PUMA

academical publication management
collect, organize, and share publications

( en | de )

 

Disambiguation of "Oppelt, Natascha"

Author of the publication

copydeleteadd this publication to your clipboard
Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking.

, , , , and . Remote Sensing, 7 (2): 1529-1539 (2015)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Natascha Verhagen University of Stuttgart

Natascha Rosenau University of Stuttgart

 

Other publications of authors with the same name

Remote Sensing in Mapping Mangrove Ecosystems - An Object-Based Approach., , , and . Remote Sensing, 5 (1): 183-201 (2013)IRSeL - An approach to enhance continuity and accuracy of remotely sensed land cover data., , and . Int. J. Applied Earth Observation and Geoinformation, (2014)Remote Sensing Data Assimilation in Dynamic Crop Models Using Particle Swarm Optimization., , , and . ISPRS Int. J. Geo-Information, 9 (2): 105 (2020)A Combination of PROBA-V/MODIS-Based Products with Sentinel-1 SAR Data for Detecting Wet and Dry Snow Cover in Mountainous Areas., , , and . Remote Sensing, 11 (16): 1904 (2019)The combination of band ratioing techniques and neural networks algorithms for MSG SEVIRI and Landsat ETM+ cloud masking., , , , and . IGARSS, page 2315-2318. IEEE, (2015)Remote Sensing of Snow Cover Using Spaceborne SAR: A Review., , , and . Remote Sensing, 11 (12): 1456 (2019)Wet and Dry Snow Detection Using Sentinel-1 SAR Data for Mountainous Areas with a Machine Learning Technique., , , and . Remote Sensing, 11 (8): 895 (2019)Submerged Kelp Detection with Hyperspectral Data., , and . Remote Sensing, 8 (6): 487 (2016)Predicting suitable breeding areas for different locust species - A multi-scale approach accounting for environmental conditions and current land cover situation., , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2022)Automatic Grassland Cutting Status Detection in the Context of Spatiotemporal Sentinel-1 Imagery Analysis and Artificial Neural Networks., , and . Remote Sensing, 11 (6): 711 (2019)