Copernicus Sentinel Research Articles

Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project

Abstract. On board the Copernicus Sentinel-5 Precursor (S5P) platform, the TROPOspheric Monitoring Instrument (TROPOMI) is a double-channel, nadir-viewing grating spectrometer measuring solar back-scattered earthshine radiances in the ultraviolet, visible, near-infrared, and shortwave infrared with global daily coverage. In the ultraviolet range, its spectral resolution and radiometric performance are equivalent to those of its predecessor OMI, but its horizontal resolution at true nadir is improved by an order of magnitude. This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the S5P operational processor and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted. Finally, verification results based on the application of the algorithm to OMI measurements are presented, demonstrating the performances expected for TROPOMI.

Appraisal of Opportunities and Perspectives for the Systematic Condition Assessment of Heritage Sites with Copernicus Sentinel-2 High-Resolution Multispectral Imagery

Very high-resolution (VHR) optical satellite imagery (≤5 m) is nowadays an established source of information to monitor cultural and archaeological heritage that is exposed to hazards and anthropogenic threats to their conservation, whereas few publications specifically investigate the role that regularly acquired images from high-resolution (HR) satellite sensors (5–30 m) may play in this application domain. This paper aims to appraise the potential of the multispectral constellation Sentinel-2 of the European Commission Earth observation programme Copernicus to detect prominent features and changes in heritage sites, during both ordinary times and crisis. We test the 10 m spatial resolution of the 3 visible spectral bands of Sentinel-2 for substantiation of single local events—that is, wall collapses in the UNESCO World Heritage site of the Old City of Aleppo (Syria)—and for hotspot mapping of recurrent incidents—that is, the archaeological looting in the archaeological site of Apamea (Syria). By screening long Sentinel-2 time series consisting of 114 images for Aleppo and 57 images for Apamea, we demonstrate that changes of textural properties and surface reflectance can be logged accurately in time and space and can be associated to events relevant for conservation. VHR imagery from Google Earth was used for the validation and identification of trends occurring prior to the Sentinel-2 launch. We also demonstrate how to exploit the Sentinel-2 short revisiting time (5 days) and large swath (290 km) for multi-temporal tracking of spatial patterns of urban sprawl across the cultural landscape of the World Heritage Site of Cyrene (Libya), and the three coastal ancient Greek sites of Tocra, Ptolemais, and Apollonia in Cyrenaica. With the future development of tailored machine learning approaches of feature extraction and pattern detection, Sentinel-2 can become extremely useful to screen wider regions with short revisiting times and to undertake comparative condition assessment analyses of different heritage sites.

MANAGEMENT EFFECTS ON GROUND COVER CLUMPINESS: SCALING FROM FIELD TO SENTINEL-2 COVER ESTIMATES

Abstract. Significant progress has been made in the development of cover data and derived products based on remotely sensed fractional cover information and field data across Australia, and these cover data sets are now used for quantifying and monitoring grazing land condition. The availability of a dense time-series of nearly 30 years of cover data to describe the spatial and temporal patterns in landscape changes over time can help with monitoring the effectiveness of grazing land management practice change. With the advent of higher spatial resolution data, such as that provided by the Copernicus Sentinel 2 series of satellites, we can look beyond reporting purely on cover amount and more closely at the operational monitoring and reporting on spatial arrangement of cover and its links with land condition. We collected high spatial resolution cover transects at 20 cm intervals over the Wambiana grazing trials in the Burdekin catchment in Queensland, Australia. Spatial variance analysis was used to determine the cover autocorrelation at various support intervals. Coincident Sentinel-2 imagery was collected and processed over all the sites providing imagery to link with the field data. We show that the spatial arrangement and temporal dynamics of cover are important indicators of grazing land condition for both productivity and water quality outcomes. The metrics and products derived from this research will assist land managers to prioritize investment and practice change strategies for long term sustainability and improved water quality, particularly in the Great Barrier Reef catchments.

ASSESSING THE AGREEMENT BETWEEN EO-BASED SEMI-AUTOMATED LANDSLIDE MAPS WITH FUZZY MANUAL LANDSLIDE DELINEATION

Abstract. Landslide mapping benefits from the ever increasing availability of Earth Observation (EO) data resulting from programmes like the Copernicus Sentinel missions and improved infrastructure for data access. However, there arises the need for improved automated landslide information extraction processes from EO data while the dominant method is still manual delineation. Object-based image analysis (OBIA) provides the means for the fast and efficient extraction of landslide information. To prove its quality, automated results are often compared to manually delineated landslide maps. Although there is awareness of the uncertainties inherent in manual delineations, there is a lack of understanding how they affect the levels of agreement in a direct comparison of OBIA-derived landslide maps and manually derived landslide maps. In order to provide an improved reference, we present a fuzzy approach for the manual delineation of landslides on optical satellite images, thereby making the inherent uncertainties of the delineation explicit. The fuzzy manual delineation and the OBIA classification are compared by accuracy metrics accepted in the remote sensing community. We have tested this approach for high resolution (HR) satellite images of three large landslides in Austria and Italy. We were able to show that the deviation of the OBIA result from the manual delineation can mainly be attributed to the uncertainty inherent in the manual delineation process, a relevant issue for the design of validation processes for OBIA-derived landslide maps.

Radiometric validation of atmospheric correction for MERIS in the Baltic Sea based on continuous observations from ships and AERONET-OC

The Baltic Sea is a semi-enclosed sea that is optically dominated by coloured dissolved organic material (CDOM) and has relatively low sun elevation which makes accurate ocean colour remote sensing challenging in these waters. The high absorption, low scattering properties of the Baltic Sea are representative of other optically similar water bodies including the Arctic Ocean, Black Sea, coastal regions adjacent to the CDOM-rich estuaries such as the Amazon, and highly absorbing lakes where radiometric validation is essential in order to develop accurate remote sensing algorithms. Previous studies in this region mainly focused on the validation and improvement of standard Chlorophyll-a (Chl a) and attenuation coefficient (kd) ocean colour products. The primary input to derive these is the water-leaving radiance (Lw) or remote sensing reflectance (Rrs) and it is therefore fundamental to obtain the most accurate Lw or Rrs before deriving higher level products. To this end, the retrieval accuracy of Rrs from Medium Resolution Imaging Spectrometer (MERIS) imagery using six atmospheric correction processors was assessed through above-water measurements at two sites of the Aerosol Robotic Network for Ocean Colour (AERONET-OC; 363 measurements) and a shipborne autonomous platform from which the highest number of measurements were obtained (4986 measurements). The six processors tested were the CoastColour processor (CC), the Case 2 Regional processor for lakes (C2R-Lakes), the Case 2 Regional CoastColour processor (C2R-CC), the FUB/WeW water processor (FUB), the MERIS ground segment processor (MEGS) and POLYMER. All processors except for CC had small average absolute percentage differences (ψ) in the wavelength range from 490nm to 709nm (ψ<40%), while other bands had larger differences with ψ>60%. Compared to in situ values, the Rrs(709)/Rrs(665) band ratio had ψ<30% for all processors. The most accurate Rrs in the 490 to 709nm domain was obtained from POLYMER with ψ<30% and coefficients of determination (R2)>0.6. Using a score system based on all statistical tests, POLYMER scored highest, while C2R-CC, C2R-Lakes and FUB had lower scores. This study represents the largest data base of in situ Rrs, the most comprehensive analysis of AC models for highly absorbing waters and for MERIS, conducted to date. The results have implications for the new generation of Copernicus Sentinel ocean colour satellites.

The ESA's Earth Observation Open Science Program [Space Agencies

The world of Earth observation (EO) data is rapidly changing, driven by exponential advances in sensor and digital technologies. Recent decades have seen the development of extraordinary new ways of collecting, storing, manipulating, and transmitting data that are radically transforming the way we conduct and organize science. This convergence of technologies creates new challenges for EO scientists and data and software providers to fully exploit large amounts of multivariate data from diverse sources. At the same time, these technological trends also generate huge opportunities to better understand our planet and turn big data into new types of information services. This article briefly describes some of the elements of the European Space Agency's (ESA) EO Open Science program, which aims to enable the digital transformation of the EO community and make the most of the large, complex, and diverse data delivered by the new generation of EO missions, such as the Copernicus Sentinels.

Sun glitter imagery of ocean surface waves. Part 1: Directional spectrum retrieval and validation

A practical method is suggested to quantitatively retrieve directional spectra of ocean surface waves from high-resolution satellite sun glitter imagery (SSGI). The method builds on direct determination of the imaging transfer function from the large-scale smoothed shape of sun glitter. Observed brightness modulations are then converted into sea surface elevations to perform directional spectral analysis. The method is applied to the Copernicus Sentinel-2 Multi-Spectral Instrument (MSI) measurements. Owing to the specific instrumental configuration of MSI (which has a primary mission dedicated to mapping land surfaces), a physical angular difference between channel detectors on the instrument focal plane array can be used to efficiently determine the surface brightness gradients in two directions, i.e. in sensor zenith and azimuthal directions. In addition, the detector configuration of MSI means that a small temporal lag between channel acquisitions exists. This feature can be exploited to detect surface waves and infer their space-time characteristics using cross-channel correlation. We demonstrate how this can be used to remove directional ambiguity in 2D detected wave spectra, and to obtain information describing local dispersion of surface waves. Directional spectra derived from Sentinel-2 MSI SSGI are compared with in situ buoy measurements. We report an encouraging agreement between SSGI-derived wave spectra and in situ measurements. This article is protected by copyright. All rights reserved.

Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S-5P) platform will measure ultraviolet earthshine radiances at high spectral and improved spatial resolution (pixel size of 7 km × 3.5 km at nadir) compared to its predecessors OMI and GOME-2. This paper presents the sulfur dioxide (SO2) vertical column retrieval algorithm implemented in the S-5P operational processor UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) and comprehensively describes its various retrieval steps. The spectral fitting is performed using the differential optical absorption spectroscopy (DOAS) method including multiple fitting windows to cope with the large range of atmospheric SO2 columns encountered. It is followed by a slant column background correction scheme to reduce possible biases or across-track-dependent artifacts in the data. The SO2 vertical columns are obtained by applying air mass factors (AMFs) calculated for a set of representative a priori profiles and accounting for various parameters influencing the retrieval sensitivity to SO2. Finally, the algorithm includes an error analysis module which is fully described here. We also discuss verification results (as part of the algorithm development) and future validation needs of the TROPOMI SO2 algorithm.

User requirements for a satellite-based advisory platform

APOLLO, a newly funded H2020 EU project will develop an agricultural advisory platform for small farmers based on Copernicus Sentinel satellites. It will provide services for tillage scheduling, irrigation scheduling, crop growth monitoring and yield estimation. The aim of this study was to identify the farmers’ requirements of the APOLLO platform. In total 121 farmers were interviewed in Spain, Serbia and Greece. More than 90% of the farmers pointed out that smart agriculture and use of satellite data in agriculture are important. Additionally, more than 80% want to have access to historical data and a flexible subscription policy to the platform according to their needs and use. However, significant differences exist among farmers of these countries in terms of technology awareness and penetration, which should be taken into consideration for developing a successful platform.

Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) spectrometer is the single payload of the Copernicus Sentinel 5 Precursor (S5P) mission. It measures Earth radiance spectra in the shortwave infrared spectral range around 2.3 µm with a dedicated instrument module. These measurements provide carbon monoxide (CO) total column densities over land, which for clear sky conditions are highly sensitive to the tropospheric boundary layer. For cloudy atmospheres over land and ocean, the column sensitivity changes according to the light path through the atmosphere. In this study, we present the physics-based operational S5P algorithm to infer atmospheric CO columns satisfying the envisaged accuracy ( &lt; 15 %) and precision ( &lt; 10 %) both for clear sky and cloudy observations with low cloud height. Here, methane absorption in the 2.3 µm range is combined with methane abundances from a global chemical transport model to infer information on atmospheric scattering. For efficient processing, we deploy a linearized two-stream radiative transfer model as forward model and a profile scaling approach to adjust the CO abundance in the inversion. Based on generic measurement ensembles, including clear sky and cloudy observations, we estimated the CO retrieval precision to be ≤ 11 % for surface albedo ≥ 0.03 and solar zenith angle ≤ 70°. CO biases of ≤ 3 % are introduced by inaccuracies in the methane a priori knowledge. For strongly enhanced CO concentrations in the tropospheric boundary layer and for cloudy conditions, CO errors in the order of 8 % can be introduced by the retrieval of cloud parameters of our algorithm. Moreover, we estimated the effect of a distorted spectral instrument response due to the inhomogeneous illumination of the instrument entrance slit in the flight direction to be &lt; 2 % with pseudo-random characteristics when averaging over space and time. Finally, the CO data exploitation is demonstrated for a TROPOMI orbit of simulated shortwave infrared measurements. Overall, the study demonstrates that for an instrument that performs in compliance with the pre-flight specifications, the CO product will meet the required product performance well.

The evolution of Earth Observation satellites in Europe and its impact on the performance of emergency response services

The paper reviews the evolution of Earth Observation systems in Europe and Worldwide and analyses the potential impact of their performance in support of emergency response services. Earth Observation satellites play already a significant role in supporting the action of first responders in case of major disasters. The main principle is the coordinated use of satellites in order to ensure a rapid response and the timely delivery of images and geospatial information of the area affected by the event.The first part of the paper reviews the main instruments and evaluates their current performance. The International Charter “Space and Major Disasters”, signed in October 2000, was the first international initiative aimed at establishing a unified system for the acquisition of space data. The charter is a cooperation agreement between space agencies and operators of space systems. At regional level, a similar instrument exists in Asia: Sentinel-Asia. In the frame of the European programme Copernicus, the emergency management service was launched in 2009. Geo-information products derived from space imagery are delivered during all phases of the emergency management cycle, in either rush or non-rush mode, free of charge for the users. In both cases, the capacities were historically drawn from national missions, funded with public money and directly operated by the space agencies or by national operators.The paper focuses on the performance of the space infrastructure (satellites and ground segments). Several trends may have a significant impact on the current performance:–The increasing number of space systems which are privately-owned and managed by commercial operators.–The emergence in Europe of shared-ownership or community-owned systems. Copernicus Sentinel missions (Copernicus) or Eumetsat satellites are two typical examples.–The development of dual-use capacities and the sovereignty dimension of these systems.–The development of unmanned airborne vehicles (UAVs) for civil applications.–The development of social media and crowd-based initiatives for humanitarian aid and emergency response.–Possible disruptions, such as large LEO constellations or GEO infrastructures enabling persistent observation.A common feature is the increased number of information sources and the higher real time dimension.Typical scenarios for the future are described and their likelihood is discussed, including political acceptance and the international dimension. Aside from rapid technological evolutions, two main driving factors are the capacity of national and international stakeholders to agree on governance and the sustainability of the economic models.

Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems

Since the launch of the first Landsat satellite in the early 1970s, the field of space-borne optical remote sensing has made significant progress. Advances have been made in all aspects of optical remote sensing data, including improved spatial, temporal, spectral and radiometric resolutions, which have increased the uptake of these data by wider scientific communities. Flagship satellite missions such as NASA’s Terra and Aqua and ESA’s Envisat with their high temporal (&lt;3days) and spectral (15–36 bands) resolutions opened new opportunities for routine monitoring of various aspects of terrestrial ecosystems at the global scale and have provided greater understanding of critical biophysical processes in the terrestrial ecosystem. The launch of new satellite sensors such as Landsat 8 and the European Space Agency’s Copernicus Sentinel missions (e.g. Sentinel 2 with improved spatial resolution (10–60 m) and potential revisit time of five days) is set to revolutionise the availability and use of remote sensing data in global terrestrial ecosystem monitoring. Furthermore, the recent move towards use of constellations of nanosatellites (e.g. the Flock missions by Planet Labs) to collect on-demand high spatial and temporal resolution optical remote sensing data would enable uptake of these data for operational monitoring. As a result of increase in data availability, optical remote sensing data are now increasingly used to support a number of operational services (e.g. land monitoring, atmosphere monitoring and climate change studies). However, many challenges still remain in exploiting the growing volume of optical remote sensing data to monitor global terrestrial ecosystems. These challenges include ensuring the highest data quality both in terms of the sensitivity of sensors and the derived biophysical products, affordability and availability of the data and continuity of data acquisition. This review provides an overview of the developments in space-borne optical remote sensing in the past decade and discusses a selection of aspects of global terrestrial ecosystems where the data are currently used. It concludes by highlighting some of the challenges and opportunities of using optical remote sensing data in monitoring global terrestrial ecosystems.

Total column water vapour from along track scanning radiometer series using thermal infrared dual view ocean cloud free measurements: The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) algorithm

Abstract This article describes a new algorithm to retrieve the atmospheric water vapour total column (TCWV) using the Thermal InfraRed (TIR) measurements from the two TIR channels of the Along Track Scanning Radiometer (ATSR) instrument series, on board the European Space Agency's ERS-1, ERS-2 and ENVISAT satellites spanning 1991 to 2012. The use of the dual view capability of the ATSR-type instruments allows for the accurate and precise, day-time and night-time retrievals of cloud free TCWV over oceans. The retrieval scheme uses the instrument physical characteristics, in combination with advanced radiative transfer models and a sea surface spectral emissivity database. The retrievals therefore do not require algorithm tuning or adjustments to independent water vapour datasets. Inter-comparisons with the Remote Sensing Systems Special Sensor Microwave Imager (RSS SSM/I) and ECMWF ERA-Interim total water vapour column products have been carried out for a set of test cases and are discussed in detail. The initial results show that the ATSR TCWV data, aggregated at the SSMM/I or ECMWF spatial resolution, have no median bias with respect to the collocated datasets, and have an estimated precision of about 4% for the ATSR-2 and AATSR instruments and up to 15% for the ATSR-1 instrument. The TCWV precision for the 1 × 1 km 2 resolution is of the order of 12% for ATSR-2 and AATSR, while is about 30% for ATSR-1. This new physical algorithm can be readily extended to dual view radiometers similar to ATSR such as the upcoming Sea and Land Surface Temperature Radiometer (SLSTR) instrument on the European Copernicus Sentinel-3 satellite series.

Urban Surface Temperature Time Series Estimation at the Local Scale by Spatial-Spectral Unmixing of Satellite Observations

The study of urban climate requires frequent and accurate monitoring of land surface temperature (LST), at the local scale. Since currently, no space-borne sensor provides frequent thermal infrared imagery at high spatial resolution, the scientific community has focused on synergistic methods for retrieving LST that can be suitable for urban studies. Synergistic methods that combine the spatial structure of visible and near-infrared observations with the more frequent, but low-resolution surface temperature patterns derived by thermal infrared imagery provide excellent means for obtaining frequent LST estimates at the local scale in cities. In this study, a new approach based on spatial-spectral unmixing techniques was developed for improving the spatial resolution of thermal infrared observations and the subsequent LST estimation. The method was applied to an urban area in Crete, Greece, for the time period of one year. The results were evaluated against independent high-resolution LST datasets and found to be very promising, with RMSE less than 2 K in all cases. The developed approach has therefore a high potential to be operationally used in the near future, exploiting the Copernicus Sentinel (2 and 3) observations, to provide high spatio-temporal resolution LST estimates in cities.