{"title":"Radiance enhancement and shortwave upwelling radiative flux methods for efficient detection of cloud scenes","authors":"R. Siddiqui, R. Jagpal, S. Abrarov, B. Quine","doi":"10.1504/IJSPACESE.2020.109745","DOIUrl":null,"url":null,"abstract":"The description, imagery and interpretation of cloud scenes by remote sensing datasets from Earth-orbiting satellites have become a great debate for several decades. Presently, there are many models for cloud detection and its classifications have been reported. However, none of the existing models can efficiently detect the clouds within the small band of shortwave upwelling radiative wavelength flux (SWupRF) in the spectral range from 1100 to 1700 nm. Therefore, in order to detect the clouds more effectively, a method known as the radiance enhancement (RE) can be implemented (Siddiqui et al., 2015). This article proposes new approaches how with RE and SWupRF methods to distinguish cloud scenes by space orbiting Argus 1000 micro-spectrometer utilizing the GENSPECT line-by-line radiative transfer model (Quine and Drummond, 2002; Siddiqui, 2017). This RE approach can also be used within the selected wavelength band for the detection of combustion-originated aerosols due to seasonal forest fires.","PeriodicalId":41578,"journal":{"name":"International Journal of Space Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.2000,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJSPACESE.2020.109745","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Space Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSPACESE.2020.109745","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The description, imagery and interpretation of cloud scenes by remote sensing datasets from Earth-orbiting satellites have become a great debate for several decades. Presently, there are many models for cloud detection and its classifications have been reported. However, none of the existing models can efficiently detect the clouds within the small band of shortwave upwelling radiative wavelength flux (SWupRF) in the spectral range from 1100 to 1700 nm. Therefore, in order to detect the clouds more effectively, a method known as the radiance enhancement (RE) can be implemented (Siddiqui et al., 2015). This article proposes new approaches how with RE and SWupRF methods to distinguish cloud scenes by space orbiting Argus 1000 micro-spectrometer utilizing the GENSPECT line-by-line radiative transfer model (Quine and Drummond, 2002; Siddiqui, 2017). This RE approach can also be used within the selected wavelength band for the detection of combustion-originated aerosols due to seasonal forest fires.
几十年来,地球轨道卫星遥感数据集对云场景的描述、成像和解释一直是一个大争论。目前,云检测的模型和分类已经有了很多的报道。然而,现有的模式都不能有效地探测1100 ~ 1700 nm光谱范围内短波上升流辐射波长通量(SWupRF)小波段内的云。因此,为了更有效地探测云,可以实施一种称为辐射增强(RE)的方法(Siddiqui et al., 2015)。本文提出了利用GENSPECT逐行辐射传输模型(Quine and Drummond, 2002;西迪基,2017)。这种RE方法也可以在选定的波长范围内用于检测由于季节性森林火灾而产生的燃烧气溶胶。