Search results for "VEGETATION"

showing 10 items of 1069 documents

Analysis of winter dust activity off the coast of West Africa using a new 24-year over-water advanced very high resolution radiometer satellite dust …

2006

A 24-year (1982-2005) winter daytime advanced very high resolution radiometer (AVHRR) data set has been processed utilizing a new over-water dust detection algorithm. The dust data are for the oceanic regions surrounding West Africa and provide a long-term remotely sensed continuous record of dustiness in the region. These AVHRR dust observations are comparable to dust records produced via the Total Ozone Mapping Spectrometer and Meteosat instruments. Strong positive correlations between the wintertime Jones North Atlantic Oscillation index and this dust record are observed across the entire oceanic region, corroborating earlier studies on the relationship between the two. Also consistent w…

Atmospheric ScienceDaytimeEcologyAdvanced very-high-resolution radiometerTotal Ozone Mapping SpectrometerPaleontologySoil ScienceForestryVegetationAquatic ScienceOceanographyNormalized Difference Vegetation IndexGeophysicsSpace and Planetary ScienceGeochemistry and PetrologyNorth Atlantic oscillationClimatologyEarth and Planetary Sciences (miscellaneous)Environmental scienceSatellitePrecipitationEarth-Surface ProcessesWater Science and TechnologyJournal of Geophysical Research
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Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning

2009

In recent years, LIDAR (light detection and ranging) sensors have been widely used to measure environmental parameters such as the structural characteristics of trees, crops and forests. Knowledge of the structural characteristics of plants has a high scientific value due to their influence in many biophysical processes including, photosynthesis, growth, CO2-sequestration and evapotranspiration, playing a key role in the exchange of matter and energy between plants and the atmosphere, and affecting terrestrial, above-ground, carbon storage. In this work, we report the use of a 2D LIDAR scanner in agriculture to obtain three-dimensional (3D) structural characteristics of plants. LIDAR allows…

Atmospheric ScienceGlobal and Planetary ChangeCorrelation coefficientForestryVegetationOptical radarRadar òpticTree volumeFotogrametria aèriaArbresTerrestrial LIDARTree (data structure)Lidar:Enginyeria agroalimentària::Ciències forestals [Àrees temàtiques de la UPC]Evapotranspiration3D Plant structureEnvironmental scienceOrchardLeaf area indexAgronomy and Crop ScienceLaser measurementsRemote sensingWoody plant
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Improving RAMS and WRF mesoscale forecasts over two distinct vegetation covers using an appropriate thermal roughness length parameterization

2019

Land Surface Models (LSM) have shown some difficulties to properly simulate day-time 2-m air and surface skin temperatures. This kind of models are coupled to atmospheric models in mesoscale modelling, such as the Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) Model. This model coupling is used within Numerical Weather Prediction Systems (NWP) in order to forecast key physical processes for agricultural meteorology and forestry as well as in ecological modelling. The current study first evaluates the surface energy fluxes and temperatures simulated by these two state-of-the-art NWP models over two distinct vegetated covers, one corresponding to a …

Atmospheric ScienceGlobal and Planetary ChangeMeteorologyNumerical weather prediction/forecastingFísica de la TierraMesoscale meteorologyEuropean Regional Development FundSurface-layer parameterizationForestryVegetationMesoscale modellingBoscos i silviculturaSurface energy fluxRoughness lengthThermal roughness lengthWeather Research and Forecasting ModelEnvironmental scienceLand surface modelsSurface energy fluxesAgronomy and Crop SciencePhysics::Atmospheric and Oceanic Physics
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Integrated remote sensing approach to global agricultural drought monitoring

2018

Abstract This study explores the use of the Soil Moisture Agricultural Drought Index (SMADI) as a global estimator of agricultural drought. Previous research presented SMADI as a novel index based on the joint use of remotely sensed datasets of land surface temperature (LST) and normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) together with the surface soil moisture (SSM) from the Soil Moisture and Ocean Salinity (SMOS) mission. This study presents the results of applying SMADI at the global scale with a spatial resolution of 0.05° every 15 days. The period of the study spanned from 2010 to 2015. Three spatial scales (local, region…

Atmospheric ScienceGlobal and Planetary Changegeographygeography.geographical_feature_categoryIndex (economics)010504 meteorology & atmospheric sciencesWarning systembusiness.industry0211 other engineering and technologiesForestry02 engineering and technology01 natural sciencesNormalized Difference Vegetation IndexAgriculturePeninsulaClimatologyEnvironmental scienceModerate-resolution imaging spectroradiometerScale (map)businessAgronomy and Crop ScienceWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesAgricultural and Forest Meteorology
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Trend Analysis of Global MODIS-Terra Vegetation Indices and Land Surface Temperature Between 2000 and 2011

2013

Previous works have shown that the combination of vegetation indices with land surface temperature (LST) improves the analysis of vegetation changes. Here, global MODIS-Terra monthly data from 2000 to 2011 were downloaded and organized into LST, NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) time series. These time series were then corrected from cloud and atmospheric residual contamination through the IDR (iterative Interpolation for Data Reconstruction) method. Then, statistics were retrieved from both corrected time series, and the YLCD (Yearly Land Cover Dynamics) approach has been applied to data sources (NDVI-LST and EVI-LST) to analyze changes in th…

Atmospheric ScienceGlobal warmingEnhanced vegetation indexLand coverSpatial distributionNormalized Difference Vegetation IndexTrend analysisBorealClimatologymedicineEnvironmental scienceComputers in Earth Sciencesmedicine.symptomVegetation (pathology)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Comparative study of three satellite image time-series decomposition methods for vegetation change detection

2018

International audience; Satellite image time-series (SITS) methods have contributed notably to detection of global change over the last decades, for instance by tracking vegetation changes. Compared with multi-temporal change detection methods, temporally highly resolved SITS methods provide more information in a single analysis, for instance on the type and consistency of change. In particular, SITS decomposition methods show a great potential in extracting various components from non-stationary time series, which allows for an improved interpretation of the temporal variability. Even though many case studies have applied SITS decomposition methods, a systematic comparison of common algori…

Atmospheric ScienceNon-stationary010504 meteorology & atmospheric sciencesBFASTSTL0211 other engineering and technologiesMRA-WT02 engineering and technology01 natural sciencesNormalized Difference Vegetation Indexlcsh:OceanographyDecomposition (computer science)medicineSatellite imagerylcsh:GC1-1581Computers in Earth SciencesNDVI time series021101 geological & geomatics engineering0105 earth and related environmental sciencesGeneral Environmental ScienceRemote sensingApplied Mathematicslcsh:QE1-996.5Global change15. Life on landSeasonalitymedicine.diseaselcsh:GeologyEnvironmental scienceChange detectionSatellite Image Time Seriesmedicine.symptomVegetation (pathology)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingChange detection
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Multilayer modelling of ozone fluxes on winter wheat reveals large deposition on wet senescing leaves

2015

Understanding how ozone is deposited on vegetation canopies is needed to perform tropospheric greenhouse gas budgets and evaluate the associated damage on vegetation. In this study, we propose a new multilayer scheme of ozone deposition on vegetation canopies that predicts stomatal, cuticular and soil deposition pathways separately. This mechanistic ozone deposition scheme is based on the multi-layer, multi-leaf mass and energy transfer model MuSICA. This model was chosen because it explicitly simulates the processes of rain interception, through fall and evaporation at different depths within the vegetation canopy, so that ozone deposition on wet leaf cuticles can be explicitly modelled wi…

Atmospheric ScienceOzonesenescence010504 meteorology & atmospheric sciences[SDV]Life Sciences [q-bio]010501 environmental sciencesAtmospheric sciences01 natural scienceswater filmchemistry.chemical_compoundMuSICAozone depositionEvapotranspirationwheat0105 earth and related environmental sciencesHydrologyGlobal and Planetary Change[ SDV ] Life Sciences [q-bio]ForestryVegetation15. Life on landchemistry13. Climate actionGreenhouse gasEnvironmental scienceDewcuticleInterceptionAgronomy and Crop ScienceDeposition (chemistry)Water vapor
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Vegetation fire emissions and their impact on air pollution and climate

2009

Gaseous and particulate emissions from vegetation fires substantially modify the atmospheric chemical composition, degrade air quality and can alter weather and climate. The impact of vegetation fire emissions on air pollution and climate has been recognised in the late 1970s. The application of satellite data for fire-related studies in the beginning of the 21th century represented a major break through in our understanding of the global importance of fires. Today the location and extent of vegetation fires, burned area and emissions released from fires are determined from satellite products even though many uncertainties persist. Numerous dedicated experimental and modeling studies contri…

Atmospheric SciencePeat010504 meteorology & atmospheric sciencesMeteorologyAir pollutionWeather and climate010501 environmental sciencesmedicine.disease_cause01 natural sciences/dk/atira/pure/sustainabledevelopmentgoals/climate_actionEnvironmental protection11. SustainabilitymedicineSDG 13 - Climate ActionEnvironmental impact assessment[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentAir quality indexComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesGeneral Environmental Science[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereVegetation15. Life on landParticulatesSeasonalitymedicine.disease13. Climate actionEnvironmental scienceAtmospheric Environment
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Evaluation of split-window and dual-angle correction methods for land surface temperature retrieval from Envisat/Advanced Along Track Scanning Radiom…

2006

[1] Land surface temperature (LST) can be derived from thermal infrared remote sensing data provided that atmospheric and emissivity effects are corrected for. In this paper, two correction methods were evaluated using a database of ground LST measurements and concurrent Envisat/Advanced Along Track Scanning Radiometer (AATSR) data. They were the split-window (SW) method, which uses two channels at 11 and 12 μm, and the dual-angle (DA) method, using one single channel (11 μm) at two observation angles (close to nadir and around 55° forward). The ground LST measurements were performed in a large, flat, and thermally homogeneous area of rice fields during the summers of 2002–2005, when the cr…

Atmospheric ScienceRadiometerEcologyPaleontologySoil ScienceForestryAATSRLand coverVegetationAquatic ScienceOceanographyStandard deviationGeophysicsSpace and Planetary ScienceGeochemistry and PetrologyEarth and Planetary Sciences (miscellaneous)NadirTrajectoryEmissivityEnvironmental scienceEarth-Surface ProcessesWater Science and TechnologyRemote sensingJournal of Geophysical Research
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Hyperspectral response of agronomic variables to background optical variability: Results of a numerical experiment

2022

Understanding how biophysical and biochemical variables contribute to the spectral characteristics of vegetation canopies is critical for their monitoring. Quantifying these contributions, however, remains difficult due to extraneous factors such as the spectral variability of canopy background materials, including soil/crop-residue moisture, soil-type, and non-photosynthetic vegetation (NPV). This study focused on exploring the spectral response of two important agronomic variables (1) leaf chlorophyll content (Cab ) and (2) leaf area index (LAI) under various canopy backgrounds through a global sensitivity analysis of wheat-like canopy spectra simulated using the physically-based PROSAIL …

Atmospheric ScienceResilient LivelihoodsLEAF-AREA-INDEXSoil typePHOTOCHEMICAL REFLECTANCE INDEXBIOPHYSICAL PROPERTIESMeteorology & Atmospheric SciencesAdaptationLeaf chlorophyll contentGlobal and Planetary ChangeScience & TechnologyVEGETATION INDEXESSPECTRAL INDEXESGLOBAL SENSITIVITY-ANALYSISAgricultureNon-photosynthetic vegetationForestry22/4 OA procedureAgronomyHyperspectral responseGlobal sensitivity analysisITC-ISI-JOURNAL-ARTICLEPhysical SciencesLeaf area indexCHLOROPHYLL CONTENTGREEN LAILife Sciences & BiomedicineCANOPY REFLECTANCEAgronomy and Crop ScienceRADIATIVE-TRANSFER MODELAgricultural and Forest Meteorology
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