0000000000413435

AUTHOR

Philippe Maisongrande

showing 4 related works from this author

The CoSMOS L-band experiment in Southeast Australia

2007

The CoSMOS (Campaign for validating the Operation of the Soil Moisture and Ocean Salinity mission) campaign was conducted during November of 2005 in the Goulburn River Catchment, in SE Australia. The main objective of CoSMOS was to obtain a series of L-band measurements from the air in order to validate the L-band emission model that will be used by the SMOS (Soil Moisture and Ocean Salinity) ground segment processor. In addition, the campaign was designed to investigate open questions including the Sun-glint effect over land, the application of polarimetric measurements over land, and to clarify the importance of dew and interception for soil moisture retrievals. This paper summarises the …

Radiometer010504 meteorology & atmospheric sciencesMeteorologyPASSIVE MICROWAVES[SDV]Life Sciences [q-bio]BRIGHTNESS TEMPERATURE0211 other engineering and technologiesL-BAND EMISSION MODEL02 engineering and technology15. Life on land01 natural sciencesSalinity13. Climate action[SDE]Environmental SciencesSOIL MOISTUREEnvironmental scienceRadiometryDewGround segmentInterceptionWater contentCosmosComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciences
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Indo-French High-resolution Thermal Infrared Space Mission for Earth Natural Resources Assessment and Monitoring -Concept and Definition of TRISHNA

2019

The Indian and French Space Agencies, ISRO and CNES, have conceptualized a space-borne Thermal Infrared Reflectance (TIR) mission, TRISHNA (Thermal infRared Imaging Satellite for High-resolution Natural Resource Assessment). The primary design drivers of TRISHNA are the monitoring of (i) terrestrial water stress and use, and of (ii) coastal and continental water. A suit of four TIR bands and six optical bands is planned. The TIR bands will be centred at 8.6 μm, 9.1 μm, 10.3 μm and 11.5 μm to provide noon-night global observations at 57m nadir resolution over land and coastal regions. The field of view (FOV) is ±34° and the orbit of 761&thin…

lcsh:Applied optics. Photonics010504 meteorology & atmospheric sciences0207 environmental engineering[SDU.STU]Sciences of the Universe [physics]/Earth Sciences02 engineering and technology01 natural scienceslcsh:Technologyglobal monitoringEvapotranspirationNadir020701 environmental engineering0105 earth and related environmental sciencesRemote sensingTIR remote sensing;surface energy balance;TRISHNA mission;global monitoringSpacecraftbusiness.industrylcsh:Tsurface energy balancePrimary productionlcsh:TA1501-1820Natural resourceTRISHNA mission13. Climate actionlcsh:TA1-2040TIR remote sensingEnvironmental scienceRadiometrySatellitebusinesslcsh:Engineering (General). Civil engineering (General)Water use
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An integrated modelling and remote sensing approach for hydrological study in arid and semi-arid regions: the SUDMED Program

2008

International audience; Recent efforts have been concentrated in the development of models to understand and predict the impact of environmental changes on hydrological cycle and water resources in arid and semi-arid regions. In this context, remote sensing data have been widely used to initialize, to force, or to control the simulations of these models. However, for several reasons, including the difficulty in establishing relationships between observational and model variables, the potential offered by satellite data has not been fully used. As a matter of fact, a few hydrological studies that use remote sensing data emanating from different sources (sensors, platforms) have been performe…

[SPI.OTHER]Engineering Sciences [physics]/OtherProcess modeling010504 meteorology & atmospheric sciencesARID ZONECLIMATE CHANGE0207 environmental engineeringClimate changeContext (language use)02 engineering and technology01 natural sciencesREMOTE SENSING[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsSemi-aridWater cycle[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment020701 environmental engineering0105 earth and related environmental sciencesRemote sensingSEMI ARID ZONEArid6. Clean waterWater resources13. Climate actionRemote sensing (archaeology)WATER BUDGETGeneral Earth and Planetary SciencesPrognosticsEnvironmental scienceland-surface interactions
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Varying-time random effects models for longitudinal data: unmixing and temporal interpolation of remote-sensing data

2008

Remote sensing is a helpful tool for crop monitoring or vegetation-growth estimation at a country or regional scale. However, satellite images generally have to cope with a compromise between the time frequency of observations and their resolution (i.e. pixel size). When concerned with high temporal resolution, we have to work with information on the basis of kilometric pixels, named mixed pixels, that represent aggregated responses of multiple land cover. Disaggreggation or unmixing is then necessary to downscale from the square kilometer to the local dynamic of each theme (crop, wood, meadows, etc.). Assuming the land use is known, that is to say the proportion of each theme within each m…

Statistics and ProbabilityPixelCovariance functionComputer scienceEstimatorLand coverStatistics Probability and UncertaintyBest linear unbiased predictionRandom effects modelScale (map)Remote sensingDownscalingJournal of Applied Statistics
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