Katja Berger
Orcid: 0000-0003-0784-7717
According to our database1,
Katja Berger
authored at least 28 papers
between 2017 and 2023.
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Bibliography
2023
Untangling the Causal Links between Satellite Vegetation Products and Environmental Drivers on a Global Scale by the Granger Causality Method.
Remote. Sens., October, 2023
Cloud-Free Global Maps of Essential Vegetation Traits Processed from the TOA Sentinel-3 Catalogue in Google Earth Engine.
Remote. Sens., July, 2023
Synergy of Sentinel-1 and Sentinel-2 Time Series for Cloud-Free Vegetation Water Content Mapping with Multi-Output Gaussian Processes.
Remote. Sens., April, 2023
2022
Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data.
Remote. Sens., 2022
Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression.
Remote. Sens., 2022
Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine.
Remote. Sens., 2022
Quantifying Irrigated Winter Wheat LAI in Argentina Using Multiple Sentinel-1 Incidence Angles.
Remote. Sens., 2022
Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery.
Remote. Sens., 2022
Estimating soil moisture content under grassland with hyperspectral data using radiative transfer modelling and machine learning.
Int. J. Appl. Earth Obs. Geoinformation, 2022
2021
Monitoring the Foliar Nutrients Status of Mango Using Spectroscopy-Based Spectral Indices and PLSR-Combined Machine Learning Models.
Remote. Sens., 2021
Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow.
Remote. Sens., 2021
Remote. Sens., 2021
A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data.
Remote. Sens., 2021
Intelligent Sampling for Vegetation Nitrogen Mapping Based on Hybrid Machine Learning Algorithms.
IEEE Geosci. Remote. Sens. Lett., 2021
Prototyping Vegetation Traits Models in the Context of the Hyperspectral Chime Mission Preparation.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
Introducing the Potential of the EnMAP-Box for Agricultural Applications Using Desis and Prisma Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
Towards Quantifying Non-Photosynthetic Vegetation for Agriculture Using Spaceborne Imaging Spectroscopy.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
2020
RTM-based dynamic absorption integrals for the retrieval of biochemical vegetation traits.
Int. J. Appl. Earth Obs. Geoinformation, 2020
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method.
Int. J. Appl. Earth Obs. Geoinformation, 2020
2019
Fitted PROSAIL Parameterization of Leaf Inclinations, Water Content and Brown Pigment Content for Winter Wheat and Maize Canopies.
Remote. Sens., 2019
2018
Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data.
Remote. Sens., 2018
Model-Based Optimization of Spectral Sampling for the Retrieval of Crop Variables with the PROSAIL Model.
Remote. Sens., 2018
Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study.
Remote. Sens., 2018
Hyperspectral Retrieval of Canopy Water Content Through Inversion of the Beer-Lambert Law.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Simulation of Spaceborne Hyperspectral Remote Sensing to Assist Crop Nitrogen Content Monitoring in Agricultural Crops.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
2017
Remote. Sens., 2017