The MissionLabAirborneDataset-Clouds contains aerial images of clouds and associated labeled cloud masks from a flight experiment conducted on October 12, 2023, in the Upper Bavaria region of Germany.

The augmented dataset consists of 5488 RGB images captured from forward-looking perspective.

MLAD-C is designed to develop models for cloud segmentation.

In our cloud detection approach, cloud segmentation functions as a pre-stage to cloud position estimation for sense & avoid purposes.

More detailed information about MLAD-C and the developed cloud segmentation model can be found in our journal article:
A Cloud Detection System for UAV Sense and Avoid: Analysis of a Monocular Approach in Simulation and Flight Tests

MLAD-C is provided in two formats:

1. augmented sensor recordings prepared for YOLO-v8 framework to reproduce results of journal article
2. non-augmented sensor recordings in Full HD resolution

The directory structure is as follows:

If you use MLAD-C, please cite the following publication: 

Dudek, A.; Stütz, P. A Cloud Detection System for UAV Sense and Avoid: Analysis of a Monocular Approach in Simulation and Flight Tests. Drones 2025, 9, 55. https://doi.org/10.3390/drones9010055

The research project MissionLab is funded by dtec.bw – Digitalization and Technology Research Center of

the Bundeswehr which we gratefully acknowledge. dtec.bw is funded by the European Union –

NextGenerationEU.