scholarly journals Reconstruction of Cloud-free Sentinel-2 Image Time-series Using an Extended Spatiotemporal Image Fusion Approach

2020 ◽  
Vol 12 (16) ◽  
pp. 2595
Author(s):  
Fuqun Zhou ◽  
Detang Zhong ◽  
Rihana Peiman
Keyword(s):  
Time Series ◽  
Image Fusion ◽  
European Space Agency ◽  
Synthetic Image ◽  
Fusion Model ◽  
Spectral Bands ◽  
Space Agency ◽  
Image Pairs ◽  
Fusion Approach ◽  
Sentinel 2

Time-series for medium spatial resolution satellite imagery are a valuable resource for environmental assessment and monitoring at regional and local scales. Sentinel-2 satellites from the European Space Agency (ESA) feature a multispectral instrument (MSI) with 13 spectral bands and spatial resolutions from 10 m to 60 m, offering a revisit range from 5 days at the equator to a daily approach of the poles. Since their launch, the Sentinel-2 MSI image time-series from satellites have been used widely in various environmental studies. However, the values of Sentinel-2 image time-series have not been fully realized and their usage is impeded by cloud contamination on images, especially in cloudy regions. To increase cloud-free image availability and usage of the time-series, this study attempted to reconstruct a Sentinel-2 cloud-free image time-series using an extended spatiotemporal image fusion approach. First, a spatiotemporal image fusion model was applied to predict synthetic Sentinel-2 images when clear-sky images were not available. Second, the cloudy and cloud shadow pixels of the cloud contaminated images were identified based on analysis of the differences of the synthetic and observation image pairs. Third, the cloudy and cloud shadow pixels were replaced by the corresponding pixels of its synthetic image. Lastly, the pixels from the synthetic image were radiometrically calibrated to the observation image via a normalization process. With these processes, we can reconstruct a full length cloud-free Sentinel-2 MSI image time-series to maximize the values of observation information by keeping observed cloud-free pixels and calibrating the synthetized images by using the observed cloud-free pixels as references for better quality.

scholarly journals MARRYING DEEP LEARNING AND DATA FUSION FOR ACCURATE SEMANTIC LABELING OF SENTINEL-2 IMAGES

2021 ◽  
Vol V-3-2021 ◽  
pp. 101-107
Author(s):  
G. Fonteix ◽  
M. Swaine ◽  
M. Leras ◽  
Y. Tarabalka ◽  
S. Tripodi ◽  
...  
Keyword(s):  
Deep Learning ◽  
European Space Agency ◽  
External Source ◽  
Convolutional Network ◽  
Spectral Bands ◽  
Space Agency ◽  
Semantic Labeling ◽  
Multi Temporal ◽  
Correction Step ◽  
Sentinel 2

Abstract. The understanding of the Earth through global land monitoring from satellite images paves the way towards many applications including flight simulations, urban management and telecommunications. The twin satellites from the Sentinel-2 mission developed by the European Space Agency (ESA) provide 13 spectral bands with a high observation frequency worldwide. In this paper, we present a novel multi-temporal approach for land-cover classification of Sentinel-2 images whereby a time-series of images is classified using fully convolutional network U-Net models and then coupled by a developed probabilistic algorithm. The proposed pipeline further includes an automatic quality control and correction step whereby an external source can be introduced in order to validate and correct the deep learning classification. The final step consists of adjusting the combined predictions to the cloud-free mosaic built from Sentinel-2 L2A images in order for the classification to more closely match the reference mosaic image.

scholarly journals Oil Spill Index (OSI) to Sentinel-2 Satellite Data: QU in International Contribution

2021 ◽  
Author(s):  
S Rajendran ◽  
AS Fahad ◽  
FN Sadooni ◽  
HAS Al-Kuwari ◽  
P Vethamony ◽  
...  
Keyword(s):  
Oil Spill ◽  
Satellite Data ◽  
Emergency Preparedness ◽  
Oil Spills ◽  
European Space Agency ◽  
Optical Data ◽  
Spectral Absorption ◽  
Spectral Bands ◽  
Space Agency ◽  
Sentinel 2

An Oil Spill Index (OSI = (B3+B4)/B2) was developed and applied to Sentinel-2 optical satellite data of the European Space Agency (ESA) to map marine oil spills using spectral absorption characters of spectral bands of the Sentinel-2. The potential application of OSI and derived indices [i. (5+6)/7, (3+4)/2, (11+12)/8 and ii. 3/2, (3+4)/2, (6+7)/5] were demonstrated to the oil spills that occurred off Mauritius, Indian Ocean, on August 06, 2020, and Norilsk region, Russia on May 29, 2020, and the results were published in the peer-reviewed research journals. Recently (August 19, 2021), our methodology was recognized by the Sentinel-Hub (a repository of custom scripts) https://custom-scripts.sentinel-hub.com/sentinel-2/oil-spill-index/ for OSI calculation. We validated the remote sensing results with the drone images taken during the incident. Our OSI index is the first to be applied to Sentinel-2 optical data to map oil spills. We proved the potential of indices and the capability of Sentinel sensors to detect, map, monitor, and assess the oil spill, which can be used for emergency preparedness of oil spills.

scholarly journals Quantifying Horizontal and Vertical Movements in Ho Chi Minh City by Sentinel-1 Radar Interferometry

2020 ◽  
Author(s):  
Dinh Ho Tong Minh ◽  
Yen-Nhi NGO ◽  
Thu Trang Lê ◽  
Trung Chon Le ◽  
Hong Son Bui ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
European Space Agency ◽  
Ground Subsidence ◽  
Ho Chi Minh City ◽  
Vertical Movements ◽  
Space Agency ◽  
Permanent Scatterers ◽  
The City ◽  
East West

Ho Chi Minh City (HCMC), the most populous city and the economic center of Viet Nam, has faced ground subsidence in recent decades. This work aims at providing an unprecedented spatial extent coverage of the subsidence in HCMC in both horizontal and vertical components using Interferometric Synthetic Aperture Radar (InSAR) time series. For this purpose, an advanced InSAR technique PSDS (Permanent Scatterers and Distributed Scatterers) was applied to two big European Space Agency (ESA) Sentinel-1 datasets composed of 96 ascending and 202 descending images, acquired from 2014 to 2020 over HCMC area. A time series of 33 Cosmos SkyMED images was also used for comparison purpose. The combination of ascending and descending satellite passes allows the decomposition of the light of sight velocities into horizontal East-west and vertical components. By taking into account the presence of the horizontal East-west movement, our finding indicates that the precision of the decomposed vertical velocity can be improved up to 3 mm/year for Sentinel-1 data. The obtained results revealed that subsidence is most severe in areas along the Sai Gon river in the northwest-southeast axis and the southwest of the city with the maximum value up to 80 mm/year, consistent with findings in the literature. The magnitude of horizontal East-West velocities is relatively small and a large-scale westward motion can be observed in the northwest of the city at a rate of 2-5 mm/year. Together, these results reinforced the remarkable suitability of ESA's Sentinel-1 SAR for subsidence applications even for non-Europe countries such as Vietnam and Southeast Asia.

scholarly journals OLCI A/B Tandem Phase Analysis, Part 1: Level 1 Homogenisation and Harmonisation

2020 ◽  
Vol 12 (11) ◽  
pp. 1804 ◽  
Author(s):  
Nicolas Lamquin ◽  
Sébastien Clerc ◽  
Ludovic Bourg ◽  
Craig Donlon
Keyword(s):  
European Space Agency ◽  
Companion Paper ◽  
The Other ◽  
Satellite Mission ◽  
Space Agency ◽  
The Future ◽  
Level 1 ◽  
Level 2 ◽  
Very High ◽  
Sentinel 2

Copernicus is a European system for monitoring the Earth in support of European policy. It includes the Sentinel-3 satellite mission which provides reliable and up-to-date measurements of the ocean, atmosphere, cryosphere, and land. To fulfil mission requirements, two Sentinel-3 satellites are required on-orbit at the same time to meet revisit and coverage requirements in support of Copernicus Services. The inter-unit consistency is critical for the mission as more S3 platforms are planned in the future. A few weeks after its launch in April 2018, the Sentinel-3B satellite was manoeuvred into a tandem configuration with its operational twin Sentinel-3A already in orbit. Both satellites were flown only thirty seconds apart on the same orbit ground track to optimise cross-comparisons. This tandem phase lasted from early June to mid October 2018 and was followed by a short drift phase during which the Sentinel-3B satellite was progressively moved to a specific orbit phasing of 140° separation from the sentinel-3A satellite. In this paper, an output of the European Space Agency (ESA) Sentinel-3 Tandem for Climate study (S3TC), we provide a full methodology for the homogenisation and harmonisation of the two Ocean and Land Colour Instruments (OLCI) based on the tandem phase. Homogenisation adjusts for unavoidable slight spatial and spectral differences between the two sensors and provide a basis for the comparison of the radiometry. Persistent radiometric biases of 1–2% across the OLCI spectrum are found with very high confidence. Harmonisation then consists of adjusting one instrument on the other based on these findings. Validation of the approach shows that such harmonisation then procures an excellent radiometric alignment. Performed on L1 calibrated radiances, the benefits of harmonisation are fully appreciated on Level 2 products as reported in a companion paper. Whereas our methodology aligns one sensor to behave radiometrically as the other, discussions consider the choice of the reference to be used within the operational framework. Further exploitation of the measurements indeed provides evidence of the need to perform flat-fielding on both payloads, prior to any harmonisation. Such flat-fielding notably removes inter-camera differences in the harmonisation coefficients. We conclude on the extreme usefulness of performing a tandem phase for the OLCI mission continuity as well as for any optical mission to which the methodology presented in this paper applies (e.g., Sentinel-2). To maintain the climate record, it is highly recommended that the future Sentinel-3C and Sentinel-3D satellites perform tandem flights when injected into the Sentinel-3 time series.

scholarly journals Gaia Data Release 2

2018 ◽  
Vol 616 ◽  
pp. A16 ◽  
Author(s):  
A. C. Lanzafame ◽  
E. Distefano ◽  
S. Messina ◽  
I. Pagano ◽  
A. F. Lanza ◽  
...  
Keyword(s):  
Time Series ◽  
European Space Agency ◽  
Magnetic Activity ◽  
Variable Stars ◽  
Stellar Rotation ◽  
Dynamo Action ◽  
Space Agency ◽  
Data Release ◽  
Flux Modulation ◽  
Two Populations

Context. Amongst the ≈5 × 105 sources identified as variable stars in Gaia Data Release 2 (DR2), 26% are rotational modulation variable candidates of the BY Dra class. Gaia DR2 provides their multi-band (G, GBP, and GRP) photometric time series collected by the European Space Agency spacecraft Gaia during the first 22 months of operations as well as the essential parameters related to their flux modulation induced by surface inhomogeneities and rotation. Aims. We developed methods to identify the BY Dra variable candidates and to infer their variability parameters. Methods. BY Dra candidates were pre-selected from their position in the Hertzsprung–Russel diagram, built from Gaia parallaxes, G magnitudes, and (GBP − GRP) colours. Since the time evolution of the stellar active region can disrupt the coherence of the signal, segments not much longer than their expected evolution timescale were extracted from the entire photometric time series, and period search algorithms were applied to each segment. For the Gaia DR2, we selected sources with similar periods in at least two segments as candidate BY Dra variables. Results were further filtered considering the time-series phase coverage and the expected approximate light-curve shape. Results. Gaia DR2 includes rotational periods and modulation amplitudes of 147 535 BY Dra candidates. The data unveil the existence of two populations with distinctive period and amplitude distributions. The sample covers 38% of the whole sky when divided into bins (HEALPix) of ≈0.84 square degrees, and we estimate that this represents 0.7–5% of all BY Dra stars potentially detectable with Gaia. Conclusions. The preliminary data contained in Gaia DR2 illustrate the vast and unique information that the mission is going to provide on stellar rotation and magnetic activity. This information, complemented by the exquisite Gaia parallaxes, proper motions, and astrophysical parameters, is opening new and unique perspectives for our understanding of the evolution of stellar angular momentum and dynamo action.

scholarly journals ASSESSMENT OF THE GEOMETRIC QUALITY OF SENTINEL-2 DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 489-494 ◽  
Author(s):  
M. Pandžic ◽  
D. Mihajlovic ◽  
J. Pandžic ◽  
N. Pfeifer
Keyword(s):  
Visual Analysis ◽  
High Reliability ◽  
European Space Agency ◽  
Statistical Parameter ◽  
Quality Analysis ◽  
Line Segments ◽  
Total Length ◽  
Space Agency ◽  
New Perspective ◽  
Sentinel 2

High resolution (10 m and 20 m) optical imagery satellite Sentinel-2 brings a new perspective to Earth observation. Its frequent revisit time enables monitoring the Earth surface with high reliability. Since Sentinel-2 data is provided free of charge by the European Space Agency, its mass use for variety of purposes is expected. Quality evaluation of Sentinel-2 data is thus necessary. Quality analysis in this experiment is based on comparison of Sentinel-2 imagery with reference data (orthophoto). From the possible set of features to compare (point features, texture lines, objects, etc.) line segments were chosen because visual analysis suggested that scale differences matter least for these features. The experiment was thus designed to compare long line segments (e.g. airstrips, roads, etc.) in both datasets as the most representative entities. Edge detection was applied to both images and corresponding edges were manually selected. The statistical parameter which describes the geometrical relation between different images (and between datasets in general) covering the same area is calculated as the distance between corresponding curves in two datasets. The experiment was conducted for two different test sites, Austria and Serbia. From 21 lines with a total length of ca. 120 km the average offset of 6.031 m (0.60 pixel of Sentinel-2) was obtained for Austria, whereas for Serbia the average offset of 12.720 m (1.27 pixel of Sentinel-2) was obtained out of 10 lines with a total length of ca. 38 km.

scholarly journals Global maps of Forel-Ule index, hue angle and Secchi disk depth derived from twenty-one years of monthly ESA-OC-CCI data

2020 ◽  
Author(s):  
Jaime Pitarch ◽  
Marco Bellacicco ◽  
Salvatore Marullo ◽  
Hendrik J. van der Woerd
Keyword(s):  
Time Series ◽  
Spatial Resolution ◽  
European Space Agency ◽  
Sensor Data ◽  
Secchi Disk ◽  
Secchi Disk Depth ◽  
The North ◽  
Space Agency ◽  
Free Data ◽  
Hue Angle

Abstract. We document the development and public release of a new dataset (1997–2018), consisting of global maps of the Forel-Ule index, hue angle and Secchi disk depth. Source data comes from the European Space Agency (ESA) Ocean Colour (OC) Climate Change Initiative (CCI), which is providing merged multi-sensor data from the mid-resolution sensors in operation at a specific time from 1997 to the present day. Multi-sensor satellite datasets are advantageous tools for ecological studies because they increase the probabilities of cloud-free data over a given region, as data from multiple satellites whose overpass times differ by a few hours are combined. Moreover, data merging from heritage and present satellites can expand the duration of the time series indefinitely, which allows the calculation of significant trends. Additionally, data are remapped consistently and analysis-ready for scientists. Also, the products described in this article have the exclusive advantage of being linkable to in-situ historic observations and thus enabling the construction of very long time series. Monthly data are presented at a spatial resolution of ~4 km at the equator and are available at PANGAEA, https://doi.org/10.1594/PANGAEA.904266 (Pitarch et al., 2019a). Two smaller and easier to handle test datasets have been produced from the former: a global dataset at 1 degree spatial resolution and another one for the North Atlantic at 0.25 degree resolution.

scholarly journals Fires Monitoring by Means of Spectral Indices from Sentinel-2 Data: the Case Study of the Vesuvius and Lattari Mountains, Campania (Italy)

2020 ◽  
Author(s):  
Domenico Antonio Giuseppe Dell'Aglio ◽  
Carmine Gambardella ◽  
Massimiliano Gargiulo ◽  
Antonio Iodice ◽  
Rosaria Parente ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
European Space Agency ◽  
Fire Risk ◽  
Fire Detection ◽  
Spectral Indices ◽  
Active Fire ◽  
Space Agency ◽  
Repeat Time ◽  
Sentinel 2

Forest fires are part of a set of natural disasters that have always affected regions of the world typically characterized by a tropical climate with long periods of drought. However, due to climate change in recent years, other regions of our planet have also been affected by this phenomenon, never seen before. One of them is certainly the Italian peninsula, and especially the regions of southern Italy. For this reason, the scientific community, as well as remote sensing one, is highly concerned in developing reliable techniques to provide useful support to the competent authorities. In particular, three specific tasks have been carried out in this work: (i) fire risk prevention, (ii) active fire detection, and (iii) post-fire area assessment. To accomplish these analyses, the capability of a set of spectral indices, derived from spaceborne remote sensing (RS) data, is assessed to monitor the forest fires. The spectral indices are obtained from Sentinel-2 multispectral images of the European Space Agency (ESA), which are free of charge and openly accessible. Moreover, the twin Sentinel-2 sensors allow to overcome some restrictions on time delivery and observation repeat time. The performance of the proposed analyses were assessed experimentally to monitor the forest fires occurred in two specific study areas during the summer of 2017: the volcano Vesuvius, near Naples, and the Lattari mountains, near Sorrento (both in Campania, Italy).

scholarly journals IDENTIFICATION OF DROUGHT EXTENT BASED ON VCI USING SENTINEL DATA: A CASE STUDY OF THE EASTERN OF IAŞI COUNTY

2019 ◽  
Vol 13 (2) ◽  
pp. 179-186
Author(s):  
Paul Macarof ◽  
Florian Statescu ◽  
Cristian Iulian Birlica ◽  
Paul Gherasim
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
European Space Agency ◽  
Condition Index ◽  
Landsat 8 ◽  
Natural Phenomena ◽  
Space Agency ◽  
Vegetation Condition Index ◽  
Sentinel 2

In this study was analyzed zones affected by drought using Vegetation Condition Index (VCI), that is based on Normalized Difference Vegetation Index (NDVI). This fact, drought, is one of the most wide -spread and least understood natural phenomena. In this paper was used remote sensing (RS) data, kindly provided by The European Space Agency (ESA), namely Sentinel-2 (S-2) Multispectral Instrument (MSI) and wellkonwn images Landsat 8 Operational Land Imager (OLI). The RS images was processed in SNAP and ArcMap. Study Area, was considered the eastern of Iasi county. The main purpose of paper was to investigating if Sentinel images can be used for VCI analysis.

Sentinel 5 Precursor: Status of TROPOMI and the Operational Data Products

2020 ◽  
Author(s):  
Pepijn Veefkind ◽  
Ilse Aben ◽  
Angelika Dehn ◽  
Quintus Kleipool ◽  
Diego Loyola ◽  
...  
Keyword(s):  
Near Infrared ◽  
European Space Agency ◽  
Atmospheric Composition ◽  
Spectral Bands ◽  
Space Agency ◽  
Swir Band ◽  
Data Products ◽  
The Status ◽  
New Research ◽  
Operational Data

<p>The Copernicus Sentinel 5 Precursor (S5P) is the first of the Sentinel satellites dedicated to the observation of the atmospheric composition, for climate, air quality and ozone monitoring applications. The payload of S5P is TROPOMI (TROPOspheric Monitoring Instrument), a spectrometer covering spectral bands in ultraviolet, visible, near infrared and shortwave infrared, which was developed by The Netherlands in cooperation with the European Space Agency (ESA). TROPOMI has a wide swath of 2600 km, enabling daily global coverage, in combination with a high spatial resolution of about 3.5 x 5.5 km<sup>2</sup> (7 x 5.5 km<sup>2</sup> for the SWIR band).</p><p>S5P was successfully launched on 13 October 2017 and following a six-month commissioning phase, the operational data stream started at the end of April 2018. All of the TROPOMI operational data products have been released, with the exception of the ozone profile, which is planned to become available with the next major release[AR1]  of the Level 1B data. In addition to the operational data products, new research products are also being developed.</p><p>In this contribution, the status of TROPOMI and its data products will be presented. Results for observations of recent events will be provided, along with an outlook on the next release of the data products.</p><div> <div> <div> </div> </div> </div>

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