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MODIS影像的局地云量信息元数据提取算法与应用
引用本文:钟洪麟,施润和,曲培青,张慧芳,高炜.MODIS影像的局地云量信息元数据提取算法与应用[J].地球信息科学,2010,12(4):587-592.
作者姓名:钟洪麟  施润和  曲培青  张慧芳  高炜
作者单位:华东师范大学地理信息科学教育部重点实验室, 上海 200062; 华东师范大学-中国科学院对地观测与数字地球科学中心环境遥感与数据同化联合实验室, 上海 200062
基金项目:国家重点基础研究发展计划(2006CB403404); 上海市教育发展基金会晨光计划(2008CG28); 中央高校基本科研业务费专项
摘    要:云对于光学遥感影像质量及其反演地表参数精度有着重要影响,且其作为时空多变要素之一,在一定程度上制约了光学遥感影像的应用。对于具有2 330km的大扫描幅宽MODIS影像而言,现有的元数据标准仅能反映影像的总体云量,而无法反映云的空间分布状况,限制了MODIS数据的局地研究和应用。本文在现有遥感影像元数据标准的基础上,提出了新的元数据项--局地云量,用于反映云在条带影像中的空间分布状况,并实现在MODIS二级云掩膜条带产品(MOD35)中针对特定区域的局地云量信息提取算法。经验证,本算法能较快速和准确地提取省级行政区的局地云量信息,并可根据用户的需求进一步推广到任意指定的多边形区域,为MODIS数据在局地研究和应用提供了便利。

关 键 词:MODIS  局地云量  遥感元数据  数据检索  
收稿时间:2010-01-20;

The Regional Cloud-cover Metadata Extraction Based on MODIS Image
ZHONG Honglin,SHI Runhe,QU Peiqing,ZHANG Huifang,GAO Wei.The Regional Cloud-cover Metadata Extraction Based on MODIS Image[J].Geo-information Science,2010,12(4):587-592.
Authors:ZHONG Honglin  SHI Runhe  QU Peiqing  ZHANG Huifang  GAO Wei
Institution:Key Laboratory of Geographic Information Science,Ministry of Education,East China Normal University,Shanghai 200062,China;Joint Laboratory for Environmental Remote Sensing and Data Assimilation,ECNU & CEODE,CAS,Shanghai 200062,China
Abstract:The cloud had a significant influence to the quality of optical remote sensing images and the retrieval accuracy of land surface parameters.As one of the variable spatial-temporal factors,cloud would limit the application of optical remote sensed images.For the MODIS data with its swaths cover about 2330 km,the current metadata standards can only describe cloud quantity of the whole image,which limited regional studies and the application of MODIS images.Based on studies of current remote sensing metadata standards,we introduced a new metadata item named "regional cloud-cover" in order to describe the images' cloud spatial distribution,and extract the cloud cover information of specific areas from the MODIS level two cloud mask production(MOD35).This algorithm can extract provincial cloud quantity fast and accurately,and users can upload the vector boundary data or use tools provided by the system to draw their study area on the map,in order to specify the region that they study in the remotely sensed images,which would bring convenience to the regional research using MODIS data.In this paper,we realized the algorithm in the Visual C++ environment.First,we overlaid the girded vector boundary onto the raster data which has no projection.Then extract the cloud-cover percentage from sub-image that tripped from the original image.Finally we made a comparison between the results retrieved from the remote sensing images before and after geometric correction.It showed that,the geometric correction can improve the accuracy of the result little,but need to take much more time.We also made a comparison of the cloud cover percentage between the whole image and the regional one(Anhui Province),the result shows that the regional cloud-cover can represent the cloud-cover status of the specify region much more accurately than before.
Keywords:MODIS  regional cloud cover quantity  remote sensing metadata  data query
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