Spatial Data Mining Theory and Applications

Author: Li Deren, Wang Shuliang, Li Dyi
Publisher:
Publish Date: 2006-10-01
Features: This book primarily proposes new technologies such as cloud models, data fields, geospatial rough spaces, and spatial data mining perspectives, constructs a spatial data mining pyramid, studies the data sources of spatial data mining, derives the "Li Deren Method" for spatial observation data cleaning, and investigates image data mining based on spatial statistics. It introduces clustering algorithms such as "data field-cloud" clustering, fuzzy comprehensive clustering based on data fields, and clustering knowledge mining algorithms based on mathematical morphology. The book also explores spatial data mining based on inductive learning, remote sensing image data mining based on concept lattices, and GIS data control. Through case studies in landslide monitoring, bank operating revenue analysis and site evaluation, remote sensing image land use classification, land resource assessment, and train movement safety detection, it examines the operability of spatial data control. On this basis, the authors independently developed the spatial data mining prototype systems GISDBMiner and RSImageMiner.