The recent rapid progress of computing, communication, and information technologies enables unprecedented acquisition of spatial data (e.g., in the form of massive movement trajectory datasets or fine-resolution environmental data), novel spatio-temporal analyses, and cyberGIS advances. In order to pursue knowledge discovery from these complex and massive spatial data, machine learning approaches are being applied in diverse ‘spatial disciplines’, such as geography, transportation science, environmental science, or behavioral science. The importance of spatial big data and machine learning in GIScience is both manifested through recent scholarly work as well as in industry. This workshop will bring together researchers who already analyze spatial big data with machine learning approaches or want to do so in the future. It aims to explore the various opportunities and particular challenges of applying cutting-edge machine learning approaches to spatial big data.