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作 者:李俊杰[1] 姜涛 傅俏燕[1] LI Junjie;JIANG Tao;FU Qiaoyan(China Centre for Resources Satellite Data and Application,Beijing 100094,China)
出 处:《航天返回与遥感》2020年第5期95-101,共7页Spacecraft Recovery & Remote Sensing
基 金:国家重点研发计划资助(2018YFB0505000)。
摘 要:云对光学遥感卫星影像影响较大,影像上的云及其阴影均会不同程度遮掩地物,降低影像的使用价值。“高分一号”(GF-1)卫星多光谱宽幅相机(WFV)影像相较于美国的陆地卫星系列和欧空局的“哨兵2号”卫星影像,空间分辨率适中,时间分辨率较高,更有利于进行无云影像合成。利用WFV影像的高频时间序列数据合成无云影像,可使GF-1卫星数据在土地利用和覆盖变化、农作物监测等领域得到更有效的应用。文章基于已有的最大植被指数和最小蓝光波段反射率影像合成方法,提出了一种新的影像合成方法,该方法既解决了最大植被指数合成影像中水体有云和耀斑的问题,也弥补了最小蓝光波段合成影像中陆地上部分云和阴影去除效果不佳的缺陷。将该方法应用于湖南省多云月份GF-1卫星WFV影像的合成实现,结果表明该方法可用于中分辩率、高频时间序列卫星遥感影像合成,合成影像成果中云和云阴影比例低,效果较好。Clouds have a greater impact on optical satellite remote sensing images.The clouds and their shadows on the images will cover the ground to varying degrees,reducing the use value of the images.Compared with the US Landsat satellite series and ESA's Sentinel-2 satellite images,the GF-1 WFV image has moderate spatial resolution and high temporal resolution,which is more conducive to cloud-free image composition.Using the high-frequency time series data of the GF-1 WFV image to compose cloud-free images can make GF-1 satellite data more convenient and effective in land use and cover change,crop monitoring and other fields.This paper proposes a new image composite method based on the existing maximum NDVI and minimum blue band reflectance image composite methods,combining the advantages of the two methods above.This method not only solves the problem of cloud and flare in the water body in the maximum NDVI composite image,but also solves the problem of poor cloud and shadow removal on the land in the minimum light band composite image.The method proposed in this paper is used to compose the GF-1 WFV image on a cloudy month in Hunan Province.The results show that this method can be used to compose satellite remote sensing images with mid-resolution and high-frequency time series.The ratio of clouds to cloud shadow of the composite images is low and the result is good.
关 键 词:无云影像 时间序列 影像合成 多光谱宽幅相机 “高分一号”卫星
分 类 号:P237[天文地球—摄影测量与遥感]
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