based on the analysis of system user need, basic geographic information data, wetland resources, land-use data, employee information, biodiversity data (including text, images, etc.), blacknecked crane monitoring data (including behavior monitoring data, number monitoring data), scientific research fruits, as well as data, such as user information on natural reserves, have been acquired, processed, and filed. (2) The paper presents the solution on structure, function module and database of the Web GIS-based information management system of Dashanbao black-necked crane national natural reserve in Zhaotong, Yunnan. (3) ArcSDE Geographic Database has been used to storage data and established the geographic database and professional database of the natural reserve. (4) ArcGIS Server API for Flex has been adopted to realize Web GIS functions, like GIS releasing, spatial data editing, spatial measurement, spatial query, buffer analysis. The development model of JSP, Servlet and JavaBean combined has been used to implement routine management function as achieve data add, query statistics, data output. The system can provide basic data management platform for the natural reserve, promote actively the digital, information construction of protection area, enhance the level and efficiency of management to a certain extent.
基于现代空间地理信息技术，深度整合各类信息资源，构建数字化自然保护区信息管理平台，是提高自然保护区管理质量的最有效途径之一。(1)在系统用户需求分析的基础上，获取基础地理信息数据、湿地资源、土地利用数据、员工信息、生物多样性数据(包括文字、图像等)、黑颈鹤监测数据(包括行为监测数据、数量监测数据)、科研成果以及自然保护区用户信息等数据，并进行处理和归档。(2)提出了基于Web gis的云南昭通大山堡黑颈鹤国家级自然保护区信息管理系统的结构、功能模块和数据库解决方案。(3)利用ArcSDE地理数据库进行数据存储，建立了自然保护区地理数据库和专业数据库。(4)采用ArcGIS Server API for Flex实现了GIS发布、空间数据编辑、空间测量、空间查询、缓冲区分析等Web GIS功能。采用JSP、Servlet和JavaBean相结合的开发模式，实现了数据添加、查询统计、数据输出等日常管理功能。该系统可为自然保护区提供基础数据管理平台，积极推动保护区数字化、信息化建设，在一定程度上提高管理水平和效率。
{"title":"Web GIS-based information management system of Dashanbao black-necked crane national natural reserve in Zhaotong, Yunnan","authors":"Fengzhi Wu, Jinliang Wang, Xingyao Zhong, M. Dao, Zijiao Zhao","doi":"10.1109/GEOINFORMATICS.2015.7378610","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378610","url":null,"abstract":"One of the most effective ways to improve the quality of the nature reserve management is to integrate all information resources in depth based on modern spatial geographic information technology and build digital information management platform of nature reserve. (1) Based on the analysis of system user need, basic geographic information data, wetland resources, land-use data, employee information, biodiversity data (including text, images, etc.), blacknecked crane monitoring data (including behavior monitoring data, number monitoring data), scientific research fruits, as well as data, such as user information on natural reserves, have been acquired, processed, and filed. (2) The paper presents the solution on structure, function module and database of the Web GIS-based information management system of Dashanbao black-necked crane national natural reserve in Zhaotong, Yunnan. (3) ArcSDE Geographic Database has been used to storage data and established the geographic database and professional database of the natural reserve. (4) ArcGIS Server API for Flex has been adopted to realize Web GIS functions, like GIS releasing, spatial data editing, spatial measurement, spatial query, buffer analysis. The development model of JSP, Servlet and JavaBean combined has been used to implement routine management function as achieve data add, query statistics, data output. The system can provide basic data management platform for the natural reserve, promote actively the digital, information construction of protection area, enhance the level and efficiency of management to a certain extent.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126294928","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378633
Zhenlin Fan, Fengzhe Li, Baofeng Zheng, Fangzi Cui
The Nujiang is one of the regions where debris flow disasters occur frequently. For a long time, debris flow disasters have caused serious losses of life and property, so strengthening and controling the management of debris flow disasters and predict and alert debris flow disasters has become one of the main tasks for constructing and protecting ecological environment. Based on WebGIS, Internet of things and database technology, we discussed the overall design, system database design and implement process of mudslide monitoring and early warning system. This system can adopt three tier distributed architecture, the realization of geological disaster information collection, transmission, management, analysis, release of integration. Implementation of network applications has hardware and software forreal-time monitoring and early warning of mudslide. Field implementation show that the system is stable and effective, and it could provide disaster prevention and disaster treatment services for the functional departments.
{"title":"The mudslide monitoring and early warning system based on WebGIS in Nujiang","authors":"Zhenlin Fan, Fengzhe Li, Baofeng Zheng, Fangzi Cui","doi":"10.1109/GEOINFORMATICS.2015.7378633","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378633","url":null,"abstract":"The Nujiang is one of the regions where debris flow disasters occur frequently. For a long time, debris flow disasters have caused serious losses of life and property, so strengthening and controling the management of debris flow disasters and predict and alert debris flow disasters has become one of the main tasks for constructing and protecting ecological environment. Based on WebGIS, Internet of things and database technology, we discussed the overall design, system database design and implement process of mudslide monitoring and early warning system. This system can adopt three tier distributed architecture, the realization of geological disaster information collection, transmission, management, analysis, release of integration. Implementation of network applications has hardware and software forreal-time monitoring and early warning of mudslide. Field implementation show that the system is stable and effective, and it could provide disaster prevention and disaster treatment services for the functional departments.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134021610","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378655
Zhan-Ya Xu, Yi-Hui Xiong, Hong Ye
The effective organization and management of POI data is an important basis for map service. In order to complete the auto-completion function, when users input some keywords part of an POI names to get some full name response, to improve the searching efficiency of Chinese POI data, we take the Chinese POI names as strings which are of high similarity and designed an effective data indexing method for Chinese POI names on the basis of a data structure--radix tree. So this work mainly deals with the approximate string search in large amounts of Chinese POI name strings. We present how to preprocess the Chinese POI name strings and store them in the radix tree. We then give an example to describe the procedure of input keyword string query based on the constructed radix tree of some Chinese POI names. In order to verify the effectiveness of the proposed method, we also analyzed the other two string query algorithms which are based on trie tree and ternary search tree respectively. We compare the performances between them from the perspective of time complexity and space complexity. Our results show that: 1) the performance of the POI search algorithm based on the radix tree is better than the other two algorithms both in the time complexity and space complexity for the Chinese POI names data; 2) the performance stability of the POI data search algorithm based on the radix tree is better than the latter two. The use of this kind of index mechanism makes the efficiency of Chinese POI data query respond well in Map Service which will have a promising future.
{"title":"An effective data indexing method for POI data","authors":"Zhan-Ya Xu, Yi-Hui Xiong, Hong Ye","doi":"10.1109/GEOINFORMATICS.2015.7378655","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378655","url":null,"abstract":"The effective organization and management of POI data is an important basis for map service. In order to complete the auto-completion function, when users input some keywords part of an POI names to get some full name response, to improve the searching efficiency of Chinese POI data, we take the Chinese POI names as strings which are of high similarity and designed an effective data indexing method for Chinese POI names on the basis of a data structure--radix tree. So this work mainly deals with the approximate string search in large amounts of Chinese POI name strings. We present how to preprocess the Chinese POI name strings and store them in the radix tree. We then give an example to describe the procedure of input keyword string query based on the constructed radix tree of some Chinese POI names. In order to verify the effectiveness of the proposed method, we also analyzed the other two string query algorithms which are based on trie tree and ternary search tree respectively. We compare the performances between them from the perspective of time complexity and space complexity. Our results show that: 1) the performance of the POI search algorithm based on the radix tree is better than the other two algorithms both in the time complexity and space complexity for the Chinese POI names data; 2) the performance stability of the POI data search algorithm based on the radix tree is better than the latter two. The use of this kind of index mechanism makes the efficiency of Chinese POI data query respond well in Map Service which will have a promising future.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115766477","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378570
Huiwen Li, Rui Liu, Jingchun Xie, Zili Lai
Now, there are many methods that have been used in landslide susceptibility analysis, but they all have some aspects need to be improved. Random forests methodology improves the accuracy of the model by aggregating multiple models. Especially when dealing with large data, it shows strong robustness. So, we plan to apply random forests methodology to landslide susceptibility analysis triggered by earthquakes. We made Lushan and its surrounding areas as our study area, which suffered from the earthquake in April 20, 2013. This area is located in fault zone in the Longmen Mountains, it shows guiding significance for the study of seismic landslide in southwest China. Based on seismic landslide physical mechanics, we chose slope, aspect, fault, river, Normalized Difference Vegetation Index (NDVI), waviness, lithology, seismic intensity and elevation as landslide factors. Then, we built the suitable seismic landslide model based on Random Forests. After that, we used Out-of-Bag estimates (OOB) to calculate the generalization error of our model, and we also used Receiver Operating Characteristic curve (ROC) error evaluation system to estimate the correctness of the model. When the number of sample data is greater than 50, the OOB generalization error result is less than 0.08, and the area under the ROC curve was 0.938 which means the model has a high reliability. Through this research we found that the random forests methodology showed a good performance when dealing with seismic landslide studies and should be spread to related research.
{"title":"Random forests methodology to analyze landslide susceptibility: An example in Lushan earthquake","authors":"Huiwen Li, Rui Liu, Jingchun Xie, Zili Lai","doi":"10.1109/GEOINFORMATICS.2015.7378570","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378570","url":null,"abstract":"Now, there are many methods that have been used in landslide susceptibility analysis, but they all have some aspects need to be improved. Random forests methodology improves the accuracy of the model by aggregating multiple models. Especially when dealing with large data, it shows strong robustness. So, we plan to apply random forests methodology to landslide susceptibility analysis triggered by earthquakes. We made Lushan and its surrounding areas as our study area, which suffered from the earthquake in April 20, 2013. This area is located in fault zone in the Longmen Mountains, it shows guiding significance for the study of seismic landslide in southwest China. Based on seismic landslide physical mechanics, we chose slope, aspect, fault, river, Normalized Difference Vegetation Index (NDVI), waviness, lithology, seismic intensity and elevation as landslide factors. Then, we built the suitable seismic landslide model based on Random Forests. After that, we used Out-of-Bag estimates (OOB) to calculate the generalization error of our model, and we also used Receiver Operating Characteristic curve (ROC) error evaluation system to estimate the correctness of the model. When the number of sample data is greater than 50, the OOB generalization error result is less than 0.08, and the area under the ROC curve was 0.938 which means the model has a high reliability. Through this research we found that the random forests methodology showed a good performance when dealing with seismic landslide studies and should be spread to related research.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114075041","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378683
Jia Li, Jingliang Wang
The camera calibration is a hot issue in the field of photogrammetry. A chessboard plane is introduced to simplify the difficulty of calibration. In this paper, first, corners of chessboard are detected by Harris. Then, geometrical relationships are calculated between image plane and the three-dimensional space. Finally, the intrinsic and external parameters of the camera are calibrated based on camera model. Experimental results show that the method is effective.
{"title":"Camera calibration experiment based on Harris algorithm","authors":"Jia Li, Jingliang Wang","doi":"10.1109/GEOINFORMATICS.2015.7378683","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378683","url":null,"abstract":"The camera calibration is a hot issue in the field of photogrammetry. A chessboard plane is introduced to simplify the difficulty of calibration. In this paper, first, corners of chessboard are detected by Harris. Then, geometrical relationships are calculated between image plane and the three-dimensional space. Finally, the intrinsic and external parameters of the camera are calibrated based on camera model. Experimental results show that the method is effective.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120881038","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378609
Yanke Hu, Xiwang Zhang, Liangmin Hu
With the rapid evolvement of mobile and cloud technology, the cost of collecting and studying human behavior data is largely reduced. Geo-location data is probably the most important and interesting data that vendors and researchers care about when their designed apps are being used. If an organization maintains several apps, and it wants to monitor the geo-location trend of each app's usage, it will be chaotic and redundant to implement geo-location logging module for every individual app. Instead, it's much cleaner to encapsulate geo-location logging component into SDKs, and centralize the reporting portals into the same cloud service. In this paper, we propose an approach of Modularization SDK Implementation and Cloud reporting architecture, to enable Mobile apps with sensor information logging and reporting by inserting one single line of code. We also use Geo-Location logging as an example and explain how it works on iOS and Android platforms. Our approach can bring several advantages including removing redundant implementation of function modules and bringing more scalability on backend reporting.
{"title":"A fast approach to enable mobile apps with Geo-Location logging and reporting","authors":"Yanke Hu, Xiwang Zhang, Liangmin Hu","doi":"10.1109/GEOINFORMATICS.2015.7378609","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378609","url":null,"abstract":"With the rapid evolvement of mobile and cloud technology, the cost of collecting and studying human behavior data is largely reduced. Geo-location data is probably the most important and interesting data that vendors and researchers care about when their designed apps are being used. If an organization maintains several apps, and it wants to monitor the geo-location trend of each app's usage, it will be chaotic and redundant to implement geo-location logging module for every individual app. Instead, it's much cleaner to encapsulate geo-location logging component into SDKs, and centralize the reporting portals into the same cloud service. In this paper, we propose an approach of Modularization SDK Implementation and Cloud reporting architecture, to enable Mobile apps with sensor information logging and reporting by inserting one single line of code. We also use Geo-Location logging as an example and explain how it works on iOS and Android platforms. Our approach can bring several advantages including removing redundant implementation of function modules and bringing more scalability on backend reporting.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121143343","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378665
Rong Li, Xiaotao Li, D. Su, T. Sun
The drought monitoring by remote sensing technology has advantages than traditional ground monitoring. Up to now, most researches on drought monitoring are focused on constructing the relationship between parameters of remote sensing and land surface. Most current models are complex and indirect, instead, the water area directly reflects drought situation especially in the region where the irrigation and drinking mainly depend on surface water, so it is practical to evaluate drought based on the changes of water area. In this paper, taking the Dongting Lake as an example, the extraction method of water area from images of long time serious is firstly proposed. Furthermore, the correlation between water area and water level is analyzed to validate that the water area can quantitatively indicate drought. On the basis of constructing model of water area anomaly, the approaches of identifying and verifying drought classification assisted by typical drought event in history are illustrated. The result indicates that the proposed approach is valid for monitoring drought in terms of the changes of water area.
{"title":"Drought monitoring based on the changes of water area in Dongting Lake","authors":"Rong Li, Xiaotao Li, D. Su, T. Sun","doi":"10.1109/GEOINFORMATICS.2015.7378665","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378665","url":null,"abstract":"The drought monitoring by remote sensing technology has advantages than traditional ground monitoring. Up to now, most researches on drought monitoring are focused on constructing the relationship between parameters of remote sensing and land surface. Most current models are complex and indirect, instead, the water area directly reflects drought situation especially in the region where the irrigation and drinking mainly depend on surface water, so it is practical to evaluate drought based on the changes of water area. In this paper, taking the Dongting Lake as an example, the extraction method of water area from images of long time serious is firstly proposed. Furthermore, the correlation between water area and water level is analyzed to validate that the water area can quantitatively indicate drought. On the basis of constructing model of water area anomaly, the approaches of identifying and verifying drought classification assisted by typical drought event in history are illustrated. The result indicates that the proposed approach is valid for monitoring drought in terms of the changes of water area.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116115177","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 : 2015-06-19DOI: 10.1109/GEOINFORMATICS.2015.7378669
Wu Meng-Fan, Yang Bo, Huo Fei-fei, Liao Liu-Wen
Based on Linear Spectral Mixture Model (LSMM), Zonal Statistic, Transect analyses, and Transformation analyses of urban land cover, we extracted out the Impervious Surface Coverage (ISC) of Changsha metropolitan area in 2005, 2009, and 2013, and analyzed its spatiotemporal patterns in 2005-2013. The results were: (1) we reported that increasing and improving proportion of dark vegetation can reduce the misclassification of low albedo and shadow. (2) The main increase of ISC in Changsha metropolitan area was in 20052009. Impervious surface expanded from the center to all around. The construction of urban greenspace was paid closely attention in 2009-2013. (3) The transformation between impervious surface and vegetation appeared mainly in downtown and counties. The transform from soil to impervious surface mainly arose in 20052009. (4) The Impervious Surface Coverage (ISC) and Land Surface Temperature (LST) had linear relationship in Changsha Metropolitan Area. The primary reason for the rising of urban land surface temperature (LST) was high density of impervious surface, not low density and scattered ones.
{"title":"Analyses on spatiotemporal patterns of impervious surface coverage in Changsha metropolitan area","authors":"Wu Meng-Fan, Yang Bo, Huo Fei-fei, Liao Liu-Wen","doi":"10.1109/GEOINFORMATICS.2015.7378669","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378669","url":null,"abstract":"Based on Linear Spectral Mixture Model (LSMM), Zonal Statistic, Transect analyses, and Transformation analyses of urban land cover, we extracted out the Impervious Surface Coverage (ISC) of Changsha metropolitan area in 2005, 2009, and 2013, and analyzed its spatiotemporal patterns in 2005-2013. The results were: (1) we reported that increasing and improving proportion of dark vegetation can reduce the misclassification of low albedo and shadow. (2) The main increase of ISC in Changsha metropolitan area was in 20052009. Impervious surface expanded from the center to all around. The construction of urban greenspace was paid closely attention in 2009-2013. (3) The transformation between impervious surface and vegetation appeared mainly in downtown and counties. The transform from soil to impervious surface mainly arose in 20052009. (4) The Impervious Surface Coverage (ISC) and Land Surface Temperature (LST) had linear relationship in Changsha Metropolitan Area. The primary reason for the rising of urban land surface temperature (LST) was high density of impervious surface, not low density and scattered ones.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122377974","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}
Disease risk assessment plays an important role in controlling the diffusion of infectious diseases. It needs a large number of environmental, social, and economic development data in order to discover the pathogenic factors of a given disease. However, the conventional disease risk assessment is carried out mainly through the analysis of geographic data and non-geographic data released by officials. The assessment falls far behind the propagation of the diseases. To address the issue of government data lagging, we propose a disease risk assessment framework using the open source data. Our proposed framework includes five sections: Automatic Data Discovery, Data Organization, Computing resource calling, Model selection and Visualization. The process of data discovery and organization can be done automatically. Distributed computing resources are used and users can select the spatial analysis models interactively for prediction and visualization. The rabies disease example is implemented using the proposed framework and verifies the effectiveness and efficiency of our framework by good results.
{"title":"How to use open source data to assess infection disease risk: A framework and applications","authors":"Qingchun Yan, Danhuai Guo, Wenjuan Cui, Jianhui Li, Yuanchun Zhou","doi":"10.1109/GEOINFORMATICS.2015.7378677","DOIUrl":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378677","url":null,"abstract":"Disease risk assessment plays an important role in controlling the diffusion of infectious diseases. It needs a large number of environmental, social, and economic development data in order to discover the pathogenic factors of a given disease. However, the conventional disease risk assessment is carried out mainly through the analysis of geographic data and non-geographic data released by officials. The assessment falls far behind the propagation of the diseases. To address the issue of government data lagging, we propose a disease risk assessment framework using the open source data. Our proposed framework includes five sections: Automatic Data Discovery, Data Organization, Computing resource calling, Model selection and Visualization. The process of data discovery and organization can be done automatically. Distributed computing resources are used and users can select the spatial analysis models interactively for prediction and visualization. The rabies disease example is implemented using the proposed framework and verifies the effectiveness and efficiency of our framework by good results.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123696402","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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