对地观测网传感器资源共享管理模型与方法研究
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摘要
随着地球环境的变化,人们对地球观测数据的需求日益复杂化,对地观测系统呈现多样性,对地观测网概念得以发展。对地观测网是执行地球环境事件感知任务的地理空间观测网,利用对地观测传感器对地球表面和低层大气进行探测,以获取用户感兴趣数据/信息。众所周知,传感器集成管理与协同观测是对地观测网的重大科学问题之一。
对地观测传感器是地理空间数据获取的源泉。然而,对地观测传感器类型多样、观测机理各异、数量巨大,它们呈现出封闭、孤立和自治性。由于缺乏可共享的描述模型和科学的关联方法,在面对特定陆表事件时,传感器资源的配置不准确、不全面与不及时,直接导致应急响应时传感器规划与调度低效。因此,本文旨在将这些分布式、海量与异构的对地观测传感器资源共享管理起来,这有助于及时、准确与全面地规划与调度传感器,提高对地观测传感器的可管理性和应用效能。
针对地观测网传感器资源的特点及其在陆表灾害事件监测时的低效应用,本文指出了传感器共享管理是对地观测网传感器集成管理与协同观测这一重大科学问题中迫切需要解决的一个基础问题。围绕这个问题,本文针对传感器共享管理框架进行深入的分析,从共享管理模型与方法上展开研究。即如何实现对地观测传感器共享管理,为特定陆表事件观测时传感器集成管理与协同规划奠定基础。
首先,本文总结了现有传感器信息交换标准和相关元数据标准,分析了对地观测网传感器资源共享需求,通过扩展与重利用现有传感器相关的元数据标准,提出了传感器共享八元组元数据模型。基于MOF元级理论标准化定义了传感器资源描述元模型,建立了嵌套共享元数据的传感器资源描述模型,为实现传感器资源注册发现、协同规划、动态可视化管理奠定信息模型基础。
其次,为了实现陆表事件与传感器的有机关联,本文提出了以陆表事件为中心的传感器关联方法。通过定义事件与传感器之间的关联规则,设计了基于时空约束的多层次匹配(MM-TL)算法,实现了从事件到传感器的科学关联,改变过去传感器调度与规划主要依靠被动与不完善的专家经验的局面,为对地观测网传感器集成管理与协同观测提供了可信的传感器依据。
再次,基于开放地理信息联盟(OGC)的网络目录服务(CSW)规范,本文提出了基于传感器资源描述模型和OGC/CSW的传感器注册机制,通过扩展CSW核心信息模型以支持传感器注册,设计传感器资源描述模型与传感器注册信息模型之间的映射关系,实现基于OGC/CSW的传感器标准注册,为后续传感器发现提供网络目录服务中心。
然后,结合已经建立的OGC/CSW传感器目录服务中心,设计细粒度多层次的传感器元数据查询项,基于OGC/CSW发现接口,实现传感器资源的按需发现。采用虚拟现实仿真技术,对符合要求的传感器资源一体化动态可视化,有助于传感器查询者对传感器基本信息、时空观测动态能力等信息的直观把握与理解,辅助传感器调度与规划决策生成。
最后,应用本文所提出的共享管理模型与方法。构建了对地观测传感器共享管理平台框架,以长江流域中下游段水文环境监测传感器资源与内涝型洪涝事件为实验资源,验证了本文的共享管理模型与方法的有效性与可行性。
With the changes of the Earth environment, the demands of Earth Observation (EO) data are becoming increasingly complex, the EO systems are showing greatly diverse and thus the concept of EO web are urgently developing. EO web is a geospatial observation web that implements the event-aware task to the global environment. EO sensors are used to detect the Earth's surface and lower atmosphere for obtaining the data/information of interest to the user. As we all know, the integration management and collaboration observation of the EO sensors is one of the major scientific problems under the EO web environment.
EO sensor is the source of geospatial data acquisition. However, due to the characteristics (such as:diverse observation mechanism, huge number, isolation and autonomous condition) of the EO sensors, when facing with one specific epicontinental event, the EO sensor allocation is always inaccurate, incomplete and time-lagging. The direct result is inefficiency to the sensor planning and dispatch. Therefore, this paper aims to the sharing management of those distributed, massive and heterogeneous EO sensors which facilitate the timely, accurate and comprehensive scheduling sensors, thus improving the manageability and application for the EO sensors.
According to the analysis of sensor resources above and the inefficient response to the epicontinental disaster event under the EO web, this paper points out that the sensor sharing management is a basic problem for sensor integration management and collaboration. To solve this basic problem, this paper carries out the in-depth analysis for the sensor sharing management framework, including sensor sharing management model and methodology.
Firstly, the paper starts with the summary to the existing sensor information exchange standards and related metadata standards and the analysis to the sensor resources'sharing requirements, through expansing and reusing the existing sensor-related metadata standards, this paper proposes a sensor sharing eight-tuple metadata model. Based on the MOF metamodel theory, this paper standardly defines sensor resource description metamodel and establishes the sharing metadata-nested sensor resource description model, which plays a basic information model for the achievement of registry, discovery, collaborative planning, and dynamic visualization to the EO sensors.
Secondly, in order to achieve the organic association between the specific epicontiental event and EO sensors, this paper presents an epicontinental event-centric association method. This method defines the association rules between the event and EO sensors, and designs the Multi-level Matching Algorithm based on Time and Location Constraints (MM_TL). In this manner, the scientific association between event and sensors has been realized, and it changes the past situation of that sensor scheduling and planning mainly relies on passive and imperfect expertise. This association method can provide the trust sensor collection for the sensor integration management and collaborative observation.
Thirdly, on the basis of Open GIS Consortium (OGC) Catalog Service for Web (CSW) specification, this paper proposes a standard sensor register mechanism, including the extending of CSW core information model for supporting sensor registry, designation of mapping relationship between sensor resource description model and sensor registry information model. Then, the OGC/CSW-based sensor register center can be established, which lays the foundation for sensor discovery in the following.
Fourthly, depending on the OGC/CSW sensor register center mentioned above, this paper designs the fine-grained multi-level sensor metadata query items. By adopting the OGC/CSW discovery interface, the registered EO sensor resources can be discovered on demand. Through using virtual reality simulation technology, this paper integratively visualizes the retrieved sensor resources facilitating the sensor inquirers'intuitive grasp and understanding of sensor basic information and temporal-spatial dynamic abilities, thus aiding the required sensor planning and dispatch decision-making.
Finally, this paper builds the EO sensor sharing management platform framework. By using the hydrological environment monitoring sensor resources in the downstream section of the Yangtze River basin and the waterlogging type flood event as the experimental resources, the application of proposed sharing management model and method has been examplified.
对地观测传感器是地理空间数据获取的源泉。然而,对地观测传感器类型多样、观测机理各异、数量巨大,它们呈现出封闭、孤立和自治性。由于缺乏可共享的描述模型和科学的关联方法,在面对特定陆表事件时,传感器资源的配置不准确、不全面与不及时,直接导致应急响应时传感器规划与调度低效。因此,本文旨在将这些分布式、海量与异构的对地观测传感器资源共享管理起来,这有助于及时、准确与全面地规划与调度传感器,提高对地观测传感器的可管理性和应用效能。
针对地观测网传感器资源的特点及其在陆表灾害事件监测时的低效应用,本文指出了传感器共享管理是对地观测网传感器集成管理与协同观测这一重大科学问题中迫切需要解决的一个基础问题。围绕这个问题,本文针对传感器共享管理框架进行深入的分析,从共享管理模型与方法上展开研究。即如何实现对地观测传感器共享管理,为特定陆表事件观测时传感器集成管理与协同规划奠定基础。
首先,本文总结了现有传感器信息交换标准和相关元数据标准,分析了对地观测网传感器资源共享需求,通过扩展与重利用现有传感器相关的元数据标准,提出了传感器共享八元组元数据模型。基于MOF元级理论标准化定义了传感器资源描述元模型,建立了嵌套共享元数据的传感器资源描述模型,为实现传感器资源注册发现、协同规划、动态可视化管理奠定信息模型基础。
其次,为了实现陆表事件与传感器的有机关联,本文提出了以陆表事件为中心的传感器关联方法。通过定义事件与传感器之间的关联规则,设计了基于时空约束的多层次匹配(MM-TL)算法,实现了从事件到传感器的科学关联,改变过去传感器调度与规划主要依靠被动与不完善的专家经验的局面,为对地观测网传感器集成管理与协同观测提供了可信的传感器依据。
再次,基于开放地理信息联盟(OGC)的网络目录服务(CSW)规范,本文提出了基于传感器资源描述模型和OGC/CSW的传感器注册机制,通过扩展CSW核心信息模型以支持传感器注册,设计传感器资源描述模型与传感器注册信息模型之间的映射关系,实现基于OGC/CSW的传感器标准注册,为后续传感器发现提供网络目录服务中心。
然后,结合已经建立的OGC/CSW传感器目录服务中心,设计细粒度多层次的传感器元数据查询项,基于OGC/CSW发现接口,实现传感器资源的按需发现。采用虚拟现实仿真技术,对符合要求的传感器资源一体化动态可视化,有助于传感器查询者对传感器基本信息、时空观测动态能力等信息的直观把握与理解,辅助传感器调度与规划决策生成。
最后,应用本文所提出的共享管理模型与方法。构建了对地观测传感器共享管理平台框架,以长江流域中下游段水文环境监测传感器资源与内涝型洪涝事件为实验资源,验证了本文的共享管理模型与方法的有效性与可行性。
With the changes of the Earth environment, the demands of Earth Observation (EO) data are becoming increasingly complex, the EO systems are showing greatly diverse and thus the concept of EO web are urgently developing. EO web is a geospatial observation web that implements the event-aware task to the global environment. EO sensors are used to detect the Earth's surface and lower atmosphere for obtaining the data/information of interest to the user. As we all know, the integration management and collaboration observation of the EO sensors is one of the major scientific problems under the EO web environment.
EO sensor is the source of geospatial data acquisition. However, due to the characteristics (such as:diverse observation mechanism, huge number, isolation and autonomous condition) of the EO sensors, when facing with one specific epicontinental event, the EO sensor allocation is always inaccurate, incomplete and time-lagging. The direct result is inefficiency to the sensor planning and dispatch. Therefore, this paper aims to the sharing management of those distributed, massive and heterogeneous EO sensors which facilitate the timely, accurate and comprehensive scheduling sensors, thus improving the manageability and application for the EO sensors.
According to the analysis of sensor resources above and the inefficient response to the epicontinental disaster event under the EO web, this paper points out that the sensor sharing management is a basic problem for sensor integration management and collaboration. To solve this basic problem, this paper carries out the in-depth analysis for the sensor sharing management framework, including sensor sharing management model and methodology.
Firstly, the paper starts with the summary to the existing sensor information exchange standards and related metadata standards and the analysis to the sensor resources'sharing requirements, through expansing and reusing the existing sensor-related metadata standards, this paper proposes a sensor sharing eight-tuple metadata model. Based on the MOF metamodel theory, this paper standardly defines sensor resource description metamodel and establishes the sharing metadata-nested sensor resource description model, which plays a basic information model for the achievement of registry, discovery, collaborative planning, and dynamic visualization to the EO sensors.
Secondly, in order to achieve the organic association between the specific epicontiental event and EO sensors, this paper presents an epicontinental event-centric association method. This method defines the association rules between the event and EO sensors, and designs the Multi-level Matching Algorithm based on Time and Location Constraints (MM_TL). In this manner, the scientific association between event and sensors has been realized, and it changes the past situation of that sensor scheduling and planning mainly relies on passive and imperfect expertise. This association method can provide the trust sensor collection for the sensor integration management and collaborative observation.
Thirdly, on the basis of Open GIS Consortium (OGC) Catalog Service for Web (CSW) specification, this paper proposes a standard sensor register mechanism, including the extending of CSW core information model for supporting sensor registry, designation of mapping relationship between sensor resource description model and sensor registry information model. Then, the OGC/CSW-based sensor register center can be established, which lays the foundation for sensor discovery in the following.
Fourthly, depending on the OGC/CSW sensor register center mentioned above, this paper designs the fine-grained multi-level sensor metadata query items. By adopting the OGC/CSW discovery interface, the registered EO sensor resources can be discovered on demand. Through using virtual reality simulation technology, this paper integratively visualizes the retrieved sensor resources facilitating the sensor inquirers'intuitive grasp and understanding of sensor basic information and temporal-spatial dynamic abilities, thus aiding the required sensor planning and dispatch decision-making.
Finally, this paper builds the EO sensor sharing management platform framework. By using the hydrological environment monitoring sensor resources in the downstream section of the Yangtze River basin and the waterlogging type flood event as the experimental resources, the application of proposed sharing management model and method has been examplified.
引文
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