Downscaling of METEOSAT SEVIRI 0.6 and 0.8 μm channel radiances utilizing the high-resolution visible channel

Deneke, Hartwig; Roebeling, Rob

doi:10.5194/acp-10-9761-2010

Cited by 34 publications

(50 citation statements)

References 35 publications

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“…This is an innovation in comparison to common pan-sharpening algorithms (see Strait et al, 2008 for an overview). However, statistical downscaling approaches that could most probably be used in the context of FLS detection do exist but have not proven their ability for the sharpening of thermal channels yet (Deneke and Roebeling, 2010) or cannot be used for SEVIRI data as multidimensional highresolution input is needed (Liu and Pu, 2008). The newly developed technique presented in this paper is based on a local regression approach presented by Hill et al (1999).…”

Section: H M Schulz Et Al: 1 Km Fog and Low Stratus Detectionmentioning

confidence: 99%

1 km fog and low stratus detection using pan-sharpened MSG SEVIRI data

et al. 2012

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Abstract. In this paper a new technique for the detection of fog and low stratus in 1 km resolution from MSG SEVIRI data is presented. The method relies on the pan-sharpening of 3 km narrow-band channels using the 1 km high-resolution visible (HRV) channel. As solar and thermal channels had to be sharpened for the technique, a new approach based on an existing pan-sharpening method was developed using local regressions. A fog and low stratus detection scheme originally developed for 3 km SEVIRI data was used as the basis to derive 1 km resolution fog and low stratus masks from the sharpened channels. The sharpened channels and the fog and low stratus masks based on them were evaluated visually and by various statistical measures. The sharpened channels deviate only slightly from reference images regarding their pixel values as well as spatial features. The 1 km fog and low stratus masks are therefore deemed of high quality. They contain many details, especially where fog is restricted by complex terrain in its extent, that cannot be detected in the 3 km resolution.

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Section: H M Schulz Et Al: 1 Km Fog and Low Stratus Detectionmentioning

confidence: 99%

1 km fog and low stratus detection using pan-sharpened MSG SEVIRI data

et al. 2012

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“…SEVIRI is the main instrument carried aboard the Meteosat-8 and Meteosat-9, which are positioned above the equator at longitudes of 9.6°E and 0.0°W, respectively [10]. In operational service, the SEVIRI aboard the Meteosat-9 provides very high temporal resolution and scans the complete disk of the Earth with a 15 min repeat cycle.…”

Section: Msg-sevirimentioning

confidence: 99%

“…In operational service, the SEVIRI aboard the Meteosat-9 provides very high temporal resolution and scans the complete disk of the Earth with a 15 min repeat cycle. Meteosat-8 is used as stand-by, and scans a sub region with a 5 min repeat cycle in Rapid Scan Mode [10].…”

Section: Msg-sevirimentioning

confidence: 99%

Geometric Accuracy Investigations of SEVIRI High Resolution Visible (HRV) Level 1.5 Imagery

Kocaman

2013

Remote Sensing

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GCOS (Global Climate Observing System) is a long-term program for monitoring the climate, detecting the changes, and assessing their impacts. Remote sensing techniques are being increasingly used for climate-related measurements. Imagery of the SEVIRI instrument on board of the European geostationary satellites Meteosat-8 and Meteosat-9 are often used for the estimation of essential climate variables. In a joint project between the Swiss GCOS Office and ETH Zurich, geometric accuracy and temporal stability of 1-km resolution HRV channel imagery of SEVIRI have been evaluated over Switzerland. A set of tools and algorithms has been developed for the investigations. Statistical analysis and blunder detection have been integrated in the process for robust evaluation. The relative accuracy is evaluated by tracking large numbers of feature points in consecutive HRV images taken at 15-minute intervals. For the absolute accuracy evaluation, lakes in Switzerland and surroundings are used as reference. 20 lakes digitized from Landsat orthophotos are transformed into HRV images and matched via 2D translation terms at sub-pixel level. The algorithms are tested using HRV images taken on 24 days in 2008 (2 days per month). The results show that 2D shifts that are up to 8 pixels are present both in relative and absolute terms.

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“…The input LST is given for a SEVIRI pixel that has an "irregular" shape according to the HR predictors in UTM projection. Instead of a simple geometrical resampling, the predictors were aggregated using the point spread function (PSF) of the sensor [54]. PSF was approximated by a Gaussian function in the proposed approach.…”

Section: Spatial Aggregation Of Predictors To the Seviri Gridmentioning

confidence: 99%

Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany

Bechtel¹,

2012

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Monitoring of (surface) urban heat islands (UHI) is possible through satellite remote sensing of the land surface temperature (LST). Previous UHI studies are based on medium and high spatial resolution images, which are in the best-case scenario available about four times per day. This is not adequate for monitoring diurnal UHI development. High temporal resolution LST data (a few measurements per hour) over a whole city can be acquired by instruments onboard geostationary satellites. In northern Germany, geostationary LST data are available in pixels sized 3,300 by 6,700 m. For UHI monitoring, this resolution is too coarse, it should be comparable instead to the width of a building block: usually not more than 100 m. Thus, an LST downscaling is proposed that enhances the spatial resolution by a factor of about 2,000, which is much higher than in any previous study. The case study presented here (Hamburg, Germany) yields promising results. The latter, available every 15 min in 100 m spatial resolution, showed a high explained variance (R 2 : 0.71) and a relatively low root mean square error (RMSE: 2.2 K). For lower resolutions the downscaling scheme performs even better (R 2 : 0.80, RMSE: 1.8 K for 500 m; R 2 : 0.82, RMSE: 1.6 K for 1,000 m).

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Downscaling of METEOSAT SEVIRI 0.6 and 0.8 μm channel radiances utilizing the high-resolution visible channel

Cited by 34 publications

References 35 publications

1 km fog and low stratus detection using pan-sharpened MSG SEVIRI data

1 km fog and low stratus detection using pan-sharpened MSG SEVIRI data

Geometric Accuracy Investigations of SEVIRI High Resolution Visible (HRV) Level 1.5 Imagery

Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany

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