• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Remote Sensing for Marine and Coastal Environments >LAKE MICHIGAN TIME SERIES PRODUCTIVITY MEASUREMENTS OBTAINED FROM A NEWSEAWIFS AND MODIS SATELLITE RETRIEVAL ALGORITHM*
【24h】

LAKE MICHIGAN TIME SERIES PRODUCTIVITY MEASUREMENTS OBTAINED FROM A NEWSEAWIFS AND MODIS SATELLITE RETRIEVAL ALGORITHM*

机译：从新大陆和MODIS卫星检索算法获得的密歇根湖时间序列生产力度量*

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A new operational non satellite-specific algorithm for the simultaneous retrieval from satellite data ofcontent of phytoplankton chlorophyll, suspended minerals and dissolved organics in both clear and turbidwaters is presented. It contains an array of neural networks providing input for the Levenberg-Marquardtmultivariate optimization procedure as the final retrieval tool. With a given accuracy threshold, thedeveloped algorithm is sufficiently robust for data with noise up to 15% for certain hydro-opticalconditions. To avoid inadequate retrieval results, the algorithm identifies and eventually discards the pixelswith inadequate atmospheric correction and/or water optical properties incompatible with the appliedhydro-optical model. The validity of the developed algorithm was tested for Lake Michigan. Two dedicatedfield campaigns in the vicinity of the Kalamazoo River outfall have been conducted concurrently or quasiconcurrentlywith satellite overpasses. In addition, some archival shipborne measurements of chl, sm anddoc were employed to validate the facility of the algorithm. The conducted comparison of the groundtruthand retrieved data on the water quality parameters in Lake Michigan provides evidence of the algorithmoperational efficiency.
机译：提出了一种新的非卫星专用运算算法，该算法可同时从卫星数据中检索清澈和浑浊水中的浮游植物叶绿素，悬浮矿物质和溶解有机物的含量。它包含一组神经网络，这些神经网络为Levenberg-Marquardt多变量优化过程提供了输入，作为最终的检索工具。在给定的精度阈值的情况下，对于某些水光学条件，所开发的算法对于噪声高达15％的数据具有足够的鲁棒性。为了避免检索结果不足，该算法会识别并最终丢弃像素，这些像素的大气校正和/或水光学特性与所应用的水光学模型不兼容。对密歇根湖测试了开发算法的有效性。在卡拉马祖河出水口附近，与卫星立交桥同时或准时进行了两次专门战役。此外，还使用了一些对chl，sm和doc的船载档案测量来验证算法的便利性。对密歇根湖水质参数的地面真实情况和获取的数据进行的比较提供了算法运行效率的证据。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号