云检测阈值自动生成(CDAG)算法是一种自动生成阈值的云检测方法,这种方法是使用预先准确确定出云和晴空像元的AVIRIS高光谱数据模拟出不同传感器的云和晴空像元数据,据此生成它们的云检测阈值。这种方法具有自动化程度高、云检测效果好...云检测阈值自动生成(CDAG)算法是一种自动生成阈值的云检测方法,这种方法是使用预先准确确定出云和晴空像元的AVIRIS高光谱数据模拟出不同传感器的云和晴空像元数据,据此生成它们的云检测阈值。这种方法具有自动化程度高、云检测效果好等优点。但是在原数据库的构建中,由于AVIRIS数据集中雪像元较少,导致云和雪的识别存在较大的误差。为了解决该问题,从待测数据中提取大量不同类型的雪像元,加入模拟得到的多光谱数据集中,生成新的云检测阈值,阈值生成中使用了单波段反射率、多波段反射率组合参数等作为云检测算法的输入参数。使用2013—2017年青藏高原地区多景典型Landsat8陆地成像仪(Operational Land Imager,OLI)影像进行实验验证。结果显示,在积雪覆盖的区域平均云像元识别正确率达到93.11%,对包括雪在内的晴空像元的漏判率降低到4.35%,表明此方法能有效避免雪的影响,实现高精度的云检测。展开更多
Recently,water extraction based on the indices method has been documented in many studies using various remote sensing data sources.Among them,Landsat satellites data have certain advantages in spatial resolution and ...Recently,water extraction based on the indices method has been documented in many studies using various remote sensing data sources.Among them,Landsat satellites data have certain advantages in spatial resolution and cost.After the successful launch of Landsat 8,the Operational Land Imager(OLI)data from the satellite are getting more and more attention because of its new improvements.In this study,we used the OLI imagery data source to study the water extraction performance based on the Normalized Difference Vegetation Index,Normalized Difference Water Index,Modified Normalized Water Index(MNDWI),and Automated Water Extraction Index(AWEI)and compared the results with the Thematic Mapper(TM)imagery data.Two test sites in Tianjin City of north China were selected as the study area to verify the applicability of OLI data and demonstrate its advantages over TM data.We found that the results of surface water extraction based on OLI data are slightly better than that based on TM in the two test sites,especially in the city site.The AWEI and MNDWI indices performs better than the other two indices,and the thresholds of water indices show more stability when using the OLI data.So,it is suitable to combine OLI imagery with other Landsat sensor data to study water changes for long periods of time.展开更多
文摘云检测阈值自动生成(CDAG)算法是一种自动生成阈值的云检测方法,这种方法是使用预先准确确定出云和晴空像元的AVIRIS高光谱数据模拟出不同传感器的云和晴空像元数据,据此生成它们的云检测阈值。这种方法具有自动化程度高、云检测效果好等优点。但是在原数据库的构建中,由于AVIRIS数据集中雪像元较少,导致云和雪的识别存在较大的误差。为了解决该问题,从待测数据中提取大量不同类型的雪像元,加入模拟得到的多光谱数据集中,生成新的云检测阈值,阈值生成中使用了单波段反射率、多波段反射率组合参数等作为云检测算法的输入参数。使用2013—2017年青藏高原地区多景典型Landsat8陆地成像仪(Operational Land Imager,OLI)影像进行实验验证。结果显示,在积雪覆盖的区域平均云像元识别正确率达到93.11%,对包括雪在内的晴空像元的漏判率降低到4.35%,表明此方法能有效避免雪的影响,实现高精度的云检测。
基金The authors would like to thank the support by the Key Research Program of the Chinese Academy of Science[grant number KZZD–EW–14]the Visiting Scholar Foundation of Chinese Academy of Science.The authors would like to thank USGS for processing and providing Landsat data and the reviewers for their constructive comments and suggestions.The authors especially thank Prof Xiangming Xiao in the Earth Observation and Modeling Facility,University of Oklahoma,for his useful suggestions to this paper.
文摘Recently,water extraction based on the indices method has been documented in many studies using various remote sensing data sources.Among them,Landsat satellites data have certain advantages in spatial resolution and cost.After the successful launch of Landsat 8,the Operational Land Imager(OLI)data from the satellite are getting more and more attention because of its new improvements.In this study,we used the OLI imagery data source to study the water extraction performance based on the Normalized Difference Vegetation Index,Normalized Difference Water Index,Modified Normalized Water Index(MNDWI),and Automated Water Extraction Index(AWEI)and compared the results with the Thematic Mapper(TM)imagery data.Two test sites in Tianjin City of north China were selected as the study area to verify the applicability of OLI data and demonstrate its advantages over TM data.We found that the results of surface water extraction based on OLI data are slightly better than that based on TM in the two test sites,especially in the city site.The AWEI and MNDWI indices performs better than the other two indices,and the thresholds of water indices show more stability when using the OLI data.So,it is suitable to combine OLI imagery with other Landsat sensor data to study water changes for long periods of time.
