Correction of cirrus effects in Sentinel-2 type of imagery

Richter, Rudolf; Wang, Xingjuan; Bachmann, Martin; Schläpfer, Daniel

doi:10.1080/01431161.2010.520346

Cited by 40 publications

(27 citation statements)

References 8 publications

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“…Within ATCOR, additional options are the removal of thin cirrus clouds and haze [25]. Hyperspectral pushbroom imagery affected by spectral smile (e.g., EnMAP) can be corrected.…”

Section: Enmap Atmospheric Correction Over Landmentioning

confidence: 99%

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

et al. 2015

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As part of the EnMAP preparation activities this study aims at estimating the uncertainty in the EnMAP L2A ground reflectance product using the simulated scene of Barrax, Spain. This dataset is generated using the EnMAP End-to-End Simulation tool, providing a realistic scene for a well-known test area. Focus is set on the influence of the expected radiometric calibration stability and the spectral calibration stability. Using a Monte-Carlo approach for uncertainty analysis, a larger number of realisations for the radiometric and spectral calibration are generated. Next, the ATCOR atmospheric correction is conducted for the test scene for each realisation. The subsequent analysis of the generated ground reflectance products is carried out independently for the radiometric and the spectral case. Findings are that the uncertainty in the L2A product is wavelength-dependent, and, due to the coupling with the estimation of atmospheric parameters, also spatially variable over the scene. To further illustrate the impact on subsequent data analysis, the influence on two vegetation indices is briefly analysed. Results show that the radiometric and spectral stability both have a high impact on the uncertainty of the narrow-band Photochemical Reflectance Index (PRI), and also the broad-band Normalized Difference Vegetation Index (NDVI) is affected.

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“…Within ATCOR, additional options are the removal of thin cirrus clouds and haze [25]. Hyperspectral pushbroom imagery affected by spectral smile (e.g., EnMAP) can be corrected.…”

Section: Enmap Atmospheric Correction Over Landmentioning

confidence: 99%

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

et al. 2015

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“…Generally, the 1.38µm based decirrus method performs with slightly less accuracy in the atmospheric absorption regions (e.g. in the 0.94 and 1.38µm) compared to the visible and near infrared (Richter et al, 2011) and these bands are omitted. Mean values of the absolute and relative difference as well as the root mean squared error (RMSE) calculated for each band are presented in Table 1 demonstrating that only a small difference exists between both methods.…”

Section: Landsat-8 Olimentioning

confidence: 99%

“…The 1.38µm spectral channel in a multispectral instrument design gives an opportunity to estimate the thickness distribution of cirrus cloud and to restore the upwelling reflected radiance for semitransparent cirrus. The state-of-the art methods for cirrus correction employ the 1.38µm spectral channel for the restoration (B. C. Gao et al, 2002, Gao et al, 2004, Richter et al, 2011.…”

Section: Introductionmentioning

confidence: 99%

CIRRUS REMOVAL IN MULTISPECTRAL DATAWITHOUT 1.38μM SPECTRAL DATA

Makarau¹,

Richter²,

Zekoll³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Cirrus is one of the most common artifacts in the remotely sensed optical data. Contrary to the low altitude (1-3 km) cloud the cirrus cloud (8-20 km) is semitransparent and the extinction (cirrus influence) of the upward reflected solar radiance can be compensated. The widely employed and almost 'de-facto' method for cirrus compensation is based on the 1.38µm spectral channel measuring the upwelling radiance reflected by the cirrus cloud. The knowledge on the cirrus spatial distribution allows to estimate the per spectral channel cirrus attenuation and to compensate the spectral channels. A wide range of existing and expected sensors have no 1.38µm spectral channel. These sensors data can be corrected by the recently developed haze/cirrus removal method. The additive model of the estimated cirrus thickness map (CTM) is applicable for cirrus-conditioned extinction compensation. Numeric and statistic evaluation of the CTM-based cirrus removal on more than 80 Landsat-8 OLI and 30 Sentinel-2 scenes demonstrates a close agreement with the 1.38µm channel based cirrus removal.

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“…Tan et al, 2006). Furthermore, airborne and space-borne data need to be corrected for atmospheric absorption and scattering effects (Karpouzli et al, 2003;Richter, 2011), a process that again can add further uncertainty (Drolet et al, 2005;Hilker et al, 2009). All these physical limitations could be substantially reduced by including in situ long-term spectral measurements to the network of EC flux sites (Gamon et al, 2010;Hilker et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

EUROSPEC: at the interface between remote-sensing and ecosystem CO<sub>2</sub> flux measurements in Europe

Porcar‐Castell

Arthur²,

Rossini

et al. 2015

Biogeosciences

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Abstract.Resolving the spatial and temporal dynamics of gross primary productivity (GPP) of terrestrial ecosystems across different scales remains a challenge. Remote sensing is regarded as the solution to upscale point observations conducted at the ecosystem level, using the eddy covariance (EC) technique, to the landscape and global levels. In addition to traditional vegetation indices, the photochemical reflectance index (PRI) and the emission of solarinduced chlorophyll fluorescence (SIF), now measurable from space, provide a new range of opportunities to monitor the global carbon cycle using remote sensing. However, the scale mismatch between EC observations and the much coarser satellite-derived data complicate the integration of the two sources of data. The solution is to establish a network of in situ spectral measurements that can act as a bridge between EC measurements and remote-sensing data. In situ spectral measurements have already been conducted for many years at EC sites, but using variable instrumentation, setups, and measurement standards. In Europe in particular, in situ spectral measurements remain highly heterogeneous. The goal of EUROSPEC Cost Action ES0930 was to promote the development of common measuring protocols and new instruments towards establishing best practices and standardization of these measurements. In this review we describe the background and main tradeoffs of in situ spectral measurements, review the main results of EUROSPEC Cost Action, and discuss the future challenges and opportunities Published by Copernicus Publications on behalf of the European Geosciences Union. 6104A. Porcar-Castell et al.: Linking remote-sensing and flux measurements of in situ spectral measurements for improved estimation of local and global estimates of GPP over terrestrial ecosystems.

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Correction of cirrus effects in Sentinel-2 type of imagery

Cited by 40 publications

References 8 publications

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

CIRRUS REMOVAL IN MULTISPECTRAL DATAWITHOUT 1.38μM SPECTRAL DATA

EUROSPEC: at the interface between remote-sensing and ecosystem CO<sub>2</sub> flux measurements in Europe

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Correction of cirrus effects in Sentinel-2 type of imagery

Cited by 40 publications

References 8 publications

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

CIRRUS REMOVAL IN MULTISPECTRAL DATAWITHOUT 1.38μM SPECTRAL DATA

EUROSPEC: at the interface between remote-sensing and ecosystem CO&lt;sub&gt;2&lt;/sub&gt; flux measurements in Europe

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EUROSPEC: at the interface between remote-sensing and ecosystem CO<sub>2</sub> flux measurements in Europe