Search results for " optical depth"

showing 10 items of 27 documents

Interannual Variability of Biomass (SMOS Vegetation Optical Depth) Over the Contiguous United States

2021

Interannual variability in biomass represented by SMOS vegetation optical depth (VOD) and precipitation was assessed over the Contiguous United States. The greatest interannual variability in both VOD and precipitation occurred in shrubs and herbaceous (grasslands), with forests the least variable. At a continental scale, VOD was strongly correlated with annual precipitation. Results showed a significant correlation coefficient (∼ 0.93) between interannual variability of precipitation and biomass, indicating that the interannual variability of precipitation could be a good predictor of the interannual variability of biomass.

Biomass (ecology)Vegetation optical depthCorrelation coefficientfood and beveragesEnvironmental sciencePrecipitationVegetationHerbaceous plantAtmospheric sciencescomplex mixtures2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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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
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L-Band vegetation optical depth for crop phenology monitoring and crop yield assessment

2018

Vegetation Optical Depth (VOD) at L-band is highly sensitive to the water content and above-ground biomass of vegetation. Hence, it has great potential for monitoring crop phenology and for providing crop yield forecasts. Recently, the Multi-Temporal Dual Channel Algorithm (MT -DCA) has been proposed to retrieve L-band VOD from Soil Moisture Active Passive (SMAP) measurements. In previous research, SMAP VOD has been compared to crop phenology and has been used to derive crop yield estimates. Here, we review and expand these initial research studies. In particular, we quantify the capability of VOD to detect different crop stages, and test different VOD metrics (i.e., maximum, range and inte…

Crop phenologyL bandCrop phenologyYield forecastsTeledetecció010504 meteorology & atmospheric sciencesAgricultural engineering0211 other engineering and technologiesSoil science02 engineering and technology:Enginyeria agroalimentària [Àrees temàtiques de la UPC]01 natural sciencesphenologyCropEnginyeria agronòmicacropWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesBiomass (ecology)business.industryCrop yieldVODVegetationSMAPRemote sensingyieldAgro-ecosystemsL-band:Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció [Àrees temàtiques de la UPC]AgricultureEnvironmental scienceVegetation optical DepthRadiometerbusiness
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Results from the Fourth WMO Filter Radiometer Comparison for aerosol optical depth measurements

2018

Abstract. This study presents the results of the Fourth Filter Radiometer Comparison that was held in Davos, Switzerland, between 28 September and 16 October 2015. Thirty filter radiometers and spectroradiometers from 12 countries participated including reference instruments from global aerosol networks. The absolute differences of all instruments compared to the reference have been based on the World Meteorological Organization (WMO) criterion defined as follows: 95% of the measured data has to be within 0.005 ± 0.001∕m (where m is the air mass). At least 24 out of 29 instruments achieved this goal at both 500 and 865 nm, while 12 out of 17 and 13 out of 21 achieved this at 368 and 412 nm,…

Earth's energy budgetTermodinàmica atmosfèricaAtmospheric ScienceAngstrom exponent010504 meteorology & atmospheric sciencesMeteorologi och atmosfärforskning01 natural sciencesAerosol optical depthlcsh:Chemistry010309 opticssymbols.namesakeAerosol networks0103 physical sciencesRayleigh scatteringradiometry field campaignRadiation balance0105 earth and related environmental sciencesRemote sensingAerosolsRadiometerlcsh:QC1-999AerosolSpectroradiometerlcsh:QD1-99913. Climate action[SDU]Sciences of the Universe [physics]Meteorology and Atmospheric SciencessymbolsEnvironmental scienceRadiometerSun photometerslcsh:PhysicsWater vapor
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Retrieval of Forest Water Potential from L-Band Vegetation Optical Depth

2021

A retrieval methodology for forest water potential from ground-based L-band radiometry is proposed. It contains the estimation of the gravimetric and the relative water content of a forest stand and tests in situ- and model-based functions to transform these estimates into forest water potential. The retrieval is based on vegetation optical depth data from a tower-based experiment of the SMAPVEX 19–21 campaign for the period from April to October 2019 at Harvard Forest, MA, USA. In addition, comparison and validation with in situ measurements on leaf and xylem water potential as well as on leaf wetness and complex permittivity are foreseen to understand limitations and potentials of the pro…

L bandRadiometerXylemradiometryVegetationL-bandFootprintharvard forestforestvegetation moistureEnvironmental scienceRadiometryVegetation optical depthground-basedwater potentialWater contentLeaf wetnessRemote sensing2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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Analyzing the impact of using the SRP (Simplified roughness parameterization) method on soil moisture retrieval over different regions of the globe

2015

International audience; This paper focuses on a new approach to account for soil roughness effects in the retrieval of soil moisture (SM) at L-band in the framework of the SMOS (Soil Moisture and Ocean Salinity) mission: the Simplified Roughness Parameterization (SRP). While the classical retrieval approach considers SM and τ nad (vegetation optical depth) as retrieved parameters, this approach is based on the retrieval of SM and the TR parameter combining τ nad and soil roughness (TR τ nad + Hr /2). Different roughness parameterizations were tested to find the best correlation (R), bias and unbiased RMSE (ubRMSE) when comparing homogeneous retrievals of SM and in situ SM measurements carri…

L bandVegetation optical depth010504 meteorology & atmospheric sciencesMean squared errorvegetation mapping0211 other engineering and technologiesSampling (statistics)[SDU.STU]Sciences of the Universe [physics]/Earth SciencesSoil science02 engineering and technologySurface finish01 natural sciencesL-bandHomogeneousEnvironmental sciencesoil measurementsmicrowave radiometrysoil moistureWater contentSoil roughness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingmathematical model021101 geological & geomatics engineering0105 earth and related environmental sciences
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Time-variations of zeroth-order vegetation absorption and scattering at L-band

2021

Abstract Surface soil moisture and vegetation optical depth (VOD), as an indicator of vegetation wet biomass, from passive microwave remote sensing have been increasingly applied in global ecology and climate research. Both soil moisture and VOD are retrieved from satellite brightness temperature measurements assuming a zeroth order radiative transfer model, commonly known as the tau-omega model. In this model the emission of a vegetated surface is dependent on soil moisture, vegetation absorption and vegetation scattering. Vegetation scattering is normally represented by the single scattering albedo, ω, and is commonly assumed to be a time-invariant calibration parameter to achieve high ac…

LidarScatteringSingle-scattering albedoAttenuationeffective scattering albedoSoil ScienceGeologySoil scienceContext (language use)SMAPradiometryVegetationvegetation optical depthICESat-2L-bandAtmospheric radiative transfer codesBrightness temperaturerelative canopy scatteringEnvironmental scienceComputers in Earth SciencesAbsorption (electromagnetic radiation)relative canopy absorptionRemote sensingRemote Sensing of Environment
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First evaluation of the simultaneous SMOS and ELBARA-II observations in the Mediterranean region

2012

Abstract The SMOS (Soil Moisture and Ocean Salinity) mission was launched on November 2, 2009. Over the land surfaces, simultaneous retrievals of surface soil moisture (SM) and vegetation characteristics made from the multi-angular and dual polarization SMOS observations are now available from Level-2 (L2) products delivered by the European Space Agency (ESA). Therefore, first analyses evaluating the SMOS observations in terms of Brightness Temperatures (TB) and L2 products (SM and vegetation optical depth TAU) can be carried out over several calibration/validation (cal/val) sites selected by ESA over all continents. This study is based on SMOS observations and in situ measurements carried …

Mediterranean climate010504 meteorology & atmospheric sciences[SDV]Life Sciences [q-bio]0211 other engineering and technologiesSoil Science550 - Earth sciences02 engineering and technology01 natural sciencesVineyardNormalized Difference Vegetation Index14. Life underwaterComputers in Earth SciencesWater contentComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometerGeology15. Life on land13. Climate actionBrightness temperatureSoil water[SDE]Environmental SciencesEnvironmental sciencesoil moisture; optical depth; retrievals; mediterranean environment; level 2 algorithm; brightness temperature; vineyards; soil; NDVI; MODIS;Moderate-resolution imaging spectroradiometerSMOS
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Monitoring tropical forests under a functional perspective with satellite-based vegetation optical depth.

2020

Monitoring ecosystem functions in forests is a priority in a climate change scenario, as climate-induced events may initially alter the functions more than slow-changing attributes, such as biomass. The ecosystem functional properties (EFPs) are quantities that characterize key ecosystem processes. They can be derived by point observations of gas and energy exchanges between the ecosystems and the atmosphere that are collected globally at FLUXNET flux tower sites and upscaled at ecosystem level. The properties here considered describe the ability of ecosystems to optimize the use of resources for carbon uptake. They represent functional forest information, are dependent on environmental dri…

Settore ING-INF/02010504 meteorology & atmospheric sciencesClimate Changeecosystem functional properties0211 other engineering and technologiesFluxClimate changeGPPmax02 engineering and technologyForestsAtmospheric sciences01 natural sciencesvegetation optical depthTreesFluxNetClimate change scenarioLUEEnvironmental ChemistryEcosystemWater contentEcosystem021101 geological & geomatics engineering0105 earth and related environmental sciencesGeneral Environmental ScienceGlobal and Planetary ChangeBiomass (ecology)Ecology15. Life on landSouth America13. Climate actionAfricaEnvironmental scienceSatelliteGlobal change biologyREFERENCES
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Synergistic integration of optical and microwave satellite data for crop yield estimation

2019

Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation (EO) remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave) remote sensing data for crop yield estimation and forecasting using two novel approaches. We first propose the lag between Enhanced Vegetation Index (EVI) derived from MODIS and Vegetation Optical Depth (VOD) derived from SMAP as a new joint metric combining the information from the two satellite sensors in a unique feature or des…

Signal Processing (eess.SP)FOS: Computer and information sciencesEarth observationCoefficient of determinationTeledetecció010504 meteorology & atmospheric sciencesEnhanced vegetation index0208 environmental biotechnologyFOS: Physical sciencesSoil Science02 engineering and technologyStatistics - Applications01 natural sciencesArticleModerate resolution imaging spectroradiometer (MODIS)Robustness (computer science)Machine learningLinear regressionFOS: Electrical engineering electronic engineering information engineeringFeature (machine learning)Kernel ridge regressionCrop yield estimationVegetation optical depthApplications (stat.AP)Electrical Engineering and Systems Science - Signal ProcessingComputers in Earth Sciences0105 earth and related environmental sciencesRemote sensingMathematics2. Zero hungerCrop yieldProcessos estocàsticsGeologyEnhanced vegetation indexAgro-ecosystems020801 environmental engineeringPhysics - Data Analysis Statistics and ProbabilityMetric (mathematics)Soil moisture active passive (SMAP)Data Analysis Statistics and Probability (physics.data-an)Imatges Processament
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