My review of Rogerson and Yamada’s Statistical Detection and Surveillance of Geographic Clusters has just been published in the journal Environment and Planning B. Overall I thought the book was very useful and have consulted it many times in my own work. You can read the full review here.
As I have mentioned before, archive.org provides some amazing resources for free download. I thought I would have a look to see what it had in the way of old atlases and I wasn’t disappointed. Here are a couple of my favorites: The Reynold’s Universal Atlas was published in the 19th century and includes over 400 maps an diagrams covering topics such as astronomy, vegetation, geology and the laws of matter and motion. Sadly many of the illustrations are spread over two pages but all are brilliant quality and make many of our contemporary maps appear dull by comparison. The “Tidal Chart of the World” taken from the atlas is shown below.
My second favorite is Justus Perthes’ Atlas Antiquus which is a pocket atlas of the ancient world. What is so great about this map is the fact that it has been scanned at very high resolution. The pdf is therefore >300mb! It includes some detailed maps of Rome and Athens as well as Northern Europe, North Africa, Spain and the Mediterranean. I have included the map of the UK and Ireland below. It would appear that this is part of a series of scanned atlases so there may be more to come.
***Not long after posting this, the “The Look of Maps” appears to have been removed from archive.org”***
ESRI Press have announced they will be re-printing Arthur H. Robinson’s classic book “The Look of Maps: An Examination of Cartographic Design“. The book begins with the following quote from William Morris Davis:
“It is just as important to study the proper and effective use of various forms of graphic presentation, as it is to study the values of different methods, treatments, grades, and forms of verbal presentation”.
This quote, like much of the advice in the book, remains as relevant today as it did 50 years ago. I think it is great that ESRI Press are investing in re-printing “classic” works as it is often nice to own them as a printed version. However, books are expensive, especially if you are a cash strapped student and there is a free alternative available. In this case the book can be freely downloaded from archive.org. Download Link. Archive.org is a great resource and I am sure there are many hidden gems on there to be discovered.
Over the last couple of days I have utilised some excellent free GIS resources. I have listed these and some others below.
Geospatial Analysis: This is the free online version of de Smith, Longley and Goodchild’s excellent book by the same title. It provides full coverage of current GIS methodologies. It also provides extensive information regarding the various GIS software available.
Analysing Spatial Point Patterns in R: 200 pages of workshop notes written by Adrian Baddeley. These provide extremely detailed and comprehensive overview of the spatstat in R.
GeoDa Center Tutorials: A range of tutorial material provided by creators of the GeoDa Software. I would focus on the R tutorials as the GeoDa tutorials are awaiting an update in line with the software’s latest release.
Spatial Stats. in ArcGIS: A preview chapter from the Springer’s Handbook of Applied Spatial Analysis.
CATMOGs: A hugely successful series of publications that cover the basics of spatial analysis, they have been written by many of the pioneers in the field. Topics include The Modifiable Areal Unit Problem (Openshaw), Voronoi (Thiessen) Polygons (Boots), Spatial Autocorrelation (Goodchild).
CASA Working Papers: A shameless plug for my fellow researchers. The nice thing about these is you don’t need to be part of an academic institution to access academic research.
I am sure there are many others and I welcome your suggestions…
I have just reviewed Sarkar‘s Lattice: Multivariate Data Visualization with R for the Journal of the Royal Statistical Society Series A. I would highly recommend the book to all R users who wish to produce publication quality graphics using the software. You can read the full review here.
The use of spatial data is increasing across a broad range of disciplines. The Sage Handbook of Spatial Analysis, edited by Fotheringham and Rogerson, is marketed as a response to this growing demand for specialized statistical and mathematical methods for spatial data. The contributions to this book are written for academics and graduate level students; this is reflected by the relatively high RRP.
The Sage Handbook of Spatial Analysis provides an extension to many of the topics covered by Fotheringham et al’s (2000) Quantitative Geography. Each of the book’s 25 chapters are written by leaders in their respective fields with the list of contributors including Michael Goodchild, David Martin and Luc Anselin; expertise that is reflected by the clarity and currency of much of this book.
Due to the breadth of topics and contributors to this volume I thought it best to provide general overview of the book with select comments on a couple of specific examples. The book can be split into two broad sections. The first focuses on established concepts, and the second outlines key spatial analysis methodologies. Topics covered by the first 12 chapters include the role of GIS, the modifiable areal unit problem (MAUP), geovisualization, spatial autocorrelation and spatial sampling. These early chapters are invaluable, especially to those recently initiated to advanced spatial analysis methodologies. They provide important context for understanding the later chapters of the book.
Beyond chapter 12 the focus becomes more methods-based to cover concepts such as geographically weighted regression (GWR), the detection of spatial clusters, Bayesian spatial analysis, and neural networks. These provide useful reference material to those looking for a “way in” to a particular method. Several authors, for example Fotheringham on GWR, are integral to the development of the methods and concepts they are describing and therefore provide the most authoritative explanations of them. The final two chapters are more conceptual as they discuss the challenges facing, and suggested future directions for, spatial analysis.
Integrating spatial analysis with remotely sensed data is not covered in this volume. It could, however, be included in a chapter on spatial data types and their reliability. An in depth overview of the types of spatial data and their limitations may help readers to avoid some pitfalls that could undermine their subsequent spatial analysis. In addition, the “Future for Spatial Analysis” chapter appears to conflate spatial analysis and geography. The statement that “spatial analysis holds the key for geography” is a view opposed by many who argue that in fact “geography holds the key for spatial analysis”. The contributions of geographic thought to spatial analysis are not considered. Without such considerations, there is risk that many of the quantitative methodologies developed for spatial analysis face being ignored by mainstream geography. A more balanced view has recently been published in the The Professional Geographer, Volume 61, Number 3 (2009).
The criticisms are minor and should detract very little from The SAGE Handbook of Spatial Analysis. The comprehensive insights provided by the world leading contributors are invaluable, and provide a summary of the many excellent books they have written separately on the subsets of spatial analysis. Despite its cost, this book remains a worthwhile investment for any graduate student wishing to develop a firm grounding in cutting edge spatial analysis.
Book Details:
Editors: A. Stewart Fotheringham, Peter A. Rogerson.
Publisher: Sage.
ISBN: 9781412910828.
RRP: £90 (£85 on Amazon).
511 pages (Hardback).
I have just reviewed the book Applied Spatial Data Analysis with R which has been published in the September2009 issue of the Royal Statistical Society’s Significance magazine.
Applied Spatial Data Analysis with R is an accessible text that demonstrates and explains the handling of spatial data using the R Software Platform. The text’s authors have all been key contributors to the R spatial data analysis community, and the range of their contributions is evident from the comprehensive coverage of this work. It will appeal to those familiar with R but not spatial data, and vice versa, as well as those proficient in both and in search of a reference text. I highly recommend the book to those interested in embarking on spatial data analysis, those proficient in handling spatial data in other software and want to utlise R, and those already using R to manipulate and analyze spatial data.
This is James Cheshire's research blog. James is a PhD student based in the Department of Geography and Centre for Advanced Spatial Analysis, University College London. Twitter @spatialanalysis
