0000000000310315

AUTHOR

Patrick Hostert

showing 4 related works from this author

A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover

2014

Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution. Methods included support vector regression (SVR), kernel ridge regression (KRR), artificial neural networks (NN), random forest regression (RFR) and partial least squares regression (PLSR). Our experiments demonstrate that both kernel methods SVR and KRR yield high accuracies for mapping complex urban surface types, i.e., rooftops, pavements, gras…

Computer scienceLand coverimaging spectrometrysub-pixel mappingKernel (linear algebra)urban land coverPartial least squares regressionlcsh:Sciencespatial resolutionHyMapRemote sensingmachine learning; regression; sub-pixel mapping; spatial resolution; imaging spectrometry; hyperspectral; urban land coverTraining setArtificial neural networkbusiness.industryHyperspectral imagingPattern recognitionRandom forestSupport vector machineKernel methodmachine learninghyperspectralKernel (statistics)General Earth and Planetary Sciencesregressionlcsh:QArtificial intelligencebusinessRemote Sensing
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CEFLES2: The remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the …

2009

The CEFLES2 campaign during the Carbo Europe Regional Experiment Strategy was designed to provide simultaneous airborne measurements of solar induced fluorescence and CO<sub>2</sub> fluxes. It was combined with extensive ground-based quantification of leaf- and canopy-level processes in support of ESA's Candidate Earth Explorer Mission of the "Fluorescence Explorer" (FLEX). The aim of this campaign was to test if fluorescence signal detected from an airborne platform can be used to improve estimates of plant mediated exchange on the mesoscale. Canopy fluorescence was quantified from four airborne platforms using a combination of novel sensors: (i) the prototype ai…

Imaging spectrometerMesoscale meteorology1904 Earth-Surface Processeslcsh:Life550 - Earth sciencesPhotosynthetic efficiencyINDUCED CHLOROPHYLL FLUORESCENCE; GROSS PRIMARY PRODUCTION; LIGHT-USE EFFICIENCY; STEADY-STATE; WATER-STRESS; REFLECTANCE; FIELD; HETEROGENEITY; DYNAMICS; BOREALremote sensingEvapotranspirationddc:570lcsh:QH540-549.5910 Geography & travelTransectEcology Evolution Behavior and SystematicsEarth-Surface ProcessesRemote sensingphotosynthesisSpectrometerlcsh:QE1-996.5Hyperspectral imagingFluorescenceFLEX Fluorescence AHS HYPER AirFLEXJlcsh:Geologylcsh:QH501-531GEO/10 - GEOFISICA DELLA TERRA SOLIDA10122 Institute of Geography1105 Ecology Evolution Behavior and SystematicsEnvironmental sciencefluorescencelcsh:Ecologyoxygenprimary production
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Remote sensing of sun-induced fluorescence to improve modeling of diurnal courses of gross primary production (GPP)

2010

Terrestrial gross primary production (GPP) is an important parameter to explore and quantify carbon fixation by plant ecosystems at various scales. Remote sensing (RS) offers a unique possibility to investigate GPP in a spatially explicit fashion; however, budgeting of terrestrial carbon cycles based on this approach still remains uncertain. To improve calculations, spatio-temporal variability of GPP must be investigated in more detail on local and regional scales. The overarching goal of this study is to enhance our knowledge on how environmentally induced changes of photosynthetic light-use efficiency (LUE) are linked with optical RS parameters. Diurnal courses of sun-induced fluorescence…

Global and Planetary ChangeEcologyEddy covarianceClimate changePrimary productionPhotosynthetic efficiencyPhotochemical Reflectance IndexPhotosynthesisCarbon cycleEnvironmental ChemistryEnvironmental sciencePrimary productivityGeneral Environmental ScienceRemote sensingGlobal Change Biology
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Mapping Cerrado woody plant traits with spaceborne hyperspectral data

2018

The Cerrado (Brazilian savannah), is the most diverse of all of the world's savannahs. While holding a high diversity and endemism of species, this biome is mostly unprotected and understudied. Also, recent studies have given focus on the importance of species traits, and on the need to incorporate them into biodiversity monitoring and conservation. In this paper, we used woody plant inventory data, plant trait data, and spaceborne hyperspectral (Hyperion) data to map woody plant traits in two study sites in the Cerrado. To this aim, we applied a Sparse Generalized Dissimilarity Modelling (SGDM) approach for modelling the species turnover on each site. Matrix calculations were applied to as…

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