An OpenStreetMap-Based Dataset of Building Footprints for Analysing Different Types of Label Noise

We present a dataset consisting of OpenStreetMap imagery and corresponding building footprint labels. Multiple label sets are provided, each containing a different type of label noise. The purpose of the dataset is to enable a systematic analysis of different label noise types in the earth observation domain and to provide a benchmark dataset for noise removal techniques. We also present some preliminary results from experiments on the effect of different label noise types on model performance.