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TileStream is an open source tile server devel­oped by Map­Box, which bor­rows exten­sively from their com­mer­cial Map­Box tile server prod­uct. TileStream loads map layer pack­ages cre­ated in the TileMill appli­ca­tion, which are stored on the server as SQLite data­bases in the mbtiles specification/schema. On the other hand, Heroku is a cloud appli­ca­tion plat­form that sup­ports Python, Ruby, Java and Node.js apps, the lat­ter of which TileStream is depen­dent upon. This post will show how to deploy a TileStream server on the Heroku cloud appli­ca­tion plat­form, thereby allow­ing you to serve your map tiles using scal­able infra­struc­ture that can respond to fluc­tu­a­tions in the demand of your web maps. See the result here.

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Life as a grad stu­dent, as many of you already know, is a con­stant bat­tle with com­plet­ing assign­ments on time, keep­ing up the grades for future fund­ing oppor­tu­ni­ties and get­ting enough sleep. My first semes­ter in the Mas­ter of Spa­tial Analy­sis pro­gram is near­ing its end in what seems like the short­est semes­ter of school I’ve ever taken. Dur­ing this time I have had the plea­sure to strengthen some of my skills in the R lan­guage for sta­tis­ti­cal com­put­ing for the pur­pose of water qual­ity trend analy­sis (SA8904GIS Project Man­age­ment). This post will show how I have used R for water qual­ity trend analy­sis, using pub­li­caly avail­able data from the USGS (due to a NDA that pro­hibits me to share my school work).

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Hi every­one!

For the past 6 months I have been work­ing hard to get you a lim­ited edi­tion print of the global flights. I am very excited to release this print in a run of 50, signed and numbered.

Find out more details and buy yours today: http://shop.www.spatialanalysis.ca

 

Sta­tis­ti­cally speak­ing, the Global Flight Paths images are my most rec­og­nized and shared pieces of work and even more so since they went viral and media crazy over the past week. The BBC News reported over 1 mil­lion UK-based vis­i­tors had read the story on their web­site and over 15,000 social shares were recorded. The BBC News also tweeted this story to over 1.5 mil­lion twit­ter fol­low­ers, which in turn retweeted the link to their many mil­lions of fol­low­ers. If any­one has a way to aggre­gate and quan­tify these tweet+retweet sta­tis­tics I would be more than happy to explore.

I am cur­rently wait­ing on licens­ing and prints infor­ma­tion from the pow­ers above me so please, if you are inter­ested in using the images or want­ing prints, kindly send me an email stat­ing so! Thank you and I will try my best to get back to every­one as quick as possible.

Some other inter­est­ing stats:

 

The Afghan War Diary, made avail­able by the Wik­ileaks group, is the dis­clo­sure of inter­nal US Mil­i­tary logs. Wik­ileaks has been known to release data that con­tains lat­i­tu­di­nal and lon­gi­tu­di­nal infor­ma­tion use­ful for spa­tial analy­sis. I’ve taken the lib­erty to map the some-76,000 mil­i­tary logs.

The mil­i­tary logs are a col­lec­tion of top secret clas­si­fied cor­re­spon­dences that detail var­i­ous mil­i­tary encoun­ters and sit­u­a­tional reports. Some of the most pop­u­lar head­ings in the log are: ene­mies killed/wounded in action, friend­lies killed/wounded in action and report­ing unit (squad/other).

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It has been a while since I posted on this web­site; but you may have noticed that I have been fairly busy else­where, such as on LinkedIn or Twit­ter.

This post will stand as a reminder to myself that we can’t always fore­see the bumps along the road. I am speak­ing about the ESRI map­book sub­mis­sion that was due on Novem­ber 16, which I missed because of undue dif­fi­cul­ties in obtain­ing and manip­u­lat­ing triv­ial data. Why do I say triv­ial? Given the way my sub­mis­sion looks at the moment, I would say it is accept­able, if not near per­fect for the map­book cat­e­gories of trans­porta­tion and cartography.

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As the City of Toronto inches closer and closer towards the green light for new Metrolinx projects like the LRT lines for Shep­pard East and Eglin­ton Crosstown, GIS will play an ever cru­cial role in assist­ing deci­sion mak­ers by fram­ing City-wide issues into a per­spec­tive that can be quickly com­pre­hended. Map­ping ser­vice den­sity aims to iden­tify tran­sit deserts in the over­all tran­sit net­work. These maps empha­size the dif­fer­ence in the lev­els of ser­vice (num­ber of trips) by using darker/stronger colours and thicker lines for higher than aver­age trips, and vice-versa for routes that dis­play below the aver­age num­ber of trips.

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Let’s face it, GIS is a term loosely (if even that) under­stood by the pub­lic. With­out a uni­ver­sity degree in Geog­ra­phy or cer­tifi­cate in GIS, web-mapping enables users to explore geospa­tial data, pat­terns and phe­nom­e­non quite effec­tively. As an exploratory tool, web-mapping bridges the gap between the ana­lyt­i­cal engine that is the GIS soft­ware, and the basic sta­tic map.

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The Open­StreetMap project has over half a mil­lion map con­trib­u­tors and a fairly exten­sive devel­oper com­mu­nity. This past week­end, the first-ever Open­StreetMap hack week­end was held in Toronto, Canada (second-ever North Amer­i­can hack) at Ryer­son Uni­ver­sity. This event was jointly hosted with the Depart­ment of Geog­ra­phy, Mas­ter of Spa­tial Analy­sis and the Stu­dent Asso­ci­a­tion of Geo­graphic Analy­sis. Event coör­di­na­tion was taken care of by Richard Weait, long-time advo­cate of OpenStreetMap.

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Late last year, Google announced that their Maps API and Google Maps Imagery would become a charged ser­vice for high vol­ume users. Any­one host­ing more than 25,000 daily map views would incur charges accord­ing to this pric­ing scheme. It is impor­tant to note that, not only is the API restricted, but the imagery (google maps lay­ers) is restricted in the same fash­ion. For those that use any other API but still call upon Google base lay­ers, the restric­tion of 25,000 daily map views still holds true. Now, this web­site cer­tainly won’t gen­er­ate that kind of traf­fic any­time in the near future, but there cer­tainly are those kinds of web­sites on the inter­net that have well over a mil­lion page views a day. Those that first come to mind are travel ser­vice providers and real-estate agen­cies. Both ser­vices use maps as spa­tial deci­sion sup­port tools (eg. where should I live? where should we visit?). I am tak­ing this oppor­tu­nity to round up the APIs that I am famil­iar with and would rec­om­mend to those mak­ing the move away from Google.

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