RSC4Earth
RSC4Earth
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Deep Learning
ml4earth
Deliver novel AI techniques for earth observation satellite data for studies in earth and climate sciences
DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin
Land use and land cover (LULC) mapping is a powerful tool for monitoring large areas. For the Amazon rainforest, automated mapping is …
Eya Cherif
,
Maximilian Hell
,
Melanie Brandmeier
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DOI
Mapping Land-Use Intensity of Grasslands in Germany with Machine Learning and Sentinel-2 Time Series
Information on grassland land-use intensity (LUI) is crucial for understanding trends and dynamics in biodiversity, ecosystem …
Maximilian Lange
,
Hannes Feilhauer
,
Ingolf Kühn
,
Daniel Doktor
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DOI
Spatially Autocorrelated Training and Validation Samples Inflate Performance Assessment of Convolutional Neural Networks
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote sensing are becoming standard analytical …
Felix Schiefer
,
Julian Frey
,
Hannes Feilhauer
,
Miguel D. Mahecha
,
Carsten F. Dormann
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DOI
Convolutional Neural Networks Accurately Predict Cover Fractions of Plant Species and Communities in Unmanned Aerial Vehicle Imagery
Abstract Unmanned Aerial Vehicles ( UAV ) greatly extended our possibilities to acquire high resolution remote sensing data for …
Jana Eichel
,
Susan Wiser
,
Larry Burrows
,
Fabian E. Fassnacht
,
Sebastian Schmidtlein
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DOI
Mapping Forest Tree Species in High Resolution UAV-based RGB-imagery by Means of Convolutional Neural Networks
The use of unmanned aerial vehicles (UAVs) in vegetation remote sensing allows a time-flexible and cost-effective acquisition of very …
Felix Schiefer
,
Annett Frick
,
Julian Frey
,
Peter Schall
,
Barbara Koch
,
Sebastian Schmidtlein
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DOI
Predicting Landscapes from Environmental Conditions Using Generative Networks
Landscapes are meaningful ecological units that strongly depend on the environmental conditions. Such dependencies between landscapes …
Christian Requena-Mesa
,
Markus Reichstein
,
Miguel D. Mahecha
,
Basil Kraft
,
Joachim Denzler
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DOI
Predicting Landscapes as Seen from Space from Environmental Conditions
Satellite images are information rich snapshots of ecosystems and landscapes. In consequence, the features in the images strongly …
C. Requena-Mesa
,
M. Reichstein
,
Miguel D. Mahecha
,
B. Kraft
,
J. Denzler
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