Removal of Thin Clouds in Landsat-8 OLI Data with Independent Component Analysis

Shen, Yang; Wang, Yong; Lv, Haitao; Qian, Jiang

doi:10.3390/rs70911481

Cited by 39 publications

(19 citation statements)

References 24 publications

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“…In addition, band 9 (Cirrus), which is mainly used for cloud detection [34,42,43], was also disregarded in the classification since it generated an increased number of artefacts in areas characterised by low amount of clouds. However, rejecting the SWIR bands had a negative effect on automatic detection of the debris class-fortunately, the class was relatively infrequent, and the number of pixels which represented it was strictly controlled by decreasing the bias for the class and its threshold.…”

Section: Snow Cover Melting Characteristics Of Hornsund Glaciers Basementioning

confidence: 99%

Melting Characteristics of Snow Cover on Tidewater Glaciers in Hornsund Fjord, Svalbard

Laska

Barzycka

Luks

2017

Water

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Abstract:In recent years, the Svalbard area, especially its southern section, has been characterised by an exceptionally thin snow cover, which has a significant impact of the annual mass balance of glaciers. The objective of this study was to determine melting processes of the snow cover deposited on 11 glaciers that terminate into Hornsund Fjord during the melting period of 2014. The study included analyses of snow pits and snow cores, meteorological data collected from automatic weather stations and Polish Polar Station Hornsund, and supervised classification of six Landsat 8 images for assessing the progress of snow cover melting. The calculated Snow-Covered Area (SCA) varied from 98% at the beginning of the melting season to 43% at the end of August. The melting vertical gradient on Hansbreen was −0.34 m 100 m −1 , leading to surface melting of −1.4 cm water equivalent (w.e.) day −1 in the ablation zone (c. 200 m a.s.l. (above sea level)) and −0.7 cm w.e. day −1 in the accumulation zone (c. 400 m a.s.l.). Furthermore, the study identified several observed features such as low snow depth in the accumulation zone of the Hornsund glaciers, a large proportion of the snow layers (12-27%) produced by rain-on-snow events, and a frequent occurrence of summer thermal inversions (80% annually), indicating that the area is experiencing intensive climate changes.

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Section: Snow Cover Melting Characteristics Of Hornsund Glaciers Basementioning

confidence: 99%

Melting Characteristics of Snow Cover on Tidewater Glaciers in Hornsund Fjord, Svalbard

Laska

Barzycka

Luks

2017

Water

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“…SI-based methods mine the statistical characteristics of clouds in the spatial and spectral domains to correct the imagery. Typical methods include filtering in the frequency domain [17,20], dark channel prior (DCP)-based methods [21][22][23][24], and spectral transformation-based methods [25][26][27][28]. These methods can remove clouds without any prior knowledge and can be combined with an RTM method to achieve an accurate correction [29].…”

Section: Related Workmentioning

confidence: 99%

Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions

Feng

et al. 2019

Remote Sensing

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Urban geographical maps are important to urban planning, urban construction, land-use studies, disaster control and relief, touring and sightseeing, and so on. Satellite remote sensing images are the most important data source for urban geographical maps. However, for optical satellite remote sensing images with high spatial resolution, certain inevitable factors, including cloud, haze, and cloud shadow, severely degrade the image quality. Moreover, the geometrical and radiometric differences amongst multiple high-spatial-resolution images are difficult to eliminate. In this study, we propose a robust and efficient procedure for generating high-resolution and high-quality seamless satellite imagery for large-scale urban regions. This procedure consists of image registration, cloud detection, thin/thick cloud removal, pansharpening, and mosaicking processes. Methodologically, a spatially adaptive method considering the variation of atmospheric scattering, and a stepwise replacement method based on local moment matching are proposed for removing thin and thick clouds, respectively. The effectiveness is demonstrated by a successful case of generating a 0.91-m-resolution image of the main city zone in Nanning, Guangxi Zhuang Autonomous Region, China, using images obtained from the Chinese Beijing-2 and Gaofen-2 high-resolution satellites.

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“…A few researchers reported the use of Band 9 for the correction of thin cirrus effects in other OLI bands [11,12]. For example, Xu et al [11] described two methods from an imaging processing perspective on using Band 9 for the removal of thin cirrus effects in other OLI bands.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Xu et al [11] described two methods from an imaging processing perspective on using Band 9 for the removal of thin cirrus effects in other OLI bands. Shen et al [12] described a cloud removal technique based on independent component analysis. However, thin cirrus corrections have not been operationally made using these published cirrus correction techniques in OLI land and ocean surface reflectance data products.…”

Section: Introductionmentioning

confidence: 99%

Removal of Thin Cirrus Scattering Effects in Landsat 8 OLI Images Using the Cirrus Detecting Channel

Gao

2017

Remote Sensing

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Thin cirrus clouds frequently contaminate images acquired with either Landsat 7 ETM+ or the earlier generation of Landsat series satellite instruments. The situation has changed since the launch of the Landsat 8 Operational Land Imager (OLI) into space in 2013. OLI implemented a cirrus detecting channel (Band 9) centered within a strong atmospheric water vapor absorption band near 1.375 µm with a width of 30 nm. The specifications for this channel were the same as those specified for the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) in the early 1990s. The OLI Band 9 has been proven to be very effective in detecting and masking thin cirrus-contaminated pixels at the high spatial resolution of 30 m. However, this channel has not yet been routinely used for the correction of thin cirrus effects in other OLI band images. In this article, we describe an empirical technique for the removal of thin cirrus scattering effects in OLI visible near infrared (IR) and shortwave IR (SWIR) spectral regions. We present results from applications of the technique to three OLI data sets. We also discuss issues associated with parallax anomalies in OLI data.

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Removal of Thin Clouds in Landsat-8 OLI Data with Independent Component Analysis

Cited by 39 publications

References 24 publications

Melting Characteristics of Snow Cover on Tidewater Glaciers in Hornsund Fjord, Svalbard

Melting Characteristics of Snow Cover on Tidewater Glaciers in Hornsund Fjord, Svalbard

Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions

Removal of Thin Cirrus Scattering Effects in Landsat 8 OLI Images Using the Cirrus Detecting Channel

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