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1
Scharroo, Remko, Hans Bonekamp, Christelle Ponsard, François Parisot, Axel von Engeln, Milen Tahtadjiev, Kristiaan de Vriendt, and François Montagner. "Jason continuity of services: continuing the Jason altimeter data records as Copernicus Sentinel-6." Ocean Science 12, no. 2 (April 1, 2016): 471–79. http://dx.doi.org/10.5194/os-12-471-2016.
Повний текст джерелаАнотація:
Abstract. The Sentinel-6 mission is proposed as a multi-partner programme to continue the Jason satellite altimeter data services beyond the Jason-2 and Jason-3 missions. The Sentinel-6 mission programme consists of two identical satellites flying in sequence to prolong the climate data record of sea level accumulated by the TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3 missions from 2020 to beyond 2030. The Sentinel-6 mission intends to maintain these services in a fully operational manner. A key feature is the simultaneous pulse-limited and synthetic aperture radar processing allowing direct and continuous comparisons of the sea surface height measurements based on these processing methods and providing backward compatibility. The Sentinel-6 mission will also include radio occultation user services.
2
Scharroo, R., H. Bonekamp, C. Ponsard, F. Parisot, A. von Engeln, M. Tahtadjiev, K. de Vriendt, and F. Montagner. "Jason continuity of services: continuing the Jason altimeter data records as Copernicus Sentinel-6." Ocean Science Discussions 12, no. 6 (December 3, 2015): 2931–53. http://dx.doi.org/10.5194/osd-12-2931-2015.
Повний текст джерелаАнотація:
Abstract. The Sentinel-6 mission is proposed as a multi-partner programme to continue the Jason satellite altimeter data services beyond the Jason-2 and Jason-3 missions. The Sentinel-6 mission programme consists of two identical satellites flying in sequence to prolong the climate data record of sea level accumulated by the TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3 missions from 2020 to beyond 2030. The Sentinel-6 mission intends to maintain these services in a fully operational manner. A key feature is the simultaneous pulse-limited and synthetic aperture radar processing allowing direct and continuous comparisons of the sea surface height measurements based on these processing methods and providing backward compatibility. The Sentinel-6 mission will also include Radio Occultation user services.
3
Timmermans, Renske, Arjo Segers, Lyana Curier, Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Henk Eskes, et al. "Impact of synthetic space-borne NO<sub>2</sub> observations from the Sentinel-4 and Sentinel-5P missions on tropospheric NO<sub>2</sub> analyses." Atmospheric Chemistry and Physics 19, no. 19 (October 14, 2019): 12811–33. http://dx.doi.org/10.5194/acp-19-12811-2019.
Повний текст джерелаАнотація:
Abstract. We present an Observing System Simulation Experiment (OSSE) dedicated to the evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for tropospheric nitrogen dioxide (NO2). Sentinel-4 is a geostationary (GEO) mission covering the European continent, providing observations with high temporal resolution (hourly). Sentinel-5P is a low Earth orbit (LEO) mission providing daily observations with a global coverage. The OSSE experiment has been carefully designed, with separate models for the simulation of observations and for the assimilation experiments and with conservative estimates of the total observation uncertainties. In the experiment we simulate Sentinel-4 and Sentinel-5P tropospheric NO2 columns and surface ozone concentrations at 7 by 7 km resolution over Europe for two 3-month summer and winter periods. The synthetic observations are based on a nature run (NR) from a chemistry transport model (MOCAGE) and error estimates using instrument characteristics. We assimilate the simulated observations into a chemistry transport model (LOTOS-EUROS) independent of the NR to evaluate their impact on modelled NO2 tropospheric columns and surface concentrations. The results are compared to an operational system where only ground-based ozone observations are ingested. Both instruments have an added value to analysed NO2 columns and surface values, reflected in decreased biases and improved correlations. The Sentinel-4 NO2 observations with hourly temporal resolution benefit modelled NO2 analyses throughout the entire day where the daily Sentinel-5P NO2 observations have a slightly lower impact that lasts up to 3–6 h after overpass. The evaluated benefits may be even higher in reality as the applied error estimates were shown to be higher than actual errors in the now operational Sentinel-5P NO2 products. We show that an accurate representation of the NO2 profile is crucial for the benefit of the column observations on surface values. The results support the need for having a combination of GEO and LEO missions for NO2 analyses in view of the complementary benefits of hourly temporal resolution (GEO, Sentinel-4) and global coverage (LEO, Sentinel-5P).
4
Kern, Michael, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, et al. "The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) high-priority candidate mission." Cryosphere 14, no. 7 (July 16, 2020): 2235–51. http://dx.doi.org/10.5194/tc-14-2235-2020.
Повний текст джерелаАнотація:
Abstract. The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) mission is one of six high-priority candidate missions (HPCMs) under consideration by the European Commission to enlarge the Copernicus Space Component. Together, the high-priority candidate missions fill gaps in the measurement capability of the existing Copernicus Space Component to address emerging and urgent user requirements in relation to monitoring anthropogenic CO2 emissions, polar environments, and land surfaces. The ambition is to enlarge the Copernicus Space Component with the high-priority candidate missions in the mid-2020s to provide enhanced continuity of services in synergy with the next generation of the existing Copernicus Sentinel missions. CRISTAL will carry a dual-frequency synthetic-aperture radar altimeter as its primary payload for measuring surface height and a passive microwave radiometer to support atmospheric corrections and surface-type classification. The altimeter will have interferometric capabilities at Ku-band for improved ground resolution and a second (non-interferometric) Ka-band frequency to provide information on snow layer properties. This paper outlines the user consultations that have supported expansion of the Copernicus Space Component to include the high-priority candidate missions, describes the primary and secondary objectives of the CRISTAL mission, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
5
Frery, Marie-Laure, Mathilde Siméon, Christophe Goldstein, Pierre Féménias, Franck Borde, Alexandre Houpert, and Ana Olea Garcia. "Sentinel-3 Microwave Radiometers: Instrument Description, Calibration and Geophysical Products Performances." Remote Sensing 12, no. 16 (August 12, 2020): 2590. http://dx.doi.org/10.3390/rs12162590.
Повний текст джерелаАнотація:
Copernicus Sentinel-3 Surface Topography Mission embarks a two-channel microwave radiometer combined with the altimeter in order to correct the altimeter range for the excess path delay resulting from the presence of water vapour in the troposphere. The in-flight calibration of a single instrument is the critical point to achieve the expected performances. In the context of a constellation, the inter-calibration is even more important. After a presentation of the instrument design, we present the diagnoses used for the calibration of Sentinel-3A, using vicarious calibration over specific areas and double difference methods. The inter-calibration of Sentinel-3B with Sentinel-3A is performed during the tandem phase, using the residual differences of co-located measurements. Finally performances are assessed at crossover points with two parameters, first the wet troposphere correction by comparison with Jason-3; secondly on the Sea Surface Height by difference of variance. Analysis results have shown that Sentinel-3A is well calibrated, consistent with other instruments, and that Sentinel-3B is calibrated within 0.4 K with Sentinel-3A as a reference. Performances and stability fulfill the requirements for both missions.
6
Phiri, Darius, Matamyo Simwanda, Serajis Salekin, Vincent R. Nyirenda, Yuji Murayama, and Manjula Ranagalage. "Sentinel-2 Data for Land Cover/Use Mapping: A Review." Remote Sensing 12, no. 14 (July 16, 2020): 2291. http://dx.doi.org/10.3390/rs12142291.
Повний текст джерелаАнотація:
The advancement in satellite remote sensing technology has revolutionised the approaches to monitoring the Earth’s surface. The development of the Copernicus Programme by the European Space Agency (ESA) and the European Union (EU) has contributed to the effective monitoring of the Earth’s surface by producing the Sentinel-2 multispectral products. Sentinel-2 satellites are the second constellation of the ESA Sentinel missions and carry onboard multispectral scanners. The primary objective of the Sentinel-2 mission is to provide high resolution satellite data for land cover/use monitoring, climate change and disaster monitoring, as well as complementing the other satellite missions such as Landsat. Since the launch of Sentinel-2 multispectral instruments in 2015, there have been many studies on land cover/use classification which use Sentinel-2 images. However, no review studies have been dedicated to the application of ESA Sentinel-2 land cover/use monitoring. Therefore, this review focuses on two aspects: (1) assessing the contribution of ESA Sentinel-2 to land cover/use classification, and (2) exploring the performance of Sentinel-2 data in different applications (e.g., forest, urban area and natural hazard monitoring). The present review shows that Sentinel-2 has a positive impact on land cover/use monitoring, specifically in monitoring of crop, forests, urban areas, and water resources. The contemporary high adoption and application of Sentinel-2 can be attributed to the higher spatial resolution (10 m) than other medium spatial resolution images, the high temporal resolution of 5 days and the availability of the red-edge bands with multiple applications. The ability to integrate Sentinel-2 data with other remotely sensed data, as part of data analysis, improves the overall accuracy (OA) when working with Sentinel-2 images. The free access policy drives the increasing use of Sentinel-2 data, especially in developing countries where financial resources for the acquisition of remotely sensed data are limited. The literature also shows that the use of Sentinel-2 data produces high accuracies (>80%) with machine-learning classifiers such as support vector machine (SVM) and Random forest (RF). However, other classifiers such as maximum likelihood analysis are also common. Although Sentinel-2 offers many opportunities for land cover/use classification, there are challenges which include mismatching with Landsat OLI-8 data, a lack of thermal bands, and the differences in spatial resolution among the bands of Sentinel-2. Sentinel-2 data show promise and have the potential to contribute significantly towards land cover/use monitoring.
7
Berger, Michael, and Josef Aschbacher. "Preface: The Sentinel missions—new opportunities for science." Remote Sensing of Environment 120 (May 2012): 1–2. http://dx.doi.org/10.1016/j.rse.2011.12.026.
Повний текст джерела
8
Zawadzki, L., and M. Ablain. "Accuracy of the mean sea level continuous record with future altimetric missions: Jason-3 vs. Sentinel-3a." Ocean Science 12, no. 1 (January 15, 2016): 9–18. http://dx.doi.org/10.5194/os-12-9-2016.
Повний текст джерелаАнотація:
Abstract. The current mean sea level (MSL) continuous record, essential to understanding the climate evolution, is computed with the altimetric measurements of the TOPEX/Poseidon mission, succeeded by Jason-1 and later Jason-2. The accurate continuity of the record is ensured by the conservation of the "historical" TOPEX orbit as well as by calibration phases between the successive missions which enable a rigorous computation of their relative biases. In order to extend the current MSL record, Jason-3 will be the natural successor of Jason-2: on the same orbit with a calibration phase. Shortly after Jason-3, another altimetric climate-oriented mission, Sentinel-3a, will be launched on a different orbit. In this paper, simulated altimetric sea level data are used to study the sensitivity of the MSL continuous record to the change of the "historical" orbit for the new Sentinel-3a orbit. By estimating the impact of the absence of calibration phase on the MSL continuous record trend accuracy at the global and regional scales and the impact of the orbit change on the long-term continuity of this MSL record, this study shows that linking Sentinel-3a data instead of Jason-3 to the MSL continuous record would not meet climate user requirements regarding the MSL trend accuracy.
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Zawadzki, L., and M. Ablain. "Accuracy of the mean sea level continuous record with future altimetric missions: Jason-3 vs. Sentinel-3a." Ocean Science Discussions 12, no. 4 (July 17, 2015): 1511–36. http://dx.doi.org/10.5194/osd-12-1511-2015.
Повний текст джерелаАнотація:
Abstract. The current mean sea level (MSL) continuous record, essential for the understanding of climate evolution, is computed with the altimetric measurements of the TOPEX/Poseidon mission, succeeded by Jason-1 and later Jason-2. The accurate continuity of the record is ensured by the conservation of the "historical" TOPEX orbit, but also by calibration phases between the successive missions which enable a rigorous computation of their relative biases. In order to extend the current MSL record, Jason-3 will be the natural successor of Jason-2: on the same orbit with a calibration phase. Shortly after Jason-3, another altimetric climate-oriented mission, Sentinel-3a, will be launched on a different orbit. In this paper, simulated altimetric sea level data is used to study the sensitivity of the MSL continuous record to the change of the "historical" orbit for the new Sentinel-3a orbit. By estimating the impact of the absence of calibration phase on the MSL continuous record trend accuracy at global and regional scale and the impact of the orbit change on the long-term continuity of this MSL record, this study shows that linking Sentinel-3a data instead of Jason-3 to the MSL continuous record would prevent from meeting climate users requirements regarding the MSL trend accuracy.
10
Radočaj, Dorijan, Jasmina Obhođaš, Mladen Jurišić, and Mateo Gašparović. "Global Open Data Remote Sensing Satellite Missions for Land Monitoring and Conservation: A Review." Land 9, no. 11 (October 23, 2020): 402. http://dx.doi.org/10.3390/land9110402.
Повний текст джерелаАнотація:
The application of global open data remote sensing satellite missions in land monitoring and conservation studies is in the state of rapid growth, ensuring an observation with high spatial and spectral resolution over large areas. The purpose of this study was to provide a review of the most important global open data remote sensing satellite missions, current state-of-the-art processing methods and applications in land monitoring and conservation studies. Multispectral (Landsat, Sentinel-2, and MODIS), radar (Sentinel-1), and digital elevation model missions (SRTM, ASTER) were analyzed, as the most often used global open data satellite missions, according to the number of scientific research articles published in Web of Science database. Processing methods of these missions’ data consisting of image preprocessing, spectral indices, image classification methods, and modelling of terrain topographic parameters were analyzed and demonstrated. Possibilities of their application in land cover, land suitability, vegetation monitoring, and natural disaster management were evaluated, having high potential in broad use worldwide. Availability of free and complementary satellite missions, as well as the open-source software, ensures the basis of effective and sustainable land use management, with the prerequisite of the more extensive knowledge and expertise gathering at a global scale.
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Berger, Michael, Jose Moreno, Johnny A. Johannessen, Pieternel F. Levelt, and Ramon F. Hanssen. "ESA's sentinel missions in support of Earth system science." Remote Sensing of Environment 120 (May 2012): 84–90. http://dx.doi.org/10.1016/j.rse.2011.07.023.
Повний текст джерела
12
Quesada-Ruiz, Samuel, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, et al. "Benefit of ozone observations from Sentinel-5P and future Sentinel-4 missions on tropospheric composition." Atmospheric Measurement Techniques 13, no. 1 (January 14, 2020): 131–52. http://dx.doi.org/10.5194/amt-13-131-2020.
Повний текст джерелаАнотація:
Abstract. We present an observing simulated system experiment (OSSE) dedicated to evaluate the potential added value from the Sentinel-4 and the Sentinel-5P observations on tropospheric ozone composition. For this purpose, the ozone data of Sentinel-4 (Ultraviolet Visible Near-infrared) and Sentinel-5P (TROPOspheric Monitoring Instrument) on board a geostationary (GEO) and a low-Earth-orbit (LEO) platform, respectively, have been simulated using the DISAMAR inversion package for the summer 2003. To ensure the robustness of the results, the OSSE has been configured with conservative assumptions. We simulate the reality by combining two chemistry transport models (CTMs): the LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) and the Transport Model version 5 (TM5). The assimilation system is based on a different CTM, the MOdèle de Chimie Atmosphérique à Grande Echelle (MOCAGE), combined with the 3-D variational technique. The background error covariance matrix does not evolve in time and its variance is proportional to the field values. The simulated data are formed of six eigenvectors to minimize the size of the dataset by removing the noise-dominated part of the observations. The results show that the satellite data clearly bring direct added value around 200 hPa for the whole assimilation period and for the whole European domain, while a likely indirect added value is identified but not for the whole period and domain at 500 hPa, and to a lower extent at 700 hPa. In addition, the ozone added value from Sentinel-5P (LEO) appears close to that from Sentinel-4 (GEO) in the free troposphere (200–500 hPa) in our OSSE. The outcome of our study is a result of the OSSE design and the choice within each of the components of the system.
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PISTONE, Frédéric, Yvan BAILLION, and Sandrine MATHIEU. "Les Missions Spatiales Hyperspectrales Developpées Par Thales Alenia Space." Revue Française de Photogrammétrie et de Télédétection 224, no. 1 (December 22, 2022): 9–10. http://dx.doi.org/10.52638/rfpt.2022.620.
Повний текст джерелаАнотація:
Embarqué sur la plateforme ENVISAT, le spectro-imageur MERIS développé par Thales Alenia Space a permis de mesurer, à partir de 1993 et jusqu’en 2012 les paramètres environnementaux notamment de la couleur de l’Océan au large et sur les zones côtières. Avec le programme Copernicus de l’Union Européenne s’est ouvert en 2014 une évolution vers des mesures opérationnelles grâce aux satellites Sentinel 3 dédiés aux océans et équipés d’une nouvelle génération de spectro-imageurs, OLCI, héritiers de MERIS; quatre satellites sont programmée afin d’assurer la continuité des mesures sur de longues séries temporelles. A l’horizon 2029, le programme Copernicus va se diversifier avec un satellite d’imagerie hyperspectrale confié à Thales Alenia Space, Sentinel-10 ou CHIME (Copernicus Hyperspectral Imaging Mission for the Environment). Cet ensemble de réalisations complété par le développement de sondeurs atmosphériques hyperspectraux comme IASI sur METOP et IRS sur METEOSAT, constituent une expertise technique de pointe, unique au monde.
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Tirelli, Cecilia, Simone Ceccherini, Nicola Zoppetti, Samuele Del Bianco, Marco Gai, Flavio Barbara, Ugo Cortesi, Jukka Kujanpää, Yu Huan, and Rossana Dragani. "Data Fusion Analysis of Sentinel-4 and Sentinel-5 Simulated Ozone Data." Journal of Atmospheric and Oceanic Technology 37, no. 4 (April 2020): 573–87. http://dx.doi.org/10.1175/jtech-d-19-0063.1.
Повний текст джерелаАнотація:
AbstractThe complete data fusion method, generalized to the case of fusing profiles of atmospheric variables retrieved on different vertical grids and referred to different true values, is applied to ozone profiles retrieved from simulated measurements in the ultraviolet, visible, and thermal infrared spectral ranges for the Sentinel-4 and Sentinel-5 missions of the Copernicus program. In this study, the production and characterization of combined low Earth orbit (Sentinel-5) and geostationary Earth orbit (Sentinel-4) fused ozone data is performed. Fused and standard products have been compared and a performance assessment of the generalized complete data fusion is presented. The analysis of the output products of the complete data fusion algorithm and of the standard processing using quality quantifiers demonstrates that the generalized complete data fusion algorithm provides products of better quality when compared with standard products.
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Attema, Evert, Ciro Cafforio, Michael Gottwald, Pietro Guccione, Andrea Monti Guarnieri, Fabio Rocca, and Paul Snoeij. "Flexible Dynamic Block Adaptive Quantization for Sentinel-1 SAR Missions." IEEE Geoscience and Remote Sensing Letters 7, no. 4 (October 2010): 766–70. http://dx.doi.org/10.1109/lgrs.2010.2047242.
Повний текст джерела
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Theofanous, Nikos, Irene Chrysafis, Giorgos Mallinis, Christos Domakinis, Natalia Verde, and Sofia Siahalou. "Aboveground Biomass Estimation in Short Rotation Forest Plantations in Northern Greece Using ESA’s Sentinel Medium-High Resolution Multispectral and Radar Imaging Missions." Forests 12, no. 7 (July 11, 2021): 902. http://dx.doi.org/10.3390/f12070902.
Повний текст джерелаАнотація:
Plantations of fast-growing forest species such as black locust (Robinia Pseudoacacia) can contribute to energy transformation, mitigate industrial pollution, and restore degraded, marginal land. In this study, the synergistic use of Sentinel-2 and Sentinel-1 time series data is explored for modeling aboveground biomass (AGB) in black locust short-rotation plantations in northeastern Greece. Optimal modeling dates and EO sensor data are also identified through the analysis. Random forest (RF) models were originally developed using monthly Sentinel-2 spectral indices, while, progressively, monthly Sentinel-1 bands were incorporated in the statistical analysis. The highest accuracy was observed for the models generated using Sentinel-2 August composites (R2 = 0.52). The inclusion of Sentinel-1 bands in the spectral indices’ models had a negligible effect on modeling accuracy during the leaf-on period. The correlation and comparative performance of the spectral indices in terms of pairwise correlation with AGB varied among the phenophases of the forest plantations. Overall, the field-measured AGB in the forest plantations plots presented a higher correlation with the optical Sentinel-2 images. The synergy of Sentinel-1 and Sentinel-2 data proved to be a non-efficient approach for improving forest biomass RF models throughout the year within the geographical and environmental context of our study.
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Trinh, Le Hung, and Van Phu Le. "Application of Sentinel 1 imagery data to detect and classify oil spills on the ocean." Petrovietnam Journal 2 (March 21, 2022): 32–38. http://dx.doi.org/10.47800/pvj.2022.02-05.
Повний текст джерелаАнотація:
Sentinel is the name of a series of Earth observation missions (from Sentinel 1 to Sentinel 6) developed by the Copernicus initiative and operated by the European Space Agency (ESA). Sentinel satellite image data, which includes optical and radar images, provided completely free of charge, has been widely and effectively used in Earth research. The paper presents a technical solution using Sentinel 1 satellite image in detecting and monitoring oil spill pollution at sea, testing for Mauritius sea area. The Otsu automatic thresholding method was applied to extract oil spills at sea from Sentinel 1A radar images. The processing was done on the Google Earth Engine (GEE) cloud computing platform. The results of the study contribute to improving the efficiency of the application of radar remote sensing data in early detection and classification of oil spills, supporting the response to oil spill pollution at sea.
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Mertikas, Stelios, Panagiotis Partsinevelos, Achilleas Tripolitsiotis, Costas Kokolakis, George Petrakis, and Xenophon Frantzis. "Validation of Sentinel-3 OLCI Integrated Water Vapor Products Using Regional GNSS Measurements in Crete, Greece." Remote Sensing 12, no. 16 (August 12, 2020): 2606. http://dx.doi.org/10.3390/rs12162606.
Повний текст джерелаАнотація:
Water vapor is one of the essential variables in monitoring the Earth’s climate. The Ocean and Land Color Instrument (OLCI) on-board the Copernicus Sentinel-3 missions measures the Integrated Water Vapor (IWV) column over land and ocean surfaces. Post-launch calibration and validation of satellite measurements constitutes a key process in the operational phase of Earth observation satellites. This work presents the external and independent validation of OLCI-A IWV product using the regional network of continuously operating Global Navigation Satellite System (GNSS) comprised 10 stations distributed over the island of Crete in the eastern Mediterranean. The Sentinel-3A/-3B OLCI imagery that captures in a single scene the entire area of Crete has been examined. For each OLCI image, the IWV value of cloud-free pixels containing the GNSS stations have been derived and compared against simultaneous GNSS-derived measurements. The absolute as well as the relative bias between OLCI-A and OLCI-B IWV measurements have been determined. There is a good agreement between OLCI and GNSS with a bias of −0.57 mm ± 2.90 mm for OLCI(A) and +2.42 ± 3.41 mm for OLCI(B). The results of this regional validation activity are compared against other studies and the regular validation carried out at the Sentinel-3 Mission Performance Center. This work concludes that the accuracy of the OLCI IWV products is within its design requirements. The potential synergy between Sentinel-2 and Sentinel-3 IWV products is also discussed.
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Braun, Scott A., Paul A. Newman, and Gerald M. Heymsfield. "NASA’s Hurricane and Severe Storm Sentinel (HS3) Investigation." Bulletin of the American Meteorological Society 97, no. 11 (November 1, 2016): 2085–102. http://dx.doi.org/10.1175/bams-d-15-00186.1.
Повний текст джерелаАнотація:
Abstract The National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) investigation was a multiyear field campaign designed to improve understanding of the physical processes that control hurricane formation and intensity change, specifically the relative roles of environmental and inner-core processes. Funded as part of NASA’s Earth Venture program, HS3 conducted 5-week campaigns during the hurricane seasons of 2012–14 using the NASA Global Hawk aircraft, along with a second Global Hawk in 2013 and a WB-57f aircraft in 2014. Flying from a base at Wallops Island, Virginia, the Global Hawk could be on station over storms for up to 18 h off the East Coast of the United States and up to about 6 h off the western coast of Africa. Over the 3 years, HS3 flew 21 missions over nine named storms, along with flights over two nondeveloping systems and several Saharan air layer (SAL) outbreaks. This article summarizes the HS3 experiment, the missions flown, and some preliminary findings related to the rapid intensification and outflow structure of Hurricane Edouard (2014) and the interaction of Hurricane Nadine (2012) with the SAL.
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An, Zhiyuan, Peng Chen, Fucai Tang, Xueying Yang, Rong Wang, and Zhihao Wang. "Evaluating the Performance of Seven Ongoing Satellite Altimetry Missions for Measuring Inland Water Levels of the Great Lakes." Sensors 22, no. 24 (December 12, 2022): 9718. http://dx.doi.org/10.3390/s22249718.
Повний текст джерелаАнотація:
Satellite altimetry can provide long-term water level time series for water bodies lacking hydrological stations. Few studies have evaluated the performance of HY-2C and Sentinel-6 satellites in inland water bodies, as they have operated for less than 1 and 2 years, respectively. This study evaluated the measured water level accuracy of CryoSat-2, HY-2B, HY-2C, ICESat-2, Jason-3, Sentinel-3A, and Sentinel-6 in the Great Lakes by in-situ data of 12 hydrological stations from 1 January 2021 to 1 April 2022. Jason-3 and Sentinel-6 have the lowest mean root-mean-square-error (RMSE) of measured water level, which is 0.07 m. The measured water level of Sentinel-6 satellite shows a high correlation at all passing stations, and the average value of all correlation coefficients (R) is also the highest among all satellites, reaching 0.94. The mean RMSE of ICESat-2 satellite is slightly lower than Jason-3 and Sentinel-6, which is 0.09 m. The stability of the average deviation (bias) of the ICESat-2 is the best, with the maximum bias only 0.07 m larger than the minimum bias. ICESat-2 satellite has an exceptionally high spatial resolution. It is the only satellite among the seven satellites that has retrieved water levels around twelve stations. HY-2C satellite has the highest temporal resolution, with a temporal resolution of 7.5 days at station 9075014 in Huron Lake and an average of 10 days in the Great Lakes region. The results show that the seven altimetry satellites currently in operation have their own advantages and disadvantages, Jason-3 and Sentinel-6 have the highest accuracy, ICESat-2 has higher accuracy and the highest spatial resolution, and HY-2C has the highest temporal resolution, although it is less accurate. In summary, with full consideration of accuracy and space-time resolution, the ICESat-2 satellite can be used as the benchmark to achieve the unification of multi-source data and establish water level time series.
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Loyola, Diego G., Jian Xu, Klaus-Peter Heue, and Walter Zimmer. "Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements." Atmospheric Measurement Techniques 13, no. 2 (March 2, 2020): 985–99. http://dx.doi.org/10.5194/amt-13-985-2020.
Повний текст джерелаАнотація:
Abstract. The retrieval of trace gas, cloud, and aerosol measurements from ultraviolet, visible, and near-infrared (UVN) sensors requires precise information on surface properties that are traditionally obtained from Lambertian equivalent reflectivity (LER) climatologies. The main drawbacks of using LER climatologies for new satellite missions are that (a) climatologies are typically based on previous missions with significantly lower spatial resolutions, (b) they usually do not account fully for satellite-viewing geometry dependencies characterized by bidirectional reflectance distribution function (BRDF) effects, and (c) climatologies may differ considerably from the actual surface conditions especially with snow/ice scenarios. In this paper we present a novel algorithm for the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) from UVN sensors; the algorithm is based on the full-physics inverse learning machine (FP_ILM) retrieval. Radiances are simulated using a radiative transfer model that takes into account the satellite-viewing geometry, and the inverse problem is solved using machine learning techniques to obtain the GE_LER from satellite measurements. The GE_LER retrieval is optimized not only for trace gas retrievals employing the DOAS algorithm, but also for the large amount of data from existing and future atmospheric Sentinel satellite missions. The GE_LER can either be deployed directly for the computation of air mass factors (AMFs) using the effective scene approximation or it can be used to create a global gapless geometry-dependent LER (G3_LER) daily map from the GE_LER under clear-sky conditions for the computation of AMFs using the independent pixel approximation. The GE_LER algorithm is applied to measurements of TROPOMI launched in October 2017 on board the EU/ESA Sentinel-5 Precursor (S5P) mission. The TROPOMI GE_LER/G3_LER results are compared with climatological OMI and GOME-2 LER datasets and the advantages of using GE_LER/G3_LER are demonstrated for the retrieval of total ozone from TROPOMI.
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Li, Zhenhong, Tim Wright, Andrew Hooper, Paola Crippa, Pablo Gonzalez, Richard Walters, John Elliott, Susanna Ebmeier, Emma Hatton, and Barry Parsons. "TOWARDS INSAR EVERYWHERE, ALL THE TIME, WITH SENTINEL-1." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 763–66. http://dx.doi.org/10.5194/isprs-archives-xli-b4-763-2016.
Повний текст джерелаАнотація:
Sentinel-1A was launched in April 2014, and has been collecting data routinely over more than one year. Sentinel-1B is set for launch on 22 April 2016. The Sentinel-1 constellation has several advantages over previous radar missions for InSAR applications: (1) Data are being acquired systematically for tectonic and volcanic areas, (2) Images cover a wide footprint, 250 km from near to far range in Interferometric Wide Swath (TOPS) mode, (3) Small perpendicular and temporal baselines greatly improve interferometric coherence at C-band, (4) Data are freely available to all users, (5) The mission is planned to be operational for 20 years, with 1C and 1D planned for future launches. These features enable us to map geological processes occurring in any place at anytime using InSAR. <br><br> We will review progress within COMET towards our ultimate goal of building a fully-automated processing system that provides deformation results and derived products to the wide InSAR and Geophysics communities. In addition to high-resolution-ECMWFbased atmospheric correction model, we will show results of a systematic analysis of interferometric coherence in tectonic and volcanic areas, and discuss the future goals and timeline for the COMET InSAR automated processing system.
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Li, Zhenhong, Tim Wright, Andrew Hooper, Paola Crippa, Pablo Gonzalez, Richard Walters, John Elliott, Susanna Ebmeier, Emma Hatton, and Barry Parsons. "TOWARDS INSAR EVERYWHERE, ALL THE TIME, WITH SENTINEL-1." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 763–66. http://dx.doi.org/10.5194/isprsarchives-xli-b4-763-2016.
Повний текст джерелаАнотація:
Sentinel-1A was launched in April 2014, and has been collecting data routinely over more than one year. Sentinel-1B is set for launch on 22 April 2016. The Sentinel-1 constellation has several advantages over previous radar missions for InSAR applications: (1) Data are being acquired systematically for tectonic and volcanic areas, (2) Images cover a wide footprint, 250 km from near to far range in Interferometric Wide Swath (TOPS) mode, (3) Small perpendicular and temporal baselines greatly improve interferometric coherence at C-band, (4) Data are freely available to all users, (5) The mission is planned to be operational for 20 years, with 1C and 1D planned for future launches. These features enable us to map geological processes occurring in any place at anytime using InSAR. <br><br> We will review progress within COMET towards our ultimate goal of building a fully-automated processing system that provides deformation results and derived products to the wide InSAR and Geophysics communities. In addition to high-resolution-ECMWFbased atmospheric correction model, we will show results of a systematic analysis of interferometric coherence in tectonic and volcanic areas, and discuss the future goals and timeline for the COMET InSAR automated processing system.
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Spada, Daniele, Paolo Molinari, Walter Bertoldi, Alfonso Vitti, and Guido Zolezzi. "Multi-Temporal Image Analysis for Fluvial Morphological Characterization with Application to Albanian Rivers." ISPRS International Journal of Geo-Information 7, no. 8 (August 3, 2018): 314. http://dx.doi.org/10.3390/ijgi7080314.
Повний текст джерелаАнотація:
A procedure for the characterization of the temporal evolution of river morphology is presented. Wet and active river channels are obtained from the processing of imagery datasets. Information about channel widths and active channel surface subdivision in water, vegetation and gravel coverage classes are evaluated along with channel centerline lengths and sinuosity indices. The analysis is carried out on a series of optical remotely-sensed imagery acquired by different satellite missions during the time period between 1968 and 2017. Data from the CORONA, LANDSAT and Sentinel-2 missions were considered. Besides satellite imagery, a digital elevation model and aerial ortho-photos were also used. The procedure was applied to three, highly dynamic, Albanian rivers: Shkumbin, Seman and Vjosë, showing a high potential for application in contexts with limitations in ground data availability. The results of the procedure were assessed against reference data produced by means of expert interpretation of a reference set of river reaches. The results differ from reference values by just a few percentage points (<6%). The time evolution of hydromorphological parameters is well characterized, and the results support the design of future studies aimed at the understanding of the relations between climatic and anthropogenic controls and the response of river morphological trajectories. Moreover, the high spatial and temporal resolution of the Sentinel-2 mission motivates the development of an automatic monitoring system based on a rolling application of the defined procedure.
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Donezar-Hoyos, U., A. Larrañaga Urien, A. Tamés-Noriega, C. Sánchez-Gil, L. Albizua-Huarte, R. Ciriza-Labiano, and F. Del Barrio-Arellano. "Aplicación de imágenes Sentinel-1 y Sentinel-2 en la detección y delineación de información de crisis de desastres naturales en el marco de los servicios Copernicus EMS." Revista de Teledetección, no. 50 (December 26, 2017): 49. http://dx.doi.org/10.4995/raet.2017.8896.
Повний текст джерелаАнотація:
<p>This study shows the inclusion of Sentinel-1 and Sentinel-2 images in the workflows to obtain of crisis information of different types of events and their applicability in the detection and monitoring of those events. Sentinel is an Earth Observation (EO) program that is currently being developed by the European Space Agency (ESA) in the scope of the Copernicus program operative since April 2012, formerly known as Global Monitoring for Environment and Security (GMES). This program comprises six missions, out of which three are active, Sentinel-1 that provides radar images, Sentinel-.2 providing High Resolution optical images and Sentinel-3 developed to support GMES ocean, land, atmospheric, emergency, security and cryospheric applications. The present paper describes the use of Sentinel-1 radar to detect and delineate flooded areas, and the MultiTemporal Coherence (MTC) analysis applied with pre and post-event images to delimit and monitor burnt areas and lava flows. With respect to Sentinel-2, its high spectral resolution bands allowed the delineation of burnt areas by calculating differences of vegetation and burnt indices using pre and postevent images. Results using Sentinel-1 and Sentinel-2 data were compared with results using higher spatial resolution images, both optical and radar. In all cases, the usability of Sentinel images was proven.</p>
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Prandi, Pierre, Jean-Christophe Poisson, Yannice Faugère, Amandine Guillot, and Gérald Dibarboure. "Arctic sea surface height maps from multi-altimeter combination." Earth System Science Data 13, no. 12 (November 30, 2021): 5469–82. http://dx.doi.org/10.5194/essd-13-5469-2021.
Повний текст джерелаАнотація:
Abstract. We present a new Arctic sea level anomaly dataset based on the combination of three altimeter missions using an optimal interpolation scheme. Measurements from SARAL/AltiKa, CryoSat-2 and Sentinel-3A are blended together, providing an unprecedented resolution for this type of product. Such high-resolution products are necessary to tackle some contemporaneous science questions in the basin. We use the adaptive retracker to process both open ocean and lead echoes on SARAL/AltiKa, thus removing the need to estimate a bias between open ocean and ice-covered areas. The usual processing approach, involving an empirical retracking algorithm on specular echoes, is applied on CryoSat-2 and Sentinel-3A synthetic aperture radar (SAR) mode echoes. SARAL/AltiKa also provides the baseline for the cross-calibration of CryoSat-2 and Sentinel-3A data. The final gridded fields cover all latitudes north of 50∘ N, on a 25 km EASE2 grid, with one grid every 3 d over 3 years from July 2016 to April 2019. When compared to tide gauge measurements available in the Arctic Ocean, the combined product exhibits a much better performance than mono-mission datasets with a mean correlation of 0.78 and a mean root-mean-square deviation (RMSd) of 5 cm. The effective temporal resolution of the combined product is 3 times better than a single mission analysis. This dataset can be downloaded from https://doi.org/10.24400/527896/a01-2020.001 (Prandi, 2020).
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Sánchez-Crespo, Francisco A., José Rafael Marques da Silva, Maria T. Gómez-Villarino, Eutiquio Gallego, José M. Fuentes, Ana I. García, and Francisco Ayuga. "Differential Interferometry over Sentinel-1 TopSAR Images as a Tool for Water and Tillage Soil Erosion Analysis." Agronomy 11, no. 10 (October 17, 2021): 2075. http://dx.doi.org/10.3390/agronomy11102075.
Повний текст джерелаАнотація:
Erosion is a major problem on agricultural lands in Europe. Erosion measurement tools have traditionally been focused on delocalized quantification but without mapping the real places inside the basin where the erosion took effect. In this article, we use new space missions, such as Sentinel-1, and the opportunity they offer to obtain SAR (Synthetic Aperture Radar) images with high frequency, resolution, range, and, above all, availability to enable the application of techniques, like differential interferometry, in new fields. We propose to measure ground deformation caused by water and tillage erosion in small agricultural basins using TopSAR (Terrain Observation with Progressive Scans SAR, Synthetic Aperture Radar) images acquired by the Sentinel-1 mission, after previously verifying the accuracy of these measurements through comparison with measurements from a LIDAR (Light Detection and Ranging) system. The results of this work confirm the potential of monitoring erosion in agricultural basins with differential interferometry over Sentinel-1 TopSAR images. Its capabilities have been successfully tested in different conditions related to agricultural tasks without precipitation or storm events. This technique makes it possible to study both water and tillage erosion and sedimentation processes and even to test the efficiency of anti-erosion measures in the field or to verify the results of different management practices over time.
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Jugier, Rémi, Michaël Ablain, Robin Fraudeau, Adrien Guerou, and Pierre Féménias. "On the uncertainty associated with detecting global and local mean sea level drifts on Sentinel-3A and Sentinel-3B altimetry missions." Ocean Science 18, no. 5 (September 1, 2022): 1263–74. http://dx.doi.org/10.5194/os-18-1263-2022.
Повний текст джерелаАнотація:
Abstract. An instrumental drift in the point target response (PTR) parameters has been detected on the Copernicus Sentinel-3A altimetry mission. It will affect the accuracy of sea level sensing, which could result in errors in sea level change estimates of a few tenths of a millimeter per year. In order to accurately evaluate this drift, a method for detecting global and regional mean sea level relative drifts between two altimetry missions is implemented. Associated uncertainties are also accurately calculated thanks to a detailed error budget analysis. A drift on both Sentinel-3A (S3A) and Sentinel-3B (S3B) global mean sea level (GMSL) is detected with values significantly higher than expected. For S3A, the relative GMSL drift detected is 1.0 mm yr−1 with Jason-3 and 1.3 mm yr−1 with SARAL/AltiKa. For S3B, the relative GMSL drift detected is −3.4 mm yr−1 with Jason-3 and −2.2 mm yr−1 with SARAL/AltiKa. The drift detected at global level does not show detectable regional variations above the uncertainty level of the proposed method. The investigations led by the altimeter experts can now explain the origin of this drift for S3A and S3B. The ability of the implemented method to detect a sea level drift with respect to the length of the common period is also analyzed. We find that the minimum detectable sea level drift over a 5-year period is 0.3 mm yr−1 at the global scale and 1.5 mm yr−1 at the 2400 km regional scale. However, these levels of uncertainty do not meet the sea level stability requirements for climate change studies.
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Magalhaes, Jorge M., Ian G. Lapa, Adriana M. Santos-Ferreira, José C. B. da Silva, Fanny Piras, Thomas Moreau, Samira Amraoui, et al. "Using a Tandem Flight Configuration between Sentinel-6 and Jason-3 to Compare SAR and Conventional Altimeters in Sea Surface Signatures of Internal Solitary Waves." Remote Sensing 15, no. 2 (January 8, 2023): 392. http://dx.doi.org/10.3390/rs15020392.
Повний текст джерелаАнотація:
Satellite altimetry has been providing a continuous record of ocean measurements with numerous applications across the entire range of ocean sciences. A reference orbit has been used since 1992 with TOPEX/Poseidon, which was repeated in the Jason missions, and in the newly launched Sentinel-6 Michael Freilich (in November 2020) to continually monitor the trends of sea level rise and other properties of the sea surface. These multidecadal missions have evolved alongside major technological advances, whose measurements are unified into a single data record owing to continuous intercalibration and validation efforts. However, the new Sentinel-6 provides synthetic aperture radar (SAR) processing, which improves the along-track resolution of conventional altimeters from a few kilometres (e.g., for Jason-3) to about 300 m. This means a major leap in sampling towards higher frequencies of the ocean spectrum, which inevitably means reconciling the assumption of a uniform Brown surface between the footprints of the larger kilometre-scale conventional altimetry and those of the finer-scale SAR altimetry. To explore this issue, this study uses the vantage point of the Sentinel-6/Jason-3 tandem phase to compare simultaneous sea surface signatures of large-scale Internal Solitary Waves (ISWs) between SAR and conventional altimetry. These waves can modulate the sea surface into arrayed sections of increased and decreased roughness with horizontal scales up to 10 km, which inflict sharp transitions between increased and decreased backscatter in the radar altimeters. It is found that Sentinel-6 can provide more detailed structures of ISWs in standard level-2 products, when compared with those from the conventional Jason-3 (similarly to previous results reported from the SAR altimeter from Sentinel-3). However, a new and striking feature is found when comparing the radar backscatter between Sentinel-6 and Jason-3, which are in opposite phases in the ISWs. These intriguing results are discussed in light of the intrinsically different acquisition geometries of SAR and conventional altimeters as well as possible implications thereof.
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Zhao, Qiang, Le Yu, Zhenrong Du, Dailiang Peng, Pengyu Hao, Yongguang Zhang, and Peng Gong. "An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends." Remote Sensing 14, no. 8 (April 13, 2022): 1863. http://dx.doi.org/10.3390/rs14081863.
Повний текст джерелаАнотація:
As satellite observation technology develops and the number of Earth observation (EO) satellites increases, satellite observations have become essential to developments in the understanding of the Earth and its environment. However, the current impacts to the remote sensing community of different EO satellite data and possible future trends of EO satellite data applications have not been systematically examined. In this paper, we review the impacts of and future trends in the use of EO satellite data based on an analysis of data from 15 EO satellites whose data are widely used. Articles that reference EO satellite missions included in the Web of Science core collection for 2020 were analyzed using scientometric analysis and meta-analysis. We found the following: (1) the number of publications and citations referencing EO satellites is increasing exponentially; however, the number of articles referencing AVHRR, SPOT, and TerraSAR is tending to decrease; (2) papers related to EO satellites are concentrated in a small number of journals: 43.79% of the articles that were reviewed were published in only 13 journals; and (3) remote sensing impact factor (RSIF), a new impact index, was constructed to measure the impacts of EO satellites and to predict future trends in applications of their data. Landsat, Sentinel, MODIS, Gaofen, and WorldView were found to be the most significant current EO satellite missions and MODIS data to have the widest range of applications. Over the next five years (2021–2025), it is expected that Sentinel will become the satellite mission with the greatest influence.
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Shu, Song, Hongxing Liu, Richard A. Beck, Frédéric Frappart, Johanna Korhonen, Minxuan Lan, Min Xu, Bo Yang, and Yan Huang. "Evaluation of historic and operational satellite radar altimetry missions for constructing consistent long-term lake water level records." Hydrology and Earth System Sciences 25, no. 3 (April 1, 2021): 1643–70. http://dx.doi.org/10.5194/hess-25-1643-2021.
Повний текст джерелаАнотація:
Abstract. A total of 13 satellite missions have been launched since 1985, with different types of radar altimeters on board. This study intends to make a comprehensive evaluation of historic and currently operational satellite radar altimetry missions for lake water level retrieval over the same set of lakes and to develop a strategy for constructing consistent long-term water level records for inland lakes at global scale. The lake water level estimates produced by different retracking algorithms (retrackers) of the satellite missions were compared with the gauge measurements over 12 lakes in four countries. The performance of each retracker was assessed in terms of the data missing rate, the correlation coefficient r, the bias, and the root mean square error (RMSE) between the altimetry-derived lake water level estimates and the concurrent gauge measurements. The results show that the model-free retrackers (e.g., OCOG/Ice-1/Ice) outperform the model-based retrackers for most of the missions, particularly over small lakes. Among the satellite altimetry missions, Sentinel-3 gave the best results, followed by SARAL. ENVISAT has slightly better lake water level estimates than Jason-1 and Jason-2, but its data missing rate is higher. For small lakes, ERS-1 and ERS-2 missions provided more accurate lake water level estimates than the TOPEX/Poseidon mission. In contrast, for large lakes, TOPEX/Poseidon is a better option due to its lower data missing rate and shorter repeat cycle. GeoSat and GeoSat Follow-On (GFO) both have an extremely high data missing rate of lake water level estimates. Although several contemporary radar altimetry missions provide more accurate lake level estimates than GFO, GeoSat was the sole radar altimetry mission, between 1985 and 1990, that provided the lake water level estimates. With a full consideration of the performance and the operational duration, the best strategy for constructing long-term lake water level records should be a two-step bias correction and normalization procedure. In the first step, use Jason-2 as the initial reference to estimate the systematic biases with TOPEX/Poseidon, Jason-1, and Jason-3 and then normalize them to form a consistent TOPEX/Poseidon–Jason series. Then, use the TOPEX/Poseidon–Jason series as the reference to estimate and remove systematic biases with other radar altimetry missions to construct consistent long-term lake water level series for ungauged lakes.
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Valade, Sébastien, Andreas Ley, Francesco Massimetti, Olivier D’Hondt, Marco Laiolo, Diego Coppola, David Loibl, Olaf Hellwich, and Thomas R. Walter. "Towards Global Volcano Monitoring Using Multisensor Sentinel Missions and Artificial Intelligence: The MOUNTS Monitoring System." Remote Sensing 11, no. 13 (June 27, 2019): 1528. http://dx.doi.org/10.3390/rs11131528.
Повний текст джерелаАнотація:
Most of the world’s 1500 active volcanoes are not instrumentally monitored, resulting in deadly eruptions which can occur without observation of precursory activity. The new Sentinel missions are now providing freely available imagery with unprecedented spatial and temporal resolutions, with payloads allowing for a comprehensive monitoring of volcanic hazards. We here present the volcano monitoring platform MOUNTS (Monitoring Unrest from Space), which aims for global monitoring, using multisensor satellite-based imagery (Sentinel-1 Synthetic Aperture Radar SAR, Sentinel-2 Short-Wave InfraRed SWIR, Sentinel-5P TROPOMI), ground-based seismic data (GEOFON and USGS global earthquake catalogues), and artificial intelligence (AI) to assist monitoring tasks. It provides near-real-time access to surface deformation, heat anomalies, SO2 gas emissions, and local seismicity at a number of volcanoes around the globe, providing support to both scientific and operational communities for volcanic risk assessment. Results are visualized on an open-access website where both geocoded images and time series of relevant parameters are provided, allowing for a comprehensive understanding of the temporal evolution of volcanic activity and eruptive products. We further demonstrate that AI can play a key role in such monitoring frameworks. Here we design and train a Convolutional Neural Network (CNN) on synthetically generated interferograms, to operationally detect strong deformation (e.g., related to dyke intrusions), in the real interferograms produced by MOUNTS. The utility of this interdisciplinary approach is illustrated through a number of recent eruptions (Erta Ale 2017, Fuego 2018, Kilauea 2018, Anak Krakatau 2018, Ambrym 2018, and Piton de la Fournaise 2018–2019). We show how exploiting multiple sensors allows for assessment of a variety of volcanic processes in various climatic settings, ranging from subsurface magma intrusion, to surface eruptive deposit emplacement, pre/syn-eruptive morphological changes, and gas propagation into the atmosphere. The data processed by MOUNTS is providing insights into eruptive precursors and eruptive dynamics of these volcanoes, and is sharpening our understanding of how the integration of multiparametric datasets can help better monitor volcanic hazards.
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Quartly, Graham D., Ge Chen, Francesco Nencioli, Rosemary Morrow, and Nicolas Picot. "An Overview of Requirements, Procedures and Current Advances in the Calibration/Validation of Radar Altimeters." Remote Sensing 13, no. 1 (January 1, 2021): 125. http://dx.doi.org/10.3390/rs13010125.
Повний текст джерелаАнотація:
Analysis of the radar echoes from a spaceborne altimeter gives information on sea surface height, wave height and wind speed, as well as other parameters over land and ice. The first spaceborne radar altimeter was pioneered on Skylab in 1974. Since then, there have been about 20 further missions, with several advances in the sophistication of hardware and complexity of processing with the aim of increased accuracy and precision. Because of that, the importance of regular and precise calibration and validation (“cal/val”) remains undiminished, especially with efforts to merge altimetric records from multiple missions spanning different domains and time periods. This special issue brings together 19 papers, with a focus on the recent missions (Jason-2, Jason-3, Sentinel-3A and HY-2B) as well as detailing the issues for anticipated future missions such as SWOT. This editorial provides a brief guide to the approaches and issues for cal/val of the various different derived parameters, including a synopsis of the papers in this special issue.
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Chan, Ka Lok, Pieter Valks, Sander Slijkhuis, Claas Köhler, and Diego Loyola. "Total column water vapor retrieval for Global Ozone Monitoring Experience-2 (GOME-2) visible blue observations." Atmospheric Measurement Techniques 13, no. 8 (August 7, 2020): 4169–93. http://dx.doi.org/10.5194/amt-13-4169-2020.
Повний текст джерелаАнотація:
Abstract. We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Metop satellites. The blue band algorithm allows the retrieval of water vapor from sensors which do not cover longer wavelengths, such as the Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel-5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical columns using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from the chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME-2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing it to the operational product retrieved in the red spectral band, sun photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.
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Cavallo, Carmela, Maria Nicolina Papa, Massimiliano Gargiulo, Guillermo Palau-Salvador, Paolo Vezza, and Giuseppe Ruello. "Continuous Monitoring of the Flooding Dynamics in the Albufera Wetland (Spain) by Landsat-8 and Sentinel-2 Datasets." Remote Sensing 13, no. 17 (September 5, 2021): 3525. http://dx.doi.org/10.3390/rs13173525.
Повний текст джерелаАнотація:
Satellite data are very useful for the continuous monitoring of ever-changing environments, such as wetlands. In this study, we investigated the use of multispectral imagery to monitor the winter evolution of land cover in the Albufera wetland (Spain), using Landsat-8 and Sentinel-2 datasets. With multispectral data, the frequency of observation is limited by the possible presence of clouds. To overcome this problem, the data acquired by the two missions, Landsat-8 and Sentinel-2, were jointly used, thus roughly halving the revisit time. The varied types of land cover were grouped into four classes: (1) open water, (2) mosaic of water, mud and vegetation, (3) bare soil and (4) vegetated soil. The automatic classification of the four classes was obtained through a rule-based method that combined the NDWI, MNDWI and NDVI indices. Point information, provided by geo-located ground pictures, was spatially extended with the help of a very high-resolution image (GeoEye-1). In this way, surfaces with known land cover were obtained and used for the validation of the classification method. The overall accuracy was found to be 0.96 and 0.98 for Landsat-8 and Sentinel-2, respectively. The consistency evaluation between Landsat-8 and Sentinel-2 was performed in six days, in which acquisitions by both missions were available. The observed dynamics of the land cover were highly variable in space. For example, the presence of the open water condition lasted for around 60–80 days in the areas closest to the Albufera lake and progressively decreased towards the boundaries of the park. The study demonstrates the feasibility of using moderate-resolution multispectral images to monitor land cover changes in wetland environments.
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Bayramov, Emil, Giulia Tessari, and Martin Kada. "Quantifying Two-Dimensional Surface Displacements Using High-Resolution Cosmo-SkyMed, TerraSAR-X and Medium-Resolution Sentinel-1 SAR Interferometry: Case Study for the Tengiz Oilfield." Sensors 22, no. 17 (August 25, 2022): 6416. http://dx.doi.org/10.3390/s22176416.
Повний текст джерелаАнотація:
The present study was aimed at comparing vertical and horizontal surface displacements derived from the Cosmo-SkyMED, TerraSAR-X and Sentinel-1 satellite missions for the detection of oil extraction-induced subsidence in the Tengiz oilfield during 2018–2021. The vertical and horizontal surface displacements were derived using the 2D decomposition of line-of-sight measurements from three satellite missions. Since the TerraSAR-X mission was only available from an ascending track, it was successfully decomposed by combining it with the Cosmo-SkyMED descending track. Vertical displacement velocities derived from 2D Decomposition showed a good agreement in similar ground motion patterns and an average regression coefficient of 0.98. The maximum average vertical subsidence obtained from the three satellite missions was observed to be −57 mm/year. Higher variations and deviations were observed for horizontal displacement velocities in terms of similar ground motion patterns and an average regression coefficient of 0.80. Fifteen wells and three facilities were observed to be located within the subsidence range between −55.6 mm/year and −42 mm/year. The spatial analyses in the present studies allowed us to suspect that the subsidence processes occurring in the Tengiz oilfield are controlled not solely by oil production activities since it was clearly observed from the detected horizontal movements. The natural tectonic factors related to two seismic faults crossing the oilfield, and terrain characteristics forming water flow towards the detected subsidence hotspot, should also be considered as ground deformation accelerating factors. The novelty of the present research for Kazakhstan’s Tengiz oilfield is based on the cross-validation of vertical and horizontal surface displacement measurements derived from three radar satellite missions, 2D Decomposition of Cosmo-SkyMED descending and TerraSAR-X ascending line-of-sight measurements and spatial analysis of man-made and natural factors triggering subsidence processes.
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Hegyi, Alexandru, and Athos Agapiou. "Rapid Assessment of 2022 Floods around the UNESCO Site of Mohenjo-Daro in Pakistan by Using Sentinel and Planet Labs Missions." Sustainability 15, no. 3 (January 21, 2023): 2084. http://dx.doi.org/10.3390/su15032084.
Повний текст джерелаАнотація:
This communication study aims to provide evidence on how Sentinel sensors and Copernicus Programme’s contributing missions can support heritage endangered by natural hazards. The recent catastrophic floods of 2022 in Pakistan, mainly in the Indus Valley, threatened one of the most iconic sites within the country; thus, the UNESCO World Heritage Site of Mohenjo-Daro was selected here as a case study. Even if the main area of the site was not directly affected by the floods but rather by the heavy rains, its landscape suffered profound damage. This study aims to report a combined remote-sensing methodology for a rapid assessment of the flooded areas around the site. By using Sentinel-1 radar data in combination with mid-resolution Sentinel-2 data and Planet Lab images, it was possible to accurately map the affected areas near the site. This approach can be used to better understand the extent of the affected areas and build a better recovery strategy. A near-real-time satellite-based investigation and observations combining various sensors and resolutions (Sentinel 1 and 2 images, as well as Planet Lab images) can provide valuable insights for local heritage managers.
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Kittel, Cecile M. M., Karina Nielsen, Christian Tøttrup, and Peter Bauer-Gottwein. "Informing a hydrological model of the Ogooué with multi-mission remote sensing data." Hydrology and Earth System Sciences 22, no. 2 (February 27, 2018): 1453–72. http://dx.doi.org/10.5194/hess-22-1453-2018.
Повний текст джерелаАнотація:
Abstract. Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa with publicly available and free remote sensing observations. We used a rainfall–runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) and forced it using precipitation from two satellite-based rainfall estimates, FEWS-RFE (Famine Early Warning System rainfall estimate) and the Tropical Rainfall Measuring Mission (TRMM) 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined three different datasets to calibrate the model using an aggregated objective function with contributions from (1) historical in situ discharge observations from the period 1953–1984 at six locations in the basin, (2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12 locations in the basin and (3) GRACE (Gravity Recovery and Climate Experiment) total water storage change (TWSC). Additionally, we extracted CryoSat-2 observations throughout the basin using a Sentinel-1 SAR (synthetic aperture radar) imagery water mask and used the observations for validation of the model. The use of new satellite missions, including Sentinel-1 and CryoSat-2, increased the spatial characterization of river stage. Throughout the basin, we achieved good agreement between observed and simulated discharge and the river stage, with an RMSD between simulated and observed water amplitudes at virtual stations of 0.74 m for the TRMM-forced model and 0.87 m for the FEWS-RFE-forced model. The hydrological model also captures overall total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modeling with multi-mission remote sensing from 10 different satellite missions, we obtain new information on an otherwise unstudied basin. The proposed model is the best current baseline characterization of hydrological conditions in the Ogooué in light of the available observations.
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Mantovani, Matteo, Giulia Bossi, Gianluca Marcato, Luca Schenato, Giacomo Tedesco, Giacomo Titti, and Alessandro Pasuto. "New Perspectives in Landslide Displacement Detection Using Sentinel-1 Datasets." Remote Sensing 11, no. 18 (September 13, 2019): 2135. http://dx.doi.org/10.3390/rs11182135.
Повний текст джерелаАнотація:
Space-borne radar interferometry is a fundamental tool to detect and measure a variety of ground surface deformations, either human induced or originated by natural processes. Latest development of radar remote sensing imaging techniques and the increasing number of space missions, specifically designed for interferometry analyses, led to the development of new and more effective approaches, commonly referred to as Advanced DInSAR (A-DInSAR) or Time Series Radar Interferometry (TS-InSAR). Nevertheless, even if these methods were proved to be suitable for the study of a large majority of ground surface dynamic phenomena, their application to landslides detection is still problematic. One of the main limiting factors is related to the rate of displacement of the unstable slopes: landslides evolving too fast decorrelate the radar signal making the interferometric phase useless. This is the reason why A-DInSAR techniques have been successfully applied exclusively to measure very slow landslides (few centimetres per year). This study demonstrates how the C-band data collected since 2014 by the Sentinel-1 (S1) mission and properly designed interferometric approaches can pull down this restriction allowing to measure rate of displacements ten times higher than previously done, thus providing new perspectives in landslides detection. The analysis was carried out on a test site located in the Cortina d’Ampezzo valley (Eastern Italian Alps), which is affected by several earth flows characterized by different size and kinematics.
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Clerc, Sébastien, Craig Donlon, Franck Borde, Nicolas Lamquin, Samuel E. Hunt, Dave Smith, Malcolm McMillan, et al. "Benefits and Lessons Learned from the Sentinel-3 Tandem Phase." Remote Sensing 12, no. 17 (August 19, 2020): 2668. http://dx.doi.org/10.3390/rs12172668.
Повний текст джерелаАнотація:
During its commissioning phase, the Copernicus Sentinel-3B satellite has been placed in a tandem formation with Sentinel-3A for a period of 6 months. This configuration allowed a direct comparison of measurements obtained by the two satellites. The purpose of this paper was to present the range of analyses that can be performed from this dataset, highlighting methodology aspects and the main outcomes for each instrument. We examined, in turn, the benefit of the tandem in understanding instrument operational modes differences, in assessing inter-satellite differences, and in validating measurement uncertainties. The results highlighted the very good consistency of the Sentinel-3A and B instruments, ensuring the complete inter-operability of the constellation. Tandem comparisons also pave the way for further improvements through harmonization of the sensors (OLCI), correction of internal stray-light sources (SLSTR), or high-frequency processing of SRAL SARM data. This paper provided a comprehensive overview of the main results obtained, as well as insights into some of the results. Finally, we drew the main lessons learned from the Sentinel-3 tandem phase and provided recommendations for future missions.
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Scharien, RK, R. Segal, JJ Yackel, SEL Howell, and S. Nasonova. "Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1." Annals of Glaciology 59, no. 76pt2 (November 27, 2017): 148–62. http://dx.doi.org/10.1017/aog.2017.43.
Повний текст джерелаАнотація:
ABSTRACTChanging Arctic sea-ice extent and melt season duration, and increasing economic interest in the Arctic have prompted the need for enhanced marine ecosystem studies and improvements to dynamical and forecast models. Sea-ice melt pond fraction fp has been shown to be correlated with the September minimum ice extent due to its impact on ice albedo and heat uptake. Ice forecasts should benefit from knowledge of fp as melt ponds form several months in advance of ice retreat. This study goes further back by examining the potential to predict fp during winter using backscatter data from the commonly available Sentinel-1 synthetic aperture radar. An object-based image analysis links the winter and spring thermodynamic states of first-year and multiyear sea-ice types. Strong correlations between winter backscatter and spring fp, detected from high-resolution visible to near infrared imagery, are observed, and models for the retrieval of fp from Sentinel-1 data are provided (r2 ≥ 0.72). The models utilize HH polarization channel backscatter that is routinely acquired over the Arctic from the two-satellite Sentinel-1 constellation mission, as well as other past, current and future SAR missions operating in the same C-band frequency. Predicted fp is generally representative of major ice types first-year ice and multiyear ice during the stage in seasonal melt pond evolution where fp is closely related to spatial variations in ice topography.
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Malenovský, Zbyněk, Helmut Rott, Josef Cihlar, Michael E. Schaepman, Glenda García-Santos, Richard Fernandes, and Michael Berger. "Sentinels for science: Potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and land." Remote Sensing of Environment 120 (May 2012): 91–101. http://dx.doi.org/10.1016/j.rse.2011.09.026.
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Galar, M., R. Sesma, C. Ayala, L. Albizua, and C. Aranda. "LEARNING SUPER-RESOLUTION FOR SENTINEL-2 IMAGES WITH REAL GROUND TRUTH DATA FROM A REFERENCE SATELLITE." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020 (August 3, 2020): 9–16. http://dx.doi.org/10.5194/isprs-annals-v-1-2020-9-2020.
Повний текст джерелаАнотація:
Abstract. Copernicus program via its Sentinel missions is making earth observation more accessible and affordable for everybody. Sentinel-2 images provide multi-spectral information every 5 days for each location. However, the maximum spatial resolution of its bands is 10m for RGB and near-infrared bands. Increasing the spatial resolution of Sentinel-2 images without additional costs, would make any posterior analysis more accurate. Most approaches on super-resolution for Sentinel-2 have focused on obtaining 10m resolution images for those at lower resolutions (20m and 60m), taking advantage of the information provided by bands of finer resolutions (10m). Otherwise, our focus is on increasing the resolution of the 10m bands, that is, super-resolving 10m bands to 2.5m resolution, where no additional information is available. This problem is known as single-image super-resolution and deep learning-based approaches have become the state-of-the-art for this problem on standard images. Obviously, models learned for standard images do not translate well to satellite images. Hence, the problem is how to train a deep learning model for super-resolving Sentinel-2 images when no ground truth exist (Sentinel-2 images at 2.5m). We propose a methodology for learning Convolutional Neural Networks for Sentinel-2 image super-resolution making use of images from other sensors having a high similarity with Sentinel-2 in terms of spectral bands, but greater spatial resolution. Our proposal is tested with a state-of-the-art neural network showing that it can be useful for learning to increase the spatial resolution of RGB and near-infrared bands of Sentinel-2.
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Tarpanelli, Angelica, Filippo Iodice, Luca Brocca, Marco Restano, and Jérôme Benveniste. "River Flow Monitoring by Sentinel-3 OLCI and MODIS: Comparison and Combination." Remote Sensing 12, no. 23 (November 25, 2020): 3867. http://dx.doi.org/10.3390/rs12233867.
Повний текст джерелаАнотація:
The monitoring of rivers by satellite is an up-to-date subject in hydrological studies as confirmed by the interest of space agencies to finance specific missions that respond to the quantification of surface water flows. We address the problem by using multi-spectral sensors, in the near-infrared (NIR) band, correlating the reflectance ratio between a dry and a wet pixel extracted from a time series of images, the C/M ratio, with five river flow-related variables: water level, river discharge, flow area, mean flow velocity and surface width. The innovative aspect of this study is the use of the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3 satellites, compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) used in previous studies. Our results show that the C/M ratio from OLCI and MODIS is more correlated with the mean flow velocity than with other variables. To improve the number of observations, OLCI and MODIS products are combined into multi-mission time series. The integration provides good quality data at around daily resolution, appropriate for the analysis of the Po River investigated in this study. Finally, the combination of only MODIS products outperforms the other configurations with a frequency slightly lower (~1.8 days).
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Su, Zhongbo, Zoltán Vekerdy, and Yijian Zeng. "Preface: Land Surface Processes and Interactions—From HCMM to Sentinel Missions and Beyond." Remote Sensing 9, no. 8 (July 31, 2017): 788. http://dx.doi.org/10.3390/rs9080788.
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Gido, Nureldin A. A., Hadi Amin, Mohammad Bagherbandi, and Faramarz Nilfouroushan. "Satellite Monitoring of Mass Changes and Ground Subsidence in Sudan’s Oil Fields Using GRACE and Sentinel-1 Data." Remote Sensing 12, no. 11 (June 2, 2020): 1792. http://dx.doi.org/10.3390/rs12111792.
Повний текст джерелаАнотація:
Monitoring environmental hazards, owing to natural and anthropogenic causes, is an important issue, which requires proper data, models, and cross-validation of the results. The geodetic satellite missions, for example, the Gravity Recovery and Climate Experiment (GRACE) and Sentinel-1, are very useful in this respect. GRACE missions are dedicated to modeling the temporal variations of the Earth’s gravity field and mass transportation in the Earth’s surface, whereas Sentinel-1 collects synthetic aperture radar (SAR) data, which enables us to measure the ground movements accurately. Extraction of large volumes of water and oil decreases the reservoir pressure and form compaction and, consequently, land subsidence occurs, which can be analyzed by both GRACE and Sentinel-1 data. In this paper, large-scale groundwater storage (GWS) changes are studied using the GRACE monthly gravity field models together with different hydrological models over the major oil reservoirs in Sudan, that is, Heglig, Bamboo, Neem, Diffra, and Unity-area oil fields. Then, we correlate the results with the available oil wells production data for the period of 2003–2012. In addition, using the only freely available Sentinel-1 data, collected between November 2015 and April 2019, the ground surface deformation associated with this oil and water depletion is studied. Owing to the lack of terrestrial geodetic monitoring data in Sudan, the use of GRACE and Sentinel-1 satellite data is very valuable to monitor water and oil storage changes and their associated land subsidence over our region of interest. Our results show that there is a significant correlation between the GRACE-based GWS anomalies (ΔGWS) and extracted oil and water volumes. The trend of ΔGWS changes due to water and oil depletion ranged from –18.5 ± 6.3 to –6.2 ± 1.3 mm/year using the CSR GRACE monthly solutions and the best tested hydrological model in this study. Moreover, our Sentinel-1 SAR data analysis using the persistent scatterer interferometry (PSI) method shows a high rate of subsidence, that is, –24.5 ± 0.85, –23.8 ± 0.96, –14.2 ± 0.85, and –6 ± 0.88 mm/year over Heglig, Neem, Diffra, and Unity-area oil fields, respectively. The results of this study can help us to control the integrity and safety of operations and infrastructure in that region, as well as to study the groundwater/oil storage behavior.
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Du, Qingsong, Guoyu Li, Yu Zhou, Dun Chen, Mingtang Chai, Shunshun Qi, Yapeng Cao, Liyun Tang, and Hailiang Jia. "Route Plans for UAV Aerial Surveys according to Different DEMs in Complex Mountainous Surroundings: A Case Study in the Zheduoshan Mountains, China." Remote Sensing 14, no. 20 (October 18, 2022): 5215. http://dx.doi.org/10.3390/rs14205215.
Повний текст джерелаАнотація:
Accurate and error-free digital elevation model (DEM) data are a basic guarantee for the safe flight of unmanned aerial vehicles (UAVs) during surveys in the wild, especially in mountainous areas with large topographic undulations. Existing free and open-source DEM data generally cover large areas, with relatively high spatial resolutions (~90, 30, and even 12.5 m), but they do not have the advantage of timeliness and cannot accurately reflect current and up-to-date topographical information in the survey area. UAV pre-scanning missions can provide highly accurate and recent terrain data as a reference for UAV route planning and ensure security for subsequent aerial survey missions; however, they are time consuming. In addition, being limited to the electric charge of the UAV, pre-scanning increases the human, financial, and time consumption of field missions, and it is not applicable for field aerial survey missions in reality, unless otherwise specified, especially in harsh environments. In this paper, we used interferometric synthetic aperture radar (InSAR) technology to process Sentinel-1a data to obtain the DEMs of the survey area, which were used for route planning, and other free and open-source DEMs were also used for flightline plans. The digital surface models (DSMs) were obtained from the structure of the UAV pre-scan mission images, applying structure for motion (SfM) technology as the elevation reference. Comparing the errors between the InSAR-derived DEMs and the four open-source DEMs based on the reference DSM to analyze the practicability of flight route planning, the results showed that among the four DEMs, the SRTM DEM with a spatial resolution of 30 m performed best, which was considered as the first reference for UAV route plans when the survey area in complex mountainous regions is covered with a poor or inoperative network. The InSAR-derived DEMs from the Sentinel-1 images have great potential value for UAV flight planning, with a large perpendicular baseline and short temporal baseline. This work quantitatively analyzed the errors among the different DEMs and provided a discussion regarding UAV flightline plans based on external DEMs. This can not only effectively reduce the manpower, materials, and time consumption of field operations, improving the efficiency of UAV survey tasks, but it also broadens the use of InSAR technology. Furthermore, with the launch of high-resolution SAR satellites, InSAR-derived DEMs with high spatial and temporal resolutions provide an optimistic and credible strategy for UAV route planning with small errors.
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Mertikas, Stelios, Craig Donlon, Pierre Féménias, Constantin Mavrocordatos, Demitris Galanakis, Achilles Tripolitsiotis, Xenophon Frantzis, Ilias Tziavos, George Vergos, and Thierry Guinle. "Fifteen Years of Cal/Val Service to Reference Altimetry Missions: Calibration of Satellite Altimetry at the Permanent Facilities in Gavdos and Crete, Greece." Remote Sensing 10, no. 10 (September 27, 2018): 1557. http://dx.doi.org/10.3390/rs10101557.
Повний текст джерелаАнотація:
Satellite altimetry provides exceptional means for absolute and undisputable monitoring of changes in sea level and inland waters (rivers and lakes), over regional to global scales, with accuracy and with respect to the center of mass of the Earth. Altimetry system’s responses have to be continuously monitored for their quality, biases, errors, drifts, etc. with calibration. Absolute calibration of altimeters is achieved by external and independent to satellite facilities on the ground. This is the mainstay for a continuous, homogenous, and reliable monitoring of the earth and its oceans. This paper describes the development of the Permanent Facility for Altimetry Calibration in Gavdos/Crete, Greece, as of 2001 along with its infrastructure and instrumentation. Calibration results are presented for the reference missions of Jason-1, Jason-2, and Jason-3. Then, this work continues with the determination of relative calibrations with respect to reference missions for Sentinel-3A, HY-2A, and SARAL/AltiKa. Calibration results are also given for Jason-2 and Jason-3 altimeters using the transponder at the CDN1 Cal/Val site on the mountains of Crete, with simultaneous comparisons against sea-surface calibration and during their tandem mission. Finally, the paper presents procedures for estimating uncertainties for altimeter calibration to meet the Fiducial Reference Measurement standards.
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Gai, Marco, Flavio Barbara, Simone Ceccherini, Ugo Cortesi, Samuele Del Bianco, Cecilia Tirelli, Nicola Zoppetti, et al. "A Distributed Modular Data Processing Chain Applied to Simulated Satellite Ozone Observations." Remote Sensing 13, no. 2 (January 9, 2021): 210. http://dx.doi.org/10.3390/rs13020210.
Повний текст джерелаАнотація:
Remote sensing of the atmospheric composition from current and future satellites, such as the Sentinel missions of the Copernicus programme, yields an unprecedented amount of data to monitor air quality, ozone, UV radiation and other climate variables. Hence, full exploitation of the growing wealth of information delivered by spaceborne observing systems requires addressing the technological challenges for developing new strategies and tools that are capable to deal with these huge data volumes. The H2020 AURORA (Advanced Ultraviolet Radiation and Ozone Retrieval for Applications) project investigated a novel approach for synergistic use of ozone profile measurements acquired at different frequencies (ultraviolet, visible, thermal infrared) by sensors onboard Geostationary Equatorial Orbit (GEO) and Low Earth Orbit (LEO) satellites in the framework of the Copernicus Sentinel-4 and Sentinel-5 missions. This paper outlines the main features of the technological infrastructure, designed and developed to support the AURORA data processing chain as a distributed data processing and describes in detail the key components of the infrastructure and the software prototype. The latter demonstrates the technical feasibility of the automatic execution of the full processing chain with simulated data. The Data Processing Chain (DPC) presented in this work thus replicates a processing system that, starting from the operational satellite retrievals, carries out their fusion and results in the assimilation of the fused products. These consist in ozone vertical profiles from which further modules of the chain deliver tropospheric ozone and UV radiation at the Earth’s surface. The conclusions highlight the relevance of this novel approach to the synergistic use of operational satellite data and underline that the infrastructure uses general-purpose technologies and is open for applications in different contexts.
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Gai, Marco, Flavio Barbara, Simone Ceccherini, Ugo Cortesi, Samuele Del Bianco, Cecilia Tirelli, Nicola Zoppetti, et al. "A Distributed Modular Data Processing Chain Applied to Simulated Satellite Ozone Observations." Remote Sensing 13, no. 2 (January 9, 2021): 210. http://dx.doi.org/10.3390/rs13020210.
Повний текст джерелаАнотація:
Remote sensing of the atmospheric composition from current and future satellites, such as the Sentinel missions of the Copernicus programme, yields an unprecedented amount of data to monitor air quality, ozone, UV radiation and other climate variables. Hence, full exploitation of the growing wealth of information delivered by spaceborne observing systems requires addressing the technological challenges for developing new strategies and tools that are capable to deal with these huge data volumes. The H2020 AURORA (Advanced Ultraviolet Radiation and Ozone Retrieval for Applications) project investigated a novel approach for synergistic use of ozone profile measurements acquired at different frequencies (ultraviolet, visible, thermal infrared) by sensors onboard Geostationary Equatorial Orbit (GEO) and Low Earth Orbit (LEO) satellites in the framework of the Copernicus Sentinel-4 and Sentinel-5 missions. This paper outlines the main features of the technological infrastructure, designed and developed to support the AURORA data processing chain as a distributed data processing and describes in detail the key components of the infrastructure and the software prototype. The latter demonstrates the technical feasibility of the automatic execution of the full processing chain with simulated data. The Data Processing Chain (DPC) presented in this work thus replicates a processing system that, starting from the operational satellite retrievals, carries out their fusion and results in the assimilation of the fused products. These consist in ozone vertical profiles from which further modules of the chain deliver tropospheric ozone and UV radiation at the Earth’s surface. The conclusions highlight the relevance of this novel approach to the synergistic use of operational satellite data and underline that the infrastructure uses general-purpose technologies and is open for applications in different contexts.