A revised and expanded new edition of the definitive English work on map projections. The revisions take into account the huge advances in geometrical geodesy which have occurred since the early years of satellite geodesy. The detailed configuration of the geoid resulting from the GEOS and SEASAT altimetry measurements are now taken into consideration. Additionally, the chapter on computation of map projections is updated bearing in mind the availability of pocket calculators and microcomputers. Analytical derivation of some map projections including examples of pseudocylindrical and polyconic projections is also covered. Work undertaken in the USA and USSR on the creation of suitable map projections obtained through numerical analysis has been included. The book concludes with a chapter on the abuse and misrepresentation of map projections. An invaluable reference source for professional cartographers and all those interested in the fundamental problems of mapping the Earth.

This textbook is a step-by-step tutorial on the applications of Geographic Information Systems (GIS) in environmental and water resource issues. It provides information about GIS and its applications, specifically using the most advanced ESRI GIS technology and its extensions. Eighteen chapters cover GIS applications in the field of earth sciences and water resources in detail from the ground up. Author William Bajjali explains what a GIS is and what it is used for, the basics of map classification, data acquisition, coordinate systems and projections, vectorization, geodatabase and relational database, data editing, geoprocessing, suitability modeling, working with raster, watershed delineation, mathematical and statistical interpolation, and more advanced techniques, tools and extensions such as ArcScan, Topology, Geocoding, Hydrology, Geostatistical Analyst, Spatial Analyst, Network Analyst, 3-D Analyst. ArcPad, ESRI’s cutting-edge mobile GIS software, is covered in detail as well. Each chapter contains concrete case studies and exercises – many from the author’s own work in the United States and Middle East. This volume is targeted toward advanced undergraduates, but could also be useful for professionals and for anyone who utilizes GIS or practices spatial analysis in relation to geology, hydrology, ecology, and environmental sciences. Exercises and supplementary material can be downloaded by chapter here: https://link.springer.com/book/10.1007%2F978-3-319-61158-7

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.