road to gis

Road to GIS

On this inaugural GIS Appreciation Day: Following great stories by Gretchen Peterson and Bill Dollins >

My Road to GIS

I am absolutely fascinated by the various paths that lead nerds of all types to GIS. From natural sciences, social sciences, science fiction, art, wanderers of all kinds stumble upon GIS and decide to stay. Me too. Some use it as a tool to further their pursuits, others make it their career. It blends so many worlds (pun intended) that it casts a wide net and yields an interesting haul. It certainly blended four perfect worlds for me: Sociology, The Great Outdoors, Maps, and Magic.

My road to GIS started with a simple question: What is your home zip code? Little did I know how this one question would affect not only my career, but my life.

My four worlds

First, I am absolutely fascinated by people and society. So naturally I studied Sociology. Initially I had little interest in technology outside of using a word processor to write my papers and print them (yes, dot matrix). I was a social worker helping homeless mentally ill people in my hometown for five years while I finished a two year college degree. I was an idealist who was certain to save the world.

Before that happened however…and before I thought my spirit would break…I split to Alaska to “Find Myself” and to experience the thrill and serenity of the Great Outdoors. I got my copy of The Milepost and a giant fistful of maps and headed to Alaska via the famous ALCAN Highway. Suffice it to say I learned how to effectively use and respect Maps in Alaska, among other things. When it was time to return to the Lower 48 I just couldn’t bring myself to move back to the midwest, so I moved to Colorado.

Upon moving to Colorado (the first time), I was thrilled to land a job with Colorado State Parks while finishing my degree in Sociology at Colorado State University. I was able to apply my new found quantitative research skills in conducting and reporting on the Colorado State Parks Visitation Study. In analyzing the results, one question seemed to jump off the page. What is your home zip code? Simple enough, but with so many possibilities. But I just didn’t know how to analyze it. I could have looked for recurrences of the same zip code in a table, but that misses so much. How could I display this data in a useful and interesting way? I started to ask around and stumbled into those sacred three letters for the very first time: G. I. S.

Intrigued, I got a shapefile of all zip codes in the US (from what seemed to be some kind of ogre who hung out in a dark corner of our Stalin-era Denver State Building hacking commands into a blinking cursor in a black box on a Unix workstation). I then figured out how to join this shapefile to my list of zip codes and the world was never the same for me again. I had created my very first data driven map. There I had it, the merging of all the things I loved in the world: Sociology, The Great Outdoors, and Maps!

I quickly realized that what I had stumbled into was happening all around me at CSU. But not in the liberal arts college. I quickly signed up for my first GIS class and eventually earned a minor in Geography by conducting a comprehensive trail use study at Castlewood Canyon State Park that included everything from trail mapping with GPS to conducting personal interview surveys, compiling, and analyzing the results. And making maps of which trails hikers hiked.

In younger years I had very little interest in technology. In fact, I had a fascination with the Unabomber Manifesto decrying technology and its’ affects. But my encounter with GIS piqued my interest in technology enough to dig in a little. And with a proclamation from a GIS friend at the USGS that “Dude, if you’re going to do GIS you need to learn to code!” Dude, peeeeshaaw, was my reaction, as if he just insulted my first map. But, once I figured out how to control an entire stack of technology to make and control a map, it was Magic. And I was hooked on programming.

I have since made a career using all of these and all of them combine to keep me interested, engaged, and…well…employed. GIS is a journey that I couldn’t have planned for, but in the end, it fits so perfectly.

For giggles, although I still appreciate the simplicity, my first ‘published’ map:

castlewood canyon trail map survey

Recreation Facilities around Lassen Volcanic National Park


Come git it outdoorsy nerds! Recreation facilities for all (developers)!

The Recreation Information Database (RIDB) is a comprehensive database containing authoritative outdoor recreation facility information for most US federal agencies that provide recreation services including the National Park Service, US Forest Service and many, many others.

I’ve been following the progress since its inception and when the USDA came out with an API to access it I dove in to make a web map to access recreation facilities, from a map.

The application is pretty straightforward. You can pan and zoom the map and recreation facilities will be display with recognizable icons within the current extent or, if zoom level is far out, a predefined radius based on zoom level. Clustering keeps things tidy. I also used the Mapzen Search service along with the Mapzen Leaflet Geocoder to provide autocomplete search capability.

Give it a try here:

Source project:

The Services:

Recreation Information Database API

Mapzen Search (geocoding API)

The Stack:


Leaflet marker cluster

Mapzen leaflet geocoder

Leaflet locate control

Mapbox for basemap



Autocomplete Map Search:

Autocomplete multi-source Search with ArcGIS REST services

Search First. Search is expected in modern web applications. And what better use of a map application than to start typing what you want, be shown a list of relevant suggestions, pick one and be taken there with potentially some useful context info.

In several posts in the great geospatial blog, MapBrief, Brian Timoney has mentioned a Search First approach to web application building. The most recent example:

Good Thing #1: A Big, Obvious Auto-Complete Text Entry Box

I couldn’t agree more. It is core to nearly every application I build and is of far greater use than most of the novelty web mapping ‘standard’ tools <uhem, looking at you, measure tool>.

Search is the number one request I get in web mapping applications so I thought I’d share how I put all the pieces together to get an autocomplete search up and running with esri ArcGIS REST services.

I’ll walk through the steps to get a fully functioning autocomplete map search feature.

Here’s the source on github and a working sample application.

Let’s build an autocomplete search box for recreation sites in Okanogan-Wenatchee National Forest.

This autocomplete solution uses twitter typeahead js, the bundled download includes the bloodhound suggestion engine and the jQuery plugin, all of which we’ll use here.

Once you get typeahead all hooked into your application, the only html you’ll need is an input for your search and the rest is done via javascript.

<input id="search-box" type="text" placeholder="Search...">

There are three parts to getting things going:

  1. Define and initialize suggestion engines
  2. Wireup typeahead with jQuery including adding the engines and defining the UI
  3. Handle the event when a user selects one of the suggestions

Define the Engines

First, we’ll define an engine (bloodhound) for each source to include. In this example we’ll use four:


A campground (arcgis) feature service layer


A trail head feature service layer


A ski area feature service layer


The esri geocoder service


Construct the remote source(s)

This is the most critical piece of the whole operation and requires some consideration because you potentially have options here. The remote source needs a url to send a request each time the user types characters. Selecting the best option will result in the best performance. Here are our best options with arcgis REST services:


If you have a map server, find is a great option if you want to search multiple layers in the same request. I’d say if you have this option, take it.


If you only have a feature server, this is for you. You can either query a layer individually or query the entire feature server. We are going to query each of our feature layers individually.


Suggest is currently meant for geocoding, for now, but I suspect a locator service could be constructed to take advantage of this service. I’ll make the assumption that this is the best option because it is intended specifically for search.

You could roll your own locator service that supports suggest (ArcGIS 10.3 +). We’ll use the world geocoder and take advantage of suggest.

The code to build the campground site suggestion search engine and initialize it:

Here’s the engine setup for the esri world geocoder service. Note the searchExtent parameter. This can be used to limit the geographic area of you suggestion results. In this case it is (roughly) Washington State.

You can see that in both of these engines we set the ajax property to show the spinner before the request and remove it when the request is complete. These calls can step over each other if you have several engines but works pretty well here.


Add the engines and style the suggestions

Now we need to setup typeahead itself and wire up the engines and tell typeahead the properties we are using for each suggestion generated by the engines. We will also define how the suggestions will be displayed in the drop down.

First, turn the input box into a typeahead via jQuery and set some options like so

minLength is the number of characters a user types before suggestions start firing.

Next tell typeahead about the engines to use, here’s our campground setup

We’ve just told typeahead that the name of this source is ‘camp’, the displayKey is ‘name’, the source is our camp bloodhound engine adapter and set the template to use for the header (a campground icon inside a header tag).

You’ll do the same for all sources chaining them together. The whole set of sources looks like this:

Define what will happen when a user selects a suggestion

Okay, cool, we’ve got some suggestions for our users.


Now we need to setup what will happen when one is actually selected. So we simply set up a jQuery event handler and chain it to our typeahead declaration. the event will pass the callback function the element and the selected datum (generated from the engine).

For the feature service layers we have set the datum to include the objectId (see the filter function in the bloodhound engine definition). This allows us to fetch the feature along with its’ geometry via another ajax call. We can then get attributes, zoom to it, make another call to get more info, whatever you want. In this sample we simply zoom to it and put a text label displaying the name right on the map.

For the geocoder a name and ‘magicKey’ are defined in the datum which allows us to call back to the service to retrieve the feature via a call to the find REST end point. For this one we simply zoom to the extent returned. Here’s the whole event handler:

That’s it, complete autocomplete.

You have an incredible amount of control over display via css as well. Here is what I’ve used in the sample app:

There are many more options available to you in this solution so please review the documentation for further info. I am very impressed with the flexibility of typeahead so if this setup doesn’t quite work for you I suspect there are ways to get it going.

BTW, If you are using esri-leaflet you can use the great geocoder plugin that also allows you to search via a geocoder service as well as map and feature services like we’re doing here.

Finally a shout out to Bryan McBride for his excellent mapping template, bootleaf, that I used as a starter for this solution.

The whole project is in a github repo here

And you can see it in action here



Many of the desktop GIS paradigms have unfortunately made their way to the web. Second only to the ‘Identify’ tool in popularity, the checkbox for toggling layers is still the most common way to turn map layers on and off. While I appreciate the simplicity it just doesn’t seem all that, well, elegant. And now that skeuomorphism is out and flat design is here to stay, the good ole checkbox might just be going the way of

This doesn’t hurt my feelings but it does leave some interesting voids and presents lots of possibilities.

Here’s my first departure from the old paradigm that I’m using pretty regularly. A sized
< div > floating directly over the map with some roundy edges and applying slight transparency. Position these togglable layer elements in a corner or off to the side and they work pretty well.
dual purpose layer toggler and legend

Set the css hover to cursor: pointer and change the background color and it becomes obvious that you can interact with it. Adding an icon can be used to invite users and indicate what it does. This allows you to maximize space by using the element for both togglability and as a legend. Moving the element into the background by lightening the background color, removing the border and changing the icon indicates its in-visibility. Conversely, applying a solid border, increasing opacity and swapping icons give the visual cue that this thing is live.

the css:

Wire up a click event for each togglable-layer element to toggle the visibility of the layer on the map and also to toggle css classes that visually indicate the visibility state of that layer.

the js:

You can see this in action,
demo of togglable layers
using recreation sites at Wenatchee National Forest

Source of demo on github.

I realize that there is a growing contingency of ‘no GIS’ proponents who would do away with the concept of turning layers of data on and off and, in some contexts, I agree. But there are many use cases where this can be extremely powerful and, if done well, dare I say, elegant.


Updated geoconverter: { geoJson } <> { arcJson }

I put together a simple geo-converter a while back (and posted about it) that converts geojson to arcjson\esrijson. I needed it to get some polygons in an arcgis feature service. I have updated that converter to also convert from arcjson to geojson as well. I used it to pull arcjson from an ArcGIS Feature Service via a query against the REST API and convert the results to geojson.

The geoconverter tool


I pulled the arcjson formatted data from City of Fort Collins ArcGIS web services

A query against the Neighborhoods layer, like so:{%22xmin%22%3a-122%2c%22ymin%22%3a40%2c%22xmax%22%3a-80%2c%22ymax%22%3a50%2c%22spatialReference%22%3a{%22wkid%22%3a4326}}&inSR=4326&spatialRel=esriSpatialRelIntersects&where=%28HOODDESC+IS+NOT+NULL%29&outSR=4326&outFields=*&f=json

Results into the geoconverter


Created a MapBox map with it


And here’s some geojson to try out, Major League Baseball Stadiums
raw data

Play ball!


geoJson > arcJson

So I put together a dead simple interface to convert geojson to arcjson using the esri geojson utils repo on github. I also threw in a feature to view it on a map, but its spotty…

source available

It truly is a wrapper around geojson utils.

Include, create, use

I ended up doing this for a few reasons: I wanted to try out the awesome geoJson creation and editing tool by And I also wanted to play with the new Boostrap 3 flatness, a significant departure from the old version in both workings and looks.

The idea hit me when I found myself in need of a course polygon dataset representing world regions and I wanted to be able to publish them to a map service for use in an ArcGIS Javascript API application. It was super simple to create the handful of regions I needed with and I ended up with geoJson polygons in just a few minutes. I then needed to get them into an ArcGIS feature service. Uh oh, although it’s looking increasingly imminent, geoJson is not supported in the ArcGIS world currently. So here we are.

The new allowed me to quickly create and publish a new feature service to contain the new data. I just copied the output from, pasted it into a text box, hit the button and I had arcJson. Another copy and paste to get it into the feature service rest endpoint, addFeatures and I had my regions in my map service.

A note that if you need the same workflow you need to ‘unwrap’ the output arcjson into just the array of features i.e. remove the outter ‘features’ object before pasting into an addFeatures end point. Peel off this bit here and the very last curly too:



Definitely ‘innovation time’ as this is just a bridge across the open water until esri provides full support for geojson. Let me know if you find it useful.

naip wms|mapbox

naip wms | mapbox satellite

On Tuesday MapBox announced the release of its new Satellite layer based, partially, on NAIP imagery in the US. So I said I’d like to test it for speed against the NAIP Web Map Service (WMS) hosted by USGS National Map I’m currently using.

I was initially planning to do some benchmarking on tile load speed etc but really, it just isn’t necessary. One zoom or pan of each will tell you that MapBox is faster, hands down. So since what I do is highly visual, and because it’s a helluvah lot more fun, I simply dropped the two maps side by side and wired up some events such that, as one side is panned or zoomed, the other is set to the same resulting extent. Some flying around in either map will indeed confirm the hypothesis that MapBox is faster. But this didn’t turn out to be the most interesting part really. You can see that the quality is higher with higher contrast and crispy colors on the MapBox side. I did not alter saturation, hues etc of the imagery but simply left the default. Lots of interesting experimentation to be done there too.

Take a look for yourself and you’ll see which is faster. You will likely also discover more interesting comparisons.

Pro tip: go full screen (F11 in Firefox and Chrome)

Hat tip: And it’s centered on DC by default, for @cageyjames  – I get it, I used to be west coast.

So if you’re looking for hard data on tile loading speeds, sorry, I’ve got no numbers. I’m sure I could rig some JavaScript to test the loading speeds and gather number of tiles loaded etc., but this setup doesn’t lend itself to rigorous, fair testing for a few reasons anyway.

  1. There isn’t a map event in Leaflet that fires when all tiles are loaded (didn’t consider using anything else)
  2. Map events are wired such that a slight advantage is given to the target map
  3. MapBox Satellite also has roads and labels so a bit more load (handicap, like bowling)

arcgis fulcrum add in

In researching the fulcrum API for potential use in a project I thought I’d push it a bit further and ended up building a tool to import fulcrum data into ArcGIS. This happens, sometimes for the good and sometimes for an exercise in clicking. This time for the good as I ultimately created a couple of useful things:

1. a c# wrapper that turns fulcrum apps and records into usable .net objects

2. an ArcGIS add-in that imports all records from a selected app into a new feature class

The wrapper turns fulcrum api json responses into c# dictionaries and lists via the JavaScriptSerializer class and creates instances of custom fulcrumrecord and fulcrumform objects. This went pretty smoothly because the fulcrum api is both documented and well thought out.

I then used this wrapper to build an ArcGIS (ArcMap) add-in that imports all records from a selected app into a new file geodatabase feature class and adds it as a layer to the current map document. This is implemented via a separate class that digs into the depths of the ArcObjects model to create the feature class and populate it. If you’re familiar with ArcObjects this should look pretty familiar, if you are not, you might want to shield your eyes.

The code is available on github and you can find it here:

You can also just grab the .esriAddIn file from here and install it:

(BSD license disclaimer applies, truly alpha at this point)

Use is pretty straight forward, first you need to get your fulcrum api key from your profile, then sign in. Then you’ll want to either create a new file geodatabase or determine which one you’d like to use. Both of these go in the Settings (gears on fulcrum add-in toolbar)


The import is a read-only snapshot of the current records in the selected app. This can obviously be extended any way you like but, as-is, the feature class created is static.

Initially I added a setting to define the folder where photos were to be located and  the (first) photo for each record was downloaded to that location. The feature class then contained the full file path to the photo. I quickly realized that this could take a very long time depending on how many recordsphotos there are. So I altered it to populate a field with the link to the photo on the fulcrum site. However, there is also a branch of the git source that contains the original functionality to define a location and download the photo to disk.

Currently only the first photo is linked todownloaded. This could be handled by creating a separate, related stand alone table to hold links to multiple photos linked via the record id.

Recursion needs to be implemented in a couple of places to fully support the fulcrum data model. Most notably in the Section element type; the application currently ignores sections. But there can be an infinite number of nested sections that contain child elements.

It’s worth a mention that, if you’re looking for a COTS solution, Arc2EarthSync (beta)  now includes fulcrum as a provider that acts to keep fulcrum data up to date. I understand there are also plans to make it bi-directional.

4 Elements of a Fair and Viable RecruiterFreelancer Business Model

After a recent spate of contacts by recruiters via LinkedIn and exchanges on twitter (which included Bill Dollins referring to recruiters on LinkedIn as the new travel agents), I started thinking about my past experience with recruiters as a freelancer and how it might actually work, fairly, for both parties. I rely heavily on network and reputation for most of my business but, I’ll be honest, that makes for a hell of a roller coaster ride — one month, all nighters, next month, crickets. Sales and business development are not my favorite parts of freelancing so it would be great to have an on-demand sales team.

So, based on my experience, here are four key elements of a fair and profitable recruiting arrangement between recruiters and freelancers:

1. Do Not Limit Future Options
Allow for a market arrangement in which, if you provide good service, I will continue to do business with you. Do not attempt to limit future opportunities by limiting who I can work with in the future, otherwise known as a non-compete clause.

From the recruiters perspective, they want to ensure that you don’t get access to their client and then bypass them and contract with them directly, I get it. But from a freelancers perspective, you simply cannot afford to put those limits in place. An example, I have an established relationship with a City, the City had a contract with a recruiting agency and asked that I go through them for a particular project. The recruiting agency contract included a non-compete by which I couldn’t contract with the City directly, now or ever. Absolutely not, my relationship with them is completely outside of that agency. We ended up diluting it to agree that I wouldn’t work through another recruiting agency with the City for a limited period of time, fair enough, but the negotiations were painful and I wouldn’t do it again. The recruiting agency needs to understand that, as a very small business (of one), competition is tough enough without these limitations. Simply provide a good service that I will continue to use.

2. Fair Markup
Pay a fair rate for services based on market value and take a fair cut for finding the work. Recognize that, as a small business, I also have overhead and pay a fair rate for my services accordingly. In return, understanding that I am not spending timeeffortresources on securing work, I will lower my rate accordingly. Further, if a significant amount of work is available, there is room for negotiation. However, offering me forty while you take one fifty is egregious. I’m not kidding you when I say that some of my best friends are recruiters, okay, one, and his mantra is ‘if you’re getting the rate that you want then why care how much the agency is billing for you’, fair, mostly… but forty ain’t that number. And that example is typical.

3. Let 1099 Shine
Provide a 1099 tax arrangement. In the recruiting biz there is a key distinction regarding your relationship with them; 1099 or W2. Simply put 1099 means you’re responsible for your own taxes etc, W2 means you are an employee. Freelancers want 1099, otherwise, well, you’re not a freelancer. I don’t think I need to go into why you wouldn’t want to be an employee as a freelancer, after all, it’s why we’re freelancers in the first place right?

4. No Branding
Allow me to maintain my identity as a business. Do not try to take credit for my skillsreputationexperience. This may seem innocuous but it can bite you before you realize it. A simple example, a recruiting agency takes your resumecvstatement of qualifications and pastes it into their letterhead and submits it to their clients. They have branded you and the more it circulates the more your own identity is diluted.

I really believe that a business model for recruiting that includes these elements is viable. If you advertise as fair to freelancers, freelancers just might *want* to work with you and spread the word. While you won’t make the killer markups, you may very well win some loyal and very talented customers.

Somebody, do this, please!

Automate Updating an ArcGIS Online Feature Service

For many of my clients purchasing and managing ArcGIS Server has been out of the question based on limited IT and GIS resources. So for years I’ve been testing hosted services that would allow them to get maps out to their customers via the web. None of them allowed for timely data updates to ever changing data however. So naturally when ArcGIS Online rolled out I had to take it for a spin to see how it might work.

My goal is to publish a map service to ArcGIS Online once and be able to update it through a simple console application that could be launched at some interval (hourly, daily, weekly).

Here’s what I did:
Publish the feature service via ArcGIS Desktop 10.1
Once you have an ArcGIS Online account and ArcGIS Desktop 10.1 installed it’s easy peasy to publish a feature service.  (how to)

Create an ArcGIS JavaScript web application for testing
In order to mimic a real world scenario as best I could (for a geo dev anyway) I created a fairly simple web map that shows recreation sites on top of a topo base map. Clicking on the map then displays that general area in a floating box with an aerial base and info about a rec site as the title if one is within clicked range. Simple (yet I have spent far too much time just browsing it).  I’ll be honest, that was the fun part. The feature service is obviously also available directly in an ArcGIS Online map.

Develop the .Net console application to update the feature service data from a local source
My console app is using the ArcObjects .Net SDK to access a feature class within a file geodatabase to mimic my clients’ typical GIS infrastructure. This requires an ArcGIS license of any flavor to be available from the running server. This could just as easily be any format you like however since all we’re really doing is building JSON objects to pass directly to the ArcGIS Spatial Data Server REST API.

I used brute force in deleting all features and then adding them all back but I could imagine something a bit more elegant. I also noticed in Fiddler that ArcGIS Online uses the applyEdits method for any edit operation (delete, add, update). applyEdits also allows you to cancel the entire request if anything fails. But I’m going for simplicity here.

Here’s the C# code that works to make these updates:

You can also find the source project on github

There’s lots of room for improvement here such as serializing the json and handling the updates more elegantly but this is a working example of how you might keep a hosted map service on ArcGIS Online updated.

I’m guessing there are use cases I hadn’t thought of and would love to hear them.