Sebastian van der Linden
Orcid: 0000-0001-6576-8377Affiliations:
- Humboldt-Universität zu Berlin, Germany
According to our database1,
Sebastian van der Linden
authored at least 33 papers
between 2006 and 2024.
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Bibliography
2024
Temporally transferable crop mapping with temporal encoding and deep learning augmentations.
Int. J. Appl. Earth Obs. Geoinformation, 2024
2023
2022
Revisiting the Past: Replicability of a Historic Long-Term Vegetation Dynamics Assessment in the Era of Big Data Analytics.
Remote. Sens., 2022
2021
Combining simulated hyperspectral EnMAP and Landsat time series for forest aboveground biomass mapping.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2020
Visualizing and labeling dense multi-sensor earth observation time series: The EO Time Series Viewer.
Environ. Model. Softw., 2020
2019
Comparing map-based and library-based training approaches for urban land-cover fraction mapping from Sentinel-2 imagery.
Int. J. Appl. Earth Obs. Geoinformation, 2019
2018
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
2017
Ensemble Learning From Synthetically Mixed Training Data for Quantifying Urban Land Cover With Support Vector Regression.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017
A Novel Spectral Library Pruning Technique for Spectral Unmixing of Urban Land Cover.
Remote. Sens., 2017
Influence of neighbourhood information on 'Local Climate Zone' mapping in heterogeneous cities.
Int. J. Appl. Earth Obs. Geoinformation, 2017
Proceedings of the Joint Urban Remote Sensing Event, 2017
Optimizing mixed spectra generation for regression-based unmixing of land cover in urban areas.
Proceedings of the Joint Urban Remote Sensing Event, 2017
2016
Global Urban Monitoring and Assessment Through Earth Observation, Qihao Weng. Taylor & Francis Series in Remote Sensing Applications, CRC Press, Boca Raton (2014). 440 pp., ISBN: 978-1-4665-6449-7.
Int. J. Appl. Earth Obs. Geoinformation, 2016
2015
Using Class Probabilities to Map Gradual Transitions in Shrub Vegetation from Simulated EnMAP Data.
Remote. Sens., 2015
The EnMAP-Box - A Toolbox and Application Programming Interface for EnMAP Data Processing.
Remote. Sens., 2015
Remote. Sens., 2015
Remote. Sens., 2015
Analyzing Hyperspectral and Hypertemporal Data by Decoupling Feature Redundancy and Feature Relevance.
IEEE Geosci. Remote. Sens. Lett., 2015
2014
Remote. Sens., 2014
IEEE Geosci. Remote. Sens. Lett., 2014
Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014
2013
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2013
Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China) Using Multi-Spectral Phenological Metrics from MODIS Time Series.
Remote. Sens., 2013
2012
imageRF - A user-oriented implementation for remote sensing image analysis with Random Forests.
Environ. Model. Softw., 2012
Using MODIS time series and random forests classification for mapping land use in South-East Asia.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
2010
Sensitivity of Support Vector Machines to Random Feature Selection in Classification of Hyperspectral Data.
IEEE Trans. Geosci. Remote. Sens., 2010
Simplifying Support Vector Machines for classification of hyperspectral imagery and selection of relevant features.
Proceedings of the 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2010
2009
IEEE Geosci. Remote. Sens. Lett., 2009
Impact of different morphological profiles on the classification accuracy of urban hyperspectral data.
Proceedings of the First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009
Simplifying Support Vector Machines for Regression analysis of hyperspectral imagery.
Proceedings of the First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009
2008
IEEE Trans. Geosci. Remote. Sens., 2008
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2008
2006
Random Feature Selection for Decision Tree Classification of Multi-temporal SAR Data.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2006