摘要
随着遥感影像数据越来越多,面向指定区域的遥感数据查询,往往出现查询结果数据量大、数据重叠且数据质量良莠不齐的问题。针对传统查询方法的问题,提出一种遥感影像区域覆盖最优数据集的筛选模型。该模型基于成像时间、云量和分辨率等参数建立归一化数学计算模型,完成指定时空范围内覆盖最优的遥感影像数据集筛选。试验结果表明,使用区域覆盖最优数据集筛选模型,能够有效剔除遥感数据中较早时相、重复覆盖和多云量的数据,有效地缩减用户数据筛选时间。
With more and more remote sensing imagery,for the querying of remote sensing data in specified region,the problem with large querying result,repeating coverage and mixed quality appeared. To improve the problem of traditional querying,a screening model for optimal coverage datasets of remote sensing imagery was proposed.A normalized mathematical computational model was built on the imaging time,cloud amount and image resolution,which realized the screening of imagery datasets with optimal coverage in the specified space-time range.The test result showed that the screening model could effectively reject the remote sensing data with early time-phase,repeating coverage and large cloud cover.And the screening time was also effectively reduced.
出处
《无线电工程》
2017年第10期45-48,共4页
Radio Engineering
基金
国土资源公益性行业科研专项基金资助项目(201411119)
关键词
遥感影像
筛选模型
最优数据集
智能AGENT
remote-sensing imagery
screening model
optimal dataset
intelligent Agent
