| The retrieval result that the existing remote sensing image data service system provided often with high redundancy and low data quality,and the retrieval systems fails to directly meet the diverse and practical research needs of users.The secondary screening of users seriously reduces the efficiency of retrieval results and increases the cost of cleaning high-quality data.In order to solve such problems,this paper chooses to use the global Landsat-8 satellite metadata retrieval information in 2015 to establish a quality evaluation system composed of three proprietary indicators.To achieve the simplification and customization requirements,the method of selection and integrating of remote sensing dataset is designed.The paper firstly establishes a remote sensing image data quality evaluation model by integrating three specific indicators:spatial integrity,temporal proximity and cloud coverage;Secondly,based on the remote sensing image data quality evaluation model,by simulating the three application scenarios,the simplest and customized integrating methods of remote sensing image dataset are designed;Finally,using data resource aggregation technology,the data validation tools for Landsat-8 dataset is designed and implemented,which includes dataset download,data list revision,metadata data file extraction,data quality inspection and data archiving to verify the accuracy of data.The experimental results show that the selection and integrating method of remote sensing dataset proposed in this paper solves the problem of data redundancy,data overlap and low data quality in the traditional retrieval system.This method provides users with data scheme list and avoids the user's participation in the manual screening process of retrieval results.This method greatly improves the efficiency and accuracy of data retrieval and the efficiency of data retrieval results without changing the existing remote sensing image data service system. |
PDF Full Text Request