Map Data Processing


Book Description

Map Data Processing is a collection of papers from a NATO study on the same subject. This collection deals with the exchange of ideas and setting directions in research, particularly in pattern-recognition-, image-processing-, and computer-related issues. The papers discuss the usefulness of computer systems in geographical data processing, as well as the viability of scan digitization resulting from improvements in line thinning and vectorization. Automated spatial data integration can also be helpful in analyzing spatial data, data collection, capture methods, and data characteristics. Another paper addresses the application of the 8-point chain-encoded lineal map data to define more accurate algorithms found in many geographical and medical imagery. One paper considers how the same data used in monochromatic images can be realized for full colored, textured, realist terrain scenes. This book can be a valuable reference for workers involved in areas of geography, computer imaging, cartography, computer graphics, and remote sensing.




Map Data Processing. Proceedings of a NATO Advanced Study Institute on Map Data Processing, Maratea 1979


Book Description

A minicomputer-based geographical data processing system; Scan digitization of cartographic data; Spatial data integration; A spatial data structure for geographic information systems; Design of a spatial information system; What is a "good" data structure for 2-D Points? Tree structures for region representation; Analysis and manipulation of linear map data; Representation and recognition of cartographic data; The effects of generalization in geographical data encoding; Methodological observations on the state of geocartographic analysis in the context of automated spatial information systems; The transfer of software systems for map data processing; Pattern recognition problems in the classification of multi-images.




Data Mapping for Data Warehouse Design


Book Description

Data mapping in a data warehouse is the process of creating a link between two distinct data models’ (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle. Covers all stages of data warehousing and the role of data mapping in each Includes a data mapping strategy and techniques that can be applied to many situations Based on the author’s years of real-world experience designing solutions







Cartography


Book Description

This Fourth Edition of Cartography: Visualization of Geospatial Data serves as an excellent introduction to general cartographic principles. It is an examination of the best ways to optimize the visualization and use of spatiotemporal data. Fully revised, it incorporates all the changes and new developments in the world of maps, such as OpenStreetMap and GPS (Global Positioning System) based crowdsourcing, and the use of new web mapping technology and adds new case studies and examples. Now printed in colour throughout, this edition provides students with the knowledge and skills needed to read and understand maps and mapping changes and offers professional cartographers an updated reference with the latest developments in cartography. Written by the leading scholars in cartography, this work is a comprehensive resource, perfect for senior undergraduate and graduate students taking courses in GIS (geographic information system) and cartography. New in This Edition: Provides an excellent introduction to general cartographic visualization principles through full-colour figures and images Addresses significant changes in data sources, technologies and methodologies, including the movement towards more open data sources and systems for mapping Includes new case studies and new examples for illustrating current trends in mapping Provides a societal and institutional framework in which future mapmakers are likely to operate, based on UN global development sustainability goals




GIS And Generalisation


Book Description

This text is the inaugural book in Taylor and Francis's GISDATA series, and is derived from the specialist workshop convened under the auspices of the European Science Foundation's GISDATA Scientific Programme. Generalisation is an integrating tool for the analysis and presentation of spatial data. Effective spatial data analysis requires multiple views of the world at various scales with different thematic layers of representation. Generalisation is a key mechanism in this process, as it filters out information which is required for particular scales or layers; hence it is critical to implement full and comprehensive generalisation capabilities in a GIS, something with which few current GIS are equipped.; This book overviews the core and as-yet unresolved issues surrounding the achievement of this goal, and presents various alternatives - both speculative views and practical examples - in the areas of automated generalisation, vis-a-vis problems such as object simplification and placement. At the same time it distinguishes between modelling with generalisation and graphical representation, and adopts a model-building perspective. It also describes artificial intelligence techniques for implementing automated generalised routines, and addresses issues of data quality and production.; The text is organized into six parts: an introduction; generic issue; object-orientated methods and knowledge-based modelling; knowledge acquisition and representation; data quality; and operation and implementation.




Geocomputation with R


Book Description

Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.




Online Maps with APIs and WebServices


Book Description

The Internet has become the major form of map delivery. The current presentation of maps is based on the use of online services. This session examines developments related to online methods of map delivery, particularly Application Programmer Interfaces (APIs) and MapServices in general, including Google Maps API and similar services. Map mashups have had a major impact on how spatial information is presented. The advantage of using a major online mapping site is that the maps represent a common and recognizable representation of the world. Overlaying features on top of these maps provides a frame of reference for the map user. A particular advantage for thematic mapping is the ability to spatially reference thematic data.




Map Projection Transformation


Book Description

With the advance of science and technology, there have been breakthroughs in the field of classical research and methods of map projection. Among these, computer science and space science have had the greater influence upon the field of research and the formation of a working body of map projection, developing them in breadth and depth. This book reflects several aspects of the development of modern mathematical cartography, especially the theory and methods of map projection transformation. Map projection transformation is an area of research in mathematical cartography newly developed over the last 25 years. It is widely used in surveying and computer-assisted cartography, data processing for information systems, and the transformation of data from space, remote sensing, and other space sciences. The development of map projection transformation not only expands new areas of research on mathematical cartography, but it also further develops the applied area with the creation and application of map projection transformation software and mapping mathematics bases on the computer.




Map Data Processing


Book Description