基于Landsat8影像的厚云及云影去除方法
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摘要
Landsat系列卫星对推动遥感应用技术的发展起到了重要作用,其遥感图像数据在多领域得到了广泛应用。但是Landsat影像常受到云的污染,使得其在地表动态监测时有效性大大下降。本文首先利用云和云阴影匹配算法Fmask实现快速、准确地识别云与云影区域并进行掩膜,然后基于时空数据融合算法ESTARFM利用多时相MODIS和Landsat数据,对Landsat8影像缺失的云及云影区域进行插补。结果表明这是一种有效地去除云及云影的方法,对Landsat8数据的定量分析或时序研究具有重要价值。
The terrestrial satellite series satellites have played an important role in promoting the development of remote sensing application technology, and its remote sensing image data has been widely used in various fields. However, Landsat images are often contaminated by clouds, making them less effective in dynamic surface monitoring. This paper firstly uses the cloud and cloud shadow matching algorithm Fmask to quickly and accurately identify the cloud and cloud shadow regions and mask them. Then, based on the spatio-temporal data fusion algorithm ESTARFM, the multi-temporal MODIS and Landsat data are used to capture the missing clouds and clouds of the Landsat8 image. The area is interpolated. The results show that this is an effective method to remove clouds and cloud shadows, which is of great value for quantitative analysis or time series research of Landsat8 data.
The terrestrial satellite series satellites have played an important role in promoting the development of remote sensing application technology, and its remote sensing image data has been widely used in various fields. However, Landsat images are often contaminated by clouds, making them less effective in dynamic surface monitoring. This paper firstly uses the cloud and cloud shadow matching algorithm Fmask to quickly and accurately identify the cloud and cloud shadow regions and mask them. Then, based on the spatio-temporal data fusion algorithm ESTARFM, the multi-temporal MODIS and Landsat data are used to capture the missing clouds and clouds of the Landsat8 image. The area is interpolated. The results show that this is an effective method to remove clouds and cloud shadows, which is of great value for quantitative analysis or time series research of Landsat8 data.
引文
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[8] GóMEZ-CHOVA,LUIS,AMORóS-LóPEZ,JULIA,Mateo-GARCíA,GONZALO,et al.Cloud Masking and Removal in Remote Sensing Image Time Series[J].Journal of Applied Remote Sensing,2017,11(1):15-19.
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[12] GAO Feng,MASEK J,SCHWALLER M,et al.On the Blending of the Landsat and MODIS Surface Reflectance:Predicting Daily Landsat Surface Reflectance[J].IEEE Transactions on Geoscience & Remote Sensing,2006,44(8):2207-2218.
[13] ZHU Xiaolin,CHEN Jin,GAO Feng,et al.An Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model for Complex Heterogeneous Regions[J].Remote Sensing of Environment,2010,114(11):2610-2623.
[14] 黄永喜,李晓松,吴炳方,等.基于改进的ESTARFM数据融合方法研究[J].遥感技术与应用,2013,28(5):753-760.
[15] 王昆,张丽,王志勇,等.基于半方差函数的STARFM改进模型[J].测绘科学,2013,38(3):140-142.
[16] 郝贵斌,吴波,张立福,等.ESTARFM模型在西藏色林错湖面积时空变化中的应用分析(1976-2014年)[J].地球信息科学学报,2016,18(6):833-846.
[2] 王兴华,崔文宏.遥感影像在地图中的应用[J].北京测绘,2015(4):123-125.
[3] 初庆伟,张洪群,吴业炜,等.Landsat-8卫星数据应用探讨[J].遥感信息,2013,28(4):110-114.
[4] JU J,ROY D P.The Availability of Cloud-free Landsat ETM+Data over the Conterminous United States and Globally[J].Remote Sensing of Environment,2008,112(3):1196-1211.
[5] ZHU Zhu,WOODCOCK C E.Object-based Cloud and Cloud Shadow Detection in Landsat Imagery[J].Remote Sensing of Environment,2012,118(6):83-94.
[6] 刘洋,白俊武.遥感影像中薄云的去除方法研究[J].测绘与空间地理信息,2008,31(3):120-122.
[7] XU Meng,JIA Xiuping,PICKERING M.Automatic Cloud Removal for Landsat 8 OLI Images Using Cirrus Band[C]//Geoscience and Remote Sensing Symposium.IEEE,2014:2511-2514.
[8] GóMEZ-CHOVA,LUIS,AMORóS-LóPEZ,JULIA,Mateo-GARCíA,GONZALO,et al.Cloud Masking and Removal in Remote Sensing Image Time Series[J].Journal of Applied Remote Sensing,2017,11(1):15-19.
[9] 赵孟银.遥感影像去云方法研究[D].天津:天津科技大学,2016.
[10] MENG Q,BORDERS B E,CIESZEWSKI C J,et al.Closest Spectral Fit for Removing Clouds and Cloud Shadows[J].Photogrammetric Engineering & Remote Sensing,2009,75(5):569-576.
[11] ZHU Zhe,WANG Shixiong,WOODCOCK C E.Improvement and Expansion of the Fmask Algorithm:Cloud,Cloud Shadow,and Snow Detection for Landsats 4-7,8,and Sentinel 2 Images[J].Remote Sensing of Environment,2015,159:269-277.
[12] GAO Feng,MASEK J,SCHWALLER M,et al.On the Blending of the Landsat and MODIS Surface Reflectance:Predicting Daily Landsat Surface Reflectance[J].IEEE Transactions on Geoscience & Remote Sensing,2006,44(8):2207-2218.
[13] ZHU Xiaolin,CHEN Jin,GAO Feng,et al.An Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model for Complex Heterogeneous Regions[J].Remote Sensing of Environment,2010,114(11):2610-2623.
[14] 黄永喜,李晓松,吴炳方,等.基于改进的ESTARFM数据融合方法研究[J].遥感技术与应用,2013,28(5):753-760.
[15] 王昆,张丽,王志勇,等.基于半方差函数的STARFM改进模型[J].测绘科学,2013,38(3):140-142.
[16] 郝贵斌,吴波,张立福,等.ESTARFM模型在西藏色林错湖面积时空变化中的应用分析(1976-2014年)[J].地球信息科学学报,2016,18(6):833-846.