Suomi NPP卫星可见光红外成像辐射仪的改进动态阈值云检测算法
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摘要
基于可见光红外成像辐射仪多波段、宽覆盖、长重访周期的特点,以及云层在可见光到热红外通道的分布及变化特性,提出了一种适用于可见光红外成像辐射仪数据的改进的动态阈值云检测算法;通过遥感目视解译的方法对云检测结果进行精度验证,并与通用动态阈值云检测算法、可见光红外成像辐射仪云掩膜产品的结果进行对比。结果表明:所提算法能以较高的精度识别不同地表上空的云层,平均总体精度为93.23%,平均Kappa系数为0.821,对薄、碎云的整体识别精度得到了明显提高,错分和漏分误差明显减小;所提算法的云检测结果整体优于通用动态阈值云检测算法和可见光红外成像辐射仪云掩膜产品的云检测结果。
Herein,we propose an improved dynamic threshold cloud detection algorithm(I-DTCDA)for visible infrared imaging radiometers(VIIRS)based on the multi-channel,wide coverage,and short revisit period features of a VIIRS.In addition,the algorithm is also based on the characteristics of the cloud distributions and variations in the visible and thermal infrared channels.We validated the accuracy of the cloud detection results using the remote sensing visual interpretation method.We compared our results with those using the universal dynamic threshold cloud detection algorithm(UDTCDA)and the VIIRS cloud mask(VCM)products.The results show that the proposed algorithm has average overall accuracy of 93%(Kappa=0.821)over different surface features.In particular,for the thin and broken clouds,the overall accuracy is significantly improved and the commission and omission errors are obviously reduced.The cloud detection results using the proposed algorithm are superior to those using UDTCDA and VCM.
Herein,we propose an improved dynamic threshold cloud detection algorithm(I-DTCDA)for visible infrared imaging radiometers(VIIRS)based on the multi-channel,wide coverage,and short revisit period features of a VIIRS.In addition,the algorithm is also based on the characteristics of the cloud distributions and variations in the visible and thermal infrared channels.We validated the accuracy of the cloud detection results using the remote sensing visual interpretation method.We compared our results with those using the universal dynamic threshold cloud detection algorithm(UDTCDA)and the VIIRS cloud mask(VCM)products.The results show that the proposed algorithm has average overall accuracy of 93%(Kappa=0.821)over different surface features.In particular,for the thin and broken clouds,the overall accuracy is significantly improved and the commission and omission errors are obviously reduced.The cloud detection results using the proposed algorithm are superior to those using UDTCDA and VCM.
引文
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[16]Piper M,Bahr T.A rapid cloud mask algorithm for suomi NPP VIIRS imagery EDRs[J].International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2015,XL-7/W3:237-242.
[17]Parmes E,Rauste Y,Molinier M,et al.Automatic cloud and shadow detection in optical satellite imagery without using thermal bands:application to suomi NPP VIIRS images over fennoscandia[J].Remote Sensing,2017,9(8):806.
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[19]Xia L,Mao K B,Sun Z W,et al.Cloud detection application on NPP VIIRS[J].China Environmental Science,2014,34(3):574-580.夏浪,毛克彪,孙知文,等.针对NPP VIIRS数据的云检测方法研究[J].中国环境科学,2014,34(3):574-580.
[20]Wei J,Sun L,Peng Y R,et al.An improved highspatial-resolution aerosol retrieval algorithm for MODIS images over land[J].Journal of Geophysical Research:Atmospheres,2018,123(21):12291-12307.
[21]National Aeronautics and Space Administration.Joint polar satellite system(JPSS)ground project[Z/OL].[2018-10-25].https://jointmission.gsfc.nasa.gov/sciencedocs/2015-06/474-00033_ATBD-VIIRS-CloudMask_E.pdf.
[22]Hutchison K D,Iisager B D,Hauss B.The use of global synthetic data for pre-launch tuning of the VIIRS cloud mask algorithm[J].International Journal of Remote Sensing,2012,33(5):1400-1423.
[23]Vermote E,Justice C,Csiszar I.Early evaluation of the VIIRS calibration,cloud mask and surface reflectance Earth data records[J].Remote Sensing of Environment,2014,148(6):134-145.
[24]Wei J,Huang B,Sun L,et al.A simple and universal aerosol retrieval algorithm for landsat series images over complex surfaces[J].Journal of Geophysical Research:Atmospheres,2017,122(24):338-355.
[25]Johnson E C.A parallel decomposition algorithm for constrained nonlinear optimization[M].[S.l.]:Rensselaer Polytechnic Institute,2001.
[26]Vermote E F,Tanre D,Deuze J L,et al.Second simulation of the satellite signal in the solar spectrum,6S:an overview[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35(3):675-686.
[27]Wei W,Wu W B,Zhou Q B,et al.Analysis and calibration of spectral response difference effects on measured NDVI with separate satellite sensors[J].Remote Sensing Information,2015,30(4):91-98.卫炜,吴文斌,周清波,等.传感器光谱响应差异对NDVI的影响[J].遥感信息,2015,30(4):91-98.
[28]Salomonson V V,Appel I.Estimating fractional snow cover from MODIS using the normalized difference snow index[J].Remote Sensing of Environment,2004,89(3):351-360.
[29]Hall D K,Riggs G A.Normalized-difference snow index(NDSI)[M]//Hall D K,Riggs G A.ed.Encyclopedia of Earth sciences series.Dordrecht:Springer Netherlands,2011:779-780.
[30]Hutchison K D,Iisager B D,Mahoney R L.Enhanced snow and ice identification with the VIIRScloud mask algorithm[J].Remote Sensing Letters,2013,4(9):929-936.
[2]Liu X Y,Sun L,Yang Y K,et al.Cloud and cloud shadow detection algorithm for Gaofen 4satellite data[J].Acta Optica Sinica,2019,39(1):0128001.刘心燕,孙林,杨以坤,等.高分四号卫星数据云和云阴影检测算法[J].光学学报,2019,39(1):0128001.
[3]Wei J,Sun L,Jia C,et al.Dynamic threshold cloud detection algorithms for MODIS and Landsat 8data[C].2016IEEE International Geoscience and Remote Sensing Symposium(IGARSS),10-15July 2016,Beijing,China,2016:566-569.
[4]Zhu Z,Wang S X,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.
[5]Irish R R,Barker J L,Goward S N,et al.Characterization of the landsat-7ETM+automated cloud-cover assessment(ACCA)algorithm[J].Photogrammetric Engineering&Remote Sensing,2006,72(10):1179-1188.
[6]Zhu Z,Woodcock C E.Object-based cloud and cloud shadow detection in Landsat imagery[J].Remote Sensing of Environment,2012,118:83-94.
[7]Visa A,Valkealahti K,Simula O.Cloud detection based on texture segmentation by neural network methods[C].1991 IEEE International Joint Conference on Neural Networks,18-21 Nov.1991,Singapore,1991:1001-1006.
[8]Jedlovec G J,Haines S L,LaFontaine F J.Spatial and temporal varying thresholds for cloud detection in GOES imagery[J].IEEE Transactions on Geoscience and Remote Sensing,2008,46(6):1705-1717.
[9]Sun L,Zhou X Y,Wang R L,et al.A comparison of the cloud detection results between the UDTCDAmask and MOD35cloud products[C]//2017IEEEInternational Geoscience and Remote Sensing Symposium(IGARSS),23-28 July 2017,Fort Worth,TX,USA,2017:25-28.
[10]Wang Q,Sun L,Wei J,et al.Improvement of universal dynamic threshold cloud detection algorithm and its application in high resolution satellite[J].Acta Optica Sinica,2018,38(10):1028002.王权,孙林,韦晶,等.动态阈值云检测算法改进及在高分辨率卫星上的应用[J].光学学报,2018,38(10):1028002
[11]Li Q Y,Lu W T,Yang J,et al.Thin cloud detection of all-sky images using markov random fields[J].IEEE Geoscience and Remote Sensing Letters,2012,9(3):417-421.
[12]Wu W,Luo J C,Hu X D,et al.A thin-cloud mask method for remote sensing images based on sparse dark pixel region detection[J].Remote Sensing,2018,10(4):617.
[13]Sun L,Wei J,Wang J,et al.A universal dynamic threshold cloud detection algorithm(UDTCDA)supported by aprior surface reflectance database[J].Journal of Geophysical Research:Atmospheres,2016,121(12):7172-7196.
[14]Kopp T J,Thomas W,Heidinger A K,et al.The VIIRS Cloud Mask:progress in the first year of S-NPP toward a common cloud detection scheme[J].Journal of Geophysical Research:Atmospheres,2014,119(5):2441-2456.
[15]Hutchison K D,Roskovensky J K,Jackson J M,et al.Automated cloud detection and classification of data collected by the Visible Infrared Imager Radiometer Suite(VIIRS)[J].International Journal of Remote Sensing,2005,26(21):4681-4706.
[16]Piper M,Bahr T.A rapid cloud mask algorithm for suomi NPP VIIRS imagery EDRs[J].International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2015,XL-7/W3:237-242.
[17]Parmes E,Rauste Y,Molinier M,et al.Automatic cloud and shadow detection in optical satellite imagery without using thermal bands:application to suomi NPP VIIRS images over fennoscandia[J].Remote Sensing,2017,9(8):806.
[18]Xia L,Mao K B,Sun Z W,et al.Introduction of Suomi NPP VIIRS Data and its application in cloud detection[J].Advances in Geosciences,2013,3(5):271-276.夏浪,毛克彪,孙知文,等.Suomi NPP VIIRS数据介绍及其在云检测上的应用分析[J].地球科学前沿,2013,3(5):271-276.
[19]Xia L,Mao K B,Sun Z W,et al.Cloud detection application on NPP VIIRS[J].China Environmental Science,2014,34(3):574-580.夏浪,毛克彪,孙知文,等.针对NPP VIIRS数据的云检测方法研究[J].中国环境科学,2014,34(3):574-580.
[20]Wei J,Sun L,Peng Y R,et al.An improved highspatial-resolution aerosol retrieval algorithm for MODIS images over land[J].Journal of Geophysical Research:Atmospheres,2018,123(21):12291-12307.
[21]National Aeronautics and Space Administration.Joint polar satellite system(JPSS)ground project[Z/OL].[2018-10-25].https://jointmission.gsfc.nasa.gov/sciencedocs/2015-06/474-00033_ATBD-VIIRS-CloudMask_E.pdf.
[22]Hutchison K D,Iisager B D,Hauss B.The use of global synthetic data for pre-launch tuning of the VIIRS cloud mask algorithm[J].International Journal of Remote Sensing,2012,33(5):1400-1423.
[23]Vermote E,Justice C,Csiszar I.Early evaluation of the VIIRS calibration,cloud mask and surface reflectance Earth data records[J].Remote Sensing of Environment,2014,148(6):134-145.
[24]Wei J,Huang B,Sun L,et al.A simple and universal aerosol retrieval algorithm for landsat series images over complex surfaces[J].Journal of Geophysical Research:Atmospheres,2017,122(24):338-355.
[25]Johnson E C.A parallel decomposition algorithm for constrained nonlinear optimization[M].[S.l.]:Rensselaer Polytechnic Institute,2001.
[26]Vermote E F,Tanre D,Deuze J L,et al.Second simulation of the satellite signal in the solar spectrum,6S:an overview[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35(3):675-686.
[27]Wei W,Wu W B,Zhou Q B,et al.Analysis and calibration of spectral response difference effects on measured NDVI with separate satellite sensors[J].Remote Sensing Information,2015,30(4):91-98.卫炜,吴文斌,周清波,等.传感器光谱响应差异对NDVI的影响[J].遥感信息,2015,30(4):91-98.
[28]Salomonson V V,Appel I.Estimating fractional snow cover from MODIS using the normalized difference snow index[J].Remote Sensing of Environment,2004,89(3):351-360.
[29]Hall D K,Riggs G A.Normalized-difference snow index(NDSI)[M]//Hall D K,Riggs G A.ed.Encyclopedia of Earth sciences series.Dordrecht:Springer Netherlands,2011:779-780.
[30]Hutchison K D,Iisager B D,Mahoney R L.Enhanced snow and ice identification with the VIIRScloud mask algorithm[J].Remote Sensing Letters,2013,4(9):929-936.
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