Artificial intelligence speeds land-use classification

An example of aerial photo analyzed by Zermatten's algorithm. Swisstopo - An EPFL Master's student has shown that artificial intelligence can be used to further automate the process of land-use classification in Switzerland, especially for rare and complicated land categories that until now have been classified manually. A stretch of land in Valais Canton served as the sample for her research. Switzerland regularly maps land use in the country in order to better track urbanization, monitor soil permeability and combat urban sprawl. Surveyors take aerial photos of the land every three years, but the survey itself is published only every six years because classifying the images into some 40 different categories is still done mostly by hand. To help speeding up the process, the Swiss Federal Statistical Office (FSO) has developed a algorithm based on artificial intelligence (AI) called Arealstatistik Deep Learning (ADELE), which can efficiently distinguish between the forests that cover a third of the country and other types of land. Valérie Zermatten, a Master's student in environmental engineering at EPFL, saw the potential for taking automation even further and developed her own machine learning algorithm as part of her thesis.