Search results for "Biosphere"

showing 5 items of 55 documents

Machine Learning Methods for Spatial and Temporal Parameter Estimation

2020

Monitoring vegetation with satellite remote sensing is of paramount relevance to understand the status and health of our planet. Accurate and constant monitoring of the biosphere has large societal, economical, and environmental implications, given the increasing demand of biofuels and food by the world population. The current democratization of machine learning, big data, and high processing capabilities allow us to take such endeavor in a decisive manner. This chapter proposes three novel machine learning approaches to exploit spatial, temporal, multi-sensor, and large-scale data characteristics. We show (1) the application of multi-output Gaussian processes for gap-filling time series of…

business.industryEstimation theoryComputer scienceBig dataBiosphereVegetationMachine learningcomputer.software_genreRandom forestsymbols.namesakeKernel (statistics)symbolsArtificial intelligenceScale (map)businessGaussian processcomputer
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Nanoscale Engineering in the Biosciences

2009

Biological matter is one of the most diverse and important classes of materials. Products of living organisms (wood, bone, cotton, wool, leather, coal, oil, drugs, etc.) are vital to humanity as foodstuffs, energy sources, engineering and construction materials, and chemicals; and by the way, they shape the environment of the biosphere.

business.industryWoolotorhinolaryngologic diseasestechnology industry and agricultureEnvironmental scienceBiosphereCoalNanotechnologybusinessEnergy sourcecomplex mixtures
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SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product

2017

© 2017 by the authors. The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product that was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d'Etudes Spatiales de la BIOsphère). One of the main go…

environmental_sciencesL bandVegetation optical depth010504 meteorology & atmospheric sciencesNDVI[SDV]Life Sciences [q-bio]Science0211 other engineering and technologiesWeather forecasting0207 environmental engineeringSoil science02 engineering and technologycomputer.software_genre01 natural sciencesSMOS; L-band; Level 3; ECMWF; SMOS-IC; soil moisture; vegetation optical depth; MODIS; NDVINormalized Difference Vegetation IndexECMWFvegetation optical depthtempératurehumidité du solluminosity14. Life underwater020701 environmental engineeringWater content021101 geological & geomatics engineeringRemote sensing0105 earth and related environmental sciencessalinité des océansQBiosphereluminositéVegetationAlbedoL-bandSpectroradiometerMODIS13. Climate actionBrightness temperatureProduct (mathematics)General Earth and Planetary SciencesEnvironmental sciencesoil moistureSMOS;L-band;level 3;ECMWF;SMOS-IC;soil moisture;vegetation optical depth;MODIS;NDVISMOS-ICcomputerLevel 3SMOSRemote Sensing
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Landscape Ecological Structure in the Eastern Part of the North Vidzeme Biosphere Reserve, Latvia

2008

Landscape Ecological Structure in the Eastern Part of the North Vidzeme Biosphere Reserve, Latvia Latvia is a country where the forest area has increased and habitat fragmentation has reversed compared with many other European countries. In order to examine the effect of this expansion on biodiversity, vegetation maps dating from 2002 and the years 1930-1936 were used for comparative landscape structure analyses while archive materials from forest plans, and data from the national forest management database were used for land use analysis. Four landscape ecoregions in the eastern side of the North Vidzeme Biosphere Reserve were selected for analysis. Landscape structure indicators derived f…

forestMultidisciplinaryGeographyGeneral interestEcologyfragmentationScienceQlatviaBiosphereGap analysis (conservation)landscape metricsgap analysisProceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences.
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Including vegetation dynamics in an atmospheric chemistry-enabled general circulation model: linking LPJ-GUESS (v4.0) with the EMAC modelling system …

2020

Central to the development of Earth system models (ESMs) has been the coupling of previously separate model types, such as ocean, atmospheric, and vegetation models, to address interactive feedbacks between the system components. A modelling framework which combines a detailed representation of these components, including vegetation and other land surface processes, enables the study of land–atmosphere feedbacks under global climate change. Here we present the initial steps of coupling LPJ-GUESS, a dynamic global vegetation model, to the atmospheric chemistry-enabled atmosphere–ocean general circulation model EMAC. The LPJ-GUESS framework is based on ecophysiological processes, such as phot…

lcsh:GeologyBiomass (ecology)ArcticGlobal warminglcsh:QE1-996.5BiosphereEnvironmental scienceGeneral MedicineVegetationPotential natural vegetationDynamic global vegetation modelPermafrostAtmospheric sciencesGeoscientific Model Development
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