Search results for "Mean squared error"

showing 5 items of 145 documents

Die Bestimmung der Molekulargewichtsverteilung von nichtkristallisierenden Polymeren mit dem Elektronenmikroskop, 6. Fehlerkorrektur der experimentel…

1977

A mathematical treatment is described, by means of which the effect of the measuring errors on the number molecular weight distribution of polymers, as obtained with an electron microscope (EM), can be eliminated. It is shown, that the difference in the nonuniformities of the measured and the corrected distribution would be negligible only in the case of samples with high average degrees of polymerization and sufficiently broad distributions. Otherwise differences of 10% or more can be found, depending on the size of the actual measuring error. This is shown by means of four practical examples. For a practical application the measuring error may not exceed some critical value, which, though…

chemistry.chemical_classificationMean squared errorPolymerizationDistribution (number theory)ChemistrylawPolymer chemistryAnalytical chemistryMolar mass distributionPolymerElectron microscopeCritical valuelaw.inventionDie Makromolekulare Chemie
researchProduct

Analysis of the performance of the TES algorithm over urban areas

2014

International audience; The temperature and emissivity separation (TES) algorithm is used to retrieve the land surface emissivity (LSE) and land surface temperature (LST) values from multispectral thermal infrared sensors. In this paper, we analyze the performance of this methodology over urban areas, which are characterized by a large number of different surface materials, a variability in the lowest layer of the atmospheric profiles, and a 3-D structure. These specificities induce errors in the LSE and LST retrieval, which should be quantified. With this aim, the efficiency of the TES algorithm over urban materials, the atmospheric correction, and the impact of the 3-D architecture of urb…

land surface temperature (LST)010504 meteorology & atmospheric sciencesMeteorologyMean squared errorMultispectral image0211 other engineering and technologies02 engineering and technologyAtmospheric model01 natural sciencestemperature and emissivity separation (TES)AtmosphereError budget[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing11. SustainabilityEmissivityRadiative transferurban.Electrical and Electronic Engineering021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingAtmospheric correctionRadianceGeneral Earth and Planetary SciencesEnvironmental scienceAlgorithmurban[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingland surface emissivity (LSE)
researchProduct

Experimental Analysis of Velocity Distribution in a Coarse-Grained Debris Flow: A Modified Bagnold’s Equation

2020

Today, Bagnold&rsquo

lcsh:Hydraulic engineering010504 meteorology & atmospheric sciencesMean squared errorGeography Planning and DevelopmentAquatic Science01 natural sciencesBiochemistry010305 fluids & plasmasDebris flowflow velocitydebris flowslcsh:Water supply for domestic and industrial purposeslcsh:TC1-9780103 physical sciencessediment concentration0105 earth and related environmental sciencesWater Science and Technologylcsh:TD201-500Function (mathematics)MechanicsDebris flowDebrisSediment concentrationFlumeDistribution (mathematics)Flow velocityprevisionGeology
researchProduct

Global Estimation of Biophysical Variables from Google Earth Engine Platform

2018

This paper proposes a processing chain for the derivation of global Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fraction Vegetation Cover (FVC), and Canopy water content (CWC) maps from 15-years of MODIS data exploiting the capabilities of the Google Earth Engine (GEE) cloud platform. The retrieval chain is based on a hybrid method inverting the PROSAIL radiative transfer model (RTM) with Random forests (RF) regression. A major feature of this work is the implementation of a retrieval chain exploiting the GEE capabilities using global and climate data records (CDR) of both MODIS surface reflectance and LAI/FAPAR datasets allowing the global estim…

random forestsCWC010504 meteorology & atmospheric sciencesMean squared errorScience0211 other engineering and technologiesGoogle Earth Engine; LAI; FVC; FAPAR; CWC; plant traits; random forests; PROSAIL02 engineering and technologyLand cover01 natural sciencesAtmospheric radiative transfer codesRange (statistics)Parametrization (atmospheric modeling)FAPARLeaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingPROSAILQ15. Life on landFVCLAIRandom forestplant traits13. Climate actionPhotosynthetically active radiationGeneral Earth and Planetary SciencesEnvironmental scienceGoogle Earth EngineRemote Sensing; Volume 10; Issue 8; Pages: 1167
researchProduct

ESTIMATING SOIL PARTICLE-SIZE DISTRIBUTION FOR SICILIAN SOILS

2009

The soil particle-size distribution (PSD) is commonly used for soil classification and for estimating soil behavior. An accurate mathematical representation of the PSD is required to estimate soil hydraulic properties and to compare texture measurements from different classification systems. The objective of this study was to evaluate the ability of the Haverkamp and Parlange (HP) and Fredlund et al. (F) PSD models to fit 243 measured PSDs from a wide range of 38 005_Bagarello(547)_33 18-11-2009 11:55 Pagina 38 soil textures in Sicily and to test the effect of the number of measured particle diameters on the fitting of the theoretical PSD. For each soil textural class, the best fitting perf…

sicilian soilsParticle-size distributionMean squared errorSoil textureMechanical Engineeringlcsh:SBioengineeringSoil classificationSoil sciencelcsh:S1-972Industrial and Manufacturing EngineeringSoil gradationlcsh:AgricultureLoamParticle-size distributionSoil waterRange (statistics)Settore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliParticle-size distribution Particle-size distribution models Soil physical properties.lcsh:Agriculture (General)MathematicsJournal of Agricultural Engineering
researchProduct