The Experts below are selected from a list of 17259 Experts worldwide ranked by ideXlab platform
Ying Luo - One of the best experts on this subject based on the ideXlab platform.
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modelbase system in remote sensing information analysis and service Grid Node
International Conference on Computational Science, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Modelbase System in Remote Sensing Information Analysis and Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Aerosol Optical Thickness Retrieval over Land from MODIS Data on Remote Sensing Information Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Jianping Guo, Ying Luo, Yong Xue, Wei Wan, Lei Zheng, Shaobo Zhong, Ying Wang, Jianqin Wang, Guoyin CaiAbstract:The signal at the top of the atmosphere will certainly contain information about both the surface and the atmosphere. To derive the geophysical parameters from satellites remote sensing images, the atmospheric effects must be decoupled. Aerosol Optical Thickness (AOT), an important aerosol optical property, should be correctly determined to remove the atmospheric effect. The retrieval process is great time-consuming and the EMS memory required is too large for a personal computing to run efficiently. Therefore, to facilitate the process smoothly, SYNTAM model is used to retrieve AOT over a wide range of land including China and one European area from MODIS data on the Remote Sensing Information Service Grid Node (RSIN, http://www.tgp.ac.cn) deployed at Institute of Remote Sensing Applications, Chinese Academy of Sciences. AOT retrieval results show that the RSIN Grid service is high efficient and has the potential to be applied to the remote sensing parameter inversion.
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a remote sensing application workflow and its implementation in remote sensing service Grid Node
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo Zhong, Zhengfang WangAbstract:In this article we describe a remote sensing application workflow in building a Remote Sensing Information Analysis and Service Grid Node at Institute of Remote Sensing Applications based on the Condor platform. The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. Implementing it we use workflow technology to manage the Node, control resources, and make traditional algorithms as a Grid service. We use web service technology to communicate with Spatial Information Grid (SIG) and other Grid systems. We use JSP technology to provide an independent portal. Finally, the current status of this ongoing work is described.
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remote sensing information processing Grid Node with loose coupling parallel structure
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo ZhongAbstract:To use traditional algorithms and software packages on Grid system, traditional algorithms and software packages, in general, have to be modified. In this paper we focus on standards and methodologies for Grid platform within the context of the Remote Sensing Data Processing Grid Node (RSDPGN) that implements a loose-coupling parallel structure for orchestrating traditional remote sensing algorithms and software packages on the Condor platform. We have implemented 17 remote sensing applications in one system using Web service and workflow technology without any change to traditional codes. Some core algorithm codes are come from a remote sensing software package which we has neither resource codes nor APIs. Others come from the program codes accumulated by our group. The design and prototype implementation of RSDPGN are presented. The advantage and shortage of loose-coupling structure is analysed. Through a case study of land surface temperature calcu-lation from MODIS data, we demonstrate the way to modify software packages in details. Moreover we discuss the problems and solutions based on our experience such as system architecture, the kinds of functional modules, fast data transfer, and state monitoring.
Yong Xue - One of the best experts on this subject based on the ideXlab platform.
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modelbase system in remote sensing information analysis and service Grid Node
International Conference on Computational Science, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Modelbase System in Remote Sensing Information Analysis and Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Aerosol Optical Thickness Retrieval over Land from MODIS Data on Remote Sensing Information Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Jianping Guo, Ying Luo, Yong Xue, Wei Wan, Lei Zheng, Shaobo Zhong, Ying Wang, Jianqin Wang, Guoyin CaiAbstract:The signal at the top of the atmosphere will certainly contain information about both the surface and the atmosphere. To derive the geophysical parameters from satellites remote sensing images, the atmospheric effects must be decoupled. Aerosol Optical Thickness (AOT), an important aerosol optical property, should be correctly determined to remove the atmospheric effect. The retrieval process is great time-consuming and the EMS memory required is too large for a personal computing to run efficiently. Therefore, to facilitate the process smoothly, SYNTAM model is used to retrieve AOT over a wide range of land including China and one European area from MODIS data on the Remote Sensing Information Service Grid Node (RSIN, http://www.tgp.ac.cn) deployed at Institute of Remote Sensing Applications, Chinese Academy of Sciences. AOT retrieval results show that the RSIN Grid service is high efficient and has the potential to be applied to the remote sensing parameter inversion.
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a remote sensing application workflow and its implementation in remote sensing service Grid Node
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo Zhong, Zhengfang WangAbstract:In this article we describe a remote sensing application workflow in building a Remote Sensing Information Analysis and Service Grid Node at Institute of Remote Sensing Applications based on the Condor platform. The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. Implementing it we use workflow technology to manage the Node, control resources, and make traditional algorithms as a Grid service. We use web service technology to communicate with Spatial Information Grid (SIG) and other Grid systems. We use JSP technology to provide an independent portal. Finally, the current status of this ongoing work is described.
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remote sensing information processing Grid Node with loose coupling parallel structure
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo ZhongAbstract:To use traditional algorithms and software packages on Grid system, traditional algorithms and software packages, in general, have to be modified. In this paper we focus on standards and methodologies for Grid platform within the context of the Remote Sensing Data Processing Grid Node (RSDPGN) that implements a loose-coupling parallel structure for orchestrating traditional remote sensing algorithms and software packages on the Condor platform. We have implemented 17 remote sensing applications in one system using Web service and workflow technology without any change to traditional codes. Some core algorithm codes are come from a remote sensing software package which we has neither resource codes nor APIs. Others come from the program codes accumulated by our group. The design and prototype implementation of RSDPGN are presented. The advantage and shortage of loose-coupling structure is analysed. Through a case study of land surface temperature calcu-lation from MODIS data, we demonstrate the way to modify software packages in details. Moreover we discuss the problems and solutions based on our experience such as system architecture, the kinds of functional modules, fast data transfer, and state monitoring.
Jianping Guo - One of the best experts on this subject based on the ideXlab platform.
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modelbase system in remote sensing information analysis and service Grid Node
International Conference on Computational Science, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Modelbase System in Remote Sensing Information Analysis and Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Aerosol Optical Thickness Retrieval over Land from MODIS Data on Remote Sensing Information Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Jianping Guo, Ying Luo, Yong Xue, Wei Wan, Lei Zheng, Shaobo Zhong, Ying Wang, Jianqin Wang, Guoyin CaiAbstract:The signal at the top of the atmosphere will certainly contain information about both the surface and the atmosphere. To derive the geophysical parameters from satellites remote sensing images, the atmospheric effects must be decoupled. Aerosol Optical Thickness (AOT), an important aerosol optical property, should be correctly determined to remove the atmospheric effect. The retrieval process is great time-consuming and the EMS memory required is too large for a personal computing to run efficiently. Therefore, to facilitate the process smoothly, SYNTAM model is used to retrieve AOT over a wide range of land including China and one European area from MODIS data on the Remote Sensing Information Service Grid Node (RSIN, http://www.tgp.ac.cn) deployed at Institute of Remote Sensing Applications, Chinese Academy of Sciences. AOT retrieval results show that the RSIN Grid service is high efficient and has the potential to be applied to the remote sensing parameter inversion.
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a remote sensing application workflow and its implementation in remote sensing service Grid Node
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo Zhong, Zhengfang WangAbstract:In this article we describe a remote sensing application workflow in building a Remote Sensing Information Analysis and Service Grid Node at Institute of Remote Sensing Applications based on the Condor platform. The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. Implementing it we use workflow technology to manage the Node, control resources, and make traditional algorithms as a Grid service. We use web service technology to communicate with Spatial Information Grid (SIG) and other Grid systems. We use JSP technology to provide an independent portal. Finally, the current status of this ongoing work is described.
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remote sensing information processing Grid Node with loose coupling parallel structure
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo ZhongAbstract:To use traditional algorithms and software packages on Grid system, traditional algorithms and software packages, in general, have to be modified. In this paper we focus on standards and methodologies for Grid platform within the context of the Remote Sensing Data Processing Grid Node (RSDPGN) that implements a loose-coupling parallel structure for orchestrating traditional remote sensing algorithms and software packages on the Condor platform. We have implemented 17 remote sensing applications in one system using Web service and workflow technology without any change to traditional codes. Some core algorithm codes are come from a remote sensing software package which we has neither resource codes nor APIs. Others come from the program codes accumulated by our group. The design and prototype implementation of RSDPGN are presented. The advantage and shortage of loose-coupling structure is analysed. Through a case study of land surface temperature calcu-lation from MODIS data, we demonstrate the way to modify software packages in details. Moreover we discuss the problems and solutions based on our experience such as system architecture, the kinds of functional modules, fast data transfer, and state monitoring.
Lei Zheng - One of the best experts on this subject based on the ideXlab platform.
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modelbase system in remote sensing information analysis and service Grid Node
International Conference on Computational Science, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Modelbase System in Remote Sensing Information Analysis and Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Aerosol Optical Thickness Retrieval over Land from MODIS Data on Remote Sensing Information Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Jianping Guo, Ying Luo, Yong Xue, Wei Wan, Lei Zheng, Shaobo Zhong, Ying Wang, Jianqin Wang, Guoyin CaiAbstract:The signal at the top of the atmosphere will certainly contain information about both the surface and the atmosphere. To derive the geophysical parameters from satellites remote sensing images, the atmospheric effects must be decoupled. Aerosol Optical Thickness (AOT), an important aerosol optical property, should be correctly determined to remove the atmospheric effect. The retrieval process is great time-consuming and the EMS memory required is too large for a personal computing to run efficiently. Therefore, to facilitate the process smoothly, SYNTAM model is used to retrieve AOT over a wide range of land including China and one European area from MODIS data on the Remote Sensing Information Service Grid Node (RSIN, http://www.tgp.ac.cn) deployed at Institute of Remote Sensing Applications, Chinese Academy of Sciences. AOT retrieval results show that the RSIN Grid service is high efficient and has the potential to be applied to the remote sensing parameter inversion.
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a remote sensing application workflow and its implementation in remote sensing service Grid Node
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo Zhong, Zhengfang WangAbstract:In this article we describe a remote sensing application workflow in building a Remote Sensing Information Analysis and Service Grid Node at Institute of Remote Sensing Applications based on the Condor platform. The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. Implementing it we use workflow technology to manage the Node, control resources, and make traditional algorithms as a Grid service. We use web service technology to communicate with Spatial Information Grid (SIG) and other Grid systems. We use JSP technology to provide an independent portal. Finally, the current status of this ongoing work is described.
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remote sensing information processing Grid Node with loose coupling parallel structure
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo ZhongAbstract:To use traditional algorithms and software packages on Grid system, traditional algorithms and software packages, in general, have to be modified. In this paper we focus on standards and methodologies for Grid platform within the context of the Remote Sensing Data Processing Grid Node (RSDPGN) that implements a loose-coupling parallel structure for orchestrating traditional remote sensing algorithms and software packages on the Condor platform. We have implemented 17 remote sensing applications in one system using Web service and workflow technology without any change to traditional codes. Some core algorithm codes are come from a remote sensing software package which we has neither resource codes nor APIs. Others come from the program codes accumulated by our group. The design and prototype implementation of RSDPGN are presented. The advantage and shortage of loose-coupling structure is analysed. Through a case study of land surface temperature calcu-lation from MODIS data, we demonstrate the way to modify software packages in details. Moreover we discuss the problems and solutions based on our experience such as system architecture, the kinds of functional modules, fast data transfer, and state monitoring.
Wei Wan - One of the best experts on this subject based on the ideXlab platform.
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modelbase system in remote sensing information analysis and service Grid Node
International Conference on Computational Science, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Modelbase System in Remote Sensing Information Analysis and Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Yong Xue, Ying Luo, Jianping Guo, Wei Wan, Lei Zheng, Wei Wei, Ying WangAbstract:In this article we describe a modelbase system used in Remote Sensing Information Analysis and Service Grid Node (RISN) at Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences (CAS). The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. With the modelbase system, we can organize and manage models better and make full use of models. With this system, we update both local and remote models easily, and we can also add remote modelbase into our modelbase management system. At the same time, we provide interfaces to access and run models from our Node. Implementing it, we use Oracle to organize and manage models, use java language to connect with Oracle database and run models on Condor platform.
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International Conference on Computational Science (2) - Aerosol Optical Thickness Retrieval over Land from MODIS Data on Remote Sensing Information Service Grid Node
Computational Science – ICCS 2007, 2007Co-Authors: Jianping Guo, Ying Luo, Yong Xue, Wei Wan, Lei Zheng, Shaobo Zhong, Ying Wang, Jianqin Wang, Guoyin CaiAbstract:The signal at the top of the atmosphere will certainly contain information about both the surface and the atmosphere. To derive the geophysical parameters from satellites remote sensing images, the atmospheric effects must be decoupled. Aerosol Optical Thickness (AOT), an important aerosol optical property, should be correctly determined to remove the atmospheric effect. The retrieval process is great time-consuming and the EMS memory required is too large for a personal computing to run efficiently. Therefore, to facilitate the process smoothly, SYNTAM model is used to retrieve AOT over a wide range of land including China and one European area from MODIS data on the Remote Sensing Information Service Grid Node (RSIN, http://www.tgp.ac.cn) deployed at Institute of Remote Sensing Applications, Chinese Academy of Sciences. AOT retrieval results show that the RSIN Grid service is high efficient and has the potential to be applied to the remote sensing parameter inversion.
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a remote sensing application workflow and its implementation in remote sensing service Grid Node
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo Zhong, Zhengfang WangAbstract:In this article we describe a remote sensing application workflow in building a Remote Sensing Information Analysis and Service Grid Node at Institute of Remote Sensing Applications based on the Condor platform. The goal of the Node is to make good use of physically distributed resources in the field of remote sensing science such as data, models and algorithms, and computing resource left unused on Internet. Implementing it we use workflow technology to manage the Node, control resources, and make traditional algorithms as a Grid service. We use web service technology to communicate with Spatial Information Grid (SIG) and other Grid systems. We use JSP technology to provide an independent portal. Finally, the current status of this ongoing work is described.
-
remote sensing information processing Grid Node with loose coupling parallel structure
International Conference on Computational Science, 2006Co-Authors: Ying Luo, Yong Xue, Jianping Guo, Wei Wan, Lei Zheng, Guoyin Cai, Shaobo ZhongAbstract:To use traditional algorithms and software packages on Grid system, traditional algorithms and software packages, in general, have to be modified. In this paper we focus on standards and methodologies for Grid platform within the context of the Remote Sensing Data Processing Grid Node (RSDPGN) that implements a loose-coupling parallel structure for orchestrating traditional remote sensing algorithms and software packages on the Condor platform. We have implemented 17 remote sensing applications in one system using Web service and workflow technology without any change to traditional codes. Some core algorithm codes are come from a remote sensing software package which we has neither resource codes nor APIs. Others come from the program codes accumulated by our group. The design and prototype implementation of RSDPGN are presented. The advantage and shortage of loose-coupling structure is analysed. Through a case study of land surface temperature calcu-lation from MODIS data, we demonstrate the way to modify software packages in details. Moreover we discuss the problems and solutions based on our experience such as system architecture, the kinds of functional modules, fast data transfer, and state monitoring.
