Archive for the ‘Maps’ Category

Going My Way? – Explore 1.2 billion taxi rides

Friday, September 30th, 2016

Explore 1.2 billion taxi rides by Hannah Judge.

From the post:

Last year the New York City Taxi and Limousine Commission released a massive dataset of pickup and dropoff locations, times, payment types, and other attributes for 1.2 billion trips between 2009 and 2015. The dataset is a model for municipal open data, a tool for transportation planners, and a benchmark for database and visualization platforms looking to test their mettle.

MapD, a GPU-powered database that uses Mapbox for its visualization layer, made it possible to quickly and easily interact with the data. Mapbox enables MapD to display the entire results set on an interactive map. That map powers MapD’s dynamic dashboard, updating the data as you zoom and pan across New York.

Very impressive demonstration of the capabilities of MapD!

Imagine how you can visualize data from your hundreds of users geo-spotting security forces with their smartphones.

Or visualizing data from security forces tracking your citizens.

Technology cuts both ways.

The question is whether the sharper technology sword is going to be in your hands or those of your opponents?

How Mapmakers Make Mountains Rise Off the Page

Saturday, September 17th, 2016

How Mapmakers Make Mountains Rise Off the Page by Greg Miller.

From the post:

The world’s most beautiful places are rarely flat. From the soaring peaks of the Himalaya to the vast chasm of the Grand Canyon, many of the most stunning sites on Earth extend in all three dimensions. This poses a problem for mapmakers, who typically only have two dimensions to work with.

Fortunately, cartographers have some clever techniques for creating the illusion of depth, many of them developed by trial and error in the days before computers. The best examples of this work use a combination of art and science to evoke a sense of standing on a mountain peak or looking out an airplane window.

One of the oldest surviving maps, scratched onto an earthenware plate in Mesopotamia more than 4,000 years ago, depicts mountains as a series of little domes. It’s an effective symbol, still used today in schoolchildren’s drawings and a smartphone emoji, but it’s hardly an accurate representation of terrain. Over the subsequent centuries, mapmakers made mostly subtle improvements, varying the size and shape of their mountains, for example, to indicate that some were bigger than others.

But cartography became much more sophisticated during the Renaissance. Topographic surveys were done for the first time with compasses, measuring chains, and other instruments, resulting in accurate measurements of height. And mapmakers developed new methods for depicting terrain. One method, called hachuring, used lines to indicate the direction and steepness of a slope. You can see a later example of this in the 1807 map below of the Mexican volcano Pico de Orizaba. Cartographers today refer (somewhat dismissively) to mountains depicted this way as “woolly caterpillars.”

Stunning illusions of depth on maps, creating depth illusions in 2 dimensions (think computer monitors), history of map making techniques, are all reasons to read this post.

What seals it for me is that the quest for the “best” depth illusion continues. It’s not a “solved” problem. (No spoiler, see the post.)

Physical topography to one side, how are you going to bring “depth” to your topic map?

Some resources in a topic map may have great depth and others, unfortunately, may be like Wikipedia articles marked as:

This article has multiple issues.

How do you define and then enable navigation of your topic maps?

Persuasive Cartography

Monday, September 12th, 2016

Vintage Infodesign [161]: More examples of persuasive cartography, diagrams and charts from before 1960 by Tiago Veloso.

From the post:

A recurrent topic here on Vintage InfoDesign is “persuasive cartography” – the use of maps to influence and in many cases, deceive. We showcased examples of these maps here and here, with a special mention to the PJ Mode Collection at Cornell University Library. The collection was donated to Cornell back in 2014, and until now more than 300 examples are available online in high resolution.

A must for all of those interested in the subject, and we picked a few examples to open this post, courtesy of Allison Meier, who published a rente article about the PJ Mode Collection over at Hyperallergic.


Re-reading The Power of Maps (1992) by Denis Wood, in preparation to read Rethinking The Power of Maps (2010), also by Denis Wood, has made me acutely aware of aspersions such as:

“persuasive cartography” – the use of maps to influence and in many cases, deceive.

I say “aspersion” because Wood makes the case that all maps, with no exceptions, are the results of omissions, characterizations, enhancements, emphasis on some features and not others, for stated and/or unstated purposes.

Indeed, all of The Power of Maps (1992) is devoted to teasing out, with copious examples, where a user of a map may fail to recognize the “truth” of any map, is a social construct in a context shaped by factors known and unknown.

I characterize maps I disagree with as being deceptive, disingenuous, inaccurate, etc., but doesn’t take away from Wood’s central point that all maps are acts of persuasion.

The critical question being: Do you support the persuasion a map is attempting to make?

When I teach topic maps again I will make The Power of Maps (1992) required reading.

It is an important lesson to realize that any map, even a topic map, need only map so much of the territory or domain, as is sufficient for the task at hand.

A topic maps for nuclear physics won’t have much in common with one for war criminals of the George W. Bush and Barack Obama administrations.

Moreover, even topic maps of the same subject domain, may or may not merge in a meaningful way.

The idea of useful merger of arbitrary topic maps, like the idea of “objective maps,” is a false one that serves no useful purpose.

Say rather that topic maps can make enough information explicit about subjects to determine if merging will be meaningful to one or more users of a topic map. That alone is quite a feat.

Mapping U.S. wildfire data from public feeds

Monday, August 29th, 2016

Mapping U.S. wildfire data from public feeds by David Clark.

From the post:

With the Mapbox Datasets API, you can create data-based maps that continuously update. As new data arrives, you can push incremental changes to your datasets, then update connected tilesets or use the data directly in a map.

U.S. wildfires have been in the news this summer, as they are every summer, so I set out to create an automatically updating wildfire map.

An excellent example of using public data feeds to create a resource not otherwise available.

Historical fire data can be found at: Federal Wildland Fire Occurrence Data, spanning 1980 through 2015.

The Outlooks page of the National Interagency Coordination Center provides four month (from current month) outlook and weekly outlook fire potential reports and maps.

Restricted U.S. Army Geospatial Intelligence Handbook

Friday, August 26th, 2016

Restricted U.S. Army Geospatial Intelligence Handbook

From the webpage:

This training circular provides GEOINT guidance for commanders, staffs, trainers, engineers, and military intelligence personnel at all echelons. It forms the foundation for GEOINT doctrine development. It also serves as a reference for personnel who are developing doctrine; tactics, techniques, and procedures; materiel and force structure; and institutional and unit training for intelligence operations.

1-1. Geospatial intelligence is the exploitation and analysis of imagery and geospatial information to describe, assess, and visually depict physical features and geographically referenced activities on the Earth. Geospatial intelligence consists of imagery, imagery intelligence, and geospatial information (10 USC 467).

Note. TC 2-22.7 further implements that GEOINT consists of any one or any combination of the following components: imagery, IMINT, or GI&S.

1-2. Imagery is the likeness or presentation of any natural or manmade feature or related object or activity, and the positional data acquired at the same time the likeness or representation was acquired, including: products produced by space-based national intelligence reconnaissance systems; and likenesses and presentations produced by satellites, aircraft platforms, unmanned aircraft vehicles, or other similar means (except that such term does not include handheld or clandestine photography taken by or on behalf of human intelligence collection organizations) (10 USC 467).

1-3. Imagery intelligence is the technical, geographic, and intelligence information derived through the interpretation or analysis of imagery and collateral materials (10 USC 467).

1-4. Geospatial information and services refers to information that identifies the geographic location and characteristics of natural or constructed features and boundaries on the Earth, including: statistical data and information derived from, among other things, remote sensing, mapping, and surveying technologies; and mapping, charting, geodetic data, and related products (10 USC 467).


You may not have the large fixed-wing assets described in this handbook, the “value-added layers” are within your reach with open data.


In localized environments, your value-added layers may be more current and useful than those produced on longer time scales.

Topic maps can support geospatial collations of information along side other views of the same data.

A great opportunity to understand how a modern military force understands and uses geospatial intelligence.

Not to mention testing your ability to recreate that geospatial intelligence without dedicated tools.

Spatial Module in OrientDB 2.2

Tuesday, August 23rd, 2016

Spatial Module in OrientDB 2.2

From the post:

In versions prior to 2.2, OrientDB had minimal support for storing and retrieving GeoSpatial data. The support was limited to a pair of coordinates (latitude, longitude) stored as double in an OrientDB class, with the possibility to create a spatial index against those 2 coordinates in order to speed up a geo spatial query. So the support was limited to Point.
In OrientDB v.2.2 we created a brand new Spatial Module with support for different types of Geometry objects stored as embedded objects in a user defined class

  • Point (OPoint)
  • Line (OLine)
  • Polygon (OPolygon)
  • MultiPoint (OMultiPoint)
  • MultiLine (OMultiline)
  • MultiPolygon (OMultiPlygon)
  • Geometry Collections

Along with those data types, the module extends OrientDB SQL with a subset of SQL-MM functions in order to support spatial data.The module only supports EPSG:4326 as Spatial Reference System. This blog post is an introduction to the OrientDB spatial Module, with some examples of its new capabilities. You can find the installation guide here.

Let’s start by loading some data into OrientDB. The dataset is about points of interest in Italy taken from here. Since the format is ShapeFile we used QGis to export the dataset in CSV format (geometry format in WKT) and import the CSV into OrientDB with the ETL in the class Points and the type geometry field is OPoint.

The enhanced spatial functions for OrientDB 2.2 reminded me of this passage in “Silences and Secrecy: The Hidden Agenda of Cartography in Early Modern Europe:”

Some of the most clear-cut cases of an increasing state concern with control and restriction of map knowledge are associated with military or strategic considerations. In Europe in the sixteenth and seventeenth centuries hardly a year passed without some war being fought. Maps were an object of military intelligence; statesmen and princes collected maps to plan, or, later, to commemorate battles; military textbooks advocated the use of maps. Strategic reasons for keeping map knowledge a secret included the need for confidentiality about the offensive and defensive operations of state armies, the wish to disguise the thrust of external colonization, and the need to stifle opposition within domestic populations when developing administrative and judicial systems as well as the more obvious need to conceal detailed knowledge about fortifications. (reprinted in: The New Nature of Maps: Essays in the History of Cartography, by J.B. Harley: Paul Laxton, John Hopkins, 2001. page 89)

I say “reminded me,” better to say increased my puzzling over the widespread access to geographic data that once upon a time had military value.

Is it the case that “ordinary maps,” maps of streets, restaurants, hotels, etc., aren’t normally imbued (merged?) with enough other information to make them “dangerous?”

If that’s true, the lack of commonly available “dangerous maps” is a disadvantage to emergency and security planners.

You can’t plan for the unknown.

Or to paraphrase Dibert: “Ignorance is not a reliable planning guide.”

How would you cure the ignorance of “ordinary” maps?

PS: While hunting for the quote, I ran across The Power of Maps by Denis Wood; with John Fels. Which has been up-dated: Rethinking the power of maps by Denis Wood; with John Fels and John Krygier. I am now re-reading the first edition and awaiting for the updated version to arrive.

Neither book is a guide to making “dangerous” maps but may awaken in you a sense of the power of maps and map making.

Eduard Imhof – Swiss Cartographer (Video)

Thursday, August 11th, 2016

Eduard Imhof – Swiss Cartographer

A tv documentary on the Swiss cartographer Eduard Imhof.

In Swiss German but this English sub-title caught my eye:

But what can be extracted again from the map is also important.

A concern that should be voiced with attractive but complex visualizations.

The production of topographical maps at differing scales is a recurring theme in the video.

How to visualize knowledge at different scales is an open question. Not to mention an important one as more data becomes available for visualization.

Imhof tells a number of amusing anecdotes, including answering the question: Which two cantons in Switzerland have the highest density of pigs?


For background:

Virtual Library Eduard Imhof

Eduard Imhof (1895-1986) was professor of cartography at the Swiss Federal Institute of Technology Zurich from 1925 – 1965. His fame far beyond the Institute of Technology was based on his school maps and atlases. In 1995 it was 100 years since his birthday. On this occasion several exhibitions celebrated his life and work, among others in Zurich, Bern, Bad Ragaz, Küsnacht/ZH, Barcelona, Karlsruhe and Berlin. The last such exhibition took place in summer 1997 in the Graphische Sammlung of the ETH. There it was possible to show a large number of maps and pictures in the original. At the conclusion of the exhibition Imhof’s family bequested his original works to the ETH-Bibliothek Zurich. Mrs. Viola Imhof, the widow of Eduard Imhof, being very much attached to his work, had a major part in making it accessible to the public.

Imhof wie ein Kartographische Rockstar

Eduard Imhof was born in Schiers on 25 Jan 1895 to the geographer Dr. Eduard Imhof and his wife Sophie.1 At the age of 19 he enrolled in ETH Zürich,2 and after several interruptions for military service, was awarded a geodesist/surveyor diploma in 1919.

He returned to ETH as an assistant to his mentor Prof. Fridolin Becker, himself a cartographic god widely viewed as the inventor of the Swiss style shaded relief map.3 In 1925, the year after Becker’s death, Imhof became an assistent professor and founded the Kartographische Institut (Institute of Cartography). Although the Institute was initially little more than a hand-painted sign above his small office, it was nevertheless the first of its kind in the world.

In 1925 he produced his first major work – the Schulkarte der Schweiz 1:500 000 (the School map of Switzerland). Over the years he would update the national school map several times as well as produce school maps for nearly half of the cantons in the Federation. He even did the school map for the Austrian Bundesländer of Vorarlberg. (footnotes omitted)

Google Deletes Palestine Or Does It?

Friday, August 5th, 2016

Have you heard that Google removed Palestine from Google Maps on 25 July 2016?

At first blush (warning, spoiler to this story coming):

Searching for Israel:


Searching for Palestine:


Do you see a label for Palestine? Despite the side border in Google Maps reporting:

The State of Palestine, also known simply as Palestine, is a de jure sovereign state in the Middle East that is recognized by 136 UN members and since 2012 has a status of a non-member observer state…

Searching further I found more discussions about Google removing Palestine from Google Maps, but with conflicting dates.

That sent me to the Internet Archive WayBack Machine where I found Google Maps for Israel as follows:







Some observations:

West Bank appears in 2010 but not thereafter.

Gaza is labeled if you search for Palestine but unlabeled if you search for Israel (first two images).

Curious, is there another state, recognized by 136 UN members that does not appear by name in Google Maps?

The coverage of Google Maps gets spotty the further back you go in the Internet Archive. Unfortunate because it is likely the only trusted witness to ever changing digital content.

On the whole, reports of Google deleting Palestine from Google Maps are false. Google never identified Palestine at all.

That’s not a defense to Google’s failure to identify Palestine but an attempt to illustrate Google’s historical failure to identify Palestine.

The History of Cartography

Wednesday, July 20th, 2016

The History of Cartography

From the webpage:

The first volume of the History of Cartography was published in 1987 and the three books that constitute Volume Two appeared over the following eleven years. In 1987 the worldwide web did not exist, and since 1998 book publishing has gone through a revolution in the production and dissemination of work. Although the large format and high quality image reproduction of the printed books (see right column) are still well-suited to the requirements for the publishing of maps, the online availability of material is a boon to scholars and map enthusiasts.

On this site the University of Chicago Press is pleased to present the first three volumes of the History of Cartography in PDF format. Navigate to the PDFs from the left column. Each chapter of each book is a single PDF. The search box on the left allows searching across the content of all the PDFs that make up the first six books.

Links to the parts, which are then divided into separate PDF files of each chapter:

Volume One: Cartography in Prehistoric, Ancient, and Medieval Europe and the Mediterranean

Volume Two: Book 1: Cartography in the Traditional Islamic and South Asian Societies

Volume Two: Book 2: Cartography in the Traditional East and Southeast Asian Societies

Volume Two: Book 3: Cartography in the Traditional African, American, Arctic, Australian, and Pacific Societies

Volume Three: Cartography in the European Renaissance, Part 1

Volume Three: Cartography in the European Renaissance, Part 2

Unless you want to index the parts for yourself, remember the search box at this site that searches across all six volumes.

This can be a real time sink, deeply educational but a time sink none the less.

RNC 2016 – Cleveland, OH (aka, “The Mistake on The Lake”)

Sunday, July 17th, 2016

The Mistake on The Lake” as a nickname for Cleveland, Ohio was new to me. I remember news of the Burning River rather clearly. Polluting a river until it can burn takes effort. An impressive amount of effort.

“The Mistake on The Lake” is also a fitting nickname for the RNC convention this week in Cleveland. Some mapping resources to help as stories develop:

RNC Homepage with schedule: Despite reports to the contrary, I don’t see Lucifer on the speaking schedule. Perhaps a late addition?

Google Maps, centered on the Quicken Loans Arena: easily switching between views, although the images are static. I assume you will update those with drone/helicopter imagery. Either your own or pirated off of others.

MapQuest: To give you a non-Google alternative.

Cuyahoga County Geographical Information Systems: Yeah, I could not have called the name of the county for Cleveland either. Lots of downloadable GIS data, including ownership, Lidar, contours (think noxious substances running away from you), etc. Plus they host interactive software if you don’t have your own GIS software.

Don’t forget geo-located tweets as an information source for real time updates on locations and events.


Mis-Direction: Possible What3Words App

Wednesday, June 15th, 2016

Take a minute to visit or my post Wrigley Field: 1060 W Addison St, Chicago, IL or digits.bucked.talent? (3-Word Addresses), or this post won’t be as useful as it could be.

In a nutshell, has created a 3 by 3 meter grid on the Earth’s surface and assigned each block a three-word name. For the convenience of people accustomed to more conventional addresses, where available, you can submit an address and get the three-word name for that block back.

Excellent potential for a project name “Mis-Direction,” that needs an innocent name as a smartphone app.

You send someone a three-word block name and when displayed on their smartphone, it maps to the “canonical” location. Anyone using your phone will get that result.

However, if when the location is displayed, without a prompt or signal, if you enter a 5-digit code, the actual location intended by the sender is revealed.

Would require a mapping table between 3-word name as sent and 3-word name as intended, and the locations have to be plausible to any third party who might be tracking the communication or using your phone.

I would suggest allowing 5 tries to get the correct number because locations for demonstrations and other activities need to be operationally secure for only a matter of hours.

After that, anyone can follow the trail of emergency vehicles to a location that was a closely held secret only hours before.

It isn’t clear if the uptake on What3Words will be broad enough to have an impact at large political gatherings in the United States this year but the same re-mapping principle with password applies to more conventional mapping techniques as well.

Wrigley Field: 1060 W Addison St, Chicago, IL or digits.bucked.talent? (3-Word Addresses)

Monday, June 13th, 2016

Elwood Blues says in The Blues Brothers that he falsified his drivers license renewal and listed:

“1060 W. Addision”

as his home address, somehow


doesn’t carry the same impact. Yes?

Mongolia has places as familiar as Wrigley Field is to Americans but starting next month, all locations in Mongolia are going to have three-word phrase addresses. Mongolia is changing all its addresses to three-word phrases by Joon Ian Wong.

From the post:

Mongolia will become a global pioneer next month, when its national post office starts referring to locations by a series of three-word phrases instead of house numbers and street names.

The new system is devised by a British startup called What3Words, which has assigned a three-word phrase to every point on the globe. The system is designed to solve the an often-ignored problem of 75% of the earth’s population, an estimated 4 billion people, who have no address for mailing purposes, making it difficult to open a bank account, get a delivery, or be reached in an emergency. In What3Words’ system, the idea is that a series of words is easier to remember than the strings of number that make up GPS coordinates. Each unique phrase corresponds to a specific 9-square-meter spot on the map.

For example, the White House, at 1600 Pennsylvania Avenue, becomes sulk.held.raves; the Tokyo Tower is located at fans.helpless.collects; and the Stade de France is at reporter.smoked.received.

Mongolians will be the first to use the system for government mail delivery, but organizations including the United Nations, courier companies, and mapping firms like Navmii already use What3Words’ system.

The most remarkable aspect of the is revealed if you try for:

Gandan Monastery (Gandantegchinlen Khiid), Gandan Monastery District, Ulaanbaatar 16040 (011 36 0354).

Use this URL:


Now try changing languages (upper-right).

Three-word phrase addresses for the Gandan Monastery:

  • picturing.backfired.riverside (English)
  • schneller.juwelen.schaffen (German)
  • aislados.grifo.acuerde (Spanish)
  • nuageux.lémurien.rejouer (French)
  • turbato.fotografate.tinozza (Italian)
  • chinelo.politicar.molhada (Portugese
  • matte.skivar.kasta (Swedish)
  • vücudu.ırmak.peşini (Turkish)
  • карьера.слог.шелка (Russian)

I have only had time to spot check the site but did find retraced.loudest.teaspoon for Yap Island in Micronesia.

More obscure places to try?

You can find a wealth of additional information, yes, including an API at:

A great opportunity for topic maps as previous ways of identifying locations are not going to wink out of existence. If 3-word addresses catch on, use of other locators may dwindle but that will be over generations. We are facing a very long transition period.

Thoughts on weaponizing 3-word addresses. First, using the wrong 3-word addresses to mis-lead agents of the state. Second, creating new 3-word addresses that can be embedded prose, song, without the dot separators.

Not to mention a server with proper authentication, returns the “correct” map location for a 3-word address, otherwise, you get the standard one.


Guide to Figuring Out the Age of an Undated World Map (xkcd)

Wednesday, June 1st, 2016

This is precious! The original.


Map for Long Term Investors in British Isles

Monday, May 16th, 2016

For any long range planners in the crowd:


How to create interactive maps with MapHub

Monday, May 16th, 2016

How to create interactive maps with MapHub by Mădălina Ciobanu.

From the post:

Maps may not be every graphics editor or reporter’s favourite way to illustrate information, particularly a more interesting dataset that can lend itself to a more creative format, but sometimes they are the best way to take your readers from point A to point B – literally.

We have written about mapping tools before, so make sure you check out the list (and stay tuned for an update!), but in the meantime this guide will show you how to create a quick interactive map using free platform MapHub, which is currently available in beta.

After you read about using MapHub, be sure to follow the link to resources on other mapping tools as well.

One quick use of maps for stories such as Congress, Maps and a Research Tale – Part 1, where public land is going to be mined in a noisy and toxic way, is to plot the physical residences of those who support the project versus those who oppose it.

I haven’t gathered that data, yet, but won’t be surprised if supporters DO NOT have the mine in their backyards.

Other examples of how distance increases political support for noxious activities?

“Library of Babel” (Jorge Luis Borges)

Wednesday, May 4th, 2016


Select the image for a larger view. Trust me, it’s worth it.

The illustration is from “Plotted: A Literary Atlas” by Andrew DeGraff and this particular image of the illustration is from the review: 9 Awesome Literary Maps Every Book Lover Needs To See by Krystie Lee Yandoli.

DeGraff has maps for portions of these works:

Adventures of Huckleberry Finn – Mark Twain

Around the World in Eighty Days – Jules Verne

A Christmas Carol – Charles Dickens

A Good Man Is Hard to Find – Flannery O’Connor

Hamlet, Prince of Denmark – William Shakespeare

Invisible Man – Ralph Ellison

The Library of Babel – Jorge Luis Borges

The Lottery – Shirley Jackson

Moby Dick, or, The Whale – Herman Melville

Narrative of the Life of Frederick Douglass, an American Slave – Frederick Douglas

A Narrow Fellow in the Grass – Emily Dickinson

The Odyssey – Homer

The Ones Who Walk Away from Omclas – Ursula K. Le Guinn

Pride and Prejudice – Jane Austen

A Report to the Academy – Franz Kafka

Robinson Crusoe – Daniel Defoe

Waiting for Godot – Samuel Beckett

Watership Down – Richard Adams

Wrinkle in Time – Madeleine L’Engle

Keep a copy of Plotted: A Literary Atlas on hand as inspiration.

At the same time, try your hand at capturing your spatial understanding of a narrative. Your reading experience, will be different.


When Mapping Fails – Big Time

Sunday, April 10th, 2016

How an internet mapping glitch turned a random Kansas farm into a digital hell by Kashmir Hill.

From the post:

An hour’s drive from Wichita, Kansas, in a little town called Potwin, there is a 360-acre piece of land with a very big problem.

The plot has been owned by the Vogelman family for more than a hundred years, though the current owner, Joyce Taylor née Vogelman, 82, now rents it out. The acreage is quiet and remote: a farm, a pasture, an old orchard, two barns, some hog shacks and a two-story house. It’s the kind of place you move to if you want to get away from it all. The nearest neighbor is a mile away, and the closest big town has just 13,000 people. It is real, rural America; in fact, it’s a two-hour drive from the exact geographical center of the United States.

But instead of being a place of respite, the people who live on Joyce Taylor’s land find themselves in a technological horror story.

For the last decade, Taylor and her renters have been visited by all kinds of mysterious trouble. They’ve been accused of being identity thieves, spammers, scammers and fraudsters. They’ve gotten visited by FBI agents, federal marshals, IRS collectors, ambulances searching for suicidal veterans, and police officers searching for runaway children. They’ve found people scrounging around in their barn. The renters have been doxxed, their names and addresses posted on the internet by vigilantes. Once, someone left a broken toilet in the driveway as a strange, indefinite threat.

All in all, the residents of the Taylor property have been treated like criminals for a decade. And until I called them this week, they had no idea why.

If you use “IP mapping,” you owe it to yourself and your customers to give Kahsmir’s story a close and careful read.

Nope, no spoilers, you have to read the story to appreciate how reasonable and good faith decisions can over time result in very bad unintended consequences.


PS: What sort of implied threat is a broken toilet? Just curious, thought you might know.

Pentagon Confirms Crowdsourcing of Map Data

Tuesday, April 5th, 2016

I have mentioned before, Tracking NSA/CIA/FBI Agents Just Got Easier, The DEA is Stalking You!, how citizens can invite federal agents to join the gold fish bowl being prepared for the average citizen.

Of course, that’s just me saying it, unless and until the Pentagon confirms the crowdsourcing of map data!

Aliya Sternstein writes
in Soldiers to Help Crowdsource Spy Maps:

“What a great idea if we can get our soldiers adding fidelity to the maps and operational picture that we already have” in Defense systems, Gordon told Nextgov. “All it requires is pushing out our product in a manner that they can add data to it against a common framework.”

Comparing mapping parties to combat support activities, she said, soldiers are deployed in some pretty remote areas where U.S. forces are not always familiar with the roads and the land, partly because they tend to change.

If troops have a base layer, “they can do basically the same things that that social party does and just drop pins and add data,” Gordon said from a meeting room at the annual Esri conference. “Think about some of the places in Africa and some of the less advantaged countries that just don’t have addresses in the way we do” in the United States.

Of course, you already realize the value of crowd-sourcing surveillance of government agents but for the c-suite crowd, confirmation from a respected source (the Pentagon) may help push your citizen surveillance proposal forward.

BTW, while looking at Army GeoData research plans (pages 228-232), I ran across this passage:

This effort integrates behavior and population dynamics research and analysis to depict the operational environment including culture, demographics, terrain, climate, and infrastructure, into geospatial frameworks. Research exploits existing open source text, leverages multi-media and cartographic materials, and investigates data collection methods to ingest geospatial data directly from the tactical edge to characterize parameters of social, cultural, and economic geography. Results of this research augment existing conventional geospatial datasets by providing the rich context of the human aspects of the operational environment, which offers a holistic understanding of the operational environment for the Warfighter. This item continues efforts from Imagery and GeoData Sciences, and Geospatial and Temporal Information Structure and Framework and complements the work in PE 0602784A/Project T41.

Doesn’t that just reek with subjects that would be identified differently in intersecting information systems?

One solution would be to fashion top down mapping systems that are months if not years behind demands in an operational environment. Sort of like tanks that overheat in jungle warfare.

Or you could do something a bit more dynamic that provides a “good enough” mapping for operational needs and yet also has the information necessary to integrate it with other temporary solutions.

2.95 Million Satellite Images (Did I mention free?)

Saturday, April 2nd, 2016

NASA just released 2.95 million satellite images to the public — here are 21 of the best by Rebecca Harrington.

From the post:

An instrument called the Advanced Spaceborne Thermal Emission and Reflection Radiometer — or ASTER, for short — has been taking pictures of the Earth since it launched into space in 1999.

In that time, it has photographed an incredible 99% of the planet’s surface.

Although it’s aboard NASA’s Terra spacecraft, ASTER is a Japanese instrument and most of its data and images weren’t free to the public — until now.

NASA announced April 1 that ASTER’s 2.95 million scenes of our planet are now ready-to-download and analyze for free.

With 16 years’ worth of images, there are a lot to sort through.

One of Rebecca’s favorites:


You really need to select that image and view it at full size. I promise.

The Andes Mountains. Colors reflect changes in surface temperature, materials and elevation.

Time Maps:…

Saturday, April 2nd, 2016

Time Maps: Visualizing Discrete Events Across Many Timescales by Max Watson.

From the post:

In this blog post, I’ll describe a technique for visualizing many events across multiple timescales in a single image, where little or no zooming is required. It allows the viewer to quickly identify critical features, whether they occur on a timescale of milliseconds or months. It is adopted from the field of chaotic systems, and was originally conceived to study the timing of water drops from a dripping faucet. The visualization has gone by various names: return map, return-time map, and time vs. time plot. For conciseness, I will call them “time maps.” Though time maps have been used to visualize chaotic systems, they have not been applied to information technology. I will show how time maps can provide valuable insights into the behavior of Twitter accounts and the activity of a certain type of online entity, known as a bot.

This blog post is a shorter version of a paper I recently wrote, but with slightly different examples. The paper was accepted to the 2015 IEEE Big Data Conference. The end of the blog also contains sample Python code for creating time maps.

Building a time map is easy. First, imagine a series of events as dots along a time axis. The time intervals between each event are labeled as t1, t2, t3, t4, …


A time map is simply a two-dimensional scatterplot, where the xy coordinates of the events are: (t1,t2), (t2, t3), (t3, t4), and so on. On a time map, the purple dot would be plotted like this:


In other words, each point in the scatterplot represents an event. The x-coordinate of an event is the time between the event itself and the preceding event. An event’s y-coordinate is the time between the event itself and the subsequent event. The only points that are not displayed in a time map are the first and last events of the dataset.

Max goes on to cover the heuristics of time maps, along with the Python code for generating them.

Max’s time maps use a common time line for events and so aren’t well suited to visualizing overlapping narrative time frames such as occur in novels and/or real life.

I first saw this in a tweet by Data Science Renee

Mapping Mountains – Tangram

Tuesday, March 22nd, 2016

Mapping Mountains by Peter Richardson.

From the post:

I’ve been spending a lot of time over the mountains of Northern California lately. To view mountains from above is to journey through time itself: over ancient shorelines, the trails of glaciers, the marks of countless seasons, and the front lines of perpetual tectonic struggle. Fly with me now, on a tour through the world of elevation data:

A stunning display of mapping technology!

Peter starts with an illustrated history of the depiction of elevation on maps, including a map that was a declared to be a military secret!

It’s a quick romp that leads to “Tangram functionality” which is described elsewhere as:

Tangram is a map renderer designed to grant you ludicrous levels of control over your map design. By drawing vector tiles live in a web browser, it allows real-time map design, display, and interactivity.

Using WebGL, Tangram saddles and rides your graphics card into a new world of cartographic exploration. Animated shaders, 3D buildings, and dynamic filtering can be combined to produce effects normally seen only in science fiction.

Map styles, data filters, labels, and even graphics card code can be defined in a human-readable and -writable plaintext scene file, and a JavaScript API permits direct interactive control of the style.

The balance of the post is a lengthy demonstration of Tangram that ends in a call for test pilots!

Tangram reminded of the Art of War by Sun Tzu, where it reads:

All armies prefer high ground to low and sunny places to dark.

Which should now read:

All armies prefer Tangram map renderers to all others.

Seriously. Protesters, direct action movements, irregulars, etc. should take a long look at this post.

I first saw this in a tweet by Lynn Cherny.

Superhuman Neural Network – Urban War Fighters Take Note

Wednesday, February 24th, 2016

Google Unveils Neural Network with “Superhuman” Ability to Determine the Location of Almost Any Image

From the post:

Here’s a tricky task. Pick a photograph from the Web at random. Now try to work out where it was taken using only the image itself. If the image shows a famous building or landmark, such as the Eiffel Tower or Niagara Falls, the task is straightforward. But the job becomes significantly harder when the image lacks specific location cues or is taken indoors or shows a pet or food or some other detail.

Nevertheless, humans are surprisingly good at this task. To help, they bring to bear all kinds of knowledge about the world such as the type and language of signs on display, the types of vegetation, architectural styles, the direction of traffic, and so on. Humans spend a lifetime picking up these kinds of geolocation cues.

So it’s easy to think that machines would struggle with this task. And indeed, they have.

Today, that changes thanks to the work of Tobias Weyand, a computer vision specialist at Google, and a couple of pals. These guys have trained a deep-learning machine to work out the location of almost any photo using only the pixels it contains.

Their new machine significantly outperforms humans and can even use a clever trick to determine the location of indoor images and pictures of specific things such as pets, food, and so on that have no location cues.

The full paper: PlaNet—Photo Geolocation with Convolutional Neural Networks.


Is it possible to build a system to determine the location where a photo was taken using just its pixels? In general, the problem seems exceptionally difficult: it is trivial to construct situations where no location can be inferred. Yet images often contain informative cues such as landmarks, weather patterns, vegetation, road markings, and architectural details, which in combination may allow one to determine an approximate location and occasionally an exact location. Websites such as GeoGuessr and View from your Window suggest that humans are relatively good at integrating these cues to geolocate images, especially en-masse. In computer vision, the photo geolocation problem is usually approached using image retrieval methods. In contrast, we pose the problem as one of classification by subdividing the surface of the earth into thousands of multi-scale geographic cells, and train a deep network using millions of geotagged images. While previous approaches only recognize landmarks or perform approximate matching using global image descriptors, our model is able to use and integrate multiple visible cues. We show that the resulting model, called PlaNet, outperforms previous approaches and even attains superhuman levels of accuracy in some cases. Moreover, we extend our model to photo albums by combining it with a long short-term memory (LSTM) architecture. By learning to exploit temporal coherence to geolocate uncertain photos, we demonstrate that this model achieves a 50% performance improvement over the single-image model.

You might think that with GPS engaged that the location of images is a done deal.

Not really. You can be facing in any direction from a particular GPS location and in a dynamic environment, analysts or others don’t have the time to sort out which images are relevant from those that are just noise.

Urban warfare does not occur on a global scale, bringing home the lesson it isn’t the biggest data set but the most relevant and timely data set that is important.

Relevantly oriented images and feeds are a natural outgrowth of this work. Not to mention pairing those images with other relevant data.

PS: Before I forget, enjoy paying the game at:

Satellites in Global Development [How Do You Verify Satellite Images?]

Sunday, February 21st, 2016

Satellites in Global Development

From the webpage:

We have better systems to capture, analyze, and distribute data about the earth. This is fundamentally improving, and creating, opportunities for impact in global development.

This is an exploratory overview of current and upcoming sources of data, processing pipelines and data products. It is aimed to offer non GIS experts an exploration of the unfolding revolution of earth observation, with an emphasis on development. See footer for license and contributors.

A great overview of Earth satellite data for the non-specialist.

The impressive imagery of 0.31M resolution, calls to mind the danger of relying on such data without confirmation.

The image of Fortaleza “shows” (at 0.31M) what appears to be a white car parked near the intersection of two highways. What if instead of a white car that was a mobile missile launch platform? It’s not much bigger than a car so would show up on this image.

Would you target that location based on that information alone?

Or consider the counter-case: What reassurance do you have that what appears to be a white car in the image at the intersection is not a mobile missile launcher, but is reported to you on the image as a white car?

Or in either case, what if the image is reporting an inflatable object placed there to deceive remote imaging applications?

As with all data, satellite data is presented to you for a reason.

A reason that may or may not align with your goals and purposes.

I first saw this in a tweet by Kirk Borne.

All The Pubs In Britain & Ireland & Nothing Else

Tuesday, February 2nd, 2016

All The Pubs In Britain & Ireland & Nothing Else by Ramiro Gómez.

From the post:

The map above is elegant in its simplicity. It shows Great Britain and Ireland drawn from pubs. Each blue dot represents a single pub using data extracted from OpenStreetMap with the Matplotlib Basemap Toolkit.

Interestingly, if the same map had been drawn using the number of pubs from 1980 it would have looked quite different.

In total, the map has 29,195 pub locations across both the UK and Ireland. However, the UK alone has lost 21,000 pubs since 1980 according to the Institute of Economic Affairs, with half of these occurring since 2006.

Therefore, a map from 1980 might have had nearly twice as many dots as the one above and possibly not all in the same places. Going back even further, there were a reported 99,000 pubs in the UK in 1905.

See Ramiro’s post for the map but more importantly, book travel to the UK to help stem the loss of pubs!

How many of the 29,195 pubs in the UK have you visited?

Where Does Your Dope Come From? [Interviewing Tips]

Monday, February 1st, 2016

Visualizing Mexico’s Drug Cartels: A Roundup of Maps by Aleszu Bajak.

From the post:

With the big news this week of the arrest of Joaquín “El Chapo” Guzmán’s, the head of Mexico’s largest drug cartel, most of the attention is being paid to actor Sean Penn’s Rolling Stone interview with the kingpin in his mountain hideout in Mexico.

But where’s the context? How powerful is the Sinaloa cartel that he has run for decades and the other Mexican drug cartels, for that matter? Storybench has been sifting through a wealth of graphics on the workings of the drug trade in Mexico and its impact on the United States that help readers begin to understand the bigger picture of this complex drug war. So now that you’ve read your fill on Sean Penn’s (and Rolling Stone’s) editorial shortcomings, check out these impressive visualizations taken from news organizations, non-profits and government agencies.

Bajak presents a stunning array of maps that visualize the influence of Mexican drug cartels.

One of the most interesting has the title: United States: Areas of Influence of Major Mexican Transnational Criminal Organizations.


(You will need to select the image to get a useful sized image.)

All of the maps are interesting and some possibly more useful than others, such as if you are planning on expanding drug trade in one area but not another.

What I found missing was a map of all the organizations profiting from the war on drugs. Yes?

Location and approximate incomes of drug cartels, agencies, law enforcement offices, government budgets, etc.

The war on drugs isn’t just about the income (and failure to pay taxes) of the drug cartels, it is also about the allocation of personnel and budgets in law enforcement organizations, prisons that house drug offenders, etc.

One persuasive graphic would be the economic impact on government organizations if the drug trade stopped tomorrow and drug offense prisoners were released from jail.

There is a symbiotic relationship in the war on drugs. Government agents limit available competition and help keep prices artificially high. Drug cartels provide a desired product and a rationale for the existence of police and related agencies.

A rather cozy, if adversarial arrangement. (A topic map could clarify the benefits to both sides but truth telling isn’t a characteristic of either side.)

PS: Do read the piece on what Sean Penn should have done for his interview with El Chapo. It makes a good checklist of what reporters don’t do when interviewing political candidates or sitting members of government.

They want to be asked back if you know what I mean.

Search points of interest by radius with Mapbox GL JS

Thursday, January 7th, 2016

Search points of interest by radius with Mapbox GL JS by Zach Beattie.

From the post:

Mapbox GL JS provides new and interesting ways to query data found on a map. We built an example that filters points of interest by genre, which uses the featuresAt method to only select data based on the position and radius of the circle. Drag the blue circle around the map to populate points of interest on the left. Zoom in and out on the circle to adjust the radius.

Visually, places of interest appear as colored dots on the map and you can select what type of places appear at all. You use the blue circle to move about the map and as it encompasses dots on the map, additional information appears to the left of the map.

That’s a poor description when compared to the experience. Visit the live map to really appreciate it.

Assuming a map of surveillance cameras and the movement of authorities (in near real time), this would make a handy planning tool.

The most contested real estate on Earth? [Noble Sanctuary/Temple Mount]

Tuesday, December 29th, 2015

The most contested real estate on Earth? (PDF)

I won’t try to reproduce a smaller version of this image because it would simply befoul rather remarkable work.

From the image (top right):

Muslims call it the Noble Sanctuary. Jews and Christians call it the Temple Mount. Built atop Mount Moriah in Jerusalem, this 36-acre site is the place where seminal events in Islam, Judaism and Christianity are said to have taken place, and it has been a flash point of conflict for millenniums. Many aspects of its meaning and history are still disputed by religious and political leaders, scholars, and even archaeologists. Several cycles of building and destruction have shaped what is on this hilltop today.

Great as far as it goes but the lower left bottom gives the impression that Hezekiah expanded the temple mount after Ahaz (his predecessor) plundered it. So legend holds but that leaves the reader with the false impression that the Jewish temple came to the Noble Sanctuary/Temple Mount first.

If you recall your Sunday School lessons, David conquers Jerusalem (Jebus), as told in 1 Chronicles 11:4-9.

Jerusalem was a sacred site long before David or the Israelites appear in the historical record. How long? Several thousand years at least but the type of excavation required to detail that part of the city’s history won’t happen any time soon.

Do enjoy the map, it is very impressive.

D3 Maps without the Dirty Work

Monday, December 21st, 2015

D3 Maps without the Dirty Work by

From the post:

For those like me who aren’t approaching mapping in D3 with a GIS background in tow, you may find the propretary goe data structures hard to handle. Thankfully, Scott Murray lays out a simple process in his most recent course through By the time you are through reading this post you’ll have the guide post needed from mapping any of the data sets found on Natural Earths website in D3.

First in a series of posts on D3 rendering for maps. Layers of D3 renderings is coming up next.


Magnificent Maps of New York

Sunday, November 15th, 2015

Magnificent Maps of New York by Kate Marshall.

From the post:

The British Library’s ongoing project to catalogue and digitise the King’s Topographical Collection, some 40,000 maps, prints and drawings collected by George III, has highlighted some extraordinary treasures. The improved and up-dated catalogue records are now accessible to all, anywhere in the world, via the Library’s catalogue, Explore, and offer a springboard for enhanced study.

Your donations to this and other projects enable us to digitise more of our collections, the results of which are invaluable. One such example of further research using material digitised with help from donors is the recently published book by Richard H. Brown and Paul E. Cohen, Revolution. Mapping the Road to American Independence, 1755-1783, which features a number of maps from the K.Top.

The Explore link takes to the main interface for the British Library but Maps is a more direct route to the map collection materials.

Practically everyone has made school presentations about their country’s history. With resources such as the British Map collection becoming available online, it isn’t too much to expect student to supplement their reports with historical maps.


Quartz to open source two mapping tools

Thursday, November 12th, 2015

Quartz to open source two mapping tools by Caroline Scott.

From the post:

News outlet Quartz is developing a searchable database of compiled map data from all over the world, and a tool to help journalists visualise this data.

The database, called Mapquery, received $35,000 (£22,900) from the Knight Foundation Prototype Fund on 3 November.

Keith Collins, project lead, said Mapquery will aim to make the research stage in the creation of maps easier and more accessible, by creating a system for finding, merging and refining geographic data.

Mapquery will not be able to produce visual maps itself, as it simply provides a database of information from which maps can be created – so Quartz will also open source Mapbuilder as the “front end” that will enable journalists to visualise the data.

Quartz aims to have a prototype of Mapquery by April, and will continue to develop Mapbuilder afterwards.

That’s news to look forward to in 2016!

I’m real curious where Quartz is going to draw the boundary around “map data?” The post mentions Mapquery including “historical boundary data,” which would be very useful for some stories, but is traditional “map data.”

What if Mapquery could integrate people who have posted images with geographic locations? So a reporter could quickly access a list of potential witnesses for events the Western media doesn’t cover?

Live feeds of the results of US bombing raids against ISIS for example. (Doesn’t cover out of deference to the US military propaganda machine or for other reasons I can’t say.)

Looking forward to more news on Mapquery and Mapbuilder!

I first saw this in a tweet by Journalism Tools.