DOCSLIB.ORG

Sentinel-2 Red-Edge Bands Capabilities for Retrieving Chlorophyll-A: Lake Burullus, Egypt

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Sentinel-2 Red-Edge Bands Capabilities for Retrieving Chlorophyll-A: Lake Burullus, Egypt Sentinel-2 Red-Edge Bands Capabilities for Retrieving Chlorophyll-a: Lake Burullus, Egypt M. S. Salama1, Hanan Farag1,2 and Maha Tawfik2 The TIGER initiative 1- University of Twente, The Netherlands 2- National Water Research Center, Egypt UNIVERSITY TWENTE. Outlines • Why Snetinel-2 for water quality? • Challenges. • Requirements and objectives. • Study area and data. • Why Red-bands models? • Calibration and validation. • Rapid Eye Chl-a products. • Sentinel-2 expected accuracy. • Demonstration with SPOT time series. • Preliminary conclusions. UNIVERSITY TWENTE. Why Sentinel-2 for water quality? The aquatic biosphere is uniquely monitored by EO sensors as they provide synoptic information on key water quality variables at high temporal frequency. The Multi-Spectral Instrument (MSI) payload of SENTINEL-2 mission will sample 13 spectral bands: four bands at 10 m, six bands at 20 m and three bands at 60 m spatial resolution. The twin satellites of SENTINEL-2 mission offer data at frequency of 5 days at the Equator. UNIVERSITY TWENTE. Challenges 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 Part of the 33 34 35 reality36 37 38 39 40 41 42 43 What you see is not what you get! UNIVERSITY TWENTE. Requirements and objective Consistent EO-estimates of water quality parameters in inland and coastal waters requires three components: – (i) a reliable atmospheric correction method; – (ii) an accurate retrieval algorithm and – (iii) an objective method for calibration and validation. The objective : – Investigate the capabilities of red-bands of the Sentinel-2 MSI sensor in detecting Chl-a in inland waters; – Calibrate and validate such a model. UNIVERSITY TWENTE. Study area The Lake Burullus is located on Studythe coastal Area shore of the north Nile Delta (30º 35 to 31º 8 E, 31º 22 to 31º 37 N); The Lake surface area is about 65X14 km2 with an average depth of 1 m; The gradient between the brackish (southern) part of the lake and marine waters provides a unique ecotonal zone where many marine and fresh water organisms flourish. UNIVERSITY TWENTE. Field and EO data • MERIS images and Rapid Eye acquired in 2011 and 2013 concurrent with the field measurements. • In situ Data (Chl-a), 22 in situ measuring locations (2 campaign In Jan and July 2011) matching MERIS images. • 11 in situ measuring locations, for Rapid Eye (12 May 2013) Resolution Rapid MSI MERIS nm nm Rapid nm nm Eye nm nm MSI MERIS Eye 2 490 65 1 475 70 3 490 10 3 560 35 2 555 70 5 560 10 10 m 5 m 300 m 4 665 30 3 655.5 55 7 665 10 5 705 15 4 710 40 9 709 10 20 m UNIVERSITY TWENTE. Field and EO data WQV min max mean Stdev nr Chl-a matchup MERIS [mg.m-3] 12.28 121.00 57.33 28.97 22 Chl-a matchup RapidEye 28.73 88.27 51.92 19.72 11 UNIVERSITY TWENTE. Why Red-bands models? The model establishes a linear relationship between Chl-a concentration and the : 1- Normalized Difference Chlorophyll Index (NDCI):NDCI=(R(708)-R(665))/ R(708)+R(665)) Mishra and Mishra (2012) Basically based on the Gitelson et al., (2006) model 2- RedEdg2/(RedEdge1-Red) These models did work for MERIS, Rapid Eye, SPOT, but how about the Sentinel-2? UNIVERSITY TWENTE. Calibration and validation NDCI MERIS NDCI Rapid Eye 0.4 0.2 y = 0.0064x - 0.4415 y = 0.0064x - 0.4577 0.2 R² = 0.834 0.1 R² = 0.8364 0 0 0.00 50.00 100.00 0.00 50.00 100.00 150.00 -0.1 -0.2 -0.2 NDCI MERIS NDCI NDCI Eye Rapid -0.4 -0.3 -0.4 -0.6 -3 Chl-a mg.m-3 Chl-a mg.m There is a similarity between the results of the two data sets. NDCI is positive at about >75 mg.m-3 Ideally, the validity of any model is tested against an independent data set. But how to subdivide? Many combinations of matchups can be used! UNIVERSITY TWENTE. Calibration and validation Data set • We use the n GeoCalVal model of split Salama et al., 2012 • GeoCalVal derives Cal set = k Val set = n-k the probability K=k+j distributions (PDs) of regression errors calibration model store coefficients and coefficients store validation errors apply the form new cal set model [k,j] N finish randomly picks j Y j=j+1 UNIVERSITY TWENTE. Calibration and validation, MERIS 80 80 60 60 40 40 Frequency 20 Frequency 20 0 0 4 5 6 7 8 9 10 -0.6 -0.5 -0.4 -0.3 -3 -3 -3 Slope for NDCI, [mg.m ] x 10 Intercept for NDCI ratio, [mg.m ] 100 80 80 60 60 40 40 Frequency Frequency 20 20 0 0 5 10 15 20 25 0.65 0.7 0.75 0.8 0.85 0.9 0.95 MAE of derived Chla, [mg.m-3] R2 of derived Chla UNIVERSITY TWENTE. Calibration and validation, Rapid Eye 200 150 150 100 100 50 Frequency 50 Frequency 0 0 0 0.002 0.004 0.006 0.008 0.01 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 -3 Slope for NDCI, [mg.m-3] Intercept for NDCI ratio, [mg.m ] 1500 100 80 1000 60 40 500 Frequency Frequency 20 0 0 0 10 20 30 40 50 0.2 0.4 0.6 0.8 MAE of derived Chla, [mg.m-3] R2 of derived Chla UNIVERSITY TWENTE. Rapid Eye products of Chl-a UNIVERSITY TWENTE. Rapid Eye products of Chl-a UNIVERSITY TWENTE. Sentinel-2 expected accuracy 250 Noise model: original_SNR updated_SNR S 200 Noise model = + 150 Which can be converted into: SNR 100 = + 50 R2=0.75 RMSE=26.5 First and were estimated for 0 all bands , with a correction for 0 50 100 150 200 the spatial (20x20 m) and spectral Lref[Wm-2 sr-1 ] (15 nm) resolutions. Sentinel-2 bands (2-8b) 490-865 nm UNIVERSITY TWENTE. Sentinel-2 expected accuracy Improvement in SNR of Sentinel-2 MSI over the Rapid Eye 0.8 0.7 Sentinel-2 has about 28- 0.6 70% more SNR w.r.t Rapid Eye 0.5 0.4 The expected accuracy Improvement 0.3 from Chl-a models would SNR be the same or greater 0.2 0.1 0 475 555 655.5 710 Rapid Eye vis bands UNIVERSITY TWENTE. Expected noise over water The Noise model is used to simulate 40 the noise level above water for four 35 Sentinel-2/MSI bands: 30 - Estimate the reflectance: 25 = cos 20 15 and the noise of it 10 = + 5 data field mean to noise relative 0 490 560 665 705 In comparison to field measured values, Sentinel-2/MSI bands where Chl-a varies between 12-120 The atmospheric mg.m-3 , the noise level may cancel out correction residuals may to be 13% of error! add additional errors to this! UNIVERSITY TWENTE. Demonstration with SPOT time series UNIVERSITY TWENTE. Preliminary conclusions • NDCI is consistent between MERIS and Rapid Eye matchup data. • The increased SNR of Sentinel-2 over Rapid Eye is about 28-70% and is therefore expected to improve on the results of Chl-a (<12 mg.m-3). • The noise level of Sentinel-2 can adequately be modeled and adjusted to nominal radiometric and spatial resolutions: – The SNR of the Red-band (665) is better than that of the 705 nm by ~40% (due to the course radiometric resolution 30 nm). – It is because of this wide band the reflectance at the Red band will be larger than that at the Red Edge band 705 nm for low Chl-a. i.e. the NDCI will positive for Chl-a>75 mg.m-3 • We’ve demonstrated the potential of Sentinel-2 in deriving Chl-a in productive inland waters. UNIVERSITY TWENTE. Acknowledgment This project is financed by the European Space Agency (ESA) , The Tiger initiative, Alcantara Contact: [email protected] UNIVERSITY TWENTE. .
Load more

Recommended publications
  • Status of ESA Missions
    ESA Atmospheric Science Conference, Barcelona, 2009 ESA Earth Observation missions Henri Laur ESA EO Missions Management Office EO missions handled by ESA 1990 2000 METEOSAT M-1, 2, 3, 4, 5, 6, 7 2010 METEOSAT Second Generation MSG-1, -2, -3 METEOSAT Third Generation Meteo METOP-1, -2, -3 in cooperation with EUMETSAT ESA Earth Observation 2009 budget Science ~ 600 M€ (16.3% of ESA budget) to better ERS-1, -2 understand the Earth ENVISAT Applications Services to initiate long term monitoring systems and services ERS-1ERS-1 andand ERS-2ERS-2 missionsmissions 18 years of ERS-1/2 SAR data in the archive ERS-2 achieved 14 years in orbit in April 2009 Î ERS-2 was designed for 3 years nominal lifetime ! Platform Î no gyroscopes since 2001 Æ Gyro-less operations Î failure of the Low Bit Rate recorder in 2003 Æ set-up of a collaborative network of acquisition stations Instruments Î all instruments (but ATSR) work satisfactorily and provides useful data Î Good prospect to operate ERS-2 mission until mid-2011 Envisat MERIS (Yesterday, 6 Sep. 2009) Bordeaux Toulouse Bilbao Pyrenees ESA Atmospheric Science Conference 2009 Barcelona Zaragoza ENVISAT mission: Arctic 2007 7 years ! ~2600 Bam earthquake scientific http://www.esa.int/LivingPlanet2010/ projects First images Tectonic uplift (Andaman) + GMES pre- Hurricane operational Katrina projects Global air 09 pollution ber 20 Novem e: 15 Ozone hole 2003 eadlin acts d Abstr Chlorophyll Prestige tanker B-15A concentration oil slick iceberg CO2 map Envisat Envisat Symposium IS ER y Symposium R M R
    [Show full text]
  • The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms
    environments Article The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms Igor Ogashawara Department of Earth Sciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA; [email protected] Received: 6 May 2019; Accepted: 1 June 2019; Published: 3 June 2019 Abstract: 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 identify PC and chl-a. To do this, OLCI images were collected over the Western part of Lake Erie (U.S.A.) during the summer of 2016, 2017, and 2018. When comparing the use of traditional remote sensing algorithms to estimate PC and chl-a, none was able to accurately estimate both pigments. However, when single and band ratios were used to estimate these pigments, stronger correlations were found. These results indicate that spectral band selection should be re-evaluated for the development of new algorithms for OLCI images. Overall, Sentinel 3/OLCI has the potential to be used to identify PC and chl-a. However, algorithm development is needed. Keywords: phycocyanin; chlorophyll-a; water quality; Lake Erie; cyanobacteria; bio-optical modeling 1.
    [Show full text]
  • FAME-C: Cloud Property Retrieval Using Synergistic AATSR and MERIS Observations
    Atmos. Meas. Tech., 7, 3873–3890, 2014 www.atmos-meas-tech.net/7/3873/2014/ doi:10.5194/amt-7-3873-2014 © Author(s) 2014. CC Attribution 3.0 License. FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations C. K. Carbajal Henken, R. Lindstrot, R. Preusker, and J. Fischer Institute for Space Sciences, Freie Universität Berlin (FUB), Berlin, Germany Correspondence to: C. K. Carbajal Henken ([email protected]) Received: 29 April 2014 – Published in Atmos. Meas. Tech. Discuss.: 19 May 2014 Revised: 17 September 2014 – Accepted: 11 October 2014 – Published: 25 November 2014 Abstract. A newly developed daytime cloud property re- trievals. Biases are generally smallest for marine stratocu- trieval algorithm, FAME-C (Freie Universität Berlin AATSR mulus clouds: −0.28, 0.41 µm and −0.18 g m−2 for cloud MERIS Cloud), is presented. Synergistic observations from optical thickness, effective radius and cloud water path, re- the Advanced Along-Track Scanning Radiometer (AATSR) spectively. This is also true for the root-mean-square devia- and the Medium Resolution Imaging Spectrometer (MERIS), tion. Furthermore, both cloud top height products are com- both mounted on the polar-orbiting Environmental Satellite pared to cloud top heights derived from ground-based cloud (Envisat), are used for cloud screening. For cloudy pixels radars located at several Atmospheric Radiation Measure- two main steps are carried out in a sequential form. First, ment (ARM) sites. FAME-C mostly shows an underestima- a cloud optical and microphysical property retrieval is per- tion of cloud top heights when compared to radar observa- formed using an AATSR near-infrared and visible channel.
    [Show full text]
  • The CMEMS Globcolour Chlorophyll a Product Based on Satellite Observation: Multi-Sensor Merging and flagging Strategies
    Ocean Sci., 15, 819–830, 2019 https://doi.org/10.5194/os-15-819-2019 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. The CMEMS GlobColour chlorophyll a product based on satellite observation: multi-sensor merging and flagging strategies Philippe Garnesson, Antoine Mangin, Odile Fanton d’Andon, Julien Demaria, and Marine Bretagnon ACRI-ST, Sophia Antipolis, 06904, France Correspondence: Philippe Garnesson ([email protected]) Received: 21 December 2018 – Discussion started: 2 January 2019 Revised: 20 May 2019 – Accepted: 21 May 2019 – Published: 24 June 2019 Abstract. This paper concerns the GlobColour-merged will require a better characterisation and additional inter- chlorophyll a products based on satellite observation (SeaW- comparison with in situ data. iFS, MERIS, MODIS, VIIRS and OLCI) and disseminated in the framework of the Copernicus Marine Environmental Monitoring Service (CMEMS). This work highlights the main advantages provided by the 1 Introduction Copernicus GlobColour processor which is used to serve CMEMS with a long time series from 1997 to present at The Copernicus Marine Environmental Service (CMEMS) the global level (4 km spatial resolution) and for the Atlantic provides regular and systematic reference information on the level 4 product (1 km spatial resolution). physical state and on marine ecosystems for global oceans To compute the merged chlorophyll a product, two major and for European regional seas, including temperature, cur- topics are discussed: rents, salinity, sea surface height, sea ice, marine optical properties and other such parameters. – The first of these topics is the strategy for merging This capacity encompasses satellite and in situ data- remote-sensing data, for which two options are consid- derived products, the description of the current situation ered.
    [Show full text]
  • Sentinel-2 and Sentinel-3 Mission Overview and Status
    Sentinel-2 and Sentinel-3 Mission Overview and Status Craig Donlon – Sentinel-3 Mission Scientist and Ferran Gascon – Sentinel-2 QC manager and others @ESA IOCCG-21, Santa Monica, USA 1-3rd March 2016 Overview – What is Copernicus? – Sentinel-2 mission and status – Sentinel-3 mission and status Sentinel-3A OLCI first light Svalbard: 29 Feb 14:07:45-14:09:45 UTC Bands 4, 6 and 7 (of 21) at 490, 560, 620 nm Spain and Gibraltar 1 March 10:32:48-10:34:48 UTC California USA 29 Feb 17:44:54-17:46:54 UTC What is Copernicus? Space Component In-Situ Services A European Data Component response to global needs 6 What is Copernicus? – Space in Action for You! • A source of information for policymakers, industry, scientists, business and the public • A European response to global issues: • manage the environment; • understand and to mitigate the effects of climate change; • ensure civil security • A user-driven programme of services for environment and security • An integrated Earth Observation system (combining space-based and in-situ data with Earth System Models) Components & Competences Coordinators: Partners: Private Space Industries companies Component National Space Agencies Overall Programme EMCWF EMSA Mercator snd Ocean Coordination FRONTEX Service Services operators Component EUSC EEA JRC In-situ data are supporting the Space and Services Components Copernicus Funding Funding for Development Funding for Operational Phase until 2013 (c.e.c.): Phase as from 2014 (c.e.c.): ~€ 3.7 B (from ESA and € 4.3 B for the EU) whole programme (from EU)
    [Show full text]
  • Synthetic Aperture Radar in Europe: ERS, Envisat, and Beyond
    SYNTHETIC APERTURE RADAR IN EUROPE Synthetic Aperture Radar in Europe: ERS, Envisat, and Beyond Evert Attema, Yves-Louis Desnos, and Guy Duchossois Following the successful Seasat project in 1978, the European Space Agency used advanced microwave radar techniques on the European Remote Sensing satellites ERS-1 (1991) and ERS-2 (1995) to provide global and repetitive observations, irrespective of cloud or sunlight conditions, for the scientific study of the Earth’s environment. The ERS synthetic aperture radars (SARs) demonstrated for the first time the feasibility of a highly stable SAR instrument in orbit and the significance of a long-term, reliable mission. The ERS program has created opportunities for scientific discovery, has revolutionized many Earth science disciplines, and has initiated commercial applica- tions. Another European SAR, the Advanced SAR (ASAR), is expected to be launched on Envisat in late 2000, thus ensuring the continuation of SAR data provision in C band but with important new capabilities. To maximize the use of the data, a new data policy for ERS and Envisat has been adopted. In addition, a new Earth observation program, The Living Planet, will follow Envisat, offering opportunities for SAR science and applications well into the future. (Keywords: European Remote Sensing satellite, Living Planet, Synthetic aperture radar.) INTRODUCTION In Europe, synthetic aperture radar (SAR) technol- Earth Watch component of the new Earth observation ogy for polar-orbiting satellites has been developed in program, The Living Planet, and possibly the scientific the framework of the Earth observation programs of Earth Explorer component will include future SAR the European Space Agency (ESA).
    [Show full text]
  • Envisat and MERIS Status
    MERIS US Workshop 14 July 2008 MERIS US Workshop, Silver Spring, July 14th, 2008 MERIS US Workshop Agenda a.m. ENVISAT/MERIS mission status, access to MERIS data 08:10-08:55 H. Laur (ESA) and distribution policy 08:55-09:10 Discussion Examples of the use of MERIS data in marine & land 09:10-09:40 P. Regner (ESA) applications 09:40-10:00 B. Arnone (NRL) Examples of MERIS data use for U.S. applications 10:00-10:20 S. Delwart (ESA) MERIS instrument overview 10:20-10:40 S. Delwart Instrument characterization overview 10:40-10:55 Discussion 10:55-11:10 Coffee break 11:10-11:30 S. Delwart Instrument calibration methods and results 11:30-11:50 Discussion 11:50-13:20 Lunch break MERIS US Workshop, Silver Spring, July 14th, 2008 MERIS US Workshop Agenda p.m. 13:20-13:50 L. Bourg (ACRI) Level 1 processing 13:50-14:10 Discussion 14:10-14:30 S. Delwart Vicarious calibration methods and results 14:30-14:50 Discussion 14:50-15:10 L. Bourg Overview Level 2 products 15:10-15:25 Coffee break 15:25-16:25 L. Bourg Level 2 processing 16:25-17:10 Discussion 17:10-17:25 P. Regner BEAM Toolbox 17:25-17:40 H. Laur Plans and status of the OLCI onboard GMES Sentinel-3 17:40-18:00 Discussion MERIS US Workshop, Silver Spring, July 14th, 2008 MERIS US Workshop, July 14th, 2008, Washington (USA) ENVISAT / MERIS mission status, access to MERIS data and distribution policy Henri LAUR Envisat Mission Manager & Head of EO Missions Management Office MERIS US Workshop, Silver Spring, July 14th, 2008 ESA: the European Space Agency The purpose of ESA: An inter-governmental
    [Show full text]
  • Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument Imagery in the Baltic Sea
    remote sensing Article Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument Imagery in the Baltic Sea Kaire Toming 1,2,3 ID , Tiit Kutser 1,*, Rivo Uiboupin 4, Age Arikas 4, Kaimo Vahter 4 and Birgot Paavel 1 1 Estonian Marine Institute, University of Tartu, Mäealuse 14, 12618 Tallinn, Estonia; [email protected] (K.T.); [email protected] (B.P.) 2 Centre for Limnology, Estonian University of Life Sciences, Kreutzwaldi 5, 51014 Tartu, Estonia 3 Department of Ecology and Genetics/Limnology, Uppsala University, Norbyvägen 18D, 75236 Uppsala, Sweden 4 Department of Marine Systems, School of Science, Tallinn University of Technology, Akadeemia Road 15a, 12618 Tallinn, Estonia; [email protected] (R.U.); [email protected] (A.A.); [email protected] (K.V.) * Correspondence: [email protected]; Tel.: +372-6718-947 Received: 2 August 2017; Accepted: 12 October 2017; Published: 20 October 2017 Abstract: The launch of Ocean and Land Colour Instrument (OLCI) on board Sentinel-3A in 2016 is the beginning of a new era in long time, continuous, high frequency water quality monitoring of coastal waters. Therefore, there is a strong need to validate the OLCI products to be sure that the technical capabilities provided will be used in the best possible way in water quality monitoring and research. The Baltic Sea is an optically complex waterbody where many ocean colour products, performing well in other waterbodies, fail. We tested the performance of standard Case-2 Regional/Coast Colour (C2RCC) processing chain in retrieving water reflectance, inherent optical properties (IOPs), and water quality parameters such as chlorophyll a, total suspended matter (TSM) and coloured dissolved organic matter (CDOM) in the Baltic Sea.
    [Show full text]
  • A New Orbiting Carbon Observatory 2 Cloud Flagging Method and Rapid
    Atmos. Meas. Tech., 13, 4947–4961, 2020 https://doi.org/10.5194/amt-13-4947-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. A new Orbiting Carbon Observatory 2 cloud flagging method and rapid retrieval of marine boundary layer cloud properties Mark Richardson1,2, Matthew D. Lebsock1, James McDuffie1, and Graeme L. Stephens1,2,3 1Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA 2Department of Atmospheric Science, Colorado State University, Fort Collins, CO 90095, USA 3Department of Meteorology, University of Reading, Reading, RG6 7BE, UK Correspondence: Mark Richardson ([email protected]) Received: 8 April 2020 – Discussion started: 18 May 2020 Revised: 16 July 2020 – Accepted: 28 July 2020 – Published: 18 September 2020 Abstract. The Orbiting Carbon Observatory 2 (OCO-2) car- 1 Introduction ries a hyperspectral A-band sensor that can obtain informa- tion about cloud geometric thickness (H). The OCO2CLD- LIDAR-AUX product retrieved H with the aid of collocated Hyperspectral O2 A-band measurements near λ D 0:78 µm, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder such as those taken by the Orbiting Carbon Observatory-2 Satellite Observation) lidar data to identify suitable clouds (OCO-2), may provide unique new information about bound- H and provide a priori cloud top pressure (Ptop). This colloca- ary layer clouds by retrieving their geometric thickness ( ) tion is no longer possible, since CALIPSO’s coordination fly- or droplet number concentration (Nd), provided coincident ing with OCO-2 has ended, so here we introduce a new cloud information about effective radius (re) from other channels.
    [Show full text]
  • 6.12 News Feat Earth Nightmare MH AY
    NATURE|Vol 450|6 December 2007 EARTH MONITORING NEWS FEATURE overlap between monitoring systems is another. in providing more information. the same time that NASA had been planning Frequently the problem is international; one José Achache, secretariat of the Group on the Hydrosphere State (Hydros) mission for country launches a spacecraft that partially Earth Observations in Geneva, Switzerland, is soil moisture — which has since been put on duplicates what another mission is already not so sure that duplication is a good way for- indefinite hold — and the Aquarius mission for doing. International steering committees are ward. “Essentially the agencies were in unofficial ocean salinity. supposed to cut down on the overlap, but it competition,” he says. An international steering Sometimes, though, the US–European doesn’t always work that way. “Our hope is group, the Committee on Earth Observation competition can work in science’s favour. not just to fill gaps, but to avoid duplication Satellites, exists to try to cut down on dupli- With SeaWiFS possibly close to dying, NASA of effort,” says Helen Wood, a senior adviser cation for satellite-based systems, but some- is looking at how it can jump in on the Euro- to NOAA’s satellite and information services times national interests win out. The European pean MERIS instrument, aboard Envisat, to division in Silver Spring, Maryland. Space Agency, for instance, is planning a Soil get ocean-colour data, says Paula Bontempi Moisture and Ocean Salinity mission — meas- of NASA headquarters in Washington DC. Poles apart uring two of the essential climate variables — at Although the data may not be all that the In 2003, NASA launched its ICESat mis- scientists wish they were, they will be bet- sion mainly to study the ice sheets ter than nothing once SeaWiFS gives out.
    [Show full text]
  • SPOT-4 (Take 5): Simulation of Sentinel-2 Time Series on 45 Large Sites
    Remote Sens. 2015, 7, 12242-12264; doi:10.3390/rs70912242 OPEN ACCESS remote sensing ISSN 2072-4292 www.mdpi.com/journal/remotesensing Article SPOT-4 (Take 5): Simulation of Sentinel-2 Time Series on 45 Large Sites Olivier Hagolle 1;∗, Sylvia Sylvander 2, Mireille Huc 1, Martin Claverie 3, Dominique Clesse 4, Cécile Dechoz 2, Vincent Lonjou 2 and Vincent Poulain 5 1 Centre d’études Spatiales de la Biosphère, CESBIO Unite mixte Université de Toulouse-CNES-CNRS-IRD, 18 avenue E.Belin, 31401 Toulouse Cedex 9, France; E-Mail: [email protected] 2 CNES, 18 avenue Edouard Belin 31401 Toulouse Cedex 9, France; E-Mails: [email protected] (S.S.); [email protected] (C.D.); [email protected] (V.L.) 3 NASA GSCF, Code 619, Bldg 32, N149-6, Greenbelt, MD 20771, USA; E-Mail: [email protected] 4 Capgemini Technology Services, 109 avenue Eisenhower - BP 53655, 31036 Toulouse Cedex 1, France; E-Mail: [email protected] 5 Thales Services, 3 avenue de l’Europe - Bat. D, 31400 Toulouse, France; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +33-56-128-2135. Academic Editors: Benjamin Koetz, Richard Müller and Prasad S. Thenkabail Received: 25 May 2015 / Accepted: 10 September 2015 / Published: 21 September 2015 Abstract: This paper presents the SPOT-4 (Take 5) experiment, aimed at providing time series of optical images simulating the repetitivity, the resolution and the large swath of Sentinel-2 images. The aim was to help users set up and test their applications and methods, before Sentinel-2 mission data become available.
    [Show full text]
  • Status of Envisat / MERIS GMES Sentinel-3 Coastcolour
    Status of Envisat / MERIS . GMES Sentinel-3 . CoastColour Peter Regner European Space Agency We care for a safer world 15th IOCCG Committee Meeting, 18-20 January 2010 Sentinel–3: Mission overview and status Ocean and global land mission Credit: Sentinel & GS development teams We care for a safer world GMES dedicated missions: Sentinels Sentinel 1 – SAR imaging All weather, day/night applications, interferometry 2012 Sentinel 2 – Multispectral imaging Land applications: urban, forest, agriculture,.. Continuity of Landsat, SPOT 2013 Sentinel 3 – Ocean and global land monitoring Wide-swath ocean color, vegetation, sea/land surface temperature, altimetry 2013 Sentinel 4 – Geostationary atmospheric Atmospheric composition monitoring, trans- boundary pollution 2017+ Sentinel 5 precursor – Low-orbit atmospheric Atmospheric composition monitoring 2014 We care for a safer world Sentinel–3 overview Sentinel-3 will provide an operational service for the collection of EO data for global sea and land applications over 15 to 20 years OLCI Ocean and Land Color Instrument at least at the level of quality of the MERIS MWR SLSTR Sea & Land Surface Temperature Rad. OLCI at least at the level of quality of the AATSR Sea surface topography payload Ku-/C-band Synthetic Aperture Radar Altimeter at least at the level of quality of the Envisat RA SLSTR Operational mission . High inclination (98.65°), Sun-synchronous LEO . Average altitude: 814.5 km over geoid X band antenna . Repeat cycle: 27 days (14+7/27 orbits/day) . Equatorial crossing time: 10:00 am SRAL
    [Show full text]