Search results for "HM"
showing 10 items of 10594 documents
Multioutput Automatic Emulator for Radiative Transfer Models
2018
This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…
Anticipating the impact of pitfalls in kinetic biodegradation parameter estimation from substrate depletion curves of organic pollutants
2019
[EN] Accurate and reliable estimation of kinetic parameters of pollutant biodegradation processes is essential for environmental and health risk assessment. Common biodegradation models proposed in the literature, such as the nonlinear Monod equation and its simplified versions (e.g. Michaelis-Menten-like and first-order equations), are problematic in terms of accuracy of kinetic parameters due to the parameter correlation. However, a comparison between these models in terms of accuracy and reliability, related to data imprecision, has not been performed in the literature. This task is necessary, mainly because the model selection cannot be straightforward, as shown in this work. To facilit…
THEMIS: A Parameter Estimation Framework for the Event Horizon Telescope
2020
This is an open access article.-- Full list of authors: Broderick, Avery E.; Gold, Roman; Karami, Mansour; Preciado-López, Jorge A.; Tiede, Paul; Pu, Hung-Yi; Akiyama, Kazunori; Alberdi, Antxon; Alef, Walter; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Baloković, Mislav; Barrett, John; Bintley, Dan; Blackburn, Lindy; Boland, Wilfred; Bouman, Katherine L.; Bower, Geoffrey C.; Bremer, Michael; Brinkerink, Christiaan D.; Brissenden, Roger; Britzen, Silke; Broguiere, Dominique; Bronzwaer, Thomas; Byun, Do-Young; Carlstrom, John E.; Chael, Andrew; Chatterjee, Shami; Chatterjee, Koushik; Chen, Ming-Tang; Chen, Yongjun; Cho, Ilje; Conway, John E.; Cordes, James M.; Crew, Geoffrey B.; Cu…
Comparison and Evaluation of the TES and ANEM Algorithms for Land Surface Temperature and Emissivity Separation over the Area of Valencia, Spain
2017
Land Surface temperature (LST) is a key magnitude for numerous studies, especially for climatology and assessment of energy fluxes between surface and atmosphere. Retrieval of accurate LST requires a good characterization of surface emissivity. Both quantities are coupled in a single radiance measurement; for this reason, for N spectral bands available in a remote sensor, there will always be N + 1 unknowns. To solve the indeterminacy, temperature-emissivity separation methods have been proposed, among which the Temperature Emissivity Separation (TES) algorithm is one of the most widely used. The Adjusted Normalized Emissivity Method (ANEM) was proposed as a modification of the Normalized E…
Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations
2021
Abstract Estimation of Green Area Index (GAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from decametric satellites was investigated in this study using a large database of ground measurements over croplands. It covers six main crop types including rice, corn, wheat and barley, sunflower, soybean and other types of crops. Ground measurements were completed using either digital hemispherical cameras, LAI-2000 or AccuPAR devices over sites representative of a decametric pixel. Sites were spread over the globe and the data collected at several growth stages concurrently to the acquisition of Landsat-8 images. Several machine learning techniques were investigated to re…
Vicarious Calibration of the Landsat 7 Thermal Infrared Band and LST Algorithm Validation of the ETM+ Instrument Using Three Global Atmospheric Profi…
2017
Due to problems in the thermal infrared sensor on-board the Landsat-8 satellite, Landsat-7 (L7) can be an interesting alternative source of thermal data because it is the only source of well-calibrated, free, high-resolution data. To contribute to the quality of thermal data, a vicarious calibration (VC) of the enhanced thematic mapper instrument and a validation of the single-channel general equation and the water vapor approach algorithm in conjunction with an inversion of the radiative transfer equation (RTE) have been performed during 2013–2015 over two Spanish test sites. For this purpose, three global atmospheric profile data sets were used to better characterize the error due to atmo…
A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data
2017
Abstract To determine aerosol optical thickness, AOT, and other geophysical parameters describing conditions in the atmosphere and at the earth's surface by inversion of remote sensing measurements from space based instrumentation, it is necessary to separate ground scenes into cloud free and cloudy or cloud contaminated. Identifying the presence of cloud in a ground scene and establishing an accurate and adequate cloud mask is a challenging task. In this study, measurements by the European Space Agency (ESA) MEdium Resolution Imaging Spectrometer (MERIS) have been used to develop a cloud identification and cloud mask algorithm for preprocessing prior to application of the new algorithm cal…
Determination of water speciation in hydrous haplogranitic glasses with partial Raman spectra
2020
Abstract We use a mathematical approach to decompose the Raman water band at 3000 cm−1 to 3750 cm−1 into two partial Raman spectra corresponding to the individual Raman activity of the two water species, i.e., molecular water (H2Om) and OH-groups, present in hydrous rhyolitic glasses. The approach is based on a least-squares optimization algorithm and the assumption that the water band can be expressed as a linear combination of two partial Raman spectra. Our model makes no assumptions regarding the shape of the partial Raman spectra. The model input consists of about 700 Raman spectra from hydrous haplogranitic (HPG8) compositions with total water contents from 0.6 to 3.1 wt% and with know…
Benchmarking numerical models of brittle thrust wedges
2016
International audience; We report quantitative results from three brittle thrust wedge experiments, comparing numerical resultsdirectly with each other and with corresponding analogue results. We first test whether the participatingcodes reproduce predictions from analytical critical taper theory. Eleven codes pass the stable wedgetest, showing negligible internal deformation and maintaining the initial surface slope upon horizontaltranslation over a frictional interface. Eight codes participated in the unstable wedge test that examinesthe evolution of a wedge by thrust formation from a subcritical state to the critical taper geometry. Thecritical taper is recovered, but the models show two…
Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran
2021
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then d…