The KIDA AI consultancy: Tree detection with satellite data

The AI consultancy of the KIDA project is a collaboration between seven institutions within the area of the German Federal Ministry of Food and Agriculture. The members of the AI team solve service requests from the participating institutions on a cross-institutional basis. An advisory project is presented in which the AI team has trained a recurrent neural network (LSTM) to classify different tree species (e. g. deciduous trees, conifers) and tree species groups (e. g. oak, fir, ...) on time series of satellite images of sentinel-2. Several challenges as for example cloud covers had to be overcome. Finally, an accuracy of 97.9% was achieved for the classification of tree species, 98.4% for conifers and 91.6% for deciduous trees. The results show, how promising it is to carry out corresponding data collections in the future with the help of satellite data and AI to be able to recognise changes in the tree population quickly and efficiently in order to be able to react to them. In particular, large areas with relatively small sections (10m x 10m) could be monitored automatically. This opens up new opportunities in a rapidly changing world.