Search results for "REMOTE"

showing 10 items of 1455 documents

Who's better at spotting? A comparison between aerial photography and observer-based methods to monitor floating marine litter and marine mega-fauna.

2020

Pollution by marine litter is raising major concerns due to its potential impact on marine biodiversity and, above all, on endangered mega-fauna species, such as cetaceans and sea turtles. The density and distribution of marine litter and mega-fauna have been traditionally monitored through observer-based methods, yet the advent of new technologies has introduced aerial photography as an alternative monitoring method. However, to integrate results produced by different monitoring techniques and consider the photographic method a viable alternative, this ‘new’ methodology must be validated. This study aims to compare observations obtained from the concurrent application of observer-based and…

010504 meteorology & atmospheric sciencesAerial surveyHealth Toxicology and MutagenesisEndangered speciesMarine pollution010501 environmental sciencesToxicology01 natural sciencesAerial surveysMarine pollutionMediterranean seaAerial photographyMarine debrisMediterranean SeaPhotographyAnimalsMarine vertebratesTransect0105 earth and related environmental sciencesRemote sensingWaste ProductsGeneral MedicineRemote sensingPollutionTurtlesSeabirdsMediterranean seaRemote Sensing TechnologyLitterEnvironmental scienceCetaceaPlasticsEnvironmental MonitoringEnvironmental pollution (Barking, Essex : 1987)
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Lidar sounding of volcanic plumes

2013

ABSTRACT Accurate knowledge of gas composition in volcanic plumes has high scientific and societal value. On the one hand, it gives information on the geophysical processes taking place inside volcanos; on the other hand, it provides alert on possible eruptions. For this reasons, it has been suggested to monitor volcanic plumes by lidar. In particular, one of the aims of the FP7 ERC project BRIDGE is the measurement of CO 2 concentration in volcanic gases by differential absorption lidar. This is a very challenging task due to the harsh environment, the narrowness and weakness of the CO 2 absorption lines and the difficulty to procure a suitable laser source. This paper, after a review on r…

010504 meteorology & atmospheric sciencesAerosol load01 natural sciencesVolcanic plume010309 opticsVolcanic Gases0103 physical scienceseventGas compositionAbsorption (electromagnetic radiation)Water vapor0105 earth and related environmental sciencesRemote sensingevent.disaster_typeLidargeographygeography.geographical_feature_categoryAerosolDepth soundingLidarCarbon dioxideVolcano13. Climate actionAerosol load; Carbon dioxide; Differential absorption; Lidar; Volcanic plumes; Water vaporDifferential absorptionWater vaporGeologyLidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing IX
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Validation of the Sentinel-3 Ocean and Land Colour Instrument (OLCI) Terrestrial Chlorophyll Index (OTCI): Synergetic Exploitation of the Sentinel-2 …

2018

Continuity to the Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) will be provided by the Sentinel-3 Ocean and Land Colour Instrument (OLCI), and to ensure its utility in a wide range of operational applications, validation efforts are required. In the past, these activities have been constrained by the need for costly airborne hyperspectral data acquisition, but the Sentinel-2 Multispectral Instrument (MSI) now offers a promising alternative. In this paper, we explore the synergetic use of Sentinel-2 MSI data for validation of the Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI) over the Valencia Anchor Station, a large agricultural site in the Valen…

010504 meteorology & atmospheric sciencesAgricultural siteMultispectral image0211 other engineering and technologiesImaging spectrometerHyperspectral imaging02 engineering and technology01 natural sciencesValencian communityMedium resolutionChlorophyll indexData acquisitionEnvironmental science021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

2012

Abstract ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT-5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms may be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from …

010504 meteorology & atmospheric sciencesArtificial neural networkMean squared errorbusiness.industryComputer science0211 other engineering and technologiesSoil ScienceGeology02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesRegressionSupport vector machineTemporal resolutionGround-penetrating radarCurve fittingArtificial intelligenceComputers in Earth SciencesbusinessImage resolutioncomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Smap-based retrieval of vegetation opacity and albedo

2020

Over land the vegetation canopy affects the microwave brightness temperature by emission, scattering and attenuation of surface soil emission. The questions addressed in this study are: 1) what is the transparency of the vegetation canopy for different biomes around the Globe at the low-frequency L-band?, 2) what is the seasonal amplitude of vegetation microwave optical depth for different biomes?, 3) what is the effective scattering at this frequency for different vegetation types?, 4) what is the impact of imprecise characterization of vegetation microwave properties on retrieval of soil surface conditions? These questions are addressed based on the recently completed one full annual cycl…

010504 meteorology & atmospheric sciencesBiome0211 other engineering and technologiesFOS: Physical sciences02 engineering and technology15. Life on landAlbedoAnnual cycle01 natural sciencesGeophysics (physics.geo-ph)Physics - GeophysicsMicrowave imaging13. Climate actionBrightness temperaturemedicineEnvironmental sciencemedicine.symptomVegetation (pathology)Water contentOptical depth021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Evaluating roughness effects on C-band AMSR-E observations

2014

International audience; The usefulness of microwave remote sensing to retrieve near-surface soil moisture has already been demonstrated in many studies. However, obtaining high quality estimates of soil moisture is influenced by many effects from soil, vegetation and atmosphere; one of the key parameters is surface roughness. This research focusses on a semi-empirical method to evaluate the roughness effects from space borne observations. Global maps of roughness effects are evaluated at C-band from AMSR-E measurements.

010504 meteorology & atmospheric sciencesC band[SDE.MCG]Environmental Sciences/Global Changes0211 other engineering and technologiessoil surface roughnessAMSR-E02 engineering and technologySurface finish01 natural sciences13. Climate actionEnvironmental sciencesoil moisture[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2014 IEEE Geoscience and Remote Sensing Symposium
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Vegetation vulnerability to drought in Spain

2014

[EN] Frequency of climatic extremes like long duration droughts has increased in Spain over the last century.The use of remote sensing observations for monitoring and detecting drought is justified on the basis that vegetation vigor is closely related to moisture condition. We derive satellite estimates of bio-physical variables such as fractional vegetation cover (FVC) from MODIS/EOS and SEVIRI/MSG time series. The study evaluates the strength of temporal relationships between precipitation and vegetation condition at time-lag and cumulative rainfall intervals. From this analysis, it was observed that the climatic disturbances affected both the growing season and the total amount of vegeta…

010504 meteorology & atmospheric sciencesClimateGeography Planning and Development0211 other engineering and technologiesSPIGrowing seasonlcsh:G1-92202 engineering and technology01 natural sciencesSequíaVegetation coverTropical vegetationEarth and Planetary Sciences (miscellaneous)medicineTeledetecciónPrecipitation021101 geological & geomatics engineering0105 earth and related environmental sciencesSequíasMoistureDroughtÍndices meteorológicos de sequíaVegetaciónVegetation cover15. Life on landRemote sensingVegetation dynamicsAridGeography13. Climate actionClimatologyClimamedicine.symptomVegetation (pathology)lcsh:Geography (General)
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Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud

2020

Remote sensing optical sensors onboard operational satellites cannot have high spectral, spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can adversely affect the signal contaminating the land surface observations. We present a HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to combine multispectral images of different sensors to reduce noise and produce monthly gap free high resolution (30 m) observations over land. Our approach uses images from the Landsat (30 m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500 m spatial resolution and daily revisit cycle). We implem…

010504 meteorology & atmospheric sciencesComputer science0208 environmental biotechnologyMultispectral imageSoil Science02 engineering and technology01 natural sciencesArticleComputers in Earth SciencesImage resolution0105 earth and related environmental sciencesRemote sensingPropagation of uncertaintyNoise (signal processing)GeologyKalman filterData fusionSensor fusion020801 environmental engineeringMODIS13. Climate actionScalabilityGap fillingKalman filterLandsatSmoothingSmoothingRemote Sensing of Environment
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Recent Advances in Techniques for Hyperspectral Image Processing

2009

International audience; Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information. Performance of the discussed techniques is evaluated in …

010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesSoil ScienceImage processing02 engineering and technologyMachine learningcomputer.software_genre01 natural sciences[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer visionComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingData processingContextual image classificationbusiness.industryHyperspectral imagingGeologyImaging spectroscopyInformation extractionKernel methodSnapshot (computer storage)Artificial intelligencebusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Sun-induced chlorophyll fluorescence III: benchmarking retrieval methods and sensor characteristics for proximal sensing

2019

[EN] The interest of the scientific community on the remote observation of sun-induced chlorophyll fluorescence (SIF) has increased in the recent years. In this context, hyperspectral ground measurements play a crucial role in the calibration and validation of future satellite missions. For this reason, the European cooperation in science and technology (COST) Action ES1309 OPTIMISE has compiled three papers on instrument characterization, measurement setups and protocols, and retrieval methods (current paper). This study is divided in two sections; first, we evaluated the uncertainties in SIF retrieval methods (e.g., Fraunhofer line depth (FLD) approaches and spectral fitting method (SFM))…

010504 meteorology & atmospheric sciencesComputer scienceEconomicsGround spectrometersScience0211 other engineering and technologiesContext (language use)02 engineering and technologyGround spectrometer01 natural sciencesSpectral lineRetrieval methodApproximation errorSun-induced chlorophyll fluorescenceSensitivity (control systems)910 Geography & travelChlorophyll fluorescence021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRetrieval methodsSpectrometerSun-induced chlorophyll fluorescence; Ground spectrometers; Retrieval methods1900 General Earth and Planetary SciencesQHyperspectral imagingsun-induced chlorophyll fluorescence; ground spectrometers; retrieval methods3. Good health10122 Institute of GeographyFISICA APLICADALine (geometry)General Earth and Planetary Sciencesddc:620Interpolation
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