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Journal articles on the topic 'OLCI'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Kumar, Abhishek, Deepak R. Mishra, and Nirav Ilango. "Landsat 8 Virtual Orange Band for Mapping Cyanobacterial Blooms." Remote Sensing 12, no. 5 (2020): 868. http://dx.doi.org/10.3390/rs12050868.

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The Landsat 8 Operational Land Imager (OLI) has a panchromatic band (503–676 nm) that can be used to derive a novel virtual orange band (590–635 nm) by using the multispectral green band and red band components. The orange band is useful for the accurate detection and quantification of phycocyanin (PC), an accessory pigment in toxin-producing cyanobacterial blooms, because of the specific light absorption characteristics of PC around 600–625 nm. In this study, we compared the Landsat 8 OLI’s and Sentinel-3 Ocean and Land Color Instrument’s (OLCI) derived orange band reflectance and PC products

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2

Arias-Rodriguez, Leonardo F., Zheng Duan, José de Jesús Díaz-Torres, et al. "Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine." Sensors 21, no. 12 (2021): 4118. http://dx.doi.org/10.3390/s21124118.

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Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013–2019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Senti

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3

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 (2020): 2606. http://dx.doi.org/10.3390/rs12162606.

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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 distri

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4

Hammond, Matthew L., Stephanie A. Henson, Nicolas Lamquin, Sébastien Clerc, and Craig Donlon. "Assessing the Effect of Tandem Phase Sentinel-3 OLCI Sensor Uncertainty on the Estimation of Potential Ocean Chlorophyll-a Trends." Remote Sensing 12, no. 16 (2020): 2522. http://dx.doi.org/10.3390/rs12162522.

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The Sentinel-3 tandem project represents the first time that two ocean colour satellites have been flown in the same orbit with minimal temporal separation (~30 s), thus allowing them to have virtually identical views of the ocean. This offers an opportunity for understanding how differences in individual sensor uncertainty can affect conclusions drawn from the data. Here, we specifically focus on trend estimation. Observational chlorophyll-a uncertainty is assessed from the Sentinel-3A Ocean and Land Colour Imager (OLCI-A) and Sentinel-3B OLCI (OLCI-B) sensors using a bootstrapping approach.

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5

Su, Hua, Xuemei Lu, Zuoqi Chen, Hongsheng Zhang, Wenfang Lu, and Wenting Wu. "Estimating Coastal Chlorophyll-A Concentration from Time-Series OLCI Data Based on Machine Learning." Remote Sensing 13, no. 4 (2021): 576. http://dx.doi.org/10.3390/rs13040576.

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Chlorophyll-a (chl-a) is an important parameter of water quality and its concentration can be directly retrieved from satellite observations. The Ocean and Land Color Instrument (OLCI), a new-generation water-color sensor onboard Sentinel-3A and Sentinel-3B, is an excellent tool for marine environmental monitoring. In this study, we introduce a new machine learning model, Light Gradient Boosting Machine (LightGBM), for estimating time-series chl-a concentration in Fujian’s coastal waters using multitemporal OLCI data and in situ data. We applied the Case 2 Regional CoastColour (C2RCC) processo

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6

Lamquin, Nicolas, Ludovic Bourg, Sébastien Clerc, and Craig Donlon. "OLCI A/B Tandem Phase Analysis, Part 3: Post-Tandem Monitoring of Cross-Calibration from Statistics of Deep Convective Clouds Observations." Remote Sensing 12, no. 18 (2020): 3105. http://dx.doi.org/10.3390/rs12183105.

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This study is a follow-up of a full methodology for the homogenisation and harmonisation of the two Ocean and Land Colour Instrument (OLCI) payloads based on the OLCI-A/OLCI-B tandem phase analysis. This analysis provided cross-calibration factors between the two instruments with a very high precision, providing a ‘truth’ from the direct comparison of simultaneous and collocated acquisitions. The long-term monitoring of such cross-calibration is a prerequisite for an operational application of sensors harmonisation along the mission lifetime, no other tandem phase between OLCI-A and OLCI-B bei

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7

Lamquin, Nicolas, Alexis Déru, Sébastien Clerc, Ludovic Bourg, and Craig Donlon. "OLCI A/B Tandem Phase Analysis, Part 2: Benefits of Sensors Harmonisation for Level 2 Products." Remote Sensing 12, no. 17 (2020): 2702. http://dx.doi.org/10.3390/rs12172702.

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This study is a follow-up of a full methodology for the homogenisation and harmonisation of the two Ocean and Land Colour Instrument (OLCI) payloads based on the tandem phase analysis. Sentinel-3B was manoeuvred into a tandem configuration with its operational twin Sentinel-3A already in orbit few weeks after its launch, which was followed by a short drift phase during which Sentinel-3B was progressively moved to a specific orbit phasing of 140° separation from the sentinel-3A. Harmonisation is performed at Level 1 for the radiometric alignment of the OLCI-A TOA radiances to the ones of OLCI-B

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8

Blix, Katalin, Károly Pálffy, Viktor Tóth, and Torbjørn Eltoft. "Remote Sensing of Water Quality Parameters over Lake Balaton by Using Sentinel-3 OLCI." Water 10, no. 10 (2018): 1428. http://dx.doi.org/10.3390/w10101428.

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The Ocean and Land Color Instrument (OLCI) onboard Sentinel 3A satellite was launched in February 2016. Level 2 (L2) products have been available for the public since July 2017. OLCI provides the possibility to monitor aquatic environments on 300 m spatial resolution on 9 spectral bands, which allows to retrieve detailed information about the water quality of various type of waters. It has only been a short time since L2 data became accessible, therefore validation of these products from different aquatic environments are required. In this work we study the possibility to use S3 OLCI L2 produc

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9

Zibordi, Giuseppe, Frederic Melin, and Jean-Francois Berthon. "A Regional Assessment of OLCI Data Products." IEEE Geoscience and Remote Sensing Letters 15, no. 10 (2018): 1490–94. http://dx.doi.org/10.1109/lgrs.2018.2849329.

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10

Antoine, David, Vincenzo Vellucci, Andrew C. Banks, et al. "ROSACE: A Proposed European Design for the Copernicus Ocean Colour System Vicarious Calibration Infrastructure." Remote Sensing 12, no. 10 (2020): 1535. http://dx.doi.org/10.3390/rs12101535.

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The European Copernicus programme ensures long-term delivery of high-quality, global satellite ocean colour radiometry (OCR) observations from its Sentinel-3 (S3) satellite series carrying the ocean and land colour instrument (OLCI). In particular, the S3/OLCI provides marine water leaving reflectance and derived products to the Copernicus marine environment monitoring service, CMEMS, for which data quality is of paramount importance. This is why OCR system vicarious calibration (OC-SVC), which allows uncertainties of these products to stay within required specifications, is crucial. The Europ

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11

Renosh, Pannimpullath Remanan, David Doxaran, Liesbeth De Keukelaere, and Juan Ignacio Gossn. "Evaluation of Atmospheric Correction Algorithms for Sentinel-2-MSI and Sentinel-3-OLCI in Highly Turbid Estuarine Waters." Remote Sensing 12, no. 8 (2020): 1285. http://dx.doi.org/10.3390/rs12081285.

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The present study assesses the performance of state-of-the-art atmospheric correction (AC) algorithms applied to Sentinel-2-MultiSpectral Instrument (S2-MSI) and Sentinel-3-Ocean and Land Color Instrument (S3-OLCI) data recorded over moderately to highly turbid estuarine waters, considering the Gironde Estuary (SW France) as a test site. Three spectral bands of water-leaving reflectance ( R h o w ) are considered: green (560 nm), red (655 or 665 nm) and near infrared (NIR) (865 nm), required to retrieve the suspended particulate matter (SPM) concentrations in clear to highly turbid waters (SPM

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12

Prikaziuk, Egor, Peiqi Yang, and Christiaan van der Tol. "Google Earth Engine Sentinel-3 OLCI Level-1 Dataset Deviates from the Original Data: Causes and Consequences." Remote Sensing 13, no. 6 (2021): 1098. http://dx.doi.org/10.3390/rs13061098.

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In this study, we demonstrate that the Google Earth Engine (GEE) dataset of Sentinel-3 Ocean and Land Color Instrument (OLCI) level-1 deviates from the original Copernicus Open Access Data Hub Service (DHUS) data by 10–20 W m−2 sr−1μμm−1 per pixel per band. We compared GEE and DHUS single pixel time series for the period from April 2016 to September 2020 and identified two sources of this discrepancy: the ground pixel position and reprojection. The ground pixel position of OLCI product can be determined in two ways: from geo-coordinates (DHUS) or from tie-point coordinates (GEE). We recommend

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13

Ogashawara, Igor. "The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms." Environments 6, no. 6 (2019): 60. http://dx.doi.org/10.3390/environments6060060.

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Cyanobacterial harmful algal blooms (CHABs) have been a concern for aquatic systems, especially those used for water supply and recreation. Thus, the monitoring of CHABs is essential for the establishment of water governance policies. Recently, remote sensing has been used as a tool to monitor CHABs worldwide. Remote monitoring of CHABs relies on the optical properties of pigments, especially the phycocyanin (PC) and chlorophyll-a (chl-a). The goal of this study is to evaluate the potential of recent launch the Ocean and Land Color Instrument (OLCI) on-board the Sentinel-3 satellite to identif

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14

Гоголев, Денис Григорьевич, Татьяна Васильевна Буканова та Сергей Валерьевич Александров. "РЕГИОНАЛЬНАЯ КОРРЕКЦИЯ АЛГОРИТМОВ РАСЧЕТА КОНЦЕНТРАЦИИ ХЛОРОФИЛЛА «А» ПО ДАННЫМ СПУТНИКОВЫХ РАДИОМЕТРОВ VIIRS И OLCI В ЮГО-ВОСТОЧНОЙ ЧАСТИ БАЛТИЙСКОГО МОРЯ". KSTU News, № 59 (11 січня 2020): 13–23. http://dx.doi.org/10.46845/1997-3071-2020-59-13-23.

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Работа посвящена оценке точности расчета концентрации хлорофилла «а» в поверхностном горизонте юго-восточной части Балтийского моря по спутнико-вым данным видимого диапазона. Проведено сопоставление величин концентра-ции хлорофилла «а», собранных в морских экспедициях 2019 г. и рассчитанных по данным новейших спутниковых радиометров: VIIRS, установленных на спут-никах Suomi-NPP и NOAA-20, и OLCI – на SENTINEL-3A и 3B. Сравнение тра-диционных судовых и современных данных дистанционного зондирования позво-лило рассчитать ошибки вычисления концентрации хлорофилла «а» стандартны-ми алгоритмами обр

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15

Wang, Xia, Feng Ling, Huaiying Yao, Yaolin Liu, and Shuna Xu. "Unsupervised Sub-Pixel Water Body Mapping with Sentinel-3 OLCI Image." Remote Sensing 11, no. 3 (2019): 327. http://dx.doi.org/10.3390/rs11030327.

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Mapping land surface water bodies from satellite images is superior to conventional in situ measurements. With the mission of long-term and high-frequency water quality monitoring, the launch of the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B provides the best possible approach for near real-time land surface water body mapping. Sentinel-3 OLCI contains 21 bands ranging from visible to near-infrared, but the spatial resolution is limited to 300 m, which may include lots of mixed pixels around the boundaries. Sub-pixel mapping (SPM) provides a good solution for t

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16

Wynne, Timothy T., Sachidananda Mishra, Andrew Meredith, R. Wayne Litaker, and Richard P. Stumpf. "Intercalibration of MERIS, MODIS, and OLCI Satellite Imagers for Construction of Past, Present, and Future Cyanobacterial Biomass Time Series." Remote Sensing 13, no. 12 (2021): 2305. http://dx.doi.org/10.3390/rs13122305.

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Satellite imagery has been used to monitor and assess Harmful Algal Blooms (HABs), specifically, cyanobacterial blooms in Lake Erie (the USA and Canada) for over twelve years. In recent years, imagery has been applied to the other Great Lakes as well as other U.S. lakes. The key algorithm used in this monitoring system is the cyanobacterial index (CI), a measure of the chlorophyll found in cyanobacterial blooms. The CI is a “spectral shape” (or curvature) algorithm, which is a form of the second derivative around the 681 nm (MERIS/OLCI) or 678 nm (MODIS) band, which is robust and implicitly in

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17

Yang, Xiaohong, Yue Li, Yu Wei, Zhanlong Chen, and Peng Xie. "Water Body Extraction from Sentinel-3 Image with Multiscale Spatiotemporal Super-Resolution Mapping." Water 12, no. 9 (2020): 2605. http://dx.doi.org/10.3390/w12092605.

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Water body mapping is significant for water resource management. In the view of 21 spectral bands and a short revisit time of no more than two days, a Sentinel-3 OLCI (Ocean and Land Colour Instrument) image could be the optimum data source in the near-real-time mapping of water bodies. However, the image is often limited by its low spatial resolution in practice. Super-resolution mapping (SRM) is a good solution to generate finer spatial resolution maps than the input data allows. In this paper, a multiscale spatiotemporal super-resolution mapping (MSST_SRM) method for water bodies is propose

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18

Su, Hua, Bowen Ji, and Yunpeng Wang. "Sea Ice Extent Detection in the Bohai Sea Using Sentinel-3 OLCI Data." Remote Sensing 11, no. 20 (2019): 2436. http://dx.doi.org/10.3390/rs11202436.

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Sea ice distribution is an important indicator of ice conditions and regional climate change in the Bohai Sea (China). In this study, we monitored the spatiotemporal distribution of the Bohai Sea ice in the winter of 2017–2018 by developing sea ice information indexes using 300 m resolution Sentinel-3 Ocean and Land Color Instrument (OLCI) images. We assessed and validated the index performance using Sentinel-2 MultiSpectral Instrument (MSI) images with higher spatial resolution. The results indicate that the proposed Normalized Difference Sea Ice Information Index (NDSIIIOLCI), which is based

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19

Gower, J., and S. King. "The distribution of pelagic Sargassum observed with OLCI." International Journal of Remote Sensing 41, no. 15 (2019): 5669–79. http://dx.doi.org/10.1080/01431161.2019.1658240.

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Conopio, M., R. K. Japor, A. C. Blanco, and A. M. Tamondong. "ESTIMATION OF CHLOROPHYLL-A CONCENTRATION IN LAGUNA DE BAY USING SENTINEL-3 SATELLITE DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W19 (December 23, 2019): 125–32. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w19-125-2019.

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Abstract. The mission of the European Space Agency’s Sentinel-3 satellite is to provide data for land and ocean monitoring purposes. Sentinel- 3’s Ocean and Land Colour Instrument (OLCI) data are being used largely for monitoring offshore and coastal waters but can also be used for inland waters including lakes. It has a spatial resolution of 300 meters, a temporal resolution of 2–3 days and contains 21 spectral bands. Laguna de Bay, with a surface area of around 930 km2, suffers from periodic algal blooms resulting from excessive nutrient inputs from surrounding watersheds. This study aims to

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Zhang, Zhijiang, Lin Zhao, and Aiwen Lin. "Evaluating the Performance of Sentinel-3A OLCI Land Products for Gross Primary Productivity Estimation Using AmeriFlux Data." Remote Sensing 12, no. 12 (2020): 1927. http://dx.doi.org/10.3390/rs12121927.

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Accurate and reliable estimation of gross primary productivity (GPP) is of great significance in monitoring global carbon cycles. The fraction of absorbed photosynthetically active radiation (FAPAR) and vegetation index products of the Moderate Resolution Imaging Spectroradiometer (MODIS) are currently the most widely used data in evaluating GPP. The launch of the Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite provides the FAPAR and the OLCI Terrestrial Chlorophyll Index (OTCI) products with higher temporal resolution and smoother spatial distribution than MODIS, havi

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Glukhovets, Dmitry, Oleg Kopelevich, Anna Yushmanova, et al. "Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data." Remote Sensing 12, no. 19 (2020): 3210. http://dx.doi.org/10.3390/rs12193210.

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Our work’s primary goal is to reveal the problematic issues related to estimates of the colored organic matter absorption coefficient in the northern seas from data of the Ocean and Land Color Instrument (OLCI) installed on the Sentinel-3 satellites, e.g., a comparison of the OLCI standard error assessment ADG443_NN_err relating to the measurement and the retrieval of the geophysical products and the uncertainties in the northern seas’ real situation. The natural conditions are incredibly unfavorable there, mainly due to frequent cloudiness and low sun heights. We conducted a comprehensive mul

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Uudeberg, Kristi, Ilmar Ansko, Getter Põru, Ave Ansper, and Anu Reinart. "Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters." Remote Sensing 11, no. 19 (2019): 2297. http://dx.doi.org/10.3390/rs11192297.

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The European Space Agency’s Copernicus satellites Sentinel-2 and Sentinel-3 provide observations with high spectral, spatial, and temporal resolution which can be used to monitor inland and coastal waters. Such waters are optically complex, and the water color may vary from completely clear to dark brown. The main factors influencing water color are colored dissolved organic matter, phytoplankton, and suspended sediments. Recently, there has been a growing interest in the use of the optical water type (OWT) classification in the remote sensing of ocean color. Such classification helps to clari

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Zeng, Chuiqing, and Caren E. Binding. "Consistent Multi-Mission Measures of Inland Water Algal Bloom Spatial Extent Using MERIS, MODIS and OLCI." Remote Sensing 13, no. 17 (2021): 3349. http://dx.doi.org/10.3390/rs13173349.

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Envisat’s MERIS and its successor Sentinel OLCI have proven invaluable for documenting algal bloom conditions in coastal and inland waters. Observations over turbid eutrophic waters, in particular, have benefited from the band at 708 nm, which captures the reflectance peak associated with intense algal blooms and is key to line-height algorithms such as the Maximum Chlorophyll Index (MCI). With the MERIS mission ending in early 2012 and OLCI launched in 2016, however, time-series studies relying on these two sensors have to contend with an observation gap spanning four years. Alternate sensors

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Kokhanovsky, Alexander, Maxim Lamare, Olaf Danne, et al. "Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument." Remote Sensing 11, no. 19 (2019): 2280. http://dx.doi.org/10.3390/rs11192280.

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The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400–1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size

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Li, Jamet, Zhu, et al. "Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS." Remote Sensing 11, no. 20 (2019): 2400. http://dx.doi.org/10.3390/rs11202400.

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The accuracy of remote-sensing reflectance (Rrs) estimated from ocean color imagery through the atmospheric correction step is essential in conducting quantitative estimates of the inherent optical properties and biogeochemical parameters of seawater. Therefore, finding the main source of error is the first step toward improving the accuracy of Rrs. However, the classic validation exercises provide only the total error of the retrieved Rrs. They do not reveal the error sources. Moreover, how to effectively improve this satellite algorithm remains unknown. To better understand and improve vario

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Preusker, René, Cintia Carbajal Henken, and Jürgen Fischer. "Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces." Remote Sensing 13, no. 5 (2021): 932. http://dx.doi.org/10.3390/rs13050932.

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A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One

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Mei, Linlu, Vladimir Rozanov, Marco Vountas, John P. Burrows, and Andreas Richter. "XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation." Atmospheric Chemistry and Physics 18, no. 4 (2018): 2511–23. http://dx.doi.org/10.5194/acp-18-2511-2018.

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Abstract. A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly a

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Caballero, Isabel, Richard Stumpf, and Andrew Meredith. "Preliminary Assessment of Turbidity and Chlorophyll Impact on Bathymetry Derived from Sentinel-2A and Sentinel-3A Satellites in South Florida." Remote Sensing 11, no. 6 (2019): 645. http://dx.doi.org/10.3390/rs11060645.

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Evaluation of the impact of turbidity on satellite-derived bathymetry (SDB) is a crucial step for selecting optimal scenes and for addressing the limitations of SDB. This study examines the relatively high-resolution MultiSpectral instrument (MSI) onboard Sentinel-2A (10–20–60 m) and the moderate-resolution Ocean and Land Color instrument (OLCI) onboard Sentinel-3A (300 m) for generating bathymetric maps through a conventional ratio transform model in environments with some turbidity in South Florida. Both sensors incorporate additional spectral bands in the red-edge near infrared (NIR) region

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Blix, Katalin, Juan Li, Philippe Massicotte, and Atsushi Matsuoka. "Developing a New Machine-Learning Algorithm for Estimating Chlorophyll-a Concentration in Optically Complex Waters: A Case Study for High Northern Latitude Waters by Using Sentinel 3 OLCI." Remote Sensing 11, no. 18 (2019): 2076. http://dx.doi.org/10.3390/rs11182076.

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The monitoring of Chlorophyll-a (Chl-a) concentration in high northern latitude waters has been receiving increased focus due to the rapid environmental changes in the sub-Arctic, Arctic. Spaceborne optical instruments allow the continuous monitoring of the occurrence, distribution, and amount of Chl-a. In recent years, the Ocean and Land Color Instruments (OLCI) onboard the Sentinel 3 (S3) A and B satellites were launched, which provide data about various aquatic environments on advantageous spatial, spectral, and temporal resolutions with high SNR. Although S3 OLCI could be favorable to moni

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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 (2020): 3867. http://dx.doi.org/10.3390/rs12233867.

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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 t

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Kritten, Lena, Rene Preusker, and Jürgen Fischer. "A New Retrieval of Sun-Induced Chlorophyll Fluorescence in Water from Ocean Colour Measurements Applied on OLCI L-1b and L-2." Remote Sensing 12, no. 23 (2020): 3949. http://dx.doi.org/10.3390/rs12233949.

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The retrieval of sun-induced chlorophyll fluorescence is greatly beneficial to studies of marine phytoplankton biomass, physiology, and composition, and is required for user applications and services. Customarily phytoplankton chlorophyll fluorescence is determined from satellite measurements through a fluorescence line-height algorithm using three bands around 680 nm. We propose here a modified retrieval, making use of all available bands in the relevant wavelength range, with the goal to improve the effectiveness of the algorithm in optically complex waters. For the Ocean and Land Colour Ins

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Wolters, Erwin, Carolien Toté, Sindy Sterckx, et al. "iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2." Remote Sensing 13, no. 4 (2021): 654. http://dx.doi.org/10.3390/rs13040654.

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To validate the iCOR atmospheric correction algorithm applied to the Sentinel-3 Ocean and Land Color Instrument (OLCI), Top-of-Atmosphere (TOA) observations over land, globally retrieved Aerosol Optical Thickness (AOT), Top-of-Canopy (TOC) reflectance, and Vegetation Indices (VIs) were intercompared with (i) AERONET AOT and AERONET-based TOC reflectance simulations, (ii) RadCalNet surface reflectance observations, and (iii) SYN Level 2 (L2) AOT, TOC reflectance, and VIs. The results reveal that, overall, iCOR’s statistical and temporal consistency is high. iCOR AOT retrievals overestimate rela

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Niroumand-Jadidi, Milad, Francesca Bovolo, and Lorenzo Bruzzone. "Novel Spectra-Derived Features for Empirical Retrieval of Water Quality Parameters: Demonstrations for OLI, MSI, and OLCI Sensors." IEEE Transactions on Geoscience and Remote Sensing 57, no. 12 (2019): 10285–300. http://dx.doi.org/10.1109/tgrs.2019.2933251.

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Zhang, Fengji, Zhijiang Zhang, Yi Long, and Ling Zhang. "Integration of Sentinel-3 OLCI Land Products and MERRA2 Meteorology Data into Light Use Efficiency and Vegetation Index-Driven Models for Modeling Gross Primary Production." Remote Sensing 13, no. 5 (2021): 1015. http://dx.doi.org/10.3390/rs13051015.

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Accurately and reliably estimating total terrestrial gross primary production (GPP) on a large scale is of great significance for monitoring the carbon cycle process. The Sentinel-3 satellite provides the OLCI FAPAR and OTCI products, which possess a higher spatial and temporal resolution than MODIS products. However, few studies have focused on using LUE models and VI-driven models based on the Sentinel-3 satellites to estimate GPP on a large scale. The purpose of this study is to evaluate the performance of Sentinel-3 OLCI FAPAR and OTCI products combined with meteorology reanalysis data in

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Gabet, R., E. Le Cren, C. Jin, et al. "Complete Dispersion Characterization of Few Mode Fibers by OLCI Technique." Journal of Lightwave Technology 33, no. 6 (2015): 1155–60. http://dx.doi.org/10.1109/jlt.2014.2376702.

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Nahed Toral, José, Zenón Gerardo López Tecpoyotl, José Roberto Aguilar Jiménez, Daniel Grande Cano, and Claudia Delgadillo Puga. "Compliance of Goat Farming under Extensive Grazing with the Organic Standards and Its Contribution to Sustainability in Puebla, Mexico." Sustainability 13, no. 11 (2021): 6293. http://dx.doi.org/10.3390/su13116293.

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In order to determine whether organic production may be a viable option for goat farmers of the lower Mixteca region of Puebla, Mexico, in order to increase sustainability of their farms, we evaluated the extent to which these goat farms fulfill organic standards. Additionally, we revised their level of sustainability by calculating an Organic Livestock Conversion Index (OLCI) using 10 indicators and 36 variables. Information was obtained through two means: direct observation and a questionnaire applied to 119 goat farmers of six municipalities of the region. These goat farms principally consi

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Cherif, El Khalil, Patricija Mozetič, Janja Francé, Vesna Flander-Putrle, Jana Faganeli-Pucer, and Martin Vodopivec. "Comparison of In-Situ Chlorophyll-a Time Series and Sentinel-3 Ocean and Land Color Instrument Data in Slovenian National Waters (Gulf of Trieste, Adriatic Sea)." Water 13, no. 14 (2021): 1903. http://dx.doi.org/10.3390/w13141903.

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While satellite remote sensing of ocean color is a viable tool for estimating large-scale patterns of chlorophyll-a (Chl-a) and global ocean primary production, its application in coastal waters is limited by the complex optical properties. An exploratory study was conducted in the Gulf of Trieste (Adriatic Sea) to assess the usefulness of Sentinel-3 satellite data in the Slovenian national waters. OLCI (Ocean and Land Colour Instrument) Chl-a level 2 products (OC4Me and NN) were compared to monthly Chl-a in-situ measurements at fixed sites from 2017 to 2019. In addition, eight other methods f

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Soomets, Tuuli, Kristi Uudeberg, Dainis Jakovels, Agris Brauns, Matiss Zagars, and Tiit Kutser. "Validation and Comparison of Water Quality Products in Baltic Lakes Using Sentinel-2 MSI and Sentinel-3 OLCI Data." Sensors 20, no. 3 (2020): 742. http://dx.doi.org/10.3390/s20030742.

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Inland waters, including lakes, are one of the key points of the carbon cycle. Using remote sensing data in lake monitoring has advantages in both temporal and spatial coverage over traditional in-situ methods that are time consuming and expensive. In this study, we compared two sensors on different Copernicus satellites: Multispectral Instrument (MSI) on Sentinel-2 and Ocean and Land Color Instrument (OLCI) on Sentinel-3 to validate several processors and methods to derive water quality products with best performing atmospheric correction processor applied. For validation we used in-situ data

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Tang, Yijie, Qunming Wang, Xiaohua Tong, and Peter M. Atkinson. "Integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images." ISPRS Journal of Photogrammetry and Remote Sensing 180 (October 2021): 130–50. http://dx.doi.org/10.1016/j.isprsjprs.2021.08.012.

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Blanco, A. C., A. Manuel, R. Jalbuena, et al. "ESTIMATION OF CHL-A CONCENTRATION IN LAGUNA LAKE USING SENTINEL-3 OLCI IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W11 (February 14, 2020): 17–21. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w11-17-2020.

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Abstract. The use of Sentinel-3 Ocean and Land Color Instrument (OLCI) images in estimating chlorophyll-a (total and class-differentiated)a concentration is promising owing to Sentinel-3’s 21 bands. This was investigated for the case of Laguna de Bay (or Laguna Lake), Philippines. Field surveys were conducted on 13–17 November 2018 using FluoroProbe, a submersible fluorimeter capable of quantifying concentrations of spectral classes of microalgae. These were regressed with reflectance data obtained from 10-day composite Sentinel-3 reflectance images as well as ten empirical algorithms (indices

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Liu, Bingqing, Eurico J. D'Sa, and Ishan D. Joshi. "Floodwater impact on Galveston Bay phytoplankton taxonomy, pigment composition and photo-physiological state following Hurricane Harvey from field and ocean color (Sentinel-3A OLCI) observations." Biogeosciences 16, no. 9 (2019): 1975–2001. http://dx.doi.org/10.5194/bg-16-1975-2019.

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Abstract. Phytoplankton taxonomy, pigment composition and photo-physiological state were studied in Galveston Bay (GB), Texas (USA), following the extreme flooding associated with Hurricane Harvey (25–29 August 2017) using field and satellite ocean color observations. The percentage of chlorophyll a (Chl a) in different phytoplankton groups was determined from a semi-analytical IOP (inherent optical property) inversion algorithm. The IOP inversion algorithm revealed the dominance of freshwater species (diatom, cyanobacteria and green algae) in the bay following the hurricane passage (29 Septem

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Qian, Xiaojin, and Liangyun Liu. "Retrieving Crop Leaf Chlorophyll Content Using an Improved Look-Up-Table Approach by Combining Multiple Canopy Structures and Soil Backgrounds." Remote Sensing 12, no. 13 (2020): 2139. http://dx.doi.org/10.3390/rs12132139.

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Leaf chlorophyll content (LCC) is a pivotal parameter in the monitoring of agriculture and carbon cycle modeling at regional and global scales. ENVISAT MERIS and Sentinel-3 OLCI data are suitable for use in the global monitoring of LCC because of their spectral specifications (covering red-edge bands), wide field of view and short revisit times. Generally, remote sensing approaches for LCC retrieval consist of statistically- and physically-based models. The physical approaches for LCC estimation require the use of radiative transfer models (RTMs), which are more robust and transferrable than e

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Lavrova, O. Yu, D. M. Soloviev, A. Ya Strochkov, K. R. Nazirova, E. V. Krayushkin, and E. V. Zhuk. "The use of mini-drifters in coastal current measurements conducted concurrently with satellite imaging." Исследования Земли из Космоса, no. 5 (November 5, 2019): 36–49. http://dx.doi.org/10.31857/s0205-96142019536-49.

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The results of field measurements of coastal currents using Lagrangian mini-drifters are presented. Drifter experiments were conducted concurrently with satellite imaging using Sentinel-2 MSI, Landsat-8 OLI and Sentinel-3 OLCI sensors. It is shown that the use of an inexpensive and simple to manufacture device, which is a mini-drifter, allows obtaining operational information about the parameters of coastal currents. In the experiments of April-May, 2019, in the northeastern part of the Black Sea, it was possible to estimate the velocity of coastal currents and determine the minimum distance t

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Shun, BI, LI Yunmei, LV Heng, et al. "Estimation of chlorophyll-a concentration in Lake Erhai based on OLCI data." Journal of Lake Sciences 30, no. 3 (2018): 701–12. http://dx.doi.org/10.18307/2018.0312.

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Zhang, Xudong, Jie Zhang, Junmin Meng, Chenqing Fan, and Jing Wang. "Observation of internal waves with OLCI and SRAL on board Sentinel-3." Acta Oceanologica Sinica 39, no. 3 (2020): 56–62. http://dx.doi.org/10.1007/s13131-019-1510-7.

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Giannini, Fernanda, Brian P. V. Hunt, Derek Jacoby, and Maycira Costa. "Performance of OLCI Sentinel-3A satellite in the Northeast Pacific coastal waters." Remote Sensing of Environment 256 (April 2021): 112317. http://dx.doi.org/10.1016/j.rse.2021.112317.

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Gossn, Juan, Kevin Ruddick, and Ana Dogliotti. "Atmospheric Correction of OLCI Imagery over Extremely Turbid Waters Based on the Red, NIR and 1016 nm Bands and a New Baseline Residual Technique." Remote Sensing 11, no. 3 (2019): 220. http://dx.doi.org/10.3390/rs11030220.

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A common approach to the pixel-by-pixel atmospheric correction of satellite water colour imagery is to calculate aerosol and water reflectance at two spectral bands, typically in the near infra-red (NIR, 700–1000 nm) or the short-wave-infra-red (SWIR, 1000–3000 nm), and then extrapolate aerosol reflectance to shorter wavelengths. For clear waters, this can be achieved simply for NIR bands, where the water reflectance can be assumed negligible i.e., the “black water” assumption. For moderately turbid waters, either the NIR water reflectance, which is non-negligible, must be modelled or longer w

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De Grave, Charlotte, Luca Pipia, Bastian Siegmann, et al. "Retrieving and Validating Leaf and Canopy Chlorophyll Content at Moderate Resolution: A Multiscale Analysis with the Sentinel-3 OLCI Sensor." Remote Sensing 13, no. 8 (2021): 1419. http://dx.doi.org/10.3390/rs13081419.

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ESA’s Eighth Earth Explorer mission “FLuorescence EXplorer” (FLEX) will be dedicated to the global monitoring of the chlorophyll fluorescence emitted by vegetation. In order to properly interpret the measured fluorescence signal, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem formation with Sentinel-3 (S3), which conveys the Ocean and Land Color Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In support of FLEX’s preparatory activities, this paper presents a first vali

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Lamquin, Nicolas, Sébastien Clerc, Ludovic Bourg, and Craig Donlon. "OLCI A/B Tandem Phase Analysis, Part 1: Level 1 Homogenisation and Harmonisation." Remote Sensing 12, no. 11 (2020): 1804. http://dx.doi.org/10.3390/rs12111804.

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Copernicus is a European system for monitoring the Earth in support of European policy. It includes the Sentinel-3 satellite mission which provides reliable and up-to-date measurements of the ocean, atmosphere, cryosphere, and land. To fulfil mission requirements, two Sentinel-3 satellites are required on-orbit at the same time to meet revisit and coverage requirements in support of Copernicus Services. The inter-unit consistency is critical for the mission as more S3 platforms are planned in the future. A few weeks after its launch in April 2018, the Sentinel-3B satellite was manoeuvred into

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