Search results for "Satellite image"

showing 10 items of 54 documents

Exploiting deep learning algorithms and satellite image time series for deforestation prediction

2022

In recent years, we have witnessed the emergence of Deep Learning (DL) methods, which have led to enormous progress in various fields such as automotive driving, computer vision, medicine, finances, and remote sensing data analysis. The success of these machine learning methods is due to the ever-increasing availability of large amounts of information and the computational power of computers. In the field of remote sensing, we now have considerable volumes of satellite images thanks to the large number of Earth Observation (EO) satellites orbiting the planet. With the revisit time of satellites over an area becoming shorter and shorter, it will probably soon be possible to obtain daily imag…

Artificial intelligenceDeforestation predictionRéseaux de neurones récurrentsApprentissage profondRecurrent neural networks[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingImage time seriesDeep learningSatellite imagesSéries temporelles d'imagesIntelligence artificiellePrédiction déforestationImages satellitaires
researchProduct

Discriminating irrigated and rainfed olive orchards with thermal ASTER imagery and DART 3D simulation

2009

Article in Press

Atmospheric Science010504 meteorology & atmospheric sciences0211 other engineering and technologiesBiometeorology02 engineering and technologyCanopy temperature01 natural sciencesNormalized Difference Vegetation IndexASTERAdvanced Spaceborne Thermal Emission and Reflection RadiometerVegetation indexEvapotranspirationRadiative transferIrrigatedSatellite imageryRainfed agricultureLeaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2. Zero hungerGlobal and Planetary ChangeForestry15. Life on landEnvironmental scienceDARTRainfedOrchardAgronomy and Crop ScienceAgricultural and Forest Meteorology
researchProduct

Advances in understanding mineral dust and boundary layer processes over the Sahara from Fennec aircraft observations

2015

Abstract. The Fennec climate programme aims to improve understanding of the Saharan climate system through a synergy of observations and modelling. We present a description of the Fennec airborne observations during 2011 and 2012 over the remote Sahara (Mauritania and Mali) and the advances in the understanding of mineral dust and boundary layer processes they have provided. Aircraft instrumentation aboard the UK FAAM BAe146 and French SAFIRE (Service des Avions Français Instrumentés pour la Recherche en Environnement) Falcon 20 is described, with specific focus on instrumentation specially developed for and relevant to Saharan meteorology and dust. Flight locations, aims and associated met…

Atmospheric Science010504 meteorology & atmospheric sciencesMeteorologyPlanetary boundary layerCONVECTIVE SYSTEMEnvironmental Sciences & EcologyAEROSOL OPTICAL-PROPERTIESMineral dust010502 geochemistry & geophysicsAtmospheric sciences01 natural sciencesCOARSE MODElcsh:ChemistryHaboobDust storm0201 Astronomical and Space SciencesMeteorology & Atmospheric SciencesSatellite imagerySOUTHERN MOROCCO0105 earth and related environmental sciences[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]GBScience & TechnologyHEAT LOWAIRBORNE OBSERVATIONSRETRIEVAL PRODUCTSOzone depletionlcsh:QC1-999PARTICLE-SIZEAERONETBoundary layerlcsh:QD1-99913. Climate action[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/ClimatologyPhysical SciencesWEST-AFRICAN MONSOONEnvironmental science0401 Atmospheric SciencesNORTH-ATLANTIC OCEANLife Sciences & Biomedicinelcsh:PhysicsEnvironmental SciencesAtmospheric Chemistry and Physics
researchProduct

Comparative study of three satellite image time-series decomposition methods for vegetation change detection

2018

International audience; Satellite image time-series (SITS) methods have contributed notably to detection of global change over the last decades, for instance by tracking vegetation changes. Compared with multi-temporal change detection methods, temporally highly resolved SITS methods provide more information in a single analysis, for instance on the type and consistency of change. In particular, SITS decomposition methods show a great potential in extracting various components from non-stationary time series, which allows for an improved interpretation of the temporal variability. Even though many case studies have applied SITS decomposition methods, a systematic comparison of common algori…

Atmospheric ScienceNon-stationary010504 meteorology & atmospheric sciencesBFASTSTL0211 other engineering and technologiesMRA-WT02 engineering and technology01 natural sciencesNormalized Difference Vegetation Indexlcsh:OceanographyDecomposition (computer science)medicineSatellite imagerylcsh:GC1-1581Computers in Earth SciencesNDVI time series021101 geological & geomatics engineering0105 earth and related environmental sciencesGeneral Environmental ScienceRemote sensingApplied Mathematicslcsh:QE1-996.5Global change15. Life on landSeasonalitymedicine.diseaselcsh:GeologyEnvironmental scienceChange detectionSatellite Image Time Seriesmedicine.symptomVegetation (pathology)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingChange detection
researchProduct

Characterization of the atmosphere during SEN2FLEX 2005 field campaign

2008

The European Space Agency carried out the Sentinel-2 and Fluorescence Experiment (SEN2FLEX) campaign in Barrax (Spain) during the summer of 2005, with the main objective of observe solar induced fluorescence signal using the AirFLEX airborne instrument over different vegetation targets in order to verify signal suitability for observations from space as proposed in the FLEX mission. A highly precise atmospheric correction is mandatory for adequate measurements of the AirFLEX instrument; thus a complete characterization of the atmosphere was programmed in SEN2FLEX in order to document the presence of atmospheric aerosols above the experimental area, as their effects represent the major sourc…

Atmospheric ScienceRadiació solarMeteorologySoil Science550 - Earth sciencesAquatic ScienceMineral dustOceanographyAtmosphereGeochemistry and PetrologyEarth and Planetary Sciences (miscellaneous)Satellite imageryEarth-Surface ProcessesWater Science and TechnologyRemote sensingAerosolsEcologyAtmospheric correctionPaleontologyForestryGeofísicaAerosolGeophysicsLidarSpace and Planetary ScienceEnvironmental scienceSatelliteWater vaporJOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
researchProduct

Landsat TM/ETM+ and tree-ring based assessment of spatiotemporal patterns of the autumnal moth (Epirrita autumnata) in northernmost Fennoscandia

2010

Abstract We used fine-spatial resolution remotely sensed data combined with tree-ring parameters in order to assess and reconstruct disturbances in mountain birch ( Betula pubescens ) forests caused by Epirrita autumnata (autumnal moth). Research was conducted in the area of Lake Tornetrask in northern Sweden where we utilized five proxy parameters to detect insect outbreak events over the 19th and 20th centuries. Digital change detection was applied on three pairs of multi-temporal NDVI images from Landsat TM/ETM+ to detect significant reductions in the photosynthetic activity of forested areas during disturbed growing seasons. An image segmentation gap-fill procedure was developed in orde…

Autumnal mothbiologySoil ScienceGeologyBetula pubescensbiology.organism_classificationNormalized Difference Vegetation IndexThematic MapperEpirritaDendrochronologyEnvironmental scienceSatellite imageryComputers in Earth SciencesDigital elevation modelRemote sensingRemote Sensing of Environment
researchProduct

Evaluation of the DART 3D model in the thermal domain using satellite/airborne imagery and ground-based measurements

2011

This work provides an evaluation of the discrete anisotropy radiative transfer (DART) three-dimensional (3D) model in assessing the simulation of directional brightness temperatures (Tb) at both sensor and surface levels. Satellite imagery acquired with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), airborne imagery acquired with the Airborne Hyperspectral Scanner (AHS) sensor and ground-based measurements collected over an agricultural area were used to evaluate the DART model at nadir views. Directional radiometric temperatures measured with a goniometric system at ground level were also used to evaluate modelling results at different view angles. The DART mod…

BrightnessDart010504 meteorology & atmospheric sciencesMeteorology[SDE.IE]Environmental Sciences/Environmental Engineering0211 other engineering and technologiesAtmospheric correctionHyperspectral imaging02 engineering and technology01 natural sciencesAdvanced Spaceborne Thermal Emission and Reflection Radiometer[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsEmissivityRadiative transferGeneral Earth and Planetary SciencesEnvironmental scienceSatellite imagerycomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingcomputer.programming_languageInternational Journal of Remote Sensing
researchProduct

Sensitivity of L-band vegetation optical depth to carbon stocks in tropical forests: a comparison to higher frequencies and optical indices

2019

Supplementary data to this article can be found online at https://doi.org/10.1016/j.rse.2019.111303. Monitoring vegetation carbon in tropical regions is essential to the global carbon assessment and to evaluate the actions oriented to the reduction of forest degradation. Mainly, satellite optical vegetation indices and LiDAR data have been used to this purpose. These two techniques are limited by cloud cover and are sensitive only to the top of vegetation. In addition, the vegetation attenuation to the soil microwave emission, represented by the vegetation optical depth (VOD), has been applied for biomass estimation using frequencies ranging from 4 to 30¿GHz (C- to K-bands). Atmosphere is t…

CanopyL bandTropical forestsL-band010504 meteorology & atmospheric sciencesCarbon densityCloud cover0208 environmental biotechnologySoil ScienceClimate change02 engineering and technologyCarbon sequestrationAtmospheric sciences01 natural sciencesClimate changeSatellite imageryVegetation optical depthComputers in Earth Sciences0105 earth and related environmental sciencesRemote sensingTropicsGeology:Enginyeria de la telecomunicació [Àrees temàtiques de la UPC]020801 environmental engineeringSistemes de comunicació de microonesLidarEnvironmental scienceMicrowave communication systemsSoil moistureSistemes de gestió mediambientalSòls -- Humitat
researchProduct

Prototyping of Land-SAF leaf area index algorithm with VEGETATION and MODIS data over Europe

2009

Abstract The Satellite Application Facility on Land Surface Analysis (Land-SAF) aims to provide land surface variables for the meteorological and environmental science communities from EUMETSAT satellites. This study assesses the performance of a simplified (i.e. random distribution of vegetation is assumed) version of the Land-SAF algorithm for the estimation of Leaf Area Index (LAI) when prototyped with VEGETATION (processed in CYCLOPES program) and MODIS reflectances. The prototype estimates of LAI are evaluated both by comparison with validated CYCLOPES and MODIS LAI products derived from the same sensors and directly through comparison with ground-based estimates. Emphasis is given on …

CanopyMean squared errorBiomeSoil ScienceGeologyVegetationEnvironmental scienceSpatial variabilitySatelliteSatellite imageryComputers in Earth SciencesLeaf area indexAlgorithmRemote sensingRemote Sensing of Environment
researchProduct

Cloud masking and removal in remote sensing image time series

2017

Automatic cloud masking of Earth observation images is one of the first required steps in optical remote sensing data processing since the operational use and product generation from satellite image time series might be hampered by undetected clouds. The high temporal revisit of current and forthcoming missions and the scarcity of labeled data force us to cast cloud screening as an unsupervised change detection problem in the temporal domain. We introduce a cloud screening method based on detecting abrupt changes along the time dimension. The main assumption is that image time series follow smooth variations over land (background) and abrupt changes will be mainly due to the presence of clo…

Data processingEarth observation010504 meteorology & atmospheric sciencesComputer sciencebusiness.industry0211 other engineering and technologiesImage processingCloud computing02 engineering and technology01 natural sciencesKernel methodFeature (computer vision)General Earth and Planetary SciencesSatellite Image Time SeriesbusinessChange detection021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingJournal of Applied Remote Sensing
researchProduct