Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data QualitySubstantial progress has been made toward developing effective techniques for spatial information processing in recent years. This science deals with models of reality in a GIS, however, and not with reality itself. Therefore, spatial information processes are often impre
In this cohesive collection of peer-reviewed chapters, field authorities present the latest field advancements and cover essential areas such as data acquisition, geoinformation theory, spatial statistics, and dissemination. Each chapter opens with an editorial preview of each topic from a conceptual, applied, and methodological point of view, making it easier for researchers to judge which information is most beneficial to their work. Under the editorial guidance of internationally respected geoinformatics experts, the volume addresses quality aspects in the entire spatial data mining process, from data acquisition to end user.
· 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’.
Elements of Spatial Data Quality outlines the need and suggests potential categories for the content of a comprehensive statement of data quality that must be imbedded in the metadata that accompanies the transfer of a digital spatial data file or is available in a separate metadata catalog. Members of the International Cartographic Association's Commission on Spatial Data Quality have identified seven elements of data quality: positional accuracy, attribute accuracy, completeness, logical consistency, lineage, semantic accuracy and temporal information. In the book the authors describe: components of each data quality element, possible metrics that can be used to measure the quality of each criteria, possible testing and rating schemes, and how these parameters might differ from a producer or user point of view. Finally no volume of this nature would be complete without a chapter devoted to necessary future research in this subject.
Business intelligence initiatives have been dominating the technology priority list of many organizations. However, the lack of effective information quality and governance strategies and policies has been meeting these initiatives with some challenges. Information Quality and Governance for Business Intelligence presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth. This book is an essential reference tool for researchers, practitioners, and university students specializing in business intelligence, information quality, and information systems.
Offers New Insight on Uncertainty ModellingFocused on major research relative to spatial information, Uncertainty Modelling and Quality Control for Spatial Data introduces methods for managing uncertainties-such as data of questionable quality-in geographic information science (GIS) applications. By using original research, current advancement, and
The book is dealing with recent progress in human–computer interaction (HCI) related to geographic information science (GIS). The Editorial starts with an overview about the evolution of the Internet and first HCI concepts and stimulates recent HCI developments using 3D and 4D apps, running on all mobile devices with OS Android, iOS, Linus, and Windows. Eight research articles present the state-of-the-art in HCI–GIS-related issues, starting with gender and age differences in using indoor maps via the estimation of building heights from space to an efficient visualization method for polygonal data with dynamic simplification. The review article deals with progress and challenges on entity alignment of geographic knowledge bases.
Web services, cloud computing, location based services, NoSQLdatabases, and Semantic Web offer new ways of accessing, analyzing, and elaborating geo-spatial information in both real-world and virtual spaces. This book explores the how-to of the most promising recurrent technologies and trends in GIS, such as Semantic GIS, Web GIS, Mobile GIS, NoSQL Geographic Databases, Cloud GIS, Spatial Data Warehousing-OLAP, and Open GIS. The text discusses and emphasizes the methodological aspects of such technologies and their applications in GIS.
Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.
For the fourth consecutive year, the Association of Geographic Infor- tion Laboratories for Europe (AGILE) promoted the edition of a book with the collection of the scientific papers that were submitted as full-papers to the AGILE annual international conference. Those papers went through a th competitive review process. The 13 AGILE conference call for fu- papers of original and unpublished fundamental scientific research resulted in 54 submissions, of which 21 were accepted for publication in this - lume (acceptance rate of 39%). Published in the Springer Lecture Notes in Geoinformation and Car- th graphy, this book is associated to the 13 AGILE Conference on G- graphic Information Science, held in 2010 in Guimarães, Portugal, under the title “Geospatial Thinking”. The efficient use of geospatial information and related technologies assumes the knowledge of concepts that are fundamental components of Geospatial Thinking, which is built on reasoning processes, spatial conc- tualizations, and representation methods. Geospatial Thinking is associated with a set of cognitive skills consisting of several forms of knowledge and cognitive operators used to transform, combine or, in any other way, act on that same knowledge. The scientific papers published in this volume cover an important set of topics within Geoinformation Science, including: Representation and Visualisation of Geographic Phenomena; Spatiotemporal Data Analysis; Geo-Collaboration, Participation, and Decision Support; Semantics of Geoinformation and Knowledge Discovery; Spatiotemporal Modelling and Reasoning; and Web Services, Geospatial Systems and Real-time Appli- tions.
