· This book is an updated version of a well-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 and practical overview of spatial data mining, which combines computer science and geo-spatial information science, allowing each field to profit from the knowledge and techniques of the other. To address the spatiotemporal specialties of spatial data, the authors introduce the key concepts and algorithms of the data field, cloud model, mining view, and Deren Li methods. The data field method captures the interactions between spatial objects by diffusing the data contribution from a universe of samples to a universe of population, thereby bridging the gap between the data model and the recognition model. The cloud model is a qualitative method that utilizes quantitative numerical characters to bridge the gap between pure data and linguistic concepts. The mining view method discriminates the different requirements by using scale, hierarchy, and granularity in order to uncover the anisotropy of spatial data mining. The Deren Li method performs data preprocessing to prepare it for further knowledge discovery by selecting a weight for iteration in order to clean the observed spatial data as much as possible. In addition to the essential algorithms and techniques, the book provides application examples of spatial data mining in geographic information science and remote sensing. The practical projects include spatiotemporal video data mining for protecting public security, serial image mining on nighttime lights for assessing the severity of the Syrian Crisis, and the applications in the government project ‘the Belt and Road Initiatives’.
Generalized Density Based Clustering for Spatial Data Mining
Introduces the reader to the world of spatial databases, and related subtopics.
This science deals with models of reality in a GIS, however, and not with reality itself. Therefore, spatial information processes are often impre
This book by leading experts in the field provides readers with a wide range of applications and methods for spatial database management systems, and allows readers to...
2.4 Partitioning of Spatial Object Data by Unidimensional Scaling 2.4.1 A Note on the Use of Unidimensional Scaling In Sect. ... The emphasis is on the robustness to noise and the multiplicity of scale for clusters.
The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data ...
Content Description #Includes bibliographical references and index.
... Data Center: Serving Interdisciplinary Earth Scientists,” in Proceedings of the [24] [25] 9th International Conference on Scientific and Statistical Database Value Range Queries on Earth Science Data via Histogram Clustering 75.
He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making.
Temporal, Spatial, and Spatio-Temporal Data Mining