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Target area based relational database system for managing earth observation information

机译:基于目标区域的关系数据库系统,用于管理地球观测信息

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Monitoring of environment requires several sources of information to be combined: "General knowledge" of the monitored area, measurement information on it and naturally previously made assessments of the same area. To use earth observation in monitoring of for example lake water quality, traditional images have limited value: How could they be used for example when one wishes to draw a graph of time series from several lakes in order to compare them? Indicator values stored in a database would be required. To solve these data use problems in water quality monitoring, ULAPPA system was developed using target area approach. It starts from the fact that usually the areas to be monitored are clearly defined: Lakes, fields etc. have more or less well-defined locations and boundaries. They have distinctive a priori characteristics as individual entities or according to their type, in situ measurements are made on them, they are being observed by several types of satellites and all this data is combined using several different algorithms, possibly with several versions of algorithm parameters. Sometimes model assimilation requires access to uninterpreted, usable satellite data. Management of usable earth observation data is critical for optical data, as clouds often obscure the target area. All these needs can be integrated according to user needs using the target area approach.
机译:监视环境需要将多种信息源进行组合:被监视区域的“一般知识”,有关被监视区域的测量信息以及以前自然对同一区域进行的评估。为了将地球观测用于监测例如湖泊水质,传统图像的价值有限:例如,当一个人希望绘制多个湖泊​​的时间序列图以进行比较时,如何使用它们?需要将指标值存储在数据库中。为了解决水质监测中的这些数据使用问题,使用目标区域方法开发了ULAPPA系统。首先,通常要明确定义要监视的区域:湖泊,田野等具有或多或少明确定义的位置和边界。它们具有独特的先验特征,既可以作为单个实体,也可以根据其类型进行原位测量,可以通过几种类型的卫星进行观测,并且可以使用几种不同的算法(可能还有几种算法参数)将所有这些数据组合在一起。有时模型同化需要访问未解释的可用卫星数据。由于云层经常遮挡目标区域,因此可用的地球观测数据的管理对于光学数据至关重要。使用目标区域方法可以根据用户需求整合所有这些需求。

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