Angielski
This book, an updated version of a well-received work previously published in Chinese by Science Press of China (first edition in 2006 and second in 2013), offers a systematic and practical overview of spatial data mining. The first part covers the state of the art, the fundamentals and the mining process as a pyramid of spatial data mining, while the second focuses on the theories and the third part presents sample applications. Spatial data has spatiotemporal specialties: volume, velocity, and variety. To address the special needs of spatial data mining, this book introduces the data field, cloud model, mining views, and "Deren Li" methods. Incorporating physical principles in spatial data mining, the data field method bridges the modeling gap between discovery and recognition under field theory; the cloud model method bridges the transforming gap between quantitative data and qualitative concepts under the atomic model; and the mining views method reconciles different requirements under object anisotropy. Inspired by mathematical statistics, the "Deren Li method" overcomes the preprocessing gap between polluted spatial data by selecting the weight for iteration.§§In addition to essential algorithms and techniques, the book provides detailed descriptions of the applications of spatial data mining in geographic information science (GIS) and re§mote sensing. Accordingly, it effectively combines computer science and GIS, allowing each field to profit from the knowledge and techniques of the other and significantly advance research on spatial data mining.§§
