Spatial Data Mining: Theory and Application

·        This book is an updated version of awell-received book previously published in Chinese by Science Press of China(the first edition in 2006 and the second in 2013). It offers a systematic andpractical overview of spatial data mining, which combines computer science andgeo-spatial information science, allowing each field to profit from theknowledge and techniques of the other. To address the spatiotemporalspecialties of spatial data, the authors introduce the key concepts andalgorithms of the data field, cloud model, mining view, and Deren Li methods.The data field method captures the interactions between spatial objects bydiffusing the data contribution from a universe of samples to a universe ofpopulation, thereby bridging the gap between the data model and the recognitionmodel. The cloud model is a qualitative method that utilizes quantitativenumerical characters to bridge the gap between pure data and linguisticconcepts. The mining view method discriminates the different requirements byusing scale, hierarchy, and granularity in order to uncover the anisotropy ofspatial data mining. The Deren Li method performs data preprocessing to prepareit for further knowledge discovery by selecting a weight for iteration in orderto clean the observed spatial data as much as possible. In addition to theessential algorithms and techniques, the book provides application examples ofspatial data mining in geographic information science and remote sensing. Thepractical projects include spatiotemporal video data mining for protectingpublic security, serial image mining on nighttime lights for assessing theseverity of the Syrian Crisis, and the applications in the government project''the Belt and Road Initiatives''.