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Book Review: The ESRI Guide to GIS Analysis Vol. 2: Spatial Measurements & Statistics

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Title: The ESRI Guide to GIS Analysis Vol. 2: Spatial Measurements & Statistics
Author: Andy Mitchell
Publisher: ESRI Press
Year: 2005
Aimed at: GIS/Analysts/Map Designers – intermediate
Purchased from: www.wordery.com

ESRI GA V2

This textbook acts as 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. This is the second book of the series and follows on from The ESRI Guide to GIS Analysis Volume 1: Geographic Patterns & Relationships.

The first chapter is, inevitably, an introduction to spatial measurements and statistics. You perform analysis to answer questions and to answer these questions you not only need data but you also need to understand the data. Are you using nominal, ordinal, interval or ratio values, or a combination of these? The type of value(s) will shape the analysis techniques and methods used to calculate the statistics. You will need to interpret the statistics, test their significance and question the results. These elements are briefly visited with the premise of getting more in-depth as the book progresses. The chapter ends with a section on ‘Understanding data distributions’ which is essentially a brief introduction to data exploratory techniques such as describing frequency distributions, spatial distributions, and the presence of outliers and how they can affect analysis.

Chapter 2 discusses measuring geographic distributions with the bulk of the chapter focused on finding the center (mean, meridian, central feature), and measuring compactness (standard distance), orientation and direction of distributions (spatial trends). These are discussed for points, lines, and areal features and also using weighted factors based on attributes. These are useful for adding statistical confidence to patterns derived from a map. Formulas and equations begin to surface and although not necessary to learn them off by heart, because the GIS does all the heavy lifting for you, it gives insight into what goes on under the hood, and knowing the underlying theory and formulas can often aid in troubleshooting and producing accurate analysis. The last section of this chapter is fundamental to the rest of the text, testing statistical significance. This allows you to measure a confidence level for your analysis using the null hypothesis, p-value, and z-score. This can be a difficult topic to comprehend and may require further reading.

The third chapter, a lengthy one, is based around using statistical analysis to identify patterns, to enhance and backup the visual analysis of the map with confidence or to find patterns not may not have been immediately obvious. The human eye will often see patterns that do not really exist, so alternatively, statistical analysis might indicate what you thought was a strong pattern was actually quite weak. The statistical analysis methods are beginning to heat up and here we are introduced to; the Kolmorogov-Smirnov test and Chi Square test for quadrat analysis in identifying patterns in areas of equal size; the nearest neighbour index for calculating the average distance between features and identifying clustering or dispersion; and the K-function as an alternative to the nearest neighbour index, each used to measure the pattern of feature locations. These are followed by measuring the spatial pattern of feature values using; the join count statistic for areas with categories; Geary’s c and Moran’s I for measuring the similarity of nearby features, and the General-G statistic for measuring the concentration of high and low values for features having continuous values. The formulas for each are presented along with testing the significance of and interpreting the results. The final section of this chapter discusses defining spatial neighbourhoods and weights when analysing patterns. There are a few things to consider such as local or regional influences, thresholds of influence, interaction between adjacent features, and the rate of regional decline of influence.

Chapter 4 is titled ‘Identifying Clusters’ with a main focus on hotspot analysis. First, we are introduced to nearest neighbour hierarchical clustering which is heavily used in crime analysis. While Chapter 3 discussed global methods for identifying patterns and returns a single statistic, this chapter focuses on local statistics to show where these patterns exist within the global setting. Geary’s c and Moran’s I both have local versions and their definition, implementation, and factors influencing the results are discussed and critiqued along with Art Getis’ and Keith Ord’s Gi* method for identifying hot and cold spots.While the methods in Chapter 3 enforced that there are patterns in the data (or not), the methods in Chapter 4 highlight where these clustered patterns are. The last section of Chapter 4 discusses using statistics with geographic data; how the very nature of geographic data affects your analysis, how geographic data is represented in a GIS affects your data analysis, the influence of the study area boundary, and GIS data and errors.

“To the extent you’re confident in the quality of your GIS data, you can be confident in the quality of your analysis results.”

The last chapter ventures away from identifying patterns and clusters and focuses on analysing geographic relationships and using statistics to analyse such. Geographic relationships and processes are used to predict where something is likely to occur and examining why things occur where they do. Chapter 5 looks at statistical methods for identifying geographical relationships with a Pearson’s correlation coefficient and Spearman’s correlation coefficient discussed and assessed. Linear regression (ordinary least squares), and geographically weighted regression are presented as methods for analysing geographic processes. These methods warrant a full text in their own right and there is a list of further reading available at the end of the chapter.

Overall Verdict: I feel that I will be referring back to this text a lot. Having recently completed a MSc in Geocomputation I wish that this had crossed my path during the course of my studies and I would highly recommend this book to anyone venturing into spatial analysis where statistics can aid and back up the analysis. Although they are littered throughout the chapters, you really do not need to get bogged down with the formulas behind the statistical analysis techniques, the most important points is that you understand what the methods are performing, their limitations, and how to assess the results and this book really is a fantastic reference for doing just that. Knowing the theory is a huge step to being able to apply the analysis techniques confidently and derive accurate reporting of your data.

Book Review: Learning ArcGIS Geodatabases [eBook]

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Title: Learning ArcGIS Geodatabases
Author: Hussein Nasser
Publisher: Packt Publishing
Year: 2014
Aimed at: ArcGIS – beginner to advanced
Purchased from: www.packtpub.com

Learning ArcGIS Geodatabases

After using MapInfo for four years my familiarity with ArcGIS severely declined. The last time I utilised ArcGIS in employment shapefiles were predominantly used but I knew geodatabases were the way forward. If they were going to play a big part in future employment it made sense to get more intimate with them and learn their inner secrets. This compact eBook seemed like a good place to start…

The first chapter is short and sweet and delivered at a beginner’s level with nice point to point walkthroughs and screenshots to make sure you are following correctly. You are briefed on how to design, author, and edit a geodatabase. The design process involves designing the schema and specifying the field names, data types, and the geometry types for the feature class you wish to create. This logical design is then implemented as a physical schema within the file geodatabase. Finally, we add data to the geodatabase through the use of editing tools in ArcGIS and assign attribute data for each feature created. Very simple stuff so far that provides a foundation for getting set-up for the rest of the book.

The second chapter is a lot bulkier and builds upon the first. The initial task in Chapter 2 is to add new attributes to the feature classes followed by altering field properties to suit requirements. You are introduced to domains, designed to help you reduce errors while creating features and preserve data integrity, and subtypes. We are shown how to create a relationship class so we can link one feature in a spatial dataset to multiple records in a non-spatial table stored in the geodatabase as an object table. The next venture in this chapter takes a quick look at converting labels to an annotation class before ending with importing other datasets such as shapefiles, CAD files, and coverage classes and integrating them into the geodatabase as a single point of spatial reference for a project.

Chapter 3 looks at improving the rough and ready design of the geodatabase through entity-relationship modelling, which is a logical diagram of the geodatabase that shows relationships in the data. It is used to reduce the cost of future maintenance. Most of the steps from the first two chapters are revisited as we are taken through creating a geodatabase based on the new entity relationship model. The new model reduces the number of feature classes and improves efficiency through domains, subtypes and relationship classes. Besides a new train of thought on modelling a geodatabase for simplicity the only new technical feature presented in the chapter is enabling attachments in the feature class. It is important to test the design of the geodatabases through ArcGIS, testing includes adding a feature, making use of the domains and subtypes, and test the attachment capabilities to make sure that your set-up works as it should.

Chapter 4 begins with the premise of optimizing geodatabases through tuning tools. Three key optimizing features are discussed; indexing, compressing, and compacting. The simplicity of the first three chapters dwindles and we enter a more intermediate realm. For indexing, how to enable attribute indexing and spatial indexing in ArcGIS is discussed along with using indexes effectively. Many of you may have heard about database indexing before, but the concept of compression and compacting in a database may be foreign. These concepts are explored and their effective implementation explained.

The first part of the fifth chapter steps away from the GUI of ArcGIS for Desktop and ArcCatalog and switches to Python programming for geodatabase tasks. Although laden with simplicity, if you have absolutely no experience with programming or knowledge of the general concepts well then this chapter may be beyond your comprehension, but I would suggest performing the walkthroughs as it might give you an appetite for future programming endeavours. We are shown how to programmatically create a file geodatabase, add fields, delete fields, and make a copy of a feature class to another feature class. All this is achieved through Python using the arcpy module. Although aimed at highlighting the integration of programming with geodatabase creation and maintenance the author also highlights how programming and automation improves efficiency.

The second part of the chapter provides an alternative to using programming for geoprocessing automation in the form of the Model Builder. The walkthrough shows us how to use the Model Builder to build a simple model to create a file geodatabase and add a feature class to it.

The final chapter steps up a level from file geodatabases to enterprise geodatabases.

“An enterprise geodatabase is a geodatabase that is built and configured on top of a powerful relational database management system. These geodatabases are designed for multiple users operating simultaneously over a network.”

The author walks us through installing Microsoft SQL Server Express and lists some of the benefits of employing an enterprise geodatabase system. Once the installation is complete the next step is to connect to the database from a local and remote machine. Once connections are established and tested an enterprise geodatabase can be created to and its functionality utilised. You can also migrate a file geodatabase to and enterprise geodatabase. The last part of Chapter 6 shows how privileges can be used to grant users access to data that you have created or deny them access. Security is an integral part of database management.

Overall Verdict: for such a compact eBook (158 pages) it packs a decent amount of information that provides good value for money, and it also introduces other learning ventures that come part and parcel with databases in general and therefore geodatabases. Many of the sections could be expanded based on their material but the pagination would then increase into many hundreds (and more) and beyond the scope of this book. The author, Hussein Nasser, does a great job with limiting the focus to the workings of geodatabases and not veering off on any unnecessary tangents. I would recommend using complimentary material to bolster your knowledge with regards to many of the aspects such as entity-relationship diagrams, indexing (both spatial and non-spatial), Python programming, the Model Builder, enterprise geodatabases and anything else you found interesting that was only briefly touched on. Overall the text is a foundation for easing your way into geodatabase life, especially if shapefiles are still the centre of you GIS data universe.

Book Review: The ESRI Guide to GIS Analysis Vol. 1: Geographic Patterns & Relationships

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Title: The ESRI Guide to GIS Analysis Vol. 1: Geographic Patterns & Relationships
Author: Andy Mitchell
Publisher: ESRI Press
Year: 1999
Aimed at: GIS/Analysts/Map Designers – beginner
Purchased from: www.wordery.com

GIS Analysis Vol 1

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.

Next: see The ESRI Guide to GIS Analysis Volume 2: Spatial Measurements & Statistics

Book Review: Designing Better Maps; A Guide for GIS Users

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Title: Designing Better Maps; A Guide for GIS Users
Author: Cynthia A. Brewer
Publisher: ESRI Press
Year: 2016
Aimed at: GIS/Map Designers – beginner
Available from: www.wordery.com

Designing Better Maps

“Lightness to enhance hierarchy, hue to enhance qualitative differences.”

This book is the perfect companion for anyone beginning their GIS adventure and can even teach a trick or two to those seasoned professionals. I remember back to my GIS postgraduate course and making maps for the first time. I always thought I had an element of artistic flair from my days in national school art class and I was none the wiser about my map’s lack of, well, everything, after graduating. Okay, I wasn’t placing ridiculously oversized north-arrows or scale bars that were of odd measurements and using psychedelic colouring schemes but I had no idea how far off I was from making publishing-worthy mapping outputs. Luckily my first and second jobs involved mass outputs of paper maps and it was here that I initially learned about many of the aspects of this book such as the placement and size of elements and the use of white space.

One great aspect about this book is that although it is an ESRI Press publication their products are not shoved down your throat. ArcGIS gets a mention every so often but this book is far from a tutorial style walk-through and airs more on the side of theory and practicality. The design processes discussed can be performed in the majority of GIS software and the option of performing edits in graphic design packages are also mentioned quite frequently.

The first chapter emphasises designing a map for it’s intended purpose and audience through the visual hierarchy of data and by planning your layout, balancing empty spaces and the refinement process through experimentation. Choosing the right projection can also play a key role to how the data is displayed and how it visually impacts the final product.

Basemaps are an essential part of the design process and getting the background information right can be the difference between a good map and a great map. Chapter 2 cycles through many types of basemaps and how you can control their impact on the map through raster and vector based background information and how you can keep the important information prominent.

Chapter 3 puts forward the notion of self explanatory maps. Whoever is reading the map should not have to seek the attention of the author to explain what is going on. This is achieved through the legend, wording the title appropriately, utilising supportive text and placing it in context, and making use of mapping elements such as the north-arrow, scale-bar, and graticules and their position in the visual hierarchy.

Maps are everywhere these days, there are interactive webmaps, static webmaps as images on a website, maps embedded in documents such as PDF, maps displayed on TV, and believe it or not maps still get printed in paper format. With all the output and display options available you must make sure that your map can accommodate each medium that it will be presented in. Chapter 4 explores the common pitfalls with exporting especially with handling transparency and finishes up with copyrights and attributing the source of the data to avoid infringement.

The fifth chapter addresses an area that I have had problems with in the past and that is choosing the correct font(s) for the map. This chapter alone made the purchase of the book worthwhile.

From fonts to labelling the book flows naturally and we all know how cumbersome labelling can be when trying to finalise a map. Labels can often rank higher in the visual hierarchy than intended or wanted. Clear labelling helps your audience correctly interpret the mapped data. Size, weight, case, and lightness are just some of the criteria used to communicate differences in importance. With labelling being such a time-intensive part of map creation, knowledge of labelling conventions will improve efficiency in quality map production.

Chapter 7 gets to the nuts and bolts of what I’m sure most of you thought this book would be all about, colours. I have previously sat through a whole university module for digital media where RGB and CMYK colour played a role but this chapter really simplifies it all before progressing to chapter 8 and discussing the prevalent role of colour choices for features on a map.

Colours are intended to make your maps easier to read by ensuring that your map matches the logic of your data. The author discusses several colour schemes, sequential, diverging, qualitative, bivariate (sequential, diverging, qualitative) and then fine tuning the colour selection with custom colour ramps and making maps more accessible for people who are colour-blind.

The final chapter mainly builds upon Chapter 8 but also draws from several other chapters. The main focus of the chapter is customising symbols for ordered data and symbolising categorised data into qualitative classes. Point, line and area symbols are discussed using a variety of symbolising methods such as proportion, graduated, size/width, shape, angle and patterns. The author neatly creates a table for eight visual variables for points, lines and areas giving twenty-four basic ways to vary symbols for representing your mapped data. To build upon Chapter 8 symbols for multivariate, overlaid, bivariate, quantitative and qualitative data are explored relating to sequential and diverging schemes.

The Appendix provides us with information on the ColorBrewer website and there are pages of colour palettes for reference.

Overall Verdict: I wish I had this book in my possession when I first enrolled for a career in GIS. Even after years of producing and plotting hundreds of maps this book has enforced some new and reinforced some old quality controls required to produce the best possible map for the intended audience. It’s an easy read with chapters short but very informative and to the point. I will be keeping it handy as a reference especially for the chapters relating to fonts, labelling, and colours. If you are a seasoned GIS user and feel that your maps are still lacking that final bit of quality this book is a good place to get you over that final hurdle. I am often guilty of rushing a map to final product and this book really enforces basic standards for efficient quality output.

Book Review: Learning QGIS by Anita Graser [eBook]

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Title: Learning QGIS (Second Edition)
Author: Anita Graser
Publisher: Packt Publishing
Year: 2014
Aimed at: QGIS – beginner, GIS/Python – knowledgeable
Purchased from: www.packtpub.com

Learning QGISMy New Years resolution is to upgrade skills and software knowledge instead of sitting in front of a TV for hours on end (we’ll see how long this lasts). About six years ago I installed QGIS on my laptop, never used it, removed it, reinstalled it, never used it, removed it and this cycle has continued for each year. I am putting a stop this vicious cycle as of now and aim to become proficient with this well renowned piece of open source software, with my main goal to incorporate Python for automation and develop some plugins. I will become familiar with the software before making the leap to Python.

There’s only so much you can fit into 125 pages and while this book is packed with information on the capabilities of QGIS it certainly leaves you wanting more. I think this is a good problem as it drives you to do your own research and play around with what’s on offer in QGIS based on your own interest.

The book starts off by guiding you through the installation process and then provides a brief description of the interface and available toolbars.

In Chapter 2 we begin to add spatial data (vector and raster) to the map. The link provided to download the sample data didn’t stand the test of time (a year) but was easy to locate with an internet search. We are also introduced to georeferencing, loading data from databases and accessing data from OGC web services, ending without a brief styling tutorial.

The main part of the third chapter walks us through creating and editing geometries and attribute data. We also encounter using the measurements tools, the field calculator, reprojecting and converting files, and joining tabular data.

Chapter 4 presents Spatial Analysis; clipping a raster, terrain analysis, raster calculator, vector to raster and raster to vector conversions, heatmaps, vector geoprocessing (proximity analysis), raster sampling at point locations, density with hexagonal grids, calculate are shares within a region. There is a lot of information in this chapter, without nearly being exhaustive, that emphasizes the analytical capabilities of QGIS.

“Creating Great Maps” is the title of the fifth chapter. Did it hold up to this title? In short, yes, but you are not walked through step by step with someone holding your hand, you are presented with visualization and styling techniques to help you create your own masterpiece. A whole book could be dedicated to this topic.

The final chapter jumps straight into “Extending QGIS with Python” and is certainly not for those just beginning programming with Python. Lines of code are given with a general overview of what’s happening and knowledge of syntax and the API is required here. As a newbie to the QGIS API I found this chapter a bit daunting but time, effort and the will to learn more is a challenge that I accept. The chapter and indeed the book concludes with an example of a processing script and developing and implementing a plugin.

QGIS Python Console

QGIS Python Console

One thing this book has thought me is that QGIS is highly customizable to user preferences and visualizations. My next step is to gain more familiarity with QGIS through available text books and online tutorials before heading down the customization path with Python.

Overall Verdict: Although it was difficult to follow some of the workflows exactly, and this is perhaps because it is more informative than tutorial, I felt this was a good intro to QGIS, what the software has to offer, how to navigate the GUI and the possibilities of extending QGIS with Python. The book cost me a whopping €5.63 from a sale on the Packt Publishing website. This book is packed with info and provided a solid beginning on my quest to QGIS stardom. I am already wondering why it took my so long to break out of that repetitive cycle.