气候变化领域集成服务门户(CCPortal): Evaluation of atmospheric correction methods for low to high resolutions satellite remote sensing data

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DOI	10.1016/j.atmosres.2020.105308
	Evaluation of atmospheric correction methods for low to high resolutions satellite remote sensing data
	Nazeer M.; Ilori C.O.; Bilal M.; Nichol J.E.; Wu W.; Qiu Z.; Gayene B.K.
发表日期	2021
ISSN	0169-8095
卷号	249
英文摘要	The objective of atmospheric correction is to retrieve surface reflectance from the top of atmosphere (TOA) reflectance. However, estimating surface reflectance from the TOA reflectance satellite data requires knowledge about the state of the atmosphere (e.g., water vapor and ozone) and the contribution of aerosols to the atmospheric path radiance. Thus, obtaining precise measurements of these parameters, which is very difficult, is crucial for accurate estimation of surface reflectance. The SREM (Simplified and Robust Surface Reflectance Estimation Method) is a physical-based atmospheric correction method based on the Radiative transfer (RT) equations of the second simulation of the Satellite Signal in Solar Spectrum (6SV). Essentially the SREM is a simplified version of 6SV which does not require Aerosol Optical Depth (AOD), aerosol type, water vapor, and ozone. An initial study showed accuracy comparable to the Landsat operational Surface Reflectance Products (SRProd) which is generated through different RT models using AOD, water vapor, and ozone data. To further validate the SREM under varying atmospheric conditions and at different spatial resolutions, an independent Reference Surface Reflectance (SRRef) dataset was generated using the AERONET (Aerosol Robotic Network) measurements as input to the 6SV RT model. The surface reflectances estimated by SREM (SRSREM) and SRProd from Planet Scope (PS, at 3 m spatial resolution), Sentinel-2 AB (S2AB) Multi-spectral Instrument (MSI, at 10 to 60 m spatial resolution), and Landsat-8 (L8) operational Land Imager (OLI, at 30 m spatial resolution) were validated against SRRef. Results showed that SRSREM performed similar to the SRProd of PS, S2AB MSI, and L8 OLI against SRRef. An inferior performance (R of 0.35 and 0.57) of L8 OLI's SRProd in the coastal blue (SB1) and blue (SB2) bands was observed, compared to SREM. The comparison of SRSREM with SRProd reveals the robustness of SREM, without using AOD, water vapor, and ozone data, for estimation of surface reflectance for all RT models tested. For some dates, SRRef and the SRProd under-corrected and produced higher values than the TOA reflectance, even when the atmosphere was clear but this was not the case for SREM. Analysis of surface reflectance estimation in shadowed areas revealed that the SRRef and SRProd had mainly negative values in coastal blue and blue bands for L8 OLI, while no negative SR value was observed for SREM in any band. These results recommend the utilization of SREM for the provision of surface reflectance products across a range of sensors © 2020 Elsevier B.V.
英文关键词	Atmospheric correction; Landsat-8 OLI; Sentinel-2 MSI; SREM; Surface reflectance
语种	英语
scopus关键词	Aerosols; Image resolution; Ozone; Remote sensing; Satellites; Water vapor; Aerosol optical depths; Aerosol robotic networks; Atmospheric conditions; Atmospheric corrections; Atmospheric path radiance; Operational land imager; Radiative transfer equations; Satellite remote sensing data; Reflection
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/141638
作者单位	Key Laboratory of Digital Land and Resources, East China University of Technology, Nanchang, Jiangxi 330013, China; Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada; School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Department of Geography, School of Global Studies, University of Sussex, Brighton, BN19RH, United Kingdom; Department of Remote Sensing and GIS, Vidyasagar University, Midnapore, West Bengal 721102, India
推荐引用方式 GB/T 7714	Nazeer M.,Ilori C.O.,Bilal M.,et al. Evaluation of atmospheric correction methods for low to high resolutions satellite remote sensing data[J],2021,249.
APA	Nazeer M..,Ilori C.O..,Bilal M..,Nichol J.E..,Wu W..,...&Gayene B.K..(2021).Evaluation of atmospheric correction methods for low to high resolutions satellite remote sensing data.Atmospheric Research,249.
MLA	Nazeer M.,et al."Evaluation of atmospheric correction methods for low to high resolutions satellite remote sensing data".Atmospheric Research 249(2021).