A Map Shaper

My new favorite GeoJSON editor that just enabled me to have another layer in a Power BI Azure map (and make it look how I want) without going through a lot of hoops.

https://mapshaper.org/

This one is nice too, but you can't add attributes for all points all at once.

https://geojson.io/

Healthcare GIS Learns to Lie with Maps

Since the COVID-19 lock down began in earnest roughly five weeks ago, healthcare authorities and the news media have repeatedly failed to help society protect itself.

News has been grim. Indeed, you would think there is nothing else going on in the world. The statistics continually made available paint a picture of almost certain doom. All of the social media realms wallow in it, further perpetuating the surrounding negativity, hyping that which is not hype-worthy, based on incomplete or poorly presented information.

Consequently, I contend that what we are reading everywhere most certainly qualifies as “fake news.”

Organizations involved from the Centers for Disease Control and Prevention (CDC) to The New York Times to Google to Johns Hopkins are leveraging lessons from the same manual by Mark Monmonier, “How to Lie with Maps”.

The spatial data community should be most ashamed of itself for enabling the situation. Those in the industry have allowed themselves to be manipulated by healthcare authorities and the news media, thereby crippling their ability to seize the moment and show off real Spatial Information capability.

Review the following maps and ask yourself one simple question. What does this tell me about my community? Think local, not global.  Note that all maps were captured at the time of this writing on April 16, 2020

 World Health Organization Coronavirus Map

 Google Coronavirus Map

 Johns Hopkins Coronavirus Map

New York Times Coronavirus Map

Centers for Disease Control and Prevention Map

Attempting to discover how many cases there are in my little community of about 30,000 people, I was unable to uncover any data at all.

County level data is all that is seemingly available, and it is no help. For anyone in a similar situation it paints a bleak picture, but perhaps that is the intent of these organizations.

My county covers over 400 square miles (1059 square km). It is about 50% rural/urban. One could easily draw a line between the two areas on a map. Currently, there are 128 cases, and I would hazard a guess that 95% of them are confined to the urban complex.

San Bernardino County, California — Google Maps — April 2020

San Bernardino County, California is the largest county in the United States, covering just over 20,000 square miles (51,936 square km). A very small portion of this area is urban, and I mean very small. They have 996 confirmed cases in that county. Even the sand dunes in the Mojave Desert are not safe.

Coconino County, Arizona — Google Maps — April 2020

Coconino County, Arizona is the second largest in the United States, covering 18,661 square miles (48,330 square km). They have 299 cases. Where are they in that massive county area? I suspect Flagstaff, the largest urban area, which consumes a mere 66 square miles (171 square km).

The list goes on. Comparisons could be made around the world. Identifying and analyzing county-equivalents in other countries is more of a task than necessary to make the point though.

Healthcare authorities across the country, in concert with the CDC and local governments, with full support of the news media, and plenty of backing hype from social media, seem to be taking pains to hide data. It appears that they desperately want everyone to believe that the world is facing the greatest pandemic since The Black Death of the 14th Century.

We need these organizations to help us help them.

If the true goal is to stop the spread and ensure the safety of every individual, then give citizens the data to do that. We do not need an App tracking each other. Report data in the most relevant format to individuals. Most are smart enough to know exactly what to do to avoid danger.

People need to know where cases are, specifically. County by county is wholly insufficient. Data should be displayed city by city, and in cases such as New York City or Los Angeles, we need to know borough by borough. (New York has actually begun to do that, finally.)

This method of aiding social-distancing worked well during the plagues of Europe. If one knew a town was riddled with the plague, they simply did not go there or did so at their own risk.

The world has suffered enough at the hands of misinformation in this age of technology and “big data.” It is time for governments and news organizations to quit lying with maps, and this is the best time and place to start. We need those with the data to be more honest with that data and share it, just as they ask us to share ours.

Let’s do this right for a change. Stop trying to scare everyone!

. . .

In case of curiosity, my background is in Geography, Cartography, Spatial Analysis, and Geographic Information Systems Architecture, forever with a mind towards the lessons taught by the Mark Monmonier in that one simple book, “How to Lie with Maps”

Map and App for State Parks

State Parks are a great way to spend a day getting back to nature, and many folks enjoy visiting these spaces on a regular basis to re-align their thoughts through fishing, hunting, hiking, or the variety of other activities available. Like the National Park system, they are spaces preserved and protected for the benefit of current and future generations.

It is relatively easy to find a State Park these days, with the plethora of information available at our fingertips. One can easily access a web site for their area and discover available options near through a map displaying the location of all of the parks in the state, or a listing of sorts, sometimes with an ability to filter by activity.

All of this is very helpful in finding a park suited to a particular need but can be equally confusing in some situations. Meaningless regional divisions on maps, incomplete listings, or excess detail create unnecessary confusion.

Those seeking a more holistic view of the situation, living on the border of multiple states or traveling across the country, often find themselves entangled in multiple web sites.

It is truly unfortunate too, since all of the state's host some fantastic parks containing truly extraordinary geographic and historical features. It is surprising that unlike the National Park system, there is not one map source for locating a nearby State Park anywhere in the United States. Equally surprising, there is no data set readily available to define such a map.

Leveraging information from individual State Park web sites and verifying much of that against locations already present within Google Maps, resulted in the following web map. Limitations with Google My Maps application required division of the data into generally recognizable layers, but the map displays the location of all State Parks in the country.

Add the map to your saved maps in Google Maps and take it with you anywhere!

As with any digital map, do not just follow along blindly. The generalized park locations may or may not lead you directly to the entrance of the associated park. Always double check with the State authority to ensure the exact location of the park, accessibility, and suitability to need.

Alaska remains incomplete. Their web site does not provide a wealth of information about the location of their State Parks, and Google has very few of them plotted. Completing that state will likely require more time than it took to create the entire map.

. . .

State Parks additions occur continually and maintenance of this data necessary, to ensure the map remains a valuable tool. If you are interested in collaborating on this, send a note. It would be great to have someone from every state join in keeping their state updated and accurate.

Google My Maps as GIS Alternative

Image borrowed from Lifehacker.com

Location data collection and display functionality available through the Google product “My Maps,” from an original presentation.

Intended primarily for personal use, Google My Maps is the perfect low budget, location data collection and display option; or, a great alternative method for logging location data in a pinch.

. . .

In the realm of Geographic Information Systems (GIS), most experts would have folks believe there is only one solution that can meet their needs, regardless of the size of an organization. The platform typically proposed is undoubtedly the industry leader; however, it is not usually the best budgetary fit for all organizations. Indeed, it is often comparable to deploying a crane to lift a toothpick.

Misinformation and aggressive marketing by those involved with the traditional platform has created real problems in the GIS industry. The burdensome cost of the solution often delays development of geographic data sets and applications within small organizations with limited budgets.

Those that can afford the traditional approach quickly find themselves entangled in high-cost maintenance of a platform that is again, often times, more than they will ever need. Some abandon the situation completely, or simply resign themselves to the cost of a technology they do not understand, and never realize the potential of GIS for their organization.

Compounding the problem, some schools and universities remain equally unfamiliar with GIS. They lean heavily on the traditional platform, and in some instances, teach the platform itself as GIS, which is equivalent to teaching Microsoft as Personal Computing. Consequently, a good portion of staffing in the GIS industry is oblivious to other more appropriate solutions, costing an organization even money over the long term.

Alternatives exist.

This presentation explores one relatively little-known solution with huge potential for any organization considering a GIS implementation. The Google product “My Maps” is not a full Enterprise GIS solution. However, it does enable organizations with extremely limited budgets to collect and compile data, display associated maps in their web space, and easily share data with other organizations. It can also help begin the process of moving towards a traditional platform. As well, for personal use, it can be a lot of fun just creating your own maps and sharing them around.

Getting started is relatively easy. Just access the Google Play Store, or iTunes, depending upon your device. This discussion focuses on the Android version of the App, though I suspect there are few differences between the two platforms. As well, the application is freely available through the web browser, where it offers enhanced functionality. I will get back to that in a minute though.

After installing the App to a device, and opening the same, a screen displays showing all previous maps created. If none have yet been created, there is a prompt to create a new map. Tapping the “+” starts the process of creating a new map.

The first step in the process is to give the map a title and description; both optional and can be changed later. Tapping OK accepts the title and description and opens the new map.

The typical Google Maps display renders with its title at the bottom of the screen. One can tap the title to change the description, add an additional layer, or change the base map to one of three options (Plain, Satellite, or Terrain). Additional base maps are available within the web browser version of the application.

There are three methods of adding location data to the map. Tap the search box and type in the desired location. Any matches to the search criteria display, and selecting the best match offers the opportunity to “Add to Map.” One can also simply tap the “+” and select to “Add a New Point” or “Add a New Line.”

There are two means of adding points or lines. After tapping the “+” symbol, and selecting to add a Point, a marker symbol appears at the center of whatever position the map is currently focused.

One can adjust the marker location by tapping the crosshair symbol to immediately jump to their GPS position or slide the map in any direction to reposition the location of the marker. Once repositioned, an option appears at the bottom to “Select this location.”

Adding a line is similar. After selecting to “Add a New Line,” tap the “+” to begin the line, and then slide the map in the desired location to stretch out the line. Tap the “+” to add a point on the line and then repeat until the line is complete. To finish the line drawing, tap the check mark at the top left of the display to accept the drawing. Modify any of the points or cancel the drawing entirely using the arrow buttons and “x” button at the bottom of the display.

Note that Google Maps information is included when adding Points to the map. It is removable, and automatically, if/when exported to KML/KMZ.

Confirming addition of the Point or Line, a screen displays offering an opportunity to select the layer it the feature should be included in, and update any pre-defined attributes. Default attributes are Name and Description.

When one completes adding map features, immediate distribution of the map, publicly or privately, to anyone, anywhere is easy. Tap the symbol for sharing “<” and share a link to the map via SMS/MMS (text message), eMail, or any Social Media application installed on the device.

As mentioned previously, one can access the same map in a desktop browser for enhanced capabilities, through MyMaps.Google.com. This is useful for establishing certain parameters prior to taking the map out into the field.

Select to “Create a New Map” at this point, or view those shared with you, recent maps viewed or just explore.

Click the 3-dot menu next to the title of the map to create a new map, copy it, open a new one, delete it, establish a default view (extent), get the code for embedding on a web site, export the map to KML (Keyhole Markup Language), or print the map.

The 3-dot menu next to each layer offers the ability to rename, delete, or open the associated data table.

The small down arrow next to Base Map enables one to choose six additional maps not available in the device application version.

When first created, two attribute fields (Name and Description) are associated with any layer defined automatically. The attribute table is searchable, and clicking the down arrow next to the name of any attribute title enables one to modify the table to their needs. Sorting the data is not permanent, but any of the other options are. One can insert, duplicate, or delete fields, as well as modify any field name.

Styling each layer is only possible through the browser version. Simply click “Individual Styles” to group the display marker individually, uniformly, sequentially, or by attribute. One can also chose which attribute to use for displaying labels, or choose to display no labels.

Defining the color of the markers is only possible through browser version too. Hover over any layer item to cause a small paint bucket icon to appear. Click that icon to choose a different color or a completely different sort of marker.

A couple of other options only available through the browser are Exporting and Embedding. Access the 3-dot menu next to the title, and choose either.

Embedding offers a dialog window with a snippet of code that one can simply copy and paste directly into the source code of their web site through an “iFrame.”

Exporting to KML is a great feature, as it enables one to use the data on another platform such as Google Earth or ArcMap. One can export the entire map and all associate layers, or each layer individually. Base Maps do not export though, only the data, and through either KML or KMZ (zipped KML), which ensures that any icons used remain with the file. An additional option enables one to “Keep data up to date with network link KML.”

Setting all of this up in advance is undoubtedly the preferred route, which is where the browser version comes in very handy. It not only enables options to define much of that already discussed, but also the option to import data from files either comma-delimited, Microsoft Excel, another KML, or GPS Exchange Format.

After clicking to Import, one can “drag and drop” the file into the dialog box that appears, or select the file to use from Google Drive, or Google Photos.

It is important to note that any file imported must have some location attribute, or it will not map. Location attribute types are Country, State, or City-State, City-State-Zip, Address-City-State-Zip, GPS coordinates, Latitude/Longitude. These attributes can either be in their own individual fields or together in one field.

A few limitations exist. Each map may only contain 10 layers, and a maximum of 10,000 features, and each layer may only contain 2,000 features. Attributes are limited to 50 per feature. As well, importing KML/KMZ files is limited to 5 MB, and 2000 rows, but up to 40 MB for other file types. Printing is high resolution (4x screen resolution).

When another receives a link to the map on their device, they do not need to have Google My Maps. The map will open in Google Maps automatically, overlaying standard Google Maps. An additional row in their menu will offer the option to toggle the map on or off.

The creator of the map can access the map through “Your Places” within Google Maps. All maps created through Google My Maps will appear under that heading.

Access to editing is only possible with appropriate permissions established, and only through Google My Maps.

In this example, the map appears embedded in the online magazine journal Geographica, which displays the location of stories associated with the magazine. Clicking a location causes a sidebar to slide out and display associated attributes, in this case a photo, the name of the story, a link to the story, and associated Google Maps information.

Google Maps information is included when adding Points to the map, can be removed, and are automatically removed if exported to KML/KMZ.

In this example, I quickly generated a map for use by the GIS Certification Institute, using nothing more than a Microsoft Excel spreadsheet of data obtained from the PSI Testing Centers web site. It performs similar to that in the previous example.

Lots of folks are doing a variety of one-off maps for any number of purposes. In the browser, when first accessing Google My Maps, a row of tabs at the top of the screen offers the ability to explore some of them. Below are just a few that others have done.

Platte County Parks & Recreation — I showed these folks the potential for this little application, and they have been using it to display park locations and trails for a few years now. It is the only solution they need right now or liklely, can afford.

Google I/O 2016 — Shoreline Amphitheatre — for their annual conference.

Busiek State Forest and Wildlife Area — by OzarksWalkAbout.com

South Padre Island Fishing — by TexasFishingMaps.com

A few that I have done…

Arkansas Waterfalls by GPS — map created from published GPS positions, site visits, and other random data discoveries.

National Parks Map — data originally imported to ArcMap, from a National Park Service data set, then exported to KML, and then imported.

US Farmers Markets — created from USDA spreadsheet data, and imported.

US On-Farm Markets Map — created from USDA spreadsheet data, and imported.

KC Area Historic Places — data exported from Wikipedia, then imported.

Weston Bend State Park Harbst Trail — a hiking path captured in My Tracks and imported.

Avery Badgerland — polygons (only possible in the browser) drawn, based on County Assessor data.

Feel free to ask any questions in the comment section below or visit Google My Maps Help Center for more detailed information.

PLSS Research & Data Restructuring - Restoring a County GIS (Part 6)

Map of the Public Land Survey System - US Dept of the Interior, Bureau of Land Management

The next phase in restructuring the County data towards dependency on a more solid framework of geographic data consisted of building out the Public Land Survey (PLSS) layer. As noted in the previous chapter, the essential part of this work consisted of collecting Ground Control Points and Registered Land Corners for addition to their own respective layers.

Assembling all of the point data related to the Land Corners layer, numerous inconsistencies were noted, which required further investigation to understand their relevance to the situation.

Section corners appeared to have multiple locations along the eastern edge of the county, as well as along old Kansas City boundaries. Additionally, limited availability of data related to the boundaries along the river created challenges on that front, requiring in depth research to understand all of these issues and their relationship to one another.

. . .

Downloading the PLSS layer from the Missouri Spatial Data Information Service (MSDIS) answered a few questions, but begged clarification on others. Partial sections adorned the eastern boundary of the County, and of the same Township/Range/Section as those adjacent in Clay County. What caused this?

The part of the County along the Missouri River valley had its own set of problems too. Some of the Township/Range information seemed to be completely wrong. Township/Range composed of 50s/30s dominated the County, but in this part of the County, 7/20s popped up along the river. Where did these come from?

While researching these questions, I came to know University of Missouri Professor and co-author of the “Atlas of Lewis and Clark in Missouri,” Jim Harlan. He developed the PLSS layer I downloaded, was very informative, and just a lot of fun to talk with. Validating much of what I already understood, he clarified a few other points as well.

The Platte Purchase of 1836 caused the issue along the eastern boundary. I am still not quite sure that I understand why the surveyors did not just pick up where they left off when they began their survey; instead, a slight jog remains today along the Platte County Boundary, where partial Sections of that part of the Township / Range meets partial Sections from the very same Township / Range in Clay County.

A lengthy technical discussion with Mr. Harlan did not exactly clarify the reasons behind the Sections mismatch, but did help me to understand the origin and impact. He attributed most of the issue and many other discrepancies I would soon uncover to excessive drinking on the frontier survey crews. Amusingly, it only took a little bit of reading to validate those conditions.

More easily understood, the sections along the Missouri River are a simple result of nature, which slipped my mind. Survey boundaries never move. The river does, and quite often. Most of Missouri is surveyed under the 5th Principal Meridian, while Kansas was surveyed using the 6th. Since that time, the Missouri River has wandered about quite a bit, leaving bits and pieces of what some perceive as other states on both sides of the river. This is most evident along the Mississippi River, but the Missouri has its own share too.

At least two mysteries were resolved, which only left the northern boundary of the County. That turned out to be a rather simple matter really. Everything was normal. The County boundary moved a few years prior, and several surveys were available, along with extensive documentation and precise GPS positions along the entire boundary.

. . .

Following the framework identified in the previous chapter, I started construction on what would be four distinct layers. This actually took quite a bit of time, as I originally thought that I might just put it all together in one layer, but revelations associated with the Parcel Number, forced me down another path.

The Parcel Number identified the location of the land, indicating the Township/Range, the Section, the Quarter Section, as well as a couple other elements; indeed, the first 4 numbers in the set represented the legacy Map Sheet # that any parcel with that number could be found on. The second part of that number caused a little difficulty, but a little research uncovered that it was an old National Weather Service thing that has somehow found its way into the Parcel number; it covers 4 sections.

Example Parcel Number: 18–9.0–32–400–015–001.000

• 18 = Township 52 North / Range 33 W — 5th Principal Meridian
• 9.0 = Tetrasection 9.0
• 32 = Section 32
• 400 = Southeast quarter
• 015 = Block Number
• 001.000 = Lot . SubLot Number

Taking the Land Corners feature previously generated, along with the PLSS from MSDIS, I began tying corners to points. It was strictly a Section PLSS, and most of the corners on the PLSS did not move far, usually only a handful of feet in just about every direction. There were a few exceptions, and I decided it would be best to set those aside until completing more research on the specific attributes of those.

Once complete, I began developing the framework for the PLSS that would live on our system. It would be comprised of four independent layers. The current Map Sheet number already in use would carry through all layers.

The PLSSTownships defined the Township/Ranges for further division. PLSSFirstDivision was the first division of the Township/Range layer, and contained the Tetrasections. PLSSSecondDivision was the second division of the Township/Range layer, and contained the Sections. PLSSThirdDivision was the third division of the Township/Range layer, and contained the Quarter Section information.

Fields in each of the layers were named straightforward and simple, but still abbreviated. When developing these, I discovered that while you could give field names any number of characters, if you went to export any of them to a Shapefile the names were truncated. Consequently, all of the field names needed to be eight characters to provide clarity and prevent any confusion about the name.

Most of the data was numeric, or simple text. This attribute information would rarely, if ever change. The field definitions would always work, regardless of what changed though. I used Short Integer everywhere possible, as well as limiting the length of text fields. In the case of cardinal and ordinal directions, I simply created a domain (lookup table).

The layers do not contain all of the data for each of the division. They only hold that relevant to the County, which causes it to appear as if data is missing along the boundaries. There was just no need to define Sections that were not in Platte County though.

We left the boundary on the Missouri River alone. There was just no help for that. Surveys were more than 100 years old in some cases, or had never been properly located with GPS.

GPS positions identifying County boundaries on the north and east side of the County enabled us to re-define the boundary with 99% confidence. The work added hundreds of acres to County that had not been previously included or assessed, resulting in increased revenue for the County.

In the end, we only used the PLSSThirdDivision in our production environment. It had everything we needed in it. All of the other layers ended up being really for other cartographic purposes only and for analysis, and quality control. I simply made all adjustments in the PLSSThirdDivision layer, and migrated those changes up to the other layers once a month.

Building them out independently proved to be a good exercise that provided valuable insight when I started building the Subdivision framework. It helped in understanding the numerous peculiarities of working with DB2, ArcGIS, and ArcSDE, when building out new features and tables. It also provided an excellent understanding of the idiosyncrasies of the Public Land Survey System.

We decided not to involve too many parcel adjustments at this stage. There was more work to do and another framework to complete. New parcels that did not belong to subdivisions were subject to the new PLSS, and adjacent parcels adjust out of the way of them. Additionally, the individual receiving deeds in the Office of the Assessor began updating all associated parcels, where previously they had only reviewed the legal to determine location. This worked well for the remainder of my time there, and just updating as it came through resulted in updating nearly 75% of parcels in the County over 5 years.

All individual features were stored in a Feature Dataset named Public Land Survey System, along with the LandCorners and GroundControlPoints, due to their geographic relationship and dependencies.

. . .

Map displaying all layers of the grid and Land Corners

Below are links to access the four new features created in this process. Full detail on the construction of these features is further defined within the Info Sheet, containing the Metadata, for each individual feature.

. . .

PLSSTownships feature (KML)

- Info Sheet for PLSSTownship Metadata

PLSSFirstDivision feature (KML)

- Info Sheet for PLSSFirstDivision Metadata

PLSSSecondDivision feature (KML)

- Info Sheet for PLSSSecondDivision Metadata

PLSSThirdDivision feature (KML)

- Info Sheet for PLSSThirdDivision Metadata

. . .

Coming next in the series … more data restructuring, Subdivision, re-alignment, and other points of interest!

A National Parks Web Map App

Mount Julian from Lava Cliffs Overlook in Rocky Mountain National Park — July 2004

In recognition of the 100th Anniversary of the National Park Service (NPS), I decided to put together a web map displaying the location of all of the National Parks.

While their maps have improved dramatically this year, they still lack a certain usability, and I have yet to find anything on the web that fits my needs. I want to be able to see all of the parks, where they are in relation to my route, when out on the road.

The result of this effort is the web map/app below, which displays the location of all of the Visitor Centers (when there is one) of all of the public lands under the supervision of the National Park Service, as well as a few sites under the direction of other organizations. It seems there are several National Monuments and National Historic sites managed by the Bureau of Land Management (BLM), among others.

Zoom in, pan around, and click on a point and get more info. You can also open in full screen, share it along, embed it on your web site, or save it for use on your own device! Routing is only available at the device level though, but it works fantastically.

A somewhat monumental task in itself, it certainly did not start that way. Downloading the data for all of the park boundaries, I extracted points to appear at the centroid of each of the parks using ArcMap, then exported to KML and imported into Google My Maps for revision.

However, after some discussion with a Park Ranger, I realized that was going to be relatively worthless. I forgot my own purpose. Folks needed a means of navigating to a park, more often than not, to a Visitor Center. There is no data set for that, and only one way to do it.

Researching each individual park through the National Park Service web site proved a task. While each park contains a section for Visitor Centers, it tends to be blank, and very few have an address.

Shocked by the lack of information, I was even more determined. Using satellite imagery in combination with NPS Park Maps, I was able to locate all of them.

In the meantime, there have been a few additional designations, which I have added. Keeping things updated will be a challenge, but an easy enough task. Additionally, I want to add layers for other countries too. National Parks are not just a US thing.

Usability of NPS Maps

The National Park Service (NPS) has a beautiful new face for the web and its 100th Anniversary. It follows the typical web page design that everyone is copying these days, and is definitely much more user-friendly. Information is more readily available, and Search box and Main Menu are at the top and easily identified. Selecting a State provides a listing of all of the Parks in that state, and an awesome new map of the National Parks in that State, with detail for surrounding States available also.

The new map really is the best part of the new site, but it is lacking on a few points I perceive attributable to something endemic with GIS these days. Folks generally know their data very well, but do not understand much about the intended use, or they just do not understand how most folks use maps. Below are a few things I would really like to see added/changed to increase usability for the NPS maps.

Before the NPS site launched with new maps, I created a web map for National Parks to address functionality missing within the maps on their old web site, much of which remains absent in the new maps. I collected data available from NPS into Google My Maps to meet my primary needs, which include the ability to understand the general spatial relationship between the parks, calculate driving times, and discover what others might be near my route, or where the Park I will be visiting. Google has a few thing to answer for too, but I will get to that another time.

National Map is Missing

Forcing users to narrow their search by State is somewhat helpful, but falls short of usability for those of us planning road trips. It would be much more useful to have access to a map of the entire nation.

State Switching is Awkward

With a State selected, there is no simple means of switching to another State. Users must return to the Home page or understand breadcrumbs enough to click the “Find a Park” to return to select another State. There are too many steps here; perhaps a drop-down is in order. I am quite sure this is causing the page to make entirely too many service calls too.

Scroll-Wheel Zoom Unavailable

Requiring users to click “+/-“ icons for zoom in/out is awkward at best, and not exactly 508 compliant. Every online map that is worth anything permits mouse scroll-wheel zooming. Nobody wants to click any more than necessary.

Inconsistent Labeling

Clicking a Park name on the map, within the State selected, provides more information and a link to the web page associated with the Park. However, if you click a Park in another State, only the Park name displays; clicking that name takes you away to the page associated with that Park. The map should display information consistently, regardless of the State selected.

Surprise Features

Viewing Missouri and attempting to click Harry S Truman NHS presents a label for “Santa Fe National Historic Trail.” It was not immediately obvious that there was an unlabeled feature present on the map. Presenting irrelevant information to the task is not very helpful. A better experience would be to display information only for labels visible and clicked.

Mini-Map with Listing

In the listing of Parks, a static mini-map of the State where the Park is located, with a star on the location of the Park in that State would be more useful than the thumbnail picture currently displayed. As it is now, one has to scroll up and down the screen to match name to location, and not all locations are display labels on the map.

Get Directions

For Road Trippers, this is an undeniable and absolutely must-have feature. We want to know all of the National Parks along our planned route. We are planning trips from one State to another.

Unable to turn layers on/off

Multiple layers of geographic data exist within this map; primarily, Parks and Trails. Thinking about the “Surprise Features” note above, it would be helpful to be able to turn some features off, when too many converge on the same location.

Missing North Arrow

A required cartographic element for all maps recently delegated to the trash can in favor of saving space, this should never be absent from any real map.

Missing Legend

I can get past the lack of a North arrow, but the lack of Legend, when there are multiple features delineated in various colors is inexcusable. What do those colors mean? Are they simply to differentiate between the trails? What if I were color-blind?

Missing Scale Bar

This is up there with the missing Legend. Users need to be able to understand the spatial representation in front of them, and generally calculate distance between features on the map.

Missing Map Search

A search function exists for the site, but what if a user only wants to search a Park name on the map.

. . .

originally written for and publish in The UXBlog

Road Comparison in GIS Services

At the request of the GIS group in DC, under the direction and in response to GIS-440, IPUSO created a Roads data layer and associated service for use by the [US Government Agency] in GIS applications. The data is a derivative product of US Census Tigerline data. Along with the associated service, the data will require continuous maintenance, necessitating perpetual funding of technical and business resources. Simply stated, this will have a huge cost impact to ongoing operations and maintenance of GIS systems and services for the [US Government Agency].

In contrast, an alternative solution recommended by [US Government Agency] GIS Subject Matter Experts is available, which holds no associated cost. It is available through the existing contractual arrangement with GIS vendor ESRI, developed and maintained by experts in Street and Road data, and based on US Census Tigerline data. ESRI established the data and associated service under strict usability guidelines, are highly scalable and configurable, and free for use under the existing maintenance contract.

Supporting this recommendation, OCIO mandates along with other architectural guidance from GISO, and CTS OCE Program Team indicate authoritative data and existing configurable cloud services need to be investigated and leveraged prior to development of custom or duplicated solutions for GIS within the [US Government Agency].

The following pages compare and contrast the services primarily from a usability standpoint.

The [US Government Agency] service is not Tiled or Cached, and consequently sluggish. It also lacks appropriate scaling, labeling, and configuration to meet the needs of an enterprise GIS Data. In short, the service and data are mostly incomplete, incoherent, unusable, and already in need of updating.

The ESRI layer is tiled, cached, and serves up fast and with minimal calls to the server. The service is complete, coherent, usable, and requires no updating by [US Government Agency] employees or contractors.

Note about the review platform

An inability to review the  [US Government Agency] service through ESRI ArcMap necessitated review of data services within ArcGISOnline, using a light gray canvas base map to ensure data displayed clearly as intended. Note that the light gray canvas includes roads outlined in white paths, and contain minimal labeling, as shown in the example immediately below; otherwise, roads do not appear, except as designed in the layer.

Entire US View

[US Government Agency] displays no roads at all

[US Government Agency] displays no roads at all

ESRI Layer displays major interstates with orange lines only

Regional View

[US Government Agency] layers shows no roads

ESRI layer shows interstates in orange, along with appropriate and universally understood labeling.

State-level View

[US Government Agency] shows no roads

ESRI layer shows interstates in orange with appropriate and universally understood labeling, along with major highways, also labeled and shown in light orange.

City-level View

[US Government Agency] layer shows red lines for interstates, but no labeling.  Roads also appear disconnected and incomplete.

ESRI layer shows all major roads, highways, and interstates.  Labeling is mostly clear and consistent with understood cartographic design, scaling appropriately.

City-zoom View

[US Government Agency] layers displays hard black lines for all roads, which are not labeled, and red lines for interstates, with incorrect label formatting.

ESRI layer shows all major roads and thoroughfares, interstates, and highways, as well as water-crossing routes; labeling is consistent, readable, and scales appropriately.

City Neighborhood View

[US Government Agency] layer displays hard black lines for roads and hard black typography for road names. It is easy to read on a Gray Canvas background, but impossible to read when overlaying aerial imagery.

ESRI layer at this scale reverts to labeling only, relying upon existing features on the ground. Labeling is only slightly difficult to read on a Light Gray canvas, but easily read when overlaying aerial imagery.

City Neighborhood View with Aerial Imagery

[US Government Agency] showing as indistinguishable overlying imagery

ESRI layer showing readability overlying imagery

Step Scale of [US Government Agency] over imagery, beginning with the entire United States

For the [US Government Agency] Service there is no means of visually identifying road location at any of the following scales.

At the following scale, within the [US Government Agency] Service, a single red line appears requiring further identification of the feature to determine that it is part of the US Interstate system.

For the [US Government Agency] Service there is no means of visually identifying road location at the following scale.

At the following scale, within the [US Government Agency] Service, hard black lines appear, requiring further identification of the features to determine that they represent specific roads.

At the following scale, within the [US Government Agency] Service, hard black lines appear, requiring further identification of the features to determine that they represent specific roads.

At the following scale, within the [US Government Agency] Service, hard black lines appear, requiring further identification of the features to determine that they represent specific roads.

At the following scale, within the [US Government Agency] Service, hard black lines appear along with simple black labeling identifying the roads.

At the following scale, within the [US Government Agency] Service, hard black lines appear along with simple black labeling identifying the roads.

Step Scale of ESRI Service over imagery, beginning with the entire United States

For the ESRI Service, major interstates appear without labeling at the following scale.

For the ESRI Service, major interstates appear without labeling at this scale.

For the ESRI Service, major interstates appear with labeling at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, as well as major roadways also labeled, at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, as well as major roadways also labeled, at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, as well as major roadways also labeled, at this scale.

For the ESRI Service, all interstates appear with labeling, along with major US highways and their labels, as well as major roadways also labeled, at this scale.

For the ESRI Service, interstates, highways and roads are not represented by lines, but display labeling instead.

For the ESRI Service, interstates, highways and roads are not represented by lines, but display labeling instead.

For the ESRI Service, interstates, highways and roads are not represented by lines, but display labeling instead.