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Extending the MODIS 1 km ocean colour atmospheric correction to the MODIS 500 m bands and 500 m chlorophyll-a estimation towards coastal and estuarine monitoring / J.D. Shutler in Remote sensing of environment, vol 107 n° 4 (30/04/2007)
[article]
Titre : Extending the MODIS 1 km ocean colour atmospheric correction to the MODIS 500 m bands and 500 m chlorophyll-a estimation towards coastal and estuarine monitoring Type de document : Article/Communication Auteurs : J.D. Shutler, Auteur ; P.E. Land, Auteur ; S.B. Groom, Auteur Année de publication : 2007 Article en page(s) : pp 521 - 532 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] chlorophylle
[Termes IGN] correction atmosphérique
[Termes IGN] couleur de l'océan
[Termes IGN] données de terrain
[Termes IGN] données spatiotemporelles
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] littoral
[Termes IGN] qualité des eaux
[Termes IGN] surveillance écologiqueRésumé : (Auteur) National and regional obligations to control and maintain water quality have led to an increase in coastal and estuarine monitoring. A potentially valuable tool is high temporal and spatial resolution satellite ocean colour data. NASA's MODIS-Terra and -Aqua can capture data at both 250 m and 500 m spatial resolutions and the existence of two sensors provides the possibility for multiple daily passes over a scene. However, no robust atmospheric correction method currently exists for these data, rendering them unusable for quantitative monitoring applications. Therefore, this paper presents an automatic and dynamic atmospheric correction approach allowing the determination of ocean colour. The algorithm is based around the standard MODIS 1 km atmospheric correction, includes cloud masking and is applicable to all of the visible 500 m bands. Comparison of the 500 m ocean colour data with the standard 1 km data shows good agreement and these results are further supported by in situ data comparisons. In addition, a novel method to produce 500 m chlorophyll-a estimates is presented. Comparisons of the 500 m estimates with the standard MODIS OC3M algorithm and to in situ data from a near-coast validation site are given. Copyright Elsevier Numéro de notice : A2007-157 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.10.004 En ligne : https://doi.org/10.1016/j.rse.2006.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28520
in Remote sensing of environment > vol 107 n° 4 (30/04/2007) . - pp 521 - 532[article]An operational MISR pixel classifier using support vector machines / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
[article]
Titre : An operational MISR pixel classifier using support vector machines Type de document : Article/Communication Auteurs : D. Mazzoni, Auteur ; M.J. Garay, Auteur ; R. Davies, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 149 - 158 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage automatique
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image Terra-MISRRésumé : (Auteur) The Multi-angle Imaging SpectroRadiometer (MISR) data products now include a scene classification for each 1.1-km pixel that was developed using Support Vector Machines (SVMs), a cutting-edge machine learning technique for supervised classification. Using a combination of spectral, angular, and texture features, each pixel is classified as land, water, cloud, aerosol, or snow/ice, with the aerosol class further divided into smoke, dust, and other aerosols. The classifier was trained by MISR scientists who labeled hundreds of scenes using a custom interactive tool that showed them the results of the training in real time, making the process significantly faster. Preliminary validation shows that the accuracy of the classifier is approximately 81% globally at the 1.1-km pixel level. Applications of this classifier include global studies of cloud and aerosol distribution, as well as data mining applications such as searching for smoke plumes. This is one of the largest and most ambitious operational uses of machine learning techniques for a remote-sensing instrument, and the success of this system will hopefully lead to further use of this approach. Copyright Elsevier Numéro de notice : A2007-054 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.06.021 En ligne : https://doi.org/10.1016/j.rse.2006.06.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28419
in Remote sensing of environment > vol 107 n° 1-2 (15 March 2007) . - pp 149 - 158[article]A data-mining approach to associating MISR smoke plume heights with MODIS fire measurements / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
[article]
Titre : A data-mining approach to associating MISR smoke plume heights with MODIS fire measurements Type de document : Article/Communication Auteurs : D. Mazzoni, Auteur ; J.A. Logan, Auteur ; D. Diner, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 138 - 148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aérosol
[Termes IGN] Amérique du nord
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] exploration de données
[Termes IGN] fumée
[Termes IGN] image Terra-MISR
[Termes IGN] image Terra-MODIS
[Termes IGN] incendie
[Termes IGN] nuageRésumé : (Auteur) Satellites provide unique perspectives on aerosol global and regional spatial and temporal distributions, and offer compelling evidence that visibility and air quality are affected by particulate matter transported over long distances. The heights at which emissions are injected into the atmosphere are major factors governing downwind dispersal. In order to better understand the environmental factors determining injection heights of smoke plumes from wildfires, we have developed a prototype system for automatically searching through several years of MISR and MODIS data to locate fires and the associated smoke plumes and to retrieve injection heights and other relevant measurements from them. We are refining this system and assembling a statistical database, aimed at understanding how injection height relates to the fire severity and local weather conditions. In this paper we focus on our working proof-of-concept system that demonstrates how machine-learning and data mining methods aid in processing of massive volumes of satellite data. Automated algorithms for distinguishing smoke from clouds and other aerosols, identifying plumes, and extracting height data are described. Preliminary results are presented from application to MISR and MODIS data collected over North America during the summer of 2004. Copyright Elsevier Numéro de notice : A2007-053 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.08.014 En ligne : https://doi.org/10.1016/j.rse.2006.08.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28418
in Remote sensing of environment > vol 107 n° 1-2 (15 March 2007) . - pp 138 - 148[article]MISR-based passive optical bathymetry from orbit with few-cm level of accuracy on the Salar de Uyuni, Bolivia / B.G. Bills in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
[article]
Titre : MISR-based passive optical bathymetry from orbit with few-cm level of accuracy on the Salar de Uyuni, Bolivia Type de document : Article/Communication Auteurs : B.G. Bills, Auteur ; A. Borsa, Auteur ; R.L. Comstock, Auteur Année de publication : 2007 Article en page(s) : pp 240 - 255 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bathymétrie
[Termes IGN] Bolivie
[Termes IGN] capteur passif
[Termes IGN] désert
[Termes IGN] image optique
[Termes IGN] image Terra-MISR
[Termes IGN] inondation
[Termes IGN] sel gemmeRésumé : (Auteur) We demonstrate that, under ideal circumstances, passive optical measurements can yield surface water depth estimates with an accuracy of a few centimeters. Our target area is the Salar de Uyuni, in Bolivia. It is a large, active salt flat or playa, which is maintained as an almost perfectly level and highly reflective surface by annual flooding, to a mean depth of 30–50 cm. We use MISR data to estimate spatial and temporal variations in water depth during the waning portion of the 2001 flooding cycle. We use a single ICESat laser altimetry profile to calibrate our water depth model. Though the salt surface is probably the smoothest surface of its size on Earth, with less that 30 cm RMS height variations over an area of nearly 104 km2, it is not completely featureless. Topography there includes a peripheral depression, or moat, around the edge of the salt, and several sets of prominent parallel ridges, with 5 km wavelength and 30 cm amplitude. The process by which these features form is still not well characterized. Copyright Elsevier Numéro de notice : A2007-055 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.11.006 En ligne : https://doi.org/10.1016/j.rse.2006.11.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28420
in Remote sensing of environment > vol 107 n° 1-2 (15 March 2007) . - pp 240 - 255[article]vol 107 n° 1-2 - 15 March 2007 - Multi-angle Imaging SpectroRadiometer (MISR) Special Issue MISR (Bulletin de Remote sensing of environment) / David J. Diner
[n° ou bulletin]
Titre : vol 107 n° 1-2 - 15 March 2007 - Multi-angle Imaging SpectroRadiometer (MISR) Special Issue MISR Type de document : Périodique Auteurs : David J. Diner, Éditeur scientifique ; Larry Di Girolamo, Éditeur scientifique ; Anne Nolin, Éditeur scientifique Année de publication : 2007 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] image Terra-MISR
[Termes IGN] Multi-Angle Imaging SpectroradiometerNuméro de notice : 110-0705 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Numéro de périodique En ligne : http://www.sciencedirect.com/science/journal/00344257/107/1-2?sdc=2 Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=21527 [n° ou bulletin]Contient
- The MISR radiometric calibration process / Carol J. Bruegge in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
- A data-mining approach to associating MISR smoke plume heights with MODIS fire measurements / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
- An operational MISR pixel classifier using support vector machines / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
- MISR-based passive optical bathymetry from orbit with few-cm level of accuracy on the Salar de Uyuni, Bolivia / B.G. Bills in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
- Support vector machines for recognition of semi-arid vegetation types using MISR multi-angle imagery / L. Su in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
- Support vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer / S. Durbha in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
Support vector machines for recognition of semi-arid vegetation types using MISR multi-angle imagery / L. Su in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkSupport vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer / S. Durbha in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkAnalysis of process variance in remote sensing applications / M. Matur in GIS development, vol 11 n° 2 (February 2007)PermalinkComputing coastal ocean surface curreants from infrared and ocean color satellite imagery / R.I. Crocker in IEEE Transactions on geoscience and remote sensing, vol 45 n° 2 (February 2007)PermalinkEvaluating NDVI-based emissivities of MODIS bands 31 and 32 using emissivities derived by day/night LST algorithm / M. Momeni in Remote sensing of environment, vol 106 n° 2 (30/01/2007)PermalinkReflectance seasonality and its relation to the canopy leaf area index in an eastern Siberian larch forest: Multi-satellite data and radiative transfer analyses / H. Kobayashi in Remote sensing of environment, vol 106 n° 2 (30/01/2007)PermalinkEvolution des habitats dans les montagnes d'Araucania / Rémi Pas (2007)PermalinkCalibration of NOAA16 AVHRR over a desert site using MODIS data / Eric F. Vermote in Remote sensing of environment, vol 105 n° 3 (15/12/2006)PermalinkAssessment of EOS aqua AMSR-E artic sea ice concentrations using Landsat-7 and airborne microwave imagery / D.J. Cavalieri in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 1 (November 2006)PermalinkMarch 2003 EOS Aqua AMSR-E Arctic Sea Ice Field Campaign / D.J. Cavalieri in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 1 (November 2006)Permalink