Melanie Brandmeier

Professor

Technical University of Applied Sciences Würzburg-Schweinfurt

Germany

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Professor Melanie Brandmeier is a faculty member at the Technical University of Applied Sciences Würzburg-Schweinfurt in Germany. Her research focuses on areas such as multimodal tree species classification, deep learning for tree health assessment, and precision viticulture using multisensor data. She has contributed to several recent publications that explore innovative methodologies in land use and cover classification, particularly in the context of environmental monitoring and sustainable forestry practices.

Articles (10)

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2025

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2024

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2024

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2024

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2024

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2022

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2022

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2020

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2020

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2020

Collaborators (2)

Peter Krzystek

Professor

Munich University of Applied Sciences

GERMANY

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Sebastian Briechle

University of Twente

NETHERLANDS

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Melanie Brandmeier

Research Interests

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Articles (10)

MMTSCNet: Multimodal Tree Species Classification Network for Classification of Multi-Source, Single-Tree LiDAR Point Clouds

Identifying Plausible Labels from Noisy Training Data for a Land Use and Land Cover Classification Application in Amazônia Legal

Time Series Analysis of Multisensor Data for Precision Viticulture—Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography

Evaluating Different Deep Learning Approaches for Tree Health Classification Using High-Resolution Multispectral UAV Data in the Black Forest, Harz Region, and Göttinger Forest

TreeSeg—A Toolbox for Fully Automated Tree Crown Segmentation Based on High-Resolution Multispectral UAV Data

Classification of Tree Species and Standing Dead Trees with Lidar Point Clouds Using Two Deep Neural Networks: PointCNN and 3DmFV-Net

DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin

A Deep Learning Approach for Calamity Assessment Using Sentinel-2 Data

A Hierarchical Deep-Learning Approach for Rapid Windthrow Detection on PlanetScope and High-Resolution Aerial Image Data

Boosting for Mineral Prospectivity Modeling: A New GIS Toolbox

Collaborators (2)

Peter Krzystek

Sebastian Briechle

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