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9783662485361 English 3662485362 This book is an updatedversion of a well-received book previously published in Chinese by SciencePress of China (the first edition in 2006 and the second in 2013). It offers asystematic and practical overview of spatial data mining, which combines computerscience and geo-spatial information science, allowing each field to profit fromthe knowledge 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'., 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 pre-processing 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 remote 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. ", · 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'.
9783662485361 English 3662485362 This book is an updatedversion of a well-received book previously published in Chinese by SciencePress of China (the first edition in 2006 and the second in 2013). It offers asystematic and practical overview of spatial data mining, which combines computerscience and geo-spatial information science, allowing each field to profit fromthe knowledge 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'., 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 pre-processing 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 remote 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. ", · 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'.