A novel model for tourism demand forecasting with spatial-temporal feature enhancement and image-driven method

Yunxuan Dong, Binggui Zhou, Guanghua Yang, Fen Hou, Zheng Hu, Shaodan Ma

Abstract: Highlights•Learning spatial–temporal features in urban area to forecast tourism demand.•Proposing a feature enhancement method to model the relationship among spots.•Proposing a series-to-image learning process and a deep network as predictor.•Improving Zhuhai’s daily tourism demand forecasting accuracy.