Academic literature on the topic 'Satellite SeaWIFS'
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Journal articles on the topic "Satellite SeaWIFS"
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Moore, J. Keith, Mark R. Abbott, James G. Richman, Walker O. Smith, Timothy J. Cowles, Kenneth H. Coale, Wilford D. Gardner, and Richard T. Barber. "SeaWiFS satellite ocean color data from the Southern Ocean." Geophysical Research Letters 26, no. 10 (May 15, 1999): 1465–68. http://dx.doi.org/10.1029/1999gl900242.
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Jönsson, L. "SeaWiFs satellite data analysis of Black Sea water discharge pattern into the Aegean Sea." Water Science and Technology 46, no. 8 (October 1, 2002): 195–202. http://dx.doi.org/10.2166/wst.2002.0180.
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Satellite data from the SeaWiFS sensor has been used to determine chlorophyll-a contents in the North Aegean Sea using SEADAS 3.3 software. The data is used to extract knowledge on water movements/flow phenomena using chlorophyll as a “tracer” but will also indicate water quality. More than 100 SeaWiFS scenes from 1998 up to 2001 have been analyzed in terms of hydrodynamic phenomena, mainly the transport and spreading pattern of Black Sea Water in the North Aegean Sea but also concerning the water quality and its seasonal and yearly variation at the mouth region of the Dardanelles. Some comparison with earlier studies using NOAA AVHRR thermal data and historical CZCS scenes is also made.
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Djavidnia, S., F. Mélin, and N. Hoepffner. "Comparison of global ocean colour data records." Ocean Science 6, no. 1 (January 27, 2010): 61–76. http://dx.doi.org/10.5194/os-6-61-2010.
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Abstract. The extending record of ocean colour derived information, an important asset for the study of marine ecosystems and biogeochemistry, presently relies on individual satellite missions launched by several space agencies with differences in sensor design, calibration strategies and algorithms. In this study we present an extensive comparative analysis of standard products obtained from operational global ocean colour sensors (SeaWiFS, MERIS, MODIS-Aqua, MODIS-Terra), on both global and regional scales. The analysis is based on monthly mean chlorophyll a (Chl-a) sea surface concentration between 2002 and 2009. Based on global statistics, the Chl-a records appear relatively consistent. The root mean square (RMS) difference Δ between (log-transformed) Chl-a from SeaWiFS and MODIS Aqua amounts to 0.137, with a bias of 0.074 (SeaWiFS Chl-a higher). The difference between these two products and MERIS Chl-a is approximately 0.15. Restricting the analysis to 2007 only, Δ between MODIS Aqua and Terra is 0.142. This global convergence is significantly modulated regionally. Statistics for biogeographic provinces representing a partition of the global ocean, show Δ values varying between 0.08 and 0.3. High latitude regions, as well as coastal and shelf provinces are generally the areas with the largest differences. Moreover, RMS differences and biases are modulated in time, with a coefficient of variation of Δ varying between 10% and 40%, with clear seasonal patterns in some provinces. The comparison of the province-averaged time series obtained from the various satellite products also shows a level of agreement that is geographically variable. Overall, the Chl-a SeaWiFS and MODIS Aqua series appear to have similar levels of variance and display high correlation coefficients, an agreement likely favoured by the common elements shared by the two missions. These results are degraded if the MERIS series is compared to either SeaWiFS or MODIS Aqua. An important outcome of the study is that the results of the inter-comparison analysis are variable with time and location, and therefore globally averaged statistics are not necessarily applicable on a seasonal or regional basis.
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Djavidnia, S., F. Mélin, and N. Hoepffner. "Comparative analysis of the multi-sensor global ocean colour data record." Ocean Science Discussions 6, no. 2 (July 23, 2009): 1611–53. http://dx.doi.org/10.5194/osd-6-1611-2009.
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Abstract. The extending record of ocean colour derived information, an important asset for the study of marine ecosystems and biogeochemistry, presently relies on individual satellite missions launched by several space agencies with differences in sensor design, calibration strategies and algorithms. In this study we present an extensive comparative analysis of standard products obtained from operational global ocean colour sensors (SeaWiFS, MERIS, MODIS-Aqua, MODIS-Terra), on both global and regional scales. The analysis is based on monthly mean chlorophyll-a (Chl-a) surface concentration between 2002 and 2009. Based on global statistics, the Chl-a records appear relatively consistent. The root mean square (RMS) difference Δ between (log-transformed) Chl-a from SeaWiFS and MODIS Aqua amounts to 0.137, with a bias of 0.074 (SeaWiFS Chl-a higher). The difference between these two products and MERIS Chl-a is approximately 0.15. Restricting the analysis to 2007 only, Δ between MODIS Aqua and Terra is 0.142. This global convergence is significantly modulated regionally. Statistics for biogeographic provinces representing a partition of the global ocean, show Δ values varying between 0.08 and 0.3. High latitude regions, as well as coastal and shelf provinces are generally the areas with the largest differences. Moreover, RMS differences and biases are modulated in time, with a coefficient of variation of Δ varying between 10% and 40%, with clear seasonal patterns in some provinces. The comparison of the province-averaged time series obtained from the various satellite products also shows a level of agreement that is geographically variable. Overall, the Chl-a SeaWiFS and MODIS Aqua series appear to have similar levels of variance and display high correlation coefficients, an agreement likely favoured by the common elements shared by the two missions. These results are degraded if the MERIS series is compared to either SeaWiFS or MODIS Aqua. An important outcome of the study is that the results of the inter-comparison analysis are variable with time and location, and therefore globally averaged statistics are not necessarily applicable on a seasonal or regional basis.
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Montes-Hugo, M., H. Bouakba, and R. Arnone. "Performance evaluation of ocean color satellite models for deriving accurate chlorophyll estimates in the Gulf of Saint Lawrence." Biogeosciences Discussions 11, no. 6 (June 17, 2014): 9299–340. http://dx.doi.org/10.5194/bgd-11-9299-2014.
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Abstract. The understanding of phytoplankton dynamics in the Gulf of the Saint Lawrence (GSL) is critical for managing major fisheries off the Canadian East coast. In this study, the accuracy of two atmospheric correction techniques (NASA standard algorithm, SA, and Kuchinke's spectral optimization, KU) and three ocean color inversion models (Carder's empirical for SeaWiFS (Sea-viewing Wide Field-of-View Sensor), EC, Lee's quasi-analytical, QAA, and Garver- Siegel-Maritorena semi-empirical, GSM) for estimating the phytoplankton absorption coefficient at 443 nm (aph(443)) and the chlorophyll concentration (chl) in the GSL is examined. Each model was validated based on SeaWiFS images and shipboard measurements obtained during May of 2000 and April 2001. In general, aph(443) estimates derived from coupling KU and QAA models presented the smallest differences with respect to in situ determinations as measured by High Pressure liquid Chromatography measurements (median absolute bias per cruise up to 0.005, RMSE up to 0.013). A change on the inversion approach used for estimating aph(443) values produced up to 43.4% increase on prediction error as inferred from the median relative bias per cruise. Likewise, the impact of applying different atmospheric correction schemes was secondary and represented an additive error of up to 24.3%. By using SeaDAS (SeaWiFS Data Analysis System) default values for the optical cross section of phytoplankton (i.e., aph(443) = aph(443)/chl = 0.056 m2mg−1), the median relative bias of our chl estimates as derived from the most accurate spaceborne aph(443) retrievals and with respect to in situ determinations increased up to 29%.
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Clay, Stephanie, Angelica Peña, Brendan DeTracey, and Emmanuel Devred. "Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans." Remote Sensing 11, no. 22 (November 7, 2019): 2609. http://dx.doi.org/10.3390/rs11222609.
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Remote-sensing reflectance data collected by ocean colour satellites are processed using bio-optical algorithms to retrieve biogeochemical properties of the ocean. One such important property is the concentration of chlorophyll-a, an indicator of phytoplankton biomass that serves a multitude of purposes in various ocean science studies. Here, the performance of two generic chlorophyll-a algorithms (i.e., a band ratio one, Ocean Colour X (OCx), and a semi-analytical one, Garver–Siegel Maritorena (GSM)) was assessed against two large in situ datasets of chlorophyll-a concentration collected between 1999 and 2016 in the Northeast Pacific (NEP) and Northwest Atlantic (NWA) for three ocean colour sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). In addition, new regionally-tuned versions of these two algorithms are presented, which reduced the mean error (mg m−3) of chlorophyll-a concentration modelled by OCx in the NWA from −0.40, −0.58 and −0.45 to 0.037, −0.087 and −0.018 for MODIS, SeaWiFS, and VIIRS respectively, and −0.34 and −0.36 to −0.0055 and −0.17 for SeaWiFS and VIIRS in the NEP. An analysis of the uncertainties in chlorophyll-a concentration retrieval showed a strong seasonal pattern in the NWA, which could be attributed to changes in phytoplankton community composition, but no long-term trends were found for all sensors and regions. It was also found that removing the 443 nm waveband for the OCx algorithms significantly improved the results in the NWA. Overall, GSM performed better than the OCx algorithms in both regions for all three sensors but generated fewer chlorophyll-a retrievals than the OCx algorithms.
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Chen, Chuqun, Lennart Jönsson, and Magnus Larson. "Parameters to Characterize Biological Conditions in Marine and Coastal Waters Retrieved from SeaWiFS Data." Marine Technology Society Journal 36, no. 1 (March 1, 2002): 14–22. http://dx.doi.org/10.4031/002533202787914223.
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SeaWiFS satellite data were employed to demonstrate how the biological conditions in marine and coastal waters may be characterized using the concentration of chlorophyll-α (chl-α) and dissolved organic carbon (DOC) as the leading parameters. In marine waters the standard algorithms from the SeaWiFS Data Analysis System (SeaDAS) package were used to derive the concentrations, whereas in coastal waters special algorithms were developed using field data and a simulation model for the irradiance reflectance. Analysis of the Sea-WiFS data were performed for two study areas, namely the North Aegean Sea between Greece and Turkey and the Pearl River Estuary in southern China. The analysis displayed the temporal and spatial distribution of chl-α and DOC as well as the movement and exchange of water masses. Such results are of great use for monitoring and forecasting the biological conditions in marine and coastal waters.
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Fan, Xia, and Chen. "Intercomparison of Multiple Satellite Aerosol Products against AERONET over the North China Plain." Atmosphere 10, no. 9 (August 21, 2019): 480. http://dx.doi.org/10.3390/atmos10090480.
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In this study, using Aerosol Robotic Network aerosol optical depth (AOD) products at three stations in the North China Plain (NCP)—a heavily polluted region in China—the AOD products from six satellite-borne radiometers: the Moderate Resolution Imagining Spectroradiometer (MODIS), the Multiangle Imaging Spectroradiometer (MISR), Ozone Mapping Imaging (OMI), the Visible Infrared Imaging Radiometer (VIIRS), the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), and Polarization and Directionality of the Earth’s Reflectances (POLDER), were thoroughly validated, shedding new light on their advantages and disadvantages. The MODIS Deep Blue (DB) products provide more accurate retrievals than the MODIS Dark Target (DT) and other satellite products at the Beijing site (BJ,a megacity), with higher correlations with AERONET (R > 0.93), lower mean absolute bias (MB < 0.012), and higher percentages (>68%) falling within the expected error (EE). All MODIS DT and DB products perform better than the other satellite products at the Xianghe site (XH, a suburb). The MODIS/Aqua DT products at both 3-km and 10-km resolutions performed better than the other space-borne AOD products at the Xinglong site (XL, a rural area at the top of a mountain). MISR, VIIRS, and SeaWiFS tend to underestimate high AOD values and overestimate AOD values under very low AOD conditions in the NCP. Both OMI and POLDER significantly underestimate the AOD. In terms of data volume, MISR with the limited swath width of 380 km has less data volume than the other satellite sensors. MODIS products have the highest sampling rate, especially the MODIS DT and DB merged products, and can be used for various climate study and air-quality monitoring.
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Beaulieu, C., S. A. Henson, J. L. Sarmiento, J. P. Dunne, S. C. Doney, R. R. Rykaczewski, and L. Bopp. "Factors challenging our ability to detect long-term trends in ocean chlorophyll." Biogeosciences Discussions 9, no. 11 (November 20, 2012): 16419–56. http://dx.doi.org/10.5194/bgd-9-16419-2012.
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Abstract. Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multidecadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), which failed in December 2010. The Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS) instrument, or successful launch of the Ocean Land Colour Instrument (OLCI) in 2013 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation) especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies.
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Petrenko, M., and C. Ichoku. "Coherent uncertainty analysis of aerosol measurements from multiple satellite sensors." Atmospheric Chemistry and Physics Discussions 13, no. 2 (February 18, 2013): 4637–85. http://dx.doi.org/10.5194/acpd-13-4637-2013.
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Abstract. Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS – altogether, a total of 11 different aerosol products – were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006–2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow/ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.
Dissertations / Theses on the topic "Satellite SeaWIFS"
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Heim, Birgit. "Qualitative and quantitative analyses of Lake Baikal's surface-waters using ocean colour satellite data (SeaWiFS)." Phd thesis, Universität Potsdam, 2005. http://opus.kobv.de/ubp/volltexte/2006/718/.
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One of the most difficult issues when dealing with optical water remote-sensing is its acceptance as a useful application for environmental research. This problem is, on the one hand, concerned with the optical complexity and variability of the investigated natural media, and therefore the question arises as to the plausibility of the parameters derived from remote-sensing techniques. Detailed knowledge about the regional bio- and chemico-optical properties is required for such studies, however such information is seldom available for the sites of interest. On the other hand, the primary advantage of remote-sensing information, which is the provision of a spatial overview, may not be exploited fully by the disciplines that would benefit most from such information. It is often seen in a variety of disciplines that scientists have been primarily trained to look at discrete data sets, and therefore have no experience of incorporating information dealing with spatial heterogeneity.
In this thesis, the opportunity was made available to assess the potential of Ocean Colour data to provide spatial and seasonal information about the surface waters of Lake Baikal (Siberia). While discrete limnological field data is available, the spatial extension of Lake Baikal is enormous (ca. 600 km), while the field data are limited to selected sites and expedition time windows. Therefore, this remote-sensing investigation aimed to support a multi-disciplinary limnological investigation within the framework of the paleoclimate EU-project ‘High Resolution CONTINENTal Paleoclimate Record in Lake Baikal, Siberia (CONTINENT)’ using spatial and seasonal information from the SeaWiFS satellite (NASA). From this, the SeaWiFS study evolved to become the first efficient bio-optical satellite study of Lake Baikal.
During the course of three years, field work including spectral field measurements and water sampling, was carried out at Lake Baikal in Southern Siberia, and at the Mecklenburg and Brandenburg lake districts in Germany. The first step in processing the SeaWiFS satellite data involved adapting the SeaDAS (NASA) atmospheric-correction processing to match as close as possible the specific conditions of Lake Baikal. Next, various Chl-a algorithms were tested on the atmospherically-corrected optimized SeaWiFS data set (years 2001 to 2002), comparing the CONTINENT pigment ground-truth data with the Chl-a concentrations derived from the satellite data. This showed the high performance of the global Chl-a products OC2 and OC4 for the oligotrophic, transparent waters (bio-optical Case 1) of Lake Baikal. However, considerable Chl-a overestimation prevailed in bio-optical Case 2 areas for the case of discharge events. High-organic terrigenous input into Lake Baikal could be traced and information extracted using the SeaWiFS spectral data. Suspended Particulate Matter (SPM) was quantified by the regression of the SeaDAS attenuation coefficient as the optical parameter with SPM field data.
Finally, the Chl-a and terrigenous input maps derived from the remote sensing data were used to assist with analyzing the relationships between the various discrete data obtained during the CONTINENT field work. Hence, plausible spatial and seasonal information describing autochthonous and allochthonous material in Lake Baikal could be provided by satellite data.
Lake Baikal, with its bio-optical complexity and its different areas of Case 1 and Case 2 waters, is a very interesting case study for Ocean Colour analyses. Proposals for future Ocean Colour studies of Lake Baikal are discussed, including which bio-optical parameters for analytical models still need to be clarified by field investigations.
Die Gewässerfernerkundung entwickelte sich seit den 70ern vor allem aus der Ozeanographie und der Atmosphärenforschung, und wird inzwischen als anerkannte Methode genutzt, um global die Phytoplanktonverteilung in den Weltmeeren erfassen zu können, u.a. für CO2-Haushaltsmodellierungen. Atmosphärenkorrigierte Multi- und Hyperspektralscannerdaten ermöglichen die Qualifizierung bio-optischer Gewässertypen und die Quantifizierung optisch sichtbarer Wasserinhaltsstoffe und bieten gerade auch für dynamische und heterogene Küsten- und Binnengewässer das große Potential des räumlichen Informationsgewinnes.
Im Rahmen des Paläoklimaprojektes CONTINENT wurde in dieser Arbeit das Oberflächenwasser des Baikalsees mit Gewässerfernerkungsmethoden analysiert. Wichtig für die Interpretation von Klima-Proxies sind v.a. auch Hinweise auf die Verteilung des autochthonen Materials im Baikalsee (Fernerkundungsparameter: Chlorophyll-a), ebenso wie Hinweise auf allochthone Einträge an den Bohrungsstellen (Fernerkundungsparameter ‚Terrigener Eintrag’). Auf den Geländekampagnen in den Sommern 2001, 2002, 2003 in Sibirien und in Deutschland wurden Feldspektrometermessungen mit gleichzeitiger Wasserprobenahme auf die optisch sichtbaren Wasserinhaltsstoffe Phytoplankton, Schwebstoff, und DOC durchgeführt. Dabei konnten Messtechniken für Geländespektrometer evaluiert, und grundlegende Aussagen über die spektrale Verteilung des In-Wasser Lichtfeldes im Baikalsee gemacht werden.
Die Ocean Colour Satellitendaten des NASA-Instrumentes SeaWiFS und die Möglichkeiten der komplexen NASA Software SeaDAS wurden genutzt. Für die Ableitung des am Baikalsee anzutreffenden organikreichen terrigenen Eintrages, wurde ein vorläufiger Algorithmus aus den Geländedaten generiert. Verschiedene Algorithmen für den Parameter ‚Chlorophyll-a’ wurden mit dem Geländedatensatz der Projektpartnerin S. Fietz (Institut für Gewässerökologie und Binnenfischerei, IGB) evaluiert. Als geeignetester etablierte sich der auf oligotrophe Gewässer optimierte NASA Chlorophyll Algorithmus ‚Ocean Colour (OC) 2’. Die Quantifizierungen und Ergebnisse werden diskutiert.
Als Endergebnis wird der Überblick über Sedimenteintrag und Phytoplanktondynamik im Baikalsee für den Zeitraum 2001-2002 zur Verfügung gestellt und die autochthonen versus allochthonen Einflüsse an den Projektlokationen werden beschrieben. Der Baikalsee erwies sich als bio-optisch ein sehr komplexes und interessantes Studienobjekt. Ein wichtiger Punkt, der in dieser Arbeit angesprochen wird, ist die Atmosphärenkorrektur, die wesentliche Einflüsse auf die Qualifizierungen und Quantifizierungen hat, aber als Standardprogramm nur für den pelagialen Wasserkörper in Meeresspiegelhöhe mit marinen, bzw. Küstenatmosphären konditioniert ist. Ein weiterer bedeutender Punkt, der in dieser Arbeit diskutiert wird, ist der relevante spektrale Einfluss des organikreichen terrigenen Eintrages auf die Gewässerfarbe und dadurch auf die Qualität der Chlorophyll-Ableitung. Somit boten sich die Möglichkeiten, das räumliche Ausmaß und die Dynamik rezenter terrigener Einträge zu erfassen. Auch die Entwicklung des Phytoplankton von Frühsommer bis Spätsommer im Baikalsee konnte mit den SeaWiFS Daten nachvollzogen werden. Die hier vorgestellte Studie stellte sich als die erste grundlegende optische Gewässerfernerkundungsstudie mit Satellitendaten am Baikalsee heraus, und konnte erfolgreich abgeschlossen werden.
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Heim, Brigitte. "Qualitative and quantitative analyses of Lake Baikal's surface waters using ocean colour satellite data (SeaWiFS)." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980077656.
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Alvain, Séverine. "Etude de la distribution des principaux groupes de phytoplancton par télédétection satellitaire : développement de la méthode PHYSAT à partir des données GeP&CO et application à l'archive SEAWIFS entre 1998 et 2004." Paris 7, 2005. https://tel.archives-ouvertes.fr/tel-00157372.
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Vanderbloemen, Lisa Anne. "Satellite analysis of temporal and spatial chlorophyll patterns on the West Florida shelf (1997-2003)." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001749.
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Masotti, Italo. "Dynamique des cyanobactéries fixatrices d'azote (Trichodesmium) : du Pacifique Sud-Ouest à l'océan global." Paris 6, 2007. http://www.theses.fr/2007PA066632.
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La fixation d’azote, N2 (N2fix) par les cyanobactéries, avec une introduction d’azote nouveau dans la couche éclairée, contrôlerait dans l’océan le déséquilibre actuel du cycle de l’azote, la productivité des régions les plus pauvres (oligotrophes) et la quantité de CO2 de l’atmosphère pompée par l’océan. Comment varie et quels sont les processus physiques et biogéochimiques qui contrôlent la distribution de cyanobactéries fixatrice d’azote et leur N2fix dans l’océan ? Quel est l’effet de rétroaction de la fixation de N2 sur la productivité et sur la pompe biologique de CO2? Afin de répondre à ces questions, seront évaluées la distribution et la N2fix due à la plus cosmopolite de cyanobactéries : Trichodesmium. En partant d’une étude focalisée dans le Pacifique sud-ouest, les résultats seront étendus à l’océan global. La stratégie est pluridisciplinaire et couple l’acquisition de nouvelles données in situ, in situ simulées, en laboratoire; satellitales (SeaWiFS) et le développement de modèles mathématiques. La N2fix de Trichodesmium est majoritaire dans : les régions oligotrophes de gyres anticycloniques subtropicales de grands bassins, qui associées à de convergences, restent pauvres en nutriments et en métaux et lors de conditions de forte stratification et fort éclairement (l’été et jusqu’à 20m). La fixation de N2 serait en conséquence plutôt contrôlée par la disponibilité lumineuse qui imposent les forts besoins énergétiques de ce mécanisme que par le fer. Se développant sous la forme d’accumulations étendues, ces cyanobactéries apparaissent comme un moteur biologique de fertilisation, qui conduit à la formation des oasis étendues de relative forte biomasse phytoplanctonique et forte séquestration de CO2. La fabrication de ces oasis modifie la vision traditionnelle d’extrême pauvreté et de faible pompage biologique de CO2 des océans oligotrophes.
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Yoho, Peter Kenneth. "Satellite Scatterometers: Calibration Using a Ground Station and Statistical Measurement Theory." BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/110.
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Satellite scatterometers have recently gained popularity due to their unique ability to measure global geophysical data on a daily basis. Increased interest in scatterometry mandates improved design and calibration of these instruments. This dissertation presents new techniques for scatterometer calibration and addresses issues related to the design of future instruments and applications. First, the use of a calibration ground station is considered. A new methodology is established for calibration of SeaWinds, NASA's current scatterometer, using a receive-only ground station. Principles of the methodology are implemented, new analysis techniques developed, and important results obtained for instrument timing, frequency, power, position, and pointing. Second, an investigation into methods for calibration of measurement surface location is conducted. Two new approaches are proposed and results of both approaches using SeaWinds data are provided. Third, measurement correlation, a critical issue related to new scatterometer designs, particularly those which significantly oversample the surface is considered. General statistical expressions for measurement correlation are derived and analysis of the effects on data variance is presented. Finally, a new data simulation model is developed to support instrument and application development. New applications require sophisticated models which are general, yet accurate, enabling them to rapidly and easily simulate data from multiple instruments. The model generates data which is statistically equivalent (in a mean and variance sense) to actual scatterometer measurements by separately accounting for the two main forms of variation present in scatterometer data, multiplicative fading and additive noise, and also accounting for correlation between measurements. The model is valuable for a variety of data applications including image generation and high resolution wind retrieval.
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Vidot, Jérôme. "Télédétection des aérosols au dessus des terres émergées à l'aide des capteurs "couleur de l'eau" et applications." Littoral, 2005. https://tel.archives-ouvertes.fr/tel-00011216.
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Le travail de thèse s'est organisé autour de l'application de l'algorithme de télédétection des aérosols au-dessus des terres émergées développé pour le capteur ENVISAT/MERIS sur une base de données du capteur SeaSTAR/SeaWiFS. La télédétection des aérosols au-dessus des terres émergées est basée sur la détection des cibles de végétation sombre dans le bleu et le rouge (DDV) à l'aide d'un seuil sur l'ARVI. Le point critique de l'algorithme est la faible couverture du produit aérosol (inférieur à 2% des terres émergées). Pour remédier à cette faible couverture, le concept de DDV a été étendu à des surfaces plus brillantes appelées LARS. La réflectance des LARS est modélisée grâce à la linéarité de la réflectance de surface en fonction de l'ARVI. Une étude statistique sur les données SeaWiFS basée sur l'homogénéitéspatiale des aérosols sur ces petites sous scènes a permis de confirmer le nouveau modèle établi par HYGEOS sur les données MERIS. La comparaison des produits aérosols SeaWiFS avec les données photométriques du réseau AERONET montre une bonne inversion des épaisseurs optiques des aérosols dans le bleu et une surestimation des épaisseurs optiques des aérosols dans le rouge. Nous avons maintenant un produit aérosol opérationnel sur les données SeaWiFS. Dans le cadre de deux projets européens, nous avons été amenés à appliquer l'algorithme de télédétection des aérosols au-dessus des terres émergées. Le projet EXPER/PF porte sur la qualité de l'air et la possibilité de conversion des épaisseurs optiques des aérosols en mesure de "Particulate Matter" à l'aide d'une large base de données sur les particules et des données auxiliaires. Le projet SISCAL concerne la "couleur de l'eau" et l'application de la télédétection des aérosols au-dessus des terres émergées dans une approche innovante des corrections atmosphériques au-dessus des eaux intérieuresThis work is organized on the application of the aerosol remote sensing over land algorithm developed for the ENVISAT/MERIS sensor on a large database of SeaSTAR/SeaWiFS sensor. The aerosol remote sensing over land is based on the DDV (Dense Dark Vegetation) detection selected with the ARVI thanks to the darkness of the DDV in the blue and the red. The critical point of the algorithm is the weak coverage of the aerosol product (around 2% of the land). To fix this coverage problem, the DDV concept has been extended to brighter surfaces called LARS (Land Aerosol Remote Sensing). The LARS reflectance is modelized thanks to the linearity between the surface reflectance and the ARVI. A statistical study based on the aerosol spatial homogeneity over small SeaWiFS subscenes allows confirming the new model established by HYGEOS on MERIS data. The comparison of the SeaWiFS aerosol product with AERONET data shows a good retrieval of the aerosol optical thickness in the blue and an overestimation of the aerosol optical thickness in the red. Now, we have an operational aerosol product with SeaWiFS. In the frame of two European projects, we applied the aerosol remote sensing over land algorithm. The EXPER/PF project relies on air quality and the possibility of the conversion of the aerosol optical thickness into PM with the help of a large database on particles and auxiliary data. The SISCAL project relies on the "water color" and the application of the aerosol remote sensing over land for an innovative approach of the atmospheric correction over inland waters
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Ahmad, Khalil Ali. "ESTIMATION OF OCEANIC RAINFALL USING PASSIVE AND ACTIVE MEASUREMENTS FROM SEAWINDS SPACEBORNE MICROWAVE SENSOR." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3015.
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The Ku band microwave remote sensor, SeaWinds, was developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Two identical SeaWinds instruments were launched into space. The first was flown onboard NASA QuikSCAT satellite which has been orbiting the Earth since June 1999, and the second instrument flew onboard the Japanese Advanced Earth Observing Satellite II (ADEOS-II) from December 2002 till October 2003 when an irrecoverable solar panel failure caused a premature end to the ADEOS-II satellite mission. SeaWinds operates at a frequency of 13.4 GHz, and was originally designed to measure the speed and direction of the ocean surface wind vector by relating the normalized radar backscatter measurements to the near surface wind vector through a geophysical model function (GMF). In addition to the backscatter measurement capability, SeaWinds simultaneously measures the polarized radiometric emission from the surface and atmosphere, utilizing a ground signal processing algorithm known as the QuikSCAT / SeaWinds Radiometer (QRad / SRad). This dissertation presents the development and validation of a mathematical inversion algorithm that combines the simultaneous active radar backscatter and the passive microwave brightness temperatures observed by the SeaWinds sensor to retrieve the oceanic rainfall. The retrieval algorithm is statistically based, and has been developed using collocated measurements from SeaWinds, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, and Numerical Weather Prediction (NWP) wind fields from the National Centers for Environmental Prediction (NCEP). The oceanic rain is retrieved on a spacecraft wind vector cell (WVC) measurement grid that has a spatial resolution of 25 km. To evaluate the accuracy of the retrievals, examples of the passive-only, as well as the combined active / passive rain estimates from SeaWinds are presented, and comparisons are made with the standard TRMM rain data products. Results demonstrate that SeaWinds rain measurements are in good agreement with the independent microwave rain observations obtained from TMI. Further, by applying a threshold on the retrieved rain rates, SeaWinds rain estimates can be utilized as a rain flag. In order to evaluate the performance of the SeaWinds flag, comparisons are made with the Impact based Multidimensional Histogram (IMUDH) rain flag developed by JPL. Results emphasize the powerful rain detection capabilities of the SeaWinds retrieval algorithm. Due to its broad swath coverage, SeaWinds affords additional independent sampling of the oceanic rainfall, which may contribute to the future NASA's Precipitation Measurement Mission (PMM) objectives of improving the global sampling of oceanic rain within 3 hour windows. Also, since SeaWinds is the only sensor onboard QuikSCAT, the SeaWinds rain estimates can be used to improve the flagging of rain-contaminated oceanic wind vector retrievals. The passive-only rainfall retrieval algorithm (QRad / SRad) has been implemented by JPL as part of the level 2B (L2B) science data product, and can be obtained from the Physical Oceanography Distributed Data Archive (PO.DAAC).Ph.D.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering PhD
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Bosc, Emmanuel. "Variations saisonnières et interannuelles de la biomasse phytoplanctonique et de la production primaire en Méditerranée : évaluation et utilisation des données satellitales de couleur de l'océan (SeaWiFs, Polder et OCTS)." Toulon, 2002. http://www.theses.fr/2002TOUL0008.
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Heim, Birgit [Verfasser]. "Qualitative and quantitative analyses of Lake Baikal's surface waters using ocean colour satellite data (SeaWiFS) / von Birgit Heim." 2006. http://d-nb.info/980077656/34.
Full textBooks on the topic "Satellite SeaWIFS"
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Acker, James G. The heritage of SeaWiFS: A retrospective on the CZCS NIMBUS Experiment Team (NET) Program. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1994.
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SeaWiFS Exploitation Initiative (SEI) Team Meeting (1st 1995 Southampton, England). Proceedings of the First SeaWIFS Exploitation Initiative (SEI) Team Meeting. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1996.
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SeaWiFS Intercalibration Round-Robin Experiment (SIRREX-3), 19-30 September 1994 (3rd 1994 San Diego State University, San Diego, Calif.). The Third SeaWiFS Intercalibration Round-Robin Experiment (SIRREX-3), 19-30 September 1994. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1996.
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S, Patt Frederick, Gregg Watson W, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. CATLAC: Calibration and validation Analysis Tool of Local Area Coverage for the SeaWIFS mission. [Washington, D.C.?]: National Aeronautics and Space Administration, Scientific and Technical Information Program, 1993.
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S, Patt Frederick, Gregg Watson W, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. CATLAC: Calibration and validation Analysis Tool of Local Area Coverage for the SeaWIFS mission. [Washington, D.C.?]: National Aeronautics and Space Administration, Scientific and Technical Information Program, 1993.
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Goddard DAAC (Goddard Space Flight Center), ed. Ocean color data at the Goddard DAAC: CZCS, SeaWiFS, and MODIS. Greenbelt, MD: Goddard DAAC, Goddard Space Flight Center, 2000.
Find full textBook chapters on the topic "Satellite SeaWIFS"
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Horning, Ned, Julie A. Robinson, Eleanor J. Sterling, Woody Turner, and Sacha Spector. "Disturbances: fires and floods." In Remote Sensing for Ecology and Conservation. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780199219940.003.0016.
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From space, much of Indonesia appeared to be on fire. One of the strongest El Niño/Southern Oscillation (ENSO) events of the twentieth century had generated drought conditions in the fall of 1997 and early 1998. These conditions, probably in concert with the impacts of logging, resulted in what has been called the largest fire disaster ever observed (Siegert et al. 2001). The powerful 1997–8 ENSO also led to extensive fires in Amazonia. The humid tropics, home to Earth’s greatest concentrations of biodiversity, had long been thought to be fire resistant due to high-moisture levels in the leaf litter and the humidity of the understory. The massive fires of 1997–8 increased our understanding of the complex interactions between fire and humid tropical forests. Since the late 1990s, a new synthesis has emerged linking ENSO events, drought, logging, and fire in the wet tropics. This synthesis has sought to understand the impacts of these phenomena on tropical environments and also explain the role humans play in tropical fires and fire impacts. Remote sensing has been an important tool in forging this new synthesis of understanding. For example, NOAA’s workhorse AVHRR sensor, the SeaWiFS sensor, and NASA’s TOMS instrument were among the satellite tools available to provide imagery of the dramatic events of 1997–8. In this chapter, we discuss the potential for remote sensing to detect, monitor, and increase our understanding of certain disturbance mechanisms affecting ecosystems. We focus on fires and floods, adding shorter sections at the end on two other drivers of disturbance, volcanoes and dams. A key challenge lies in understanding the degree to which logging, even selective logging, is interacting with periodic droughts to drive fires in humid forests. Are humid tropical forests essentially immune to fire unless disturbed by human logging, or have they always been subject to climate-induced droughts and subsequent fires? The answer is crucial in determining our impact on these great storehouses of biodiversity and holds major implications for forest management. Part of the answer lies in looking backward in time.
Conference papers on the topic "Satellite SeaWIFS"
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Ho, Chung-Ru, Feng-Chun Su, Nan-Jung Kuo, Shih-Jen Huang, Chun-Te Chen, and Quanan Zheng. "Detecting Internal Waves From Satellite Ocean Color Imagery." In 25th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/omae2006-92177.
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Internal waves have been observed by lots of high resolution satellite images, such as Synthetic Aperture Radar (SAR) and optical images of SPOT and Landsat. These images are usually expensive. In this study, some free but lower spatial resolution satellite images are applied to observe the internal wave phenomena. The internal waves in the Sulu Sea are detected from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) onboard the Orbview-2 satellite. The SeaWiFS image has a spatial resolution of 1.1 km. It is acceptable to observe the internal wave phenomena while the soliton width is larger than the image resolution. The results show that the internal solitary in the Sulu Sea can be observed successfully with SeaWiFS chlorophyll images. The internal waves in the Sulu Sea have amplitudes of 10 to 90 m and wavelengths of 5 to 16 km. The large-amplitude internal solitary waves may significantly influence the near-surface chlorophyll concentration. The chlorophyll concentration would be lower when the depression internal waves passed through. A theoretic model is proposed and tested to estimate the amplitudes of internal waves from chlorophyll concentration images.
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Cipollini, Paolo P., and Giovanni Corsini. "Model-derived algorithms for marine parameter retrieval from SeaWiFS data." In Satellite Remote Sensing II, edited by Donald W. Deering and Preben Gudmandsen. SPIE, 1995. http://dx.doi.org/10.1117/12.228624.
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He, Xianqiang, Delu Pan, and Zhihua Mao. "Water-transparency (Secchi Depth) monitoring in the China Sea with the SeaWiFS satellite sensor." In Remote Sensing, edited by Manfred Owe, Guido D'Urso, Ben T. Gouweleeuw, and Anne M. Jochum. SPIE, 2004. http://dx.doi.org/10.1117/12.564605.
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Lu, Douding, Jeanette Goebel, Matthias Hetscher, U. Horstmann, and Alexander Davidov. "Detection of novel algal blooms of Raphidophytes in the Eastern North Sea with satellite images of MOS and SeaWiFS." In Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Robert J. Frouin, Yeli Yuan, and Hiroshi Kawamura. SPIE, 2003. http://dx.doi.org/10.1117/12.466064.
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Bohm, Emanuele, Bruno Buongiorno Nardelli, Christophe Brunet, Raffaella Casotti, Fabio Conversano, Federico Corato, Emma D'Acunzo, et al. "SYMPLEX experiment: first results on oceanic mesoscale dynamics and related primary production from AVHRR and SeaWIFS satellite data and field experiments." In Remote Sensing, edited by Giovanna Cecchi and Eugenio Zilioli. SPIE, 1998. http://dx.doi.org/10.1117/12.332717.
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