Title: The ESRI Guide to GIS Analysis Vol. 1: Geographic Patterns & Relationships
Author: Andy Mitchell
Publisher: ESRI Press
Aimed at: GIS/Analysts/Map Designers – beginner
Purchased from: www.wordery.com
This textbook is a companion text for GIS Tutorial 2: Spatial Analysis Workbook (for ArcGIS 10.3.x) where you can match up the chapters in each book. Although not a necessity, I would recommend using both texts in tandem to apply the theory and methods discussed with practical tutorials and walkthroughs using ArcGIS.
The title of this book might lead you to believe that ArcGIS will feature heavily throughout the text but Michael F. Goodchild sets this straight in the Preface by stating that he applauds ESRI for backing this book even though it isn’t Arc eccentric. The author, Andy Mitchell, presents the material as generic GIS such that most GIS software packages should be able to utilise the techniques discussed.
Chapter 1 is a short introduction to what GIS analysis is, understanding the representation of geographic features in a GIS, and the common attributes associated with geographic features that allow for analysis. The wording is simplistic in nature and easy to follow, and acts as a good entrance to the rest of the book.
The second chapter begins to delve into the realm of visual analysis, using your brain to to discern patterns for a better understanding of the data and the area that you are mapping. Several real-life mapped examples are displayed to show how ‘mapping where things are’ aids in more focused decision making. The chapter steps through; deciding what to map, preparing your data, and making your map, with comparison figures to show you why you might perform such tasks.
Why map the most and least? Because mapping features based on quantities adds an additional level of information beyond simply mapping the locations of the features and this notion is made clear from providing some real-life examples in Chapter 3. The author then takes us down a path to understanding quantities and the importance of knowing the type of quantities that you are mapping, and this naturally leads onto the next topic of classification, why use classes? and choosing an appropriate classification method/scheme for the purpose of your data. It is important to understand how classification methods such as Natural Breaks (Jenk’s), Quantile, Equal Interval, and Standard Deviation classify your data and having a general guideline on choosing the appropriate method.
A great recurring aspect in this book is that every chapter begins with a question and Chapter 4’s is ‘Why Map Density?’ and then proceeds to answer the question and the methods available for mapping in a GIS. This chapter discusses density for defined areas, dot density mapping, and density surfaces, what the GIS does to create them and the results of the output.
The fifth chapter takes a look at mapping what’s inside an area, discusses why you would want to map inside an area?, and some analysis and results that can be derived from such. Do you need to map a single area to find what’s happening inside or multiple areas to analyse what’s happening inside each for comparison purposes? Methods are explained along with how the GIS performs these for analysis. You might want to find out if a certain feature is within an area, a list of all features inside an area and a count of each, or the sum of a designated land type area within a boundary for examples. Summaries and statistics can also be generated from what is found inside an area boundary.
Having assessed some simple techniques for mapping what’s inside an area, the next chapter casts it’s attention towards finding what’s nearby. People often think of nearness in straight lines or along transport networks, but GIS is also useful for travel cost analysis giving weight to different land use or soil types for example when considering the path for a pipeline. Nearness by straight-line distance, distance/cost over a network, and cost over a geographic surface are discussed in detail. At this point we are venturing into understanding some of the concepts behind Network Analysis.
The last chapter looks at mapping change with regards to change over time for time pattern analysis. Three ways of mapping change are presented; creating a time series, creating a tracking map, and measuring change, along with the considerations required when creating each type for change in discrete features, events, summarized areas, and continuous categories and values.
Following the last chapter there are some recommendations for some further reading.
Overall Verdict: The perfect companion for a GIS student embarking on their geospatial educational quest. The theory behind GIS is essential for accurate analysis and troubleshooting. This book is an easy read with a plethora of figures and maps utilised in real-life situations found in each chapter to aid in the experience. Although getting closer to being two decades old this text stands the test of time and acts as a solid base for a foundation in simple analysis using a GIS to find patterns and relationships.
The only shortcoming of a text of this nature is that you cannot see how methods and techniques discussed are performed in a GIS. This is where the companion text GIS Tutorial 2: Spatial Analysis Workbook (for ArcGIS 10.3.x) comes in and aids in providing walkthroughs to further enhance your understanding of the underlying theory.