Archive for January, 2012

Farmers’ Market Study

A few months ago I took a look at the USDA dataset on farmers’ market locations (data date: 3/15/2011) as part of some exploratory analysis. I took some time out from client work and book writing to map out the data along with obesity rates.

The results of the farmers’ market analysis are reported over on
Study Finds Three Times More Farmers’ Markets in Areas with the Lowest Obesity Rates.

Remember, There are many factors that affect obesity (see this interactive map we did for Urban Mapping to look at some variables and also this discussion about other factors).

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What Should Managers Do With Their Spatial Data?

When a manager is faced with a heap of spatial data but doesn’t know how to make sense of it, let alone how to drive business-critical decisions with it, then it might as well not exist at all. However, it is in their best interest to break into that vault of information and become more wealthy* as a result.

Most GIS consulting clients already know about GIS in some way. They know enough to ask the consultant what they want and have an idea of what data they might need to get there. But there are a lot of business executives and managers who have spatial data but don’t know a thing about GIS who could benefit highly from the skills that GIS consultants can offer. Sometimes this comes about by reading about a GIS study that a competitor undertook, in a trade-magazine. But short of that, without a small amount of GIS knowledge a manager may have a tough time figuring out what to do with spatial data, even if there’s an understanding that it would be helpful to them.

Here’s where to start for a new data manager or executive:

1) If there’s an in-house data staff, ask for a debriefing that focuses only on the what. What you want is a high-level presentation that tells you what is in the data storage vaults at your organization. Ask if any of it is spatial data. If there’s a dedicated GIS team, obviously the presentation can focus only on the spatial data component. Be sure to inquire how it all fits within the larger context. It’s also helpful to know the history – why the data are collected, for example.

2) In very small organizations it is entirely possible that nobody knows what data is available. Sometimes data is hoarded by individuals for their particular purposes and are not shared with others. To get a handle on these datasets, a survey or individual talks will have to suffice to gather the requisite information.

3) At the very least, visualize the data! Spatial data is meant to be seen. Map it out. Get a cartographer to explore the data and make it meaningful. In this case we aren’t talking about full-fledged analysis, just maps of what’s available.

4) Now that you know what data exists, what part of it is spatial, and have seen it mapped out, you can start to explore analysis possibilities. The most basic way to do this is to think about how those data (combined with other data that may or may not exist yet, or that you may have to get elsewhere) can answer business-critical questions, drive innovation, or add value in some other way. If, through this thinking, even a small hint of a possibility arises…

5) Get your GIS team, your data team, or your GIS consulting team (if you don’t have one – get one) to explore the idea for you. Questions to ask: is my idea feasible with the data we have? are there other ideas that are related to mine that are feasible? what other data might we need?

*Wealth is money, time, efficiency, and/or doing good.

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Introduction to Classifying Map Data

Step 1) Determine if there is a standard for data classification that you want to use. For example, analyses on impervious surface in the Northwest using 30 meter resolution data are often split into class-breaks of 5%, 10%, and 20% due to these being important breakpoints for environmental degradation in the Northwest*. Likewise, if there are a set of intuitive classes that make sense for the visualization, use those. Otherwise proceed to Step 2.

Step 2) Graph the data values. Determine if the data are skewed or normally distributed.

Step 3) Consult this chart as a starting point.

Step 4) Read more about classifications in a GIS text. Other considerations when classifying data include whether or not to normalize the data and whether or not the data might be suitable for classification by spatial proximity.

*However, when using finer resolution data, we’ve found that these values may not be applicable.


Design Inspiration Series Part II: English Garden

This is the second part of a four part series that supplies design tips for cartographers inspired by landscape design genres. The first three posts go over these three types: French Formal Garden, English Garden, and Japanese Garden. The fourth post will depart from this by seeking inspiration from the natural (non-cultivated) landscape.

An English Garden is a bit of a confusing genre because it can refer to gardens that evoke an idyllic rural scene (even a bit wild), but it can also mean a well manicured space. Here I’m focusing on the idyllic, rural type. Some characteristics of these types of English Gardens are also applicable to cartography. They are discussed below.

1) HARMONY The English Garden, especially when it first came into being, consisted mainly of rolling hills and water features that gently fit one within the other. In mapping, this would be considered a calm, non-jarring, type of scheme that allows most, and perhaps all, elements to have similar weights and colors. The perfect example map for this is a children’s book, fictional map illustration, that is hand-drawn, and contains minimal changes in color. The map here is a great example because the color is well blended* with a lot of texture. Photograph taken by thoughtbecontact, map by Peggy Turchette

2) LUSH English landscapes are known for their lush quality due to the large amount of rains they get. They can grow amazingly colorful flowers and have very green fields. A map with a lush character has a lot of bold color as well. The example shows a geologic map of the moon. Photograph by ukgardenphotos, map by USGS

3) CHARM An English Garden can be a great example of charming design. Data analysts, such as myself, don’t often involve any elements of charm in our map products, but it is nice to know that there are cartographers out there who have a map audience that can appreciate charm. The map shown here isn’t the best cartographic product in existence but it is a good example of making the look of your map match the audience. The map was made specifically to illustrate the locations of lots in a new development that describes itself as being in a “charming, private, country setting.” Photograph by vigor, map source here

*For one technique on digitally creating a watercolor effect, see this post. Also, remember that Illustrator has a watercolor effect tool that you can apply to a whole map or just part of a map.


Demand for GIS Analysts on the Rise?

Many thought that by the year 2012, GIS would not be a profession anymore. After all, it was more than 10 years ago that ArcView 3.x was released, a product which many thought was ushering in a new age of user-friendly GIS software that anyone could understand and use. It did turn out to be true that major improvements in the GUIs to GIS software (in open source land too) would make them easier to use. But along with those improvements came more analytical tools to understand, larger and more complex datasets to crunch, and a higher expectation for decent cartography.

These changes kept GIS professionals employed as long as they continued to be proficient in the skills listed above. And, according to a new McKinsey Institute report, GIS professionals may continue to be in demand for many years. Their take on it is that data analysts will be in major demand in the near future, which one can safely assume will include GIS analysts(see note at the end of the article), because organizations:

1) have a lot of data, and
2) that data is increasingly “an important factor in production.”

Another interesting take-away from the report is that, “Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers.” This implies a change in the clientele for GIS businesses. Perhaps GIS businesses will no longer deal with mid-level “data-oriented managers” who very often have the ability to say no but not the power to say yes, and instead be able to deal directly with the senior-level people in the larger organizations. This could catapult the field into a whole new level of importance, not only within those organizations, but also in terms of what it can achieve.

The report also cautions that there will be a shortage of workers, perhaps in the amount of 140,000 to 190,000 by the year 2018, who posses advanced analytical skills. An even larger shortage is predicted in management positions, where a sufficient skill set to enable the understanding of the potential of these large datasets will be needed. GIS analysts will surely be a significant subset of the workers needed to fill these gaps.

*Spatial analysis is mentioned in the report as one of the many techniques for analyzing “big data” on page 30.


Google Checkout Reviews for the Ebooks

I’ve been rummaging around the Google Merchant site lately as part of the yearly tax information gathering process and I came across this snapshot of the reviews that people have given on their Colors For Maps and/or Type For Maps transactions. Now, not everyone pays through Google Checkout – PayPal is an option too – and not everyone who pays through Google Checkout leaves a review. But here’s what the snapshot looks like…I’m pleased to say that it reports a 4.8 out of 5 stars:

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