So the *Monthly Maps* series is almost on the verge of becoming a *Bi-Monthly Maps* series! Hopefully this will be the only double month issue of the year 2014.
 

Let us begin with a map that is not really a map, but an efficient two-dimensional machine-readable representation of three-dimensional satellite imagery, which has a strange haunting appearance of a map of a disaster zone. Clement Valla, creator of this stunning work, explains that though “[t]hey may look like glitched maps, disaster scenes, cubist collages… these images are produced for other computers to use—to apply color and texture to 3d forms. These images are efficient vectors of information. But unlike a long list of 1s and 0s, or some other cold alien encoding, they still look like the objects they represent. They are uncannily close to photographs or human made collages.”

clement valla - 3d maps minus 3d

Development Seed has launched the Afghanistan Open Data Project in anticipation of the upcoming national election in the country. It is described as a “community efforts to release into the public domain a combination of political, social, and economic datasets of significance to elections in Afghanistan.” The map below displays the percentage of polling centers in each province that did not report poll results in the 2009 election.

development seed - afghanistan open data project

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Every project I have been involved thus far, I have helped people to ask the question – ‘Are maps really the right tool for us to tell this story?’ And I must say, there are not many people who are convinced. Maps are cool, they look nice, you can make them interactive, they may go viral (for good or bad), and yes, people like maps. Agree and that’s one of the many reasons why I love making maps and telling stories through them. If you do not ask the question, several things can go wrong.

I put together a repository to start gathering few examples of situations when maps go wrong. And spoke at an event in Bangalore and it was exciting. We will see some of those in this blog post. I am not intending to provide solutions to most of these, that will make a better blog post later. Broadly, there are six lists –

Misrepresentation of data

Careless handling of images and data can cause terrible mistakes, like the one below from the CNN a few weeks back.

CNN - Hong Kong is now in Brazil

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Here is another double issue of Monthly Maps to begin the new year.

The end of the year saw several great “best maps of 2013″ posts. We will go to them soon but first let’s look at the map that got the “worst map of 2013″ award from Kenneth Field, the Cartonerd. In his famous words, it features a “symposium of technicolour psychedelic vomit across the map.”

cartonerd - worst map of 2013

This beautiful three-dimensional globe-based visualisation of surface wind speed (powered by D3) was featured on both Kenneth Field’s “favourite maps from 2013″ and Wired MapLab’s “the most amazing, beautiful and viral maps of the year” posts.

nullschool.net - earth wind map

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I’ve re-entered the academic world as a student at the University of Cambridge in the United Kingdom, and one of the benefits I’m enjoying the most is near-unlimited access to one of the world’s largest repositories of recorded information; the Cambridge University Library. Commonly known as the UL, this is a copyright library which means that under British rules on legal deposit, the library has the right to request a copy of any work published in the UK free of charge. Currently, the UL has over 8 million items, which includes books, periodicals, magazines and of course, maps.

 

The Map Room in the UL is a fascinating place; it functions as the reading room for the Map Department, which holds over a million maps (as the librarian told me; Wikipedia claims it has 1.5 million). It’s not a very large room, as reading rooms go, but is a beautiful space and is very well managed. Everything is catalogued very efficiently with a filing card system, and there’s one card with the name, date of publication and classmark (UID/coordinates) for each map.  Visitors are not allowed to simply browse through the map collections; to refer to a map, one must fill out a request form with the appropriate details and submit this form to the library assistants, who will then pull out the required map folio from its storage location. The title of this post comes from the fact that  map holdings with classmarks beginning with ‘S696′, ‘Maps’ or ‘Atlases’ are held in the Map Room, in various drawers and cabinets.

 

The Map Room is a pen-free zone; if you’re writing something, use a pencil. Smartphones and hand-held cameras are allowed, but under UL policy photos cannot be taken of the building itself. With prior permission however, it is possible to take images of material in the UL, which I did. The first series is from a map on display in the UL; titled “A map containing the towns villages gentlemen’s houses roads river and other remarks for 20 miles around London“, it was printed for a William Knight in 1710 and is a wonderful piece of cartography. The second series is from a map I requested using the card-index system; this map dates back to 1949 and beautifully illustrates tea-growing regions in the Indian-subcontinent.

 

If there’s a map in the UL you want an image of (for non-commercial or private-study purposes only!), I’d be happy to do what I can to help; I would actually be very grateful for an excuse to spend an afternoon looking at maps.

IMG_6037
Detail from Knight, W. (1710). North Arrow.

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Note: Much apologies for skipping the September issue of Monthly Maps. To compensate, here’s a double issue filled with fantastic cartographies.

Guernica Magazine has published an excerpt of an interview with Denis Wood, iconic critical cartographer, from his last book titled “Everything Sings: Maps for a Narrative Atlas“. Let us begin this double issue with Wood’s penetrating analysis of what maps do:

 

Denis Wood: Maps are just nude pictures of reality, so they don’t look like arguments. They look like “Oh my god, that’s the real world.” That’s one of the places where they get their kick-ass authority. Because we’re all raised in this culture of: if you want to know what a word means, go to the dictionary; if you want to know what the longest river in the world is, look it up in an encyclopedia; if you want to know where some place is, go to an atlas. These are all reference works and they speak “the truth.” When you realize in the end that they’re all arguments, you realize this is the way culture gets reproduced. Little kids go to these things and learn these things and take them on, and they take them on as “this is the way the world is.”

The fabulous neogeographers at the Oxford Internet Institute used Alexa data to identify the most visited websites in each country, and mapped it as an old colonial style choropleth map of ‘Internet empires’. Do not miss another map included in the same page, which uses hexagonal cartograms to qualify the most-visited websites in each country by the population of Internet users in the same country.

oxford internet institute - age of internet empires

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Web and mobile applications account for most of the maps usage today. We recently read that about 54% of smartphone users have Google Maps running on their phone making it the most popular application in the market. In the recent years, the technology behind web maps have improved considerably, owing to the incredibly fast and intuitive experience that we enjoy today. What we see, drag, scroll, touch, pinch and poke today is a set of map tiles.

The OpenStreetMap Wiki defines map tiles this way –

square bitmap graphics displayed in a grid arrangement to show a map

The fine folks at MapBox defined it this way –

tiles are typically 256×256 pixels and are placed side-by-side in order to create the illusion of a very large seamless image.

This technique of preparing and serving maps changed the way they are consumed drastically. Earlier, loading the map in a browser would take up so much memory that it was practically impossible to browse the map easily. Tiles make sure that only the required (usually the area which is currently viewed) have to be displayed on the browser, reducing the memory footprint. Even though Google got the usage of tiling right, they did not invent it. Web Map Service which came out in 1999 as an OGC standard set the web mapping revolution to a new level. WMS was slow for a lot of neogeographers. This frustration lead Anselm Hook to explore the idea of tiling the map for better performance.

The core of the application is a lightweight javascript application that runs in both Internet Explorer and Firefox. The approach is similar to the one taken at SVG Tile Engine which I wrote last summer. The difference is that this one talks to conventional WMS compliant mapping sources rather than a pre-tiled blue marble database and relies only on Javascript – not on SVG. This javascript engine is actually just a straight port of a java client based tile mapping engine which is visible at Java Tile Engine . The problem with the java applet approach however is that it cannot do cross domain image loading due to flaws in the security policy of java.

WMS-C was introduced following this idea to cache the map images which was super-ceded by the Tile Map Service by OSGeo.

Let’s take another step forward and see how the tiles work and how they are generated.

tilesWhen we view a map on the browser, there’s an immensely powerful feature – zoom. The world map at the least zoom level (level 0) is usually four square images which forms a grid of tiles. Every location on the earth is represented by a tuple with two elements – [latitude, longitude]. This, on your screen, translates to [x, y] which is the pixel coordinates. Zoom levels are incorporated to this data structure by adding one more element to the tuple – [latitude, longitude, zoom]. For instance, [12.9719, 77.5938, 12] is Bangalore at zoom level 12 and [12.9719, 77.5938, 15] is Bangalore at zoom level 15.

In your browser, the map is a collection of HTML image tags. This is achieved by using one of the various JavaScript map libraries like Leaflet.js, OpenLayers.js, or MapBox.js.

The geographic data in databases or shapefiles are rendered into the tiles through a process which involves several stages. We will quickly run through the most important and commonly used pipeline using a stack of open source softwares.

Mapnik is the de facto open source rendering library written in C++ that is used by large geographic data projects like OpenStreetMap to tiny map studios. Mapnik accepts a wide variety of input data – PostgreSQL databases, Shapefiles, GeoTIFF, and renders the data into set of map tiles depending on the style that you have developed. The styles are XML files which explain what Mapnik should do for each of the geographic feature (read tags) that it finds in the data source.

	<Style name="highways">
		<Rule>
			<Filter>[highway] &lt;&gt; ''</Filter>
			<LineSymbolizer>
				<CssParameter name="stroke">#808080</CssParameter>
				<CssParameter name="stroke-width">2</CssParameter>
				<CssParameter name="stroke-linejoin">round</CssParameter>
				<CssParameter name="stroke-linecap">round</CssParameter>
			</LineSymbolizer>
		</Rule>
		<Rule>
			<Filter>[highway] &lt;&gt; ''</Filter>
			<TextSymbolizer name="name" fontset_name="book-fonts"
				size="9" fill="#000" halo_radius="1" placement="line" />
		</Rule>
	</Style>

The above XML is one of the many style tags used by OpenStreetMap to render the tiles using Mapnik. This style tag refers to the highways that you see on the map. A style tag comprises of several Rules. A common technique is to apply CSS to the features that satisfy a rule and Mapnik will pick it up.

The tiles rendered by Mapnik are then served from what is called a Tile Server. The commonly used tools for a server is Apache with the mod_tile extension. I like the Python based server called TileStache. It’s fast and easy to setup. When the browser requests for a map tile, the server checks if the tile has been already rendered, if yes it is send to the browser. Otherwise, it is send to Mapnik for rendering.

We will discuss more about the configuration and best practices of setting up a rendering stack eventually in another blog post.

As two South Asian countries celebrate their independence days in August, I decided to focus on ‘political maps’ in this *Monthly Maps* post. This means that some of the exciting maps and map news we came across in August, which did not directly speak of politics, will become part of the September post.

We begin with a fascinating map of the Bangladesh-India border along the Indian district of Cooch Behar depicting various ‘enclaves’ (parcel of Bangladeshi territory within Indian territory, and vice versa) along the border lands. This pre-1971 map (hence referring to Bangladesh as East Pakistan) posted by Frank Jacobs on the Strange Maps blog is a great example of the deeply geopolitical nature of the lines and the names that annotate and constitute maps, and also of the territorial mess often created by such politics.

 

bangladesh-india border - cooch behar - enclaves

 

Maps have also played a key political role as a tool for government to uniquely identify and classify not only national borders but also various forms of landed properties and their relationship with the government. This 1855 “vice” map of the Chinatown in San Francisco was created by the municipal government to locate places of gambling, prostitution and opium “resorts”, as part of the anti-Chinese movement and propaganda in California. Interestingly, the map fails to capture the vertical dimension of urban spaces and only identifies the usage pattern of the ground floor spaces.

david rumsey - san francisco - chinatown

Military requirements have been perhaps the most crucial driver for development of modern cartographic techniques and instruments. Jeremy Crampton recently shared a ‘jaw-dropping “OSS Theater Map”‘ produced by the Office of Strategic Affairs (predecessor of Central Intelligence Agency of USA) during the World War II. Crampton explains that the ‘unusual projection’ utilised by this map is targeted at solving a classic cartographic problem of finding a projection to represent earth’s surface as a square grid (just like how modern web-map tiles work) while not distorting the actual spherical shape form of the surface.

geohackers_2013.08_oss

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The Thermal InfraRed Sensor (TIRS) is a new instrument carried onboard the Landsat 8 satellite that is dedicated to capturing temperature-specific information.  Using radiation information from the two electromagnetic spectral bands covered by this sensor, it is possible to estimate the temperature at the Earth’s surface (albeit at a 100m resolution, compared to the 30m resolution of the other instrument, the Operational Land Imager).

I used data from the TIRS to estimate the surface temperature in the city-state of Delhi, India as of the 29th of May, 2013.  The relevant tarball file containing the data was downloaded using the United States’ Geological Survey’s (USGS) EarthExplorer tool; the area of interest was encompassed by [scene identifier: path 146 row 040] in the WRS-2 scheme. I think I’ll leave the specific explanations describing WRS-2, path/row values and the other miscellaneous small data-management operations for a later post. For now, I’ll let it be understood that these are important things to know when in the process of actually obtaining this data. When the tarball is unpacked fully, the bands from the TIRS instrument are bands 10 and 11;  the relevant .tif files are [“identifier”_B10.tif] and [“identifier”_B11.tif], and these were clipped to the administrative boundary of Delhi. There’s also a text file containing metadata: [“identifier”_MTL.txt] is essential for the math we’re going to do on these two bands.

 

Delhi as seen by Landsat 8 Band 10 (TIRS)
Delhi as seen by Landsat 8 Band 10 (TIRS)

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I planned to highlight ten maps each in month in this *Monthly Maps* series. The month of July, however, saw quite a few fabulous maps, and left me struggling to choose between them. Perhaps I will break the limit of ten maps a bit for this month.

July began with the awesome urban tweet topography maps by data visualisation scientist Nicolas Belmonte. These maps takes all the geo-tagged tweets from five cities — Buenos Aires, Istanbul, Moscow, New York, and San Francisco — and generate a three dimensional topography of these tweets with a higher contour line indicating a greater number of tweets from the place concerned. The image below is for Istanbul. Do visit the maps page to explore other cities and various thematic terrain shading, and the entire code is on GitHub too!

3d twitter topography

And Stamen came out with the *instgram for maps* – map stack. It lets you create a map by combining various basemap layers (including satellite imagery, terrain, road networks etc.), visually crafting the layers using detailed controls (e.g., masks, opacity and brightness), and to convert the final map into an image for sharing.

stamen - map stack

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Note: Welcome to this new content section we are beginning. As the name suggest, the ‘Monthly Maps’ series will do a monthly aggregation of all the maps, map codes, and map news that we loved and flagged during the month concerned (and not necessarily those that were published in the month concerned). Apologies for the late publication of the June 2013 edition. We hope you will enjoy this one and keep following the future editions.

 

The biggest international news this month was the ‘discovery’ of PRISM and associated technological systems being used by the Government of USA for global media surveillance. WikiLeaks and friends created a very informative map of snooping activities by governments across the world.

geohacker_2013.06_spyfiles

And, the OpenStreetMap community went ahead and mapped a secret data center of the National Security Agency of USA being contructed outside Salt Lake City, Utah.

geohacker_2013.06_nsa-data-center

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