6 papers
Uncertainty-aware tree height change regression
Max Gaber, Dimitri Gominski, Jaime C. Revenga +3
Monitoring canopy height change is essential for understanding carbon sinks and forest dynamics. Remote sensing enables consistent, large-scale observations of such changes, increa…
Boosted Trees on a Diet: Compact Models for Resource-Constrained Devices
Nina Herrmann, Jan Stenkamp, Benjamin Karic +2
Deploying machine learning models on compute-constrained devices has become a key building block of modern IoT applications. In this work, we present a compression scheme for boost…
Multimodal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds
Simon B. Jensen, Stefan Oehmcke, Andreas Møgelmose +4
Assessment of forest biodiversity is crucial for ecosystem management and conservation. While traditional field surveys provide high-quality assessments, they are labor-intensive a…
Where to Measure: Epistemic Uncertainty-Based Sensor Placement with ConvCNPs
Feyza Eksen, Stefan Oehmcke, Stefan Lüdtke
Accurate sensor placement is critical for modeling spatio-temporal systems such as environmental and climate processes. Neural Processes (NPs), particularly Convolutional Condition…
MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learning
Vishal Nedungadi, Ankit Kariryaa, Stefan Oehmcke +3
The volume of unlabelled Earth observation (EO) data is huge, but many important applications lack labelled training data. However, EO data offers the unique opportunity to pair da…
Nacala-Roof-Material: Drone Imagery for Roof Detection, Classification, and Segmentation to Support Mosquito-borne Disease Risk Assessment
Venkanna Babu Guthula, Stefan Oehmcke, Remigio Chilaule +5
As low-quality housing and in particular certain roof characteristics are associated with an increased risk of malaria, classification of roof types based on remote sensing imagery…