Sebastian Schmidtlein spends much of his time researching Remote sensing, Hyperspectral imaging, Ecology, Partial least squares regression and Ordination. His work deals with themes such as Fuzzy set and Land use, which intersect with Remote sensing. His research integrates issues of Normalization, Indicator value, Ecological succession, Disturbance and Vegetation in his study of Hyperspectral imaging.
His research integrates issues of Machine learning and Artificial intelligence in his study of Ecology. The study incorporates disciplines such as Linear regression and Leaf area index in addition to Partial least squares regression. His Ordination study combines topics from a wide range of disciplines, such as HyMap and Regression analysis.
His primary areas of investigation include Remote sensing, Ecology, Vegetation, Hyperspectral imaging and Remote sensing. His Remote sensing research is multidisciplinary, incorporating elements of Partial least squares regression, Ecosystem and Invasive species. His work deals with themes such as Pixel and Environmental resource management, which intersect with Ecosystem.
His Vegetation study combines topics in areas such as Biomass, Tropics and Multispectral image. Sebastian Schmidtlein combines subjects such as Ordination, Image resolution, Indicator value, Grassland and Plant functional type with his study of Hyperspectral imaging. His Remote sensing study integrates concerns from other disciplines, such as Plant traits and Nature Conservation.
Sebastian Schmidtlein mainly focuses on Remote sensing, Canopy, Remote sensing, Ecosystem and Vegetation. Sebastian Schmidtlein is studying Hyperspectral imaging, which is a component of Remote sensing. His research in Canopy intersects with topics in Growing season, Atmospheric sciences, Plant traits, Leaf area index and Plant strategies.
His Remote sensing study incorporates themes from Biodiversity and Field. His research in Ecosystem focuses on subjects like Habitat, which are connected to Regression analysis and Landscape planning. His Vegetation research incorporates elements of Forest management, Biomass, Class and Fuzzy classification.
Sebastian Schmidtlein focuses on Field, Ecosystem, Remote sensing, Biodiversity and Satellite imagery. His work carried out in the field of Ecosystem brings together such families of science as Arid, Effects of global warming, Grazing and Land use. Sebastian Schmidtlein conducts interdisciplinary study in the fields of Remote sensing and Exploit through his works.
His studies deal with areas such as Sampling, Sampling design, Cartography and Spatial heterogeneity as well as Biodiversity. His Satellite imagery research incorporates themes from Species richness, Distance matrices in phylogeny and Species diversity. As a part of the same scientific study, Sebastian Schmidtlein usually deals with the Remote sensing, concentrating on Natura 2000 and frequently concerns with Vegetation.
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Will remote sensing shape the next generation of species distribution models
Remote Sensing in Ecology and Conservation (2015)
Mapping of continuous floristic gradients in grasslands using hyperspectral imagery
Remote Sensing of Environment (2004)
Alien invasive slider turtle in unpredicted habitat: a matter of niche shift or of predictors studied?
Dennis Rödder;Sebastian Schmidtlein;Michael Veith;Stefan Lötters.
PLOS ONE (2009)
Global Amphibian Extinction Risk Assessment for the Panzootic Chytrid Fungus
Dennis Rödder;Jos Kielgast;Jon Bielby;Sebastian Schmidtlein.
Mapping plant strategy types using remote sensing
Journal of Vegetation Science (2012)
A comparative framework for broad‐scale plot‐based vegetation classification
Applied Vegetation Science (2015)
Linking earth observation and taxonomic, structural and functional biodiversity: local to ecosystem perspectives
Angela Lausch;L Bannehr;Michael Beckmann;Christoph Boehm.
Ecological Indicators (2016)
Brightness-normalized Partial Least Squares Regression for hyperspectral data
Journal of Quantitative Spectroscopy & Radiative Transfer (2010)
Uncertainty in ecosystem mapping by remote sensing
Computers & Geosciences (2013)
Mapping the floristic continuum : Ordination space position estimated from imaging spectroscopy
Journal of Vegetation Science (2007)
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