Search results for "imaging spectrometry"

showing 2 items of 2 documents

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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Unmixing methods in novel applications of spectral imaging

2014

hyperspectral imagingrikospaikkaimaging spectrometryspektrografilaskennallinen vaativuusympäristön tilaanalysmetoderihosyöpäskin abnormalitiesesitutkintaspectral unmixinghudcancerbrottsplatsenvironmental monitoringspektrografiamiljöövervakningspektral avbildningtarget detectionmiljöns tillståndspektrikuvausanalyysimenetelmätförundersökningforensicskuvantaminenympäristövalvontahyperspektrikuvaus
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