This book introduces innovative concepts like data fields, the cloud model, and a spatial data mining pyramid that visually illustrates the mining mechanism. Key algorithms, such as hierarchical clustering with data fields and the cloud model, provide practical tools for geospatial data analysis. Through real-world applications, including landslide monitoring, spatio-temporal video mining, and risk map inference, the text demonstrates how spatial data can be harnessed to solve complex problems in remote sensing and GIS data mining.

Designed for researchers and students in spatio-temporal intelligence, data science, artificial intelligence, and computer science, this book blends theory with practical insights. Readers gain a deeper understanding of spatial data mining techniques, while benefiting from the authors' interdisciplinary approach. With its novel theories and real-world case studies, this resource is essential for anyone looking to advance their knowledge in this rapidly evolving field.