Search results for "Coefficient of determination"

showing 10 items of 16 documents

An alternative conception of PM10 concentration changes after short-term precipitation in urban environment

2018

Abstract In the article, a linear model is presented which describes a reduction of PM10 mass concentration in relation to the type of precipitation and water vapour content in the air. The model was built using covariance analysis. In studies of PM10 concentration changes, the results of 247 observations were used, which were carried out in the urban area. Concentration changes were archived during short-term (30 min) convection and large-scale rainfalls. For the determination of PM10 mass concentration, the reference method was used. To describe changes in PM10 concentration in the air after precipitation, a series of linear models were created, in which the explanatory variables were: th…

ANCOVAFluid Flow and Transfer ProcessesAtmospheric ScienceEnvironmental EngineeringCoefficient of determination010504 meteorology & atmospheric sciencesTroposphereRainLinear modelMechanical EngineeringLinear modelHumidity010501 environmental sciencesParticulatesAtmospheric sciences01 natural sciencesPollutionSnowHomoscedasticityEnvironmental scienceMass concentration (chemistry)PrecipitationAerosolWater vapor0105 earth and related environmental sciencesJournal of Aerosol Science
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Comparison of Metrics for the Classification of Soils Under Variable Geometrical Conditions Using Hyperspectral Data

2008

International audience; The objective of this letter is to find a distance metric between reflectance spectra that is not sensitive to the variations on the soil reflectance induced by the geometry of solar-view angles. This is motivated by the fact that differences between spectra measured for the same soil under different observation and illumination configurations can lead to misclassifications. Using 26 soils of different compositions simulated with Hapke’s model and 92 soils of different compositions measured under 28 solarview angle geometries in laboratory conditions, we tested three metrics, namely, root-mean-square error, spectral angle mapper, and R2 (the coefficient of determinat…

Coefficient of determination010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesSOIL IDENTIFICATION02 engineering and technologySolid modeling01 natural sciencesSpectral lineCLASSIFICATION[SPI]Engineering Sciences [physics]HYPERSPECTRALSurface roughnessElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingHyperspectral imagingSoil classificationGeotechnical Engineering and Engineering GeologySOLAR-VIEW ANGLESoil waterSPECTRAL LIBRARYDISTANCE METRIC[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks

2020

In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…

Coefficient of determinationArtificial neural networkRemote sensing applicationvesien tilaspektrikuvausHyperspectral imagingneuroverkotvedenlaatuConvolutional neural networkwater qualityPearson product-moment correlation coefficientsymbols.namesakeremote sensinghyperspectralilmakuvakartoitusMultilayer perceptronconvolutional neural networkssymbolsEnvironmental scienceWater qualitykaukokartoitusRemote sensing
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Comparison of metrics to remove the influence of geometrical conditions on soil reflectance

2007

The objective of this work is to find the best metric to ignore the variations of soil reflectance induced by the solar-view angles geometry. Differences between spectra measured for the same soil under different observation and illumination configurations can leads to misclassifications. Using ninety two soils of different composition measured under twenty eight solar- view angles geometries, we tested 3 metrics : RMSE, SAM, R2 (the coefficient of determination) and we compared their performances. The best metric seems to be the coefficient of determination with 93 % of good classifications.

Coefficient of determinationMean squared errorSoil waterMultispectral imageMetric (mathematics)Surface roughnessHyperspectral imagingReflectivityRemote sensingMathematics2007 IEEE International Geoscience and Remote Sensing Symposium
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A modified applicative criterion of the physical model concept for evaluating plot soil erosion predictions

2015

Abstract In this paper, the physical model concept by Nearing (1998. Catena 32: 15–22) was assessed. Soil loss data collected on plots of different  widths (2–8 m), lengths (11–44 m) and steepnesses (14.9–26.0%), equipped in south and central Italy, were used. Differences in width between plots of given length and steepness determined a lower data correlation and more deviation of the fitted regression line from the identity one. A coefficient of determination between measured, M , and predicted, P , soil losses of 0.77 was representative of the best-case prediction scenario, according to Nearing (1998). The relative differences, Rdiff  = ( P − M ) / ( P + M ), decreased in absolute value a…

Coefficient of determinationSoil loss dataAbsolute value (algebra)Plot measurementPlot (graphics)Soil erosion; Plot measurements; Soil loss data; Physical modelPhysical modelSoil lossLinear regressionStatisticsErosionRange (statistics)Soil erosionPlot measurementsSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliEquivalence (measure theory)Earth-Surface ProcessesMathematics
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Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy

2013

Abstract Reflectance spectroscopy provides an alternate method to non-destructively characterize key soil properties. Different approaches, including chemometrics techniques or specific absorption features, have been proposed to estimate soil properties from visible and near-infrared (VNIR, 400-1200 nm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance domains. The main goal of this study was to test the performance of two distinct methods for soil texture estimation by VNIR-SWIR reflectance measurements: i) the Continuum Removal (CR) technique that was used to correlate specific spectral absorption features with clay, silt and sand content, and ii) the Partial Least-Squares Regressio…

Coefficient of determinationSoil testPartial Least Squares RegressionSoil textureReflectance spectroscopySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaMineralogySiltVNIRChemometricsContinuum RemovalSpectroradiometerSoil texturePartial least squares regressionGeneral Earth and Planetary SciencesEnvironmental scienceSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliGeneral Environmental ScienceRemote sensing
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Quantification of Listeria monocytogenes in salads by real time quantitative PCR

2005

Abstract A real time quantitative PCR (RTQ-PCR) was carried out purifying DNA extracts of Listeria monocytogenes using a High Pure Listeria Sample Preparation Kit and quantifying in a LightCycler system with hybridisation probes. A standard curve was constructed with serial dilutions. A range linear relationship, from 10 to 10 5 L. monocytogenes colony forming units (CFU), was observed between threshold cycle ( C t ) and logarithmic concentration of the serial dilutions. The assay was linear in a range from 10 to 10 5 L. monocytogenes CFU and the coefficient of determination ( r 2 ) was > 0.98. RTQ-PCR presented an efficiency of > 85%. The accuracy of the PCR-based assay, expressed as % bia…

DNA BacterialCoefficient of determinationSerial dilutionColony Count MicrobialFood ContaminationBiologymedicine.disease_causeModels BiologicalPolymerase Chain ReactionSensitivity and SpecificityMicrobiologyMicrobiologyListeria monocytogenesmedicineHumansSample preparationColony-forming unitChromatographyGeneral MedicineLettucebiology.organism_classificationListeria monocytogenesStandard curveConsumer Product SafetySpainFood MicrobiologyLinear ModelsListeriaQuantitative analysis (chemistry)Food AnalysisFood ScienceInternational Journal of Food Microbiology
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Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery

2021

Non-photosynthetic vegetation (NPV) biomass has been identified as a priority variable for upcoming spaceborne imaging spectroscopy missions, calling for a quantitative estimation of lignocellulosic plant material as opposed to the sole indication of surface coverage. Therefore, we propose a hybrid model for the retrieval of non-photosynthetic cropland biomass. The workflow included coupling the leaf optical model PROSPECT-PRO with the canopy reflectance model 4SAIL, which allowed us to simulate NPV biomass from carbon-based constituents (CBC) and leaf area index (LAI). PROSAIL-PRO provided a training database for a Gaussian process regression (GPR) algorithm, simulating a wide range of non…

PCACoefficient of determinationDimensionality reductionScienceQBiomassHyperspectral imaginghybrid retrievalPRISMAPROSAIL-PROVegetationNPVImaging spectroscopyCHIMEKrigingactive learningGeneral Earth and Planetary SciencesEnvironmental scienceLeaf area indexPRISMA; CHIME; NPV; Gaussian process regression; hybrid retrieval; active learning; PCA; PROSAIL-PROGaussian process regressionRemote sensingRemote Sensing
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Relationship between UVB and broadband solar radiation in Spain

2014

The daily values of UVB irradiation (290–315 nm), IUVB, and the broadband total irradiation (300–2800 nm), IT, measured on a horizontal plane have been correlated for the period 2000–2008 at 16 measurement sites in Spain. The results have been compared with the daily experimental values registered at the same sites during the period 2009–2011. The coefficients of determination R2 obtained by applying a linear regression are higher than 0.88 for all sites and increase to 0.94 when using a quadratic regression. When all data are considered together, the values of R2 are 0.91 and 0.97 for the linear and quadratic regressions, respectively. Three different clearness indices, which are dimension…

Polynomial regressionAtmospheric ScienceCoefficient of determinationMean squared errorMeteorologyClimatologyLinear regressionSolar zenith angleRadiationAtmospheric sciencesLatitudeMathematicsDimensionless quantityInternational Journal of Climatology
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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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