Le portail francophone de la géomatique

A man's car had flipped leaving him well offroad in cold Saskatchewan on Thursday night. He called Canadia 911, but traditional manned aircraft could not locate him. The Royal Canadian Mounted Police launched a Draganflyer X4-ES helicopter drone near the last known coordinates from his... Continue reading

A man's car had flipped leaving him well offroad in cold Saskatchewan on Thursday night. He called Canadia 911, but traditional manned aircraft could not locate him. The Royal Canadian Mounted Police launched a Draganflyer X4-ES helicopter drone near the last known coordinates from his... Continue reading

The interactive storymap of television moms is arranged by decade. Missing? Mrs. Robinson from Lost in Space! - via Journal Sentinel ... Continue reading

The interactive storymap of television moms is arranged by decade. Missing? Mrs. Robinson from Lost in Space! - via Journal Sentinel ... Continue reading

In a recent LiDAR News article by Fran Rabuck he refers to this Kickstarter project to develop a low cost LiDAR Continue reading →



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Two Google Maps really seemed to capture people's imagination this week; The Flat Route Finder and the Hate Map.

The Flat Route Finder was the most shared map on social media at the beginning of the week. While, after its release on Friday, the Hate Map quickly went viral on social media and almost as quickly was picked up by a number of the websites of the national and international press.


The Hate Map is a heat map of offensive messages made on Twitter. The map shows the rough location of every geocoded tweet in the United States from June 2012 - April 2013 that contained one or more of ten 'hate words'.

The offensive words mapped include 'racist', 'homophobic' and 'anti-disability' terms. Users of the map can view heat maps not only of these general themes but can also explore heat maps of the ten individual hate words.


As a semi-keen cyclist the thing I hate most in the world (after cars, buses and trucks) is hills. I really, really hate hills.

Thankfully I can now use the Flat Route Finder to find cycling routes that avoid the steepest slopes. The Flat Route Finder uses the Google Maps elevation service to suggest the flattest possible cycling route. Two elevation graphs are also provided to show you the steepest parts of the route and the route itself is colour-coded to show you the easiest and most difficult stages of the journey.


Also this week, The New York Times published an interesting Medicare Map that shows how much different hospitals charge Medicare throughout the country, for the same treatment.

The map compares the charges made at 3,300 hospitals nationwide for the 100 most commonly performed treatments and procedures. The colored markers on the map show whether individual hospitals charged less than the average (blue markers), 1 to 2 times the average (yellow) or twice the national average (red).

The big news in online mapping this week was the launch of OpenStreetMap's new map editor iD. iD has been designed to lower the threshold for users to edit OpenStreetMap data.

Central to this mission of easing users into the skills needed to add to OpenStreetMap is a great introductory walk-through tutorial. When you first open the editor an interactive tutorial guides you through some of the important features of editing OpenStreetMaps.

iD is a great improvement on the old OpenStreetMaps editing tools and greatly reduces the learning curve for new OpenStreetMap editors.


Ancient Maps of Jerusalem is a great new interactive tool to browse the National Library of Israel's collection of maps of Jerusalem.

A timeline interface allows users to browse the maps by date. The earliest map is Civitas Iherusalem, dating from 1486 and the timeline includes hundreds of maps, right up to the Map of Jerusalem and Environs, dated 1935.

If you click on any of the map images you can view the map in a larger format. This larger format includes a handy little magnifying glass tool that allows you to view any section of the map in close-up detail. 

an award winning introductory video on the use of LiDAR to study the effects on the river dynamics from the removal of a dam. Continue reading →



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The Hate Map is a heat map of offensive messages made on Twitter. The map shows the rough location of every geocoded tweet in the United States from June 2012 - April 2013 that contained one or more of ten 'hate words'.

Every tweet was read by a human to determine that only messages meant as negative were used on the map. Users of the map can view three different heat maps, one for homophobic tweets, one for racist tweets and one anti-diasabled tweets. The user can also view individual heat maps for any one of the ten offensive words.

At first sight the heat maps appear to be very simialr to a population heat map of America but if you look in more detail you can see that there is more than just population density at work in hate messages on Twitter. For example, relatively densely populated California, seems to be also relatively free of hate speech.

You can find out more about the methodology behind the making of this map at the excellent Floating Sheep blog.

Today was a pretty good day for the GeoJSON format.

Josh Livni announced on Twitter that the Google Map Engine API had been published. The little format that could has a good role in the API.

Ed Summers blogged about wikigeo.js, a library that gives you a GeoJSON interface to Wikipedia API results. Ed is absolutely right about how usable and right for the web mapping software has become since younger web developers and designers have started to displace older earth science programmers like myself.

A good example of which is Tom MacWright's edit geojson app: draw a shape and copy the GeoJSON representation, paste some GeoJSON and render the shape.

The business of geospatial standardization may have hit a rough patch recently, but things aren't all bad. Developers are still finding ways to agree, share, and do good work.

The excitement about the upcoming 2.0 release is growing and to add some fuel to the fires, Mathieu founded the QGIS Flickr Group. Anyone can join and add their maps done with QGIS master.

I’m looking forward to seeing what you have come up with. Please note that this group is meant for maps only (therefore no screenshots of the application please).

Summary: When you use the Pixel Locator or Cursor Location/Value tool in ENVI, the latitude and longitude co-ordinates given are based on the datum that the image is in, not necessarily WGS-84.

This may be obvious to some people, but it wasn’t to me – and I thought that if I got confused then some other people probably would too – hence this article. I often use the Pixel Locator dialog box in ENVI to find a specific location in the image by entering the X and Y pixel location (referred to in ENVI as Samples and Lines) or the map co-ordinates of whatever co-ordinate system the image is projected into (for example, the Ordnance Survey National Grid):

Alternatively, you can click the button with the arrows on it, and enter a location in latitude and longitude:

Very handily, all of these values are updated as you move around the image manually – so this dialog can also be used as an equivalent of the Pixel Location/Value window – as shown below.

This all sounds fine – but the problem is that the latitude/longitude values that are shown are calculated using the datum that is defined for the image. You can see this in the image below, where the latitude and longitude value is displayed, and the datum is listed above it:

This seems like a sensible thing to do, but it makes comparison with latitude and longitude co-ordinates from other sources very difficult – as nearly all other latitude and longitude co-ordinates are provided in the WGS-84 datum. Locations from GPS systems are always in WGS-84, and locations on web maps, in GIS systems and most other sources of latitude and longitude co-ordinate systems are very frequently in WGS-84.

So, this raises two questions:

What effect does this have?

Well, I haven’t yet done a full investigation of this (sometime I will sit down and write some code to do some proper testing), but when I found the problem it was causing offsets of around 100-200m – which can be quite significant in many applications.

What can we do about this?

There is a way to tell ENVI to use WGS-84 as the datum for calculating its latitude and longitude values, but it is a bit fiddly. Basically, when you’re in the Pixel Locator dialog before you switch to the latitude/longitude display, click the Change Proj… button and then select click the Datum button to select a new datum. Then switch to the latitude/longitude display, and you’ll find that the datum is listed as WGS-84, and the values will be correct in the WGS-84 datum:

Unfortunately, this means that the map co-ordinate values (for example, the Ordnance Survey Grid References) will now be wrong, and you’ll need to switch back to the original datum to get those to be correct. Also, I can’t find a way to get the Cursor Location/Value dialog to display WGS-84 latitudes and longitudes.

I actually found this while designing a lecture and practical session for MSc students at the University of Southampton on using the ENVI API in IDL. While writing a code example for the students on finding the pixel value at a specific lat/lon co-ordinate, I found that my results came up between ten and twenty pixels away from the place I thought they would (I was using 10m SPOT imagery), and I got different results from my IDL code and ENVI – even though my IDL code was using the ENVI API! Luckily I managed to find out what the problem was – and could therefore explain it to my students, and hopefully stop them running in to the same problem as me. It may be that I’m being silly here, and everyone naturally realises what ENVI does, and thinks it is the right thing to do – but it definitely confused me, so maybe it will helped you.

An interesting mobile app to help with your mobile file storage issues, now supporting iOS – Amazon Cloud Photos. Release for iOS just today (May 9, 2013) the app syncs up with your cloud storage service and makes your data … Continue reading →

Back in February I was invited to keynote the Esri developer meetup in Philadelphia. It was a well-attended event at a very nice venue, hosted by Jim Barry and Amy Niessen. I saw many old friends, made new ones, and learned quite a bit.

Below is my presentation "Developers and users: Divided by a common language". The jokes were much funnier at the time of delivery.

The St. Paul Crime Map is a Google Map of crime committed in St.Paul, Minnesota.

Currently users can view crime committed in the city during January and February of this year. It is possible to filter the results shown on the map by type of crime and turn on and off the neighborhood boundaries via links in the map sidebar.

If you click on a crime's marker on the map you can view details of the crime, presented beneath a Street View of the crime's location.

If it is a spill and not a ghost then there is one number you should know…1-800-424-8802…the National Response Center (NRC).  The NRC is the federal point of contact for reporting all oil and chemical spills and operates 24 hours a day, 7 days a week, 365 days a year.  When the NRC receives a call regarding oil or chemical releases it contacts EPA Federal On-Scene Coordinators. (Interesting side note…the Image on Wikipedia is of Region 7 OSC John Frey!)

Each year, thousands of emergencies involving oil spills or the release (or threatened release) of hazardous substances are reported in the United States, potentially affecting both communities and the surrounding natural environment.  Emergencies range from small scale spills to large events requiring prompt action and evacuation of nearby populations.  EPA coordinates and implements a wide range of activities to ensure that adequate and timely response measures are taken in communities affected by hazardous substances releases and oil spills where state and local first responder capabilities have been exceeded or where additional support is needed. Below is a video of Region 7 On Scene Coordinators conducting a decontamination exercise.

For the geospatial enthusiasts amongst you, it is possible to access the data regarding spills around the country all the way back to 1982.  You can download it here, although the NRC also provides for more specific queries by state and by county. The address matching might be tough, especially for those older years where addresses like ‘5 miles south on County Road WW’ were more prevalent.  I whipped up the following map of my county in just a couple minutes using ArcGIS Explorer and an Online Geocoder. I admit, I dropped about 30 or so that I could have included if I spent a bit more time cleaning up the data. 

Hopefully I can get one or two of our OSCs to write a blog entry in the future since they have some really interesting stories to tell.  That is if they aren’t too busy answering the phone.

Jeffery Robichaud is a second generation EPA scientist who has worked for the Agency since 1998.  He currently serves as Deputy Director of EPA Region 7′s Environmental Services Division, and also serves as one of the Region’s two Scientific Support Coordinator whose role is to serve as a science adviser to the Federal On-Scence Coordinators if requested to obtain consensus on scientific issues, communicate differing opinions and resolve conflicting scientific information.

 

 

Something fun that’s coming at Google I/O 2013 – map diving! Here’s a first look at a fun 3D virtual Google maps realistic fly-through experience that will be shown off at Google I/O. Details from the developers… Join the Instrument … Continue reading →

The amazing Android powered mobile devices just keep on coming… is it any wonder why Android is dominating the mobile ecosystem? Enter the 7″ tablet running Jelly Bean and supporting 3G voice calling from AirTyme (India). No longer a simple … Continue reading →

ROK is pleased to announce the release of SRC Citizens, a mobile application for the iOS platform.  Its a great tool for citizens of Santa Rosa County, FL to get quick information such as property information, school zones, airfield proximity, hurricane evacuation zones, fire hydrant proximity and more. Android coming soon...

Cultural reference explained

TL;DR – OGC looks like it is being played

A couple of weeks ago I sent this ill-tempered, ill-mannered – but quite funny – email rant (to *@*.com, so you’ve probably seen it already):

[lists.osgeo.org]

“The submitting organizations of the GeoServices REST API are and have been supporters of OGC since its earliest years. They have actively contributed to many of today’s OGC standards and have implemented many of them in their software products. They continue to be committed to the goals and mission of the OGC.”

All very motherhood and apple pie. I’m sure that the submitters help old ladies across the road too. What does it have to do with the standard though?

“Most aspects raised in the justification comments are not new and have been discussed at length before.”

The fact that the comments have been discussed before does not mean that they have been satisfactorily dealt with.

“It is also worth to point out again that the backward compatibility requirement with the existing implementations applies to the version of the candidate standard that is under vote. Once the standard has been adopted, changes will follow the OGC procedures and, for example, a future major revision could also break such backwards compatibility. However, OGC policies emphasize the importance of backwards compatibility between revisions of a standard and the careful considerations that are necessary in this process.”

So backwards compatibility overrides every other consideration now, but not in the future, except that it will because of existing OGC policies? This makes no sense at all.

“As part of the SWG deliberations, the specification has been reviewed and changes have been made to remove any implementation specific artifacts.”

The specification precisely, and in great detail, describes the entire functionality of a single piece of existing software. Simply deleting the company name from well-known constants does not constitute “removing implementation specific artifacts”.

And so and, and so forth.

Some of my procedural, er, concerns, were misplaced, but a significant one remains. The current OGC TC Policies and Procedures for TC votes allow for an appeal to arbitration to the OGC Review Board (RB). Unfortunately, the RB no longer exists, having been subsumed – more or less – into the OGC Architecture Board (OAB). However, the OAB clarified the voting procedure (leading, in part, to my rant), and does not appear to have left open the prospect of an appeal. I can’t get a definitive answer right now, so that might change. But if it doesn’t then, frankly, it stinks.

I sent that email in response to the, I felt, weasel words of the OGC GeoServices REST API Standards Working Group which were in turn a response to several No votes in the OGC standardisation process. I’d complained about the proposed standard before, and did not get a reply:

[lists.osgeo.org]

Setting aside whether or not the intentions of the submitting organisations are entirely altruistic; *and* setting aside whether or not the proposed standard is in-and-of-itself well enough written to be implementable; *and* setting aside whether or not there is too much overlap with existing OGC standards; *and* setting aside whether or not the proposed standard deserves to bear the moniker “REST”; the fact remains that the proposed standard simply presents the public face of the private data structures and functionality of a single piece of software (and why shouldn’t it – that is precisely what it was designed to do).

As such *all* other implementations must either map their capabilities to the proposed standard, or add capabilities to match the proposed standard. Whichever is necessary, the original implementation will short-to-medium term at the *very* least remain the gold standard.

This is not even about the submitting organisations, nor even the precise content of the proposed standard. Exactly the same arguments would hold true were we looking at UMN MapServer “map” files as a proposed OGC standard, for example. (Now I’ve gone and planted a crazy idea in a few heads…) The same arguments also applied over KML.

As long as the SWG can – legitimately, by the rules – cite “backwards compatibility” as a reason to reject comments made in the RFC period, as is rumoured, then everyone else just has to take the proposed standard more or less as-is.

Things have snowballed somewhat since my rant:

[lists.osgeo.org]

[lists.osgeo.org]

[lists.osgeo.org]

And:

[wiki.osgeo.org]

(As I write this, more than 60 people have signed up to a draft letter to OGC from OSGeo on that wiki page.)

Even OGC-couldn’t-care-less-er James has weighed in:

[www.spatiallyadjusted.com]

(I particularly like the first comment on that post, which makes the serious, valid point that the OGC list of standards is often used as a pick-and-mix way to generate a requirements specification. It won’t be a surprise to see W*S and GeoServices for REST (assuming that the worst happens, and it is adopted) both appearing as requirements for the same project soon.)

Where we are now is that both those in favour and those against are busy politicking, trying to get their own way. Esri even had a conference call with several OGC staffers, which I think is beyond the pale: the SWG should be standing behind this standard, not a single member, however large and influential. Of course the call might have been entirely innocent, but I can’t know for sure because no-one has told me (thus far).

I believe that this standard is bad for OGC, bad for the vast majority of  OGC members, and bad for the wider OGC community because:

• It has too much overlap with existing OGC standards
• It has had next to no changes despite multiple comments and requests, because backwards compatibility (with a single source, remember) trumped everything
• It sets an extremely unhealthy precedent for the next single-source API that comes in to OGC (maybe I’ll sponsor UMN MapServer MAP files after all…)

Howard Butler put the over-arching software engineering problem succinctly:

@jeffharrison @bflood @bartvdeijnden All of it. “Yours” or “mine” is proprietary by definition. “Ours” is an agreement.

— Howard Butler (@howardbutler) May 6, 2013

If you are reading this and are an as-yet undecided voter, then I urge you to vote No when the vote re-opens. If you are reading this and you are Ed Parsons, then shame on you for voting Yes.

My opposition to this standard does not mean that I think OGC or the W*S standards are somehow perfect; far from it.

The W*S standards suffer from the basic framework being designed back in 1998 (two years before Roy Fielding’s dissertation, RESTafarians). They have too naive a view of the web (eg abusing HTTP POST to stuff large requests into the server). In fact, I’ve argued that they are for the internet, not the web. On the other hand they have  too sophisticated a view of GIS/databases (eg feature editing, which is a good thing, but which is wrapped in transactions and feature-level locks, which are really an edge case). They suffer, like many standards – OGC and otherwise, from clever people thinking that they know best: GIS developers pontificating about the web; geodesists designing data structures; etc.

But adding more of the different-but-the-same, particularly in this manner, simply won’t help.

I’ll give myself the final word:

Painfully aware that the #OGC argle-bargle over #GeoServices is a tedious sideshow. The world is moving on from W*S, but not to more OGC

— Martin Daly (@mpdaly) April 8, 2013

 

Code reuse is always a good thing. If you use the .net MapGuide API, you may want to consider some options that can enhance re-usability of your code.



For those who don't know, the MapGuide API is an extension of a common subset known as the Geospatial Platform API. AutoCAD Map3D extends this subset to integrate with AutoCAD Map3D, MapGuide extends this common subset to support web applications and mg-desktop extends this subset to give you a portable MapGuide environment for your desktop applications.







As you can see from the diagram there are key abstract classes in the Geospatial Platform API that are derived by the various implementations (bolded for emphasis). It just so happens that these classes are the key classes for working with maps and layers and the rest of the API through service classes.

By writing your .net code to work against the abstract classes in the Geospatial Platform API, you get to maximize its reuse against the various extensions of this common subset. For example, have your code:

• Work against MgMapBase instead of MgMap, MgdMap or AcMapMap
• Work against MgLayerBase instead of MgLayer, MgdLayer or AcMapLayer
• Work against MgResourceService instead of AcMapResourceService or MgdResourceService

You hopefully get the idea. Where possible, work against the abstract class instead of the concrete implementation.



Writing code this way makes the code more amenable to easy manual dependency injection, with your MapGuide, mg-desktop or AutoCAD Map3D specific code doing the actual injecting, but the dependency injectee not having to care because it works against the abstract class and not the concrete implementations, thus allowing this injectee code to be re-used anywhere that can provide a concrete implementation of the class.

Of course, each extension of the common subset has their own implementation quirks. AutoCAD Map3D has some, mg-desktop has some too. But if such quirks do not affect you, then this coding strategy is something to consider if you want to re-use such code beyond MapGuide web applications.

FOSS4G-CEE aces up the sleeve. Part III

Yes, today is the day. Today, we shed light on our complete list of keynote speakers. In the previous weeks, we warmly welcomed: Schuyler Erle, Maria Antonia Brovelli, Dirk Frigne, Jeff McKenna, Paul C. Smits, Jáchym Čepický.

Today, the floor belongs to:

• Markus Neteler , founding-member of the Open Source Geospatial Foundation, now head of the GIS and Remote Sensing unit at the Research and Innovation Centre of the Fondazione Edmund Mach, Trento, Italy, author/co-author of several books and chapters on GRASS and various papers on GIS applications.



• Alyssa Wright, Vice President and Director of Solutions at OpenGeo, overseeing all client work for the OpenGeo Suite, OpenGeo’s comprehensive open source-based web mapping platform.



• Radu Puchiu, State Secretary in the Government of Romania, former State Counsellor to the Prime Minister, in charge of the transformation of Government online services.

We are very excited to disclose our complete keynote speakers list and we are honoured and proud that all these exceptional people have happily agreed to be part of FOSS4G-CEE 2013.

For more details, go here.

First there was the SF Live Bus map, then came the PDX Live Map (for Portland), now Seattle has its own animated live real-time map of its Metro Transit network.

Busdrone uses Google Maps to show the real-time location of Seattle's buses. Load up the map, sit back and watch as little blue markers navigate Seattle's streets. Hypnotic!

If you want to create one of these maps for your own city's bus network all you need is a timetable and a little peak at the code on GitHub.

With Mother’s Day coming up this weekend I thought I’d take a moment to share a little bit about my own mom, how she sparked my passion for the outdoors, and how we use the inReach to stay connected when I’m in the backcountry on an adventure.

I think it all started when my parents were State Park managers here in Maine. My sister and I grew up spending our summers at the parks, in places like Sebago Lake and Range Pond. Our family vacations always took place during the off season when the rest of the park visitors had gone home. It was great having the trails to ourselves although I was much older before I realized that most people wear bathing suits at the beach instead of pants and long sleeve shirts!

The picture below was taken at Bar Harbor in Acadia National Park, one of my mom’s favorite places. Our family still goes there each summer to camp at Lamoine State Park. I was two at the time of this photo and I’ve been told that during a brief moment of freedom I ran headlong into the ocean in full fall attire. I imagine this was the start of my mother’s concerns about my decision making abilities and why the inReach has become a valuable tool for her to check in and make sure I’m not doing something foolish…

My parents were teachers during the school year and led interpretive programs at their parks during the summer. My time in the outdoors was spent on nature walks and canoe trips, poking around in tide pools and climbing fire towers on the tops of mountains. I was very fortunate to have a mom who taught us to be stewards of our natural spaces. She shared her enthusiasm for the outdoors with her children and with all of the kids that she met at her State Parks over the years. To this day I hear her “leave no trace” reminders when I’m on the trail and see a bit of litter that needs to be carried out.

Fast forward a few years and flip back through the DeLorme blog a few pages and you’ll see how my mom’s influence on that two year old in the picture above has steered me to a career that, while more in the technology world – my dad was a science teacher after all, helps people explore the great outdoors while staying safe and connected, knowing where they are and being able to share their experiences with their friends and family. As you all know, I just came back from the Backpacker Climb for a Cause event raising money to send urban teens on wilderness outings. Next week I’m headed to Colorado to speak about GPS and Satellite Communication technology at the Sierra Club Leadership Outing. While I’m not as directly involved in the protection of our natural resources as my mom was, I like to think that here at DeLorme we encourage people to get outside and enjoy their time in the great outdoors.

Photo courtesy of Jon Dorn – Backpacker Magazine

Which brings us to the inReach… remember that two year old that ran headlong into the ocean? Well, I’m older now but through amazing opportunities provided by DeLorme I still manage to find myself in situations that make my mother a little nervous. The photo above was taken at the bottom of the first rope section on Mt Whitney (framed in the background) at 12,300 feet. My mom was following along on the map and sending the occasional message to see how I was doing. It was a special event for me, knowing that my family and friends were with me as I climbed. This was an experience echoed by many of the people on the Mt Whitney team who were also sharing their tracks and messages via the inReach.

So as I reflect on the different ways that my mom has helped to make me the man I am today I encourage you to do the same… and consider how you stay connected with her at Mother’s Day and with the rest of your family and friends when you strike off on your own adventures. Consider DeLorme’s inReach and inReach SE, the proven communication tool of my mom and her forever-two year old running headlong into adventures whenever he can find them.

…and one last picture taken on my mom’s last day as manager of Range Pond State Park, used as her retirement invitation. A final walk in the park with her son after 30 years of service. Well done mom, well done!

Happy Mother’s Day to you Mom, and to the rest of the mothers out there on this special weekend!

Take care,

Chip Noble

Team DeLorme

Filed under: Fun Stuff, inReach Tagged: DeLorme, inReach, Mother's Day

Popturf is a Google Map of important locations in popular culture. It can help you find out where your favorite movies or television shows were shot, where music history was made and even where your favorite books were set.

You can view all the Popturf locations on one Google Map or view individual maps showing you locations in Movies, Music, Television, Literature, Comic Books, Video Games, Technology, Art & Design and History.

Registered users can contribute to the Popturf map by adding new locations.

I found out about this TIMELAPSE Project today by TIME and Google. And as a map geek and a Landsat fanboi, I find this gem a very good time waster. […]

Planocio Eventos is a really well designed Spanish events map. My Spanish is terrible, so it is a testament to how well designed Planocio is that I had no trouble finding the categories of events and specific dates that I was interested in using the map's intuitive interface.

Users of the map can quickly find out what events are happening on a particular day by selecting a date from the left hand panel. All the events occurring on that date are then displayed on a Google Map and appear in the event listings panel.

Users can filter the events by category by selecting from the blue map marker menu that is placed to the left of the map. The user can change what week's events are displayed by clicking on the up and down arrows in the date side panel. The breadcrumb links above the map allow the user to find events by month and even by season. It really is a well thought out map.

An old feature of Foursquare that appeals to the datanerd in many tech users pops up information about location based behavior at check-in. So, after a few days of checking in at work you might learn it's the longest streak you've had of a daily check-in. This week, Foursquare upped the... Continue reading

An old feature of Foursquare that appeals to the datanerd in many tech users pops up information about location based behavior at check-in. So, after a few days of checking in at work you might learn it's the longest streak you've had of a daily check-in. This week, Foursquare upped the... Continue reading

Glass Navigation is pretty darn great. It prevents fumbling with devices and, unlike phones and some dedicated navigation devices, doesn’t require you take your eyes completely off the road in order to properly navigate. There are some obvious bugs to fix, but with a beta product... Continue reading

Glass Navigation is pretty darn great. It prevents fumbling with devices and, unlike phones and some dedicated navigation devices, doesn’t require you take your eyes completely off the road in order to properly navigate. There are some obvious bugs to fix, but with a beta product... Continue reading

If you only come out at night, or if you live in a hole, vision is perhaps not the best solution for you, and a robot modeled after a shrew can now make maps using just tactile feedback from a prodigious set of artificial whiskers. The Shrewbot ismodeled after the Etruscan pygmy... Continue reading

If you only come out at night, or if you live in a hole, vision is perhaps not the best solution for you, and a robot modeled after a shrew can now make maps using just tactile feedback from a prodigious set of artificial whiskers. The Shrewbot ismodeled after the Etruscan pygmy... Continue reading

Willamette Stream Channels Poster

Today’s MOTD is something that was going around the Twitter-sphere a few weeks ago. I put a link to it on my desktop, and re-found it tonight while organizing my files. Even though it’s not brand new, it is special enough to be noted here.

It is a spectacular piece of cartographic artwork. It’s so unique it almost doesn’t look like a map, but that is exactly what is is.

As the publication website says, this is a lidar derived digital elevation model of the Willamette River. Lidar (light-radar) is a technology that uses light to measure distances, and can be used to produce 3D images of the earths surface (i.e. a digital elevation model)

Basically, this is a topographic map. The brightest white areas are the lowest elevations, which are the existing stream channels. Older, historic stream channels show up as depressions in the landscape, shown in various shades of light-blue.

For more information about how this map was made, and to purchase a 17″ x 38″ poster, visit the Oregon Department of Geology and Mineral Resources website.

The New York Times has published an interesting Medicare Map that shows how much different hospitals charge Medicare throughout the country for the same treatment.

The map compares the charges made at 3,300 hospitals nationwide for the 100 most commonly performed treatments and procedures. The colored markers on the map show whether individual hospitals charged less than the average (blue markers), 1 to 2 times the average (yellow) or twice the national average (red).

Users can click on individual hospitals to view how much they charged Medicare in five common types of case and across a range of other types of medical case.  

Sandy Island has long appeared on maps and in GIS data. A research vessel in 2012 visit the supposed site of Sandy Island and discovered wide open ocean. How did this map myth originate?

The post The Map Myth of Sandy Island appeared first on GIS Lounge.

All these new OGC standards are sadly designed like it is still 1999.

If you don’t like ramblings, then here is the TL;DR for you:

TL;DR OGC Standards should be written for the future, not the present nor the past

I have to get something out of my chest. Yes, it is triggered by the current discussions about accepting GeoServices REST API as an OGC standard.

The current focus of the discussion, at the core, is around the issue that the GeoServices REST API is perceived as a set of competing standards (i.e redundant to the WFS/WMS/WCS/etc specs) that don’t have an open (read open source) reference implementation that any organization can refer to when trying to implement the standard.

To me, this discussion is more about politics (which I do agree is a valid topic to discuss) than about the reality of the standards that do come out of the OGC lately.

Reading any of the documents from the OGC make me feel like I am listening to Prince (before!) 1999.

Seriously.

Standards should be written for the future – not the present

I remember several years back when HTML5 was the hot new thing. The standards were being worked on a lot, but most of the browsers did not support any of the features from HTML5. The table at caniuse.com (a place where you could go to see what HTML5 features were implemented by what browsers) were mostly red (i.e. not implemented).

Fast forward four years into the future, most of it is green. That is because those standards became adopted and the functionality that it brought to life makes everyone’s life better.

Designed in the past, adopted in the future. The way it should be.

Contrast this with the current set of standards that we have “up for comment” from the OGC right now…

Before you think that I am against the OGC, let me tell you that you could not be further from the truth. In most presentations that I have given in the last 6 years (at several conferences, some keynotes, and even my own GeoMeetups ) I have always dedicated slides and time to convince/teach people about the OGC and the importance of standards.

Yet, although I have several friends that do work in these standard bodies (I love you guys – you know who you are!), it still feels that there is an unnecessary amount of bureaucracy at the OGC that is truly killing innovation.

OGC is making “standards” that are outdated, unnecessarily overly-complicated, reference implementations that cannot be used as a reference (read below!), and a whole bunch of protocols that resemble what a protocol would have looked like in 1999. They completely ignore what we have learned in the last decade.

Let me give you some real examples.

- WFS, XML Datastores and queries:

XML Datastores were all the academic hype back in the day. Yet they never took off (with reason). The query language used by OGC (which is another OGC standard) assumes the underlying data store is XML. For those of you not familiar with what this actually means, it is more than a representation of something as text. It assumes you have an XML Infoset.

At the core, the OGC spec for Filters is just an attempt to represent SQL as something equivalent to an XPath expression to be used on the web (?!?).

Anybody that has ever tried implementing WFS will understand what this means. Basically, several months of development, to create a parser that grabs an xml document and turns it back into SQL. But to do it correctly, you don’t have to generate one SQL statement, but several ones. Why? Because the query language is so expressive, than in reality you should be able to create expressions that span multiple underlying tables (it assumes it is an XML Datastore after all) which basically makes you just really sad and go home depressed because it is unnecessarily complex.

I have an idea, why, instead of writing a client application that transforms my query into OGC filter speak, goes through a middleware that grabs the OGC filter speak and turns it back into SQL which then goes to my underlying database - instead - do I just not have one method (ExecuteSQL) and be done with it. Use SQL. Let’s just not reinvent a SQL. The CartoDB guys seem to have this right in their API . One tiny little api, you pass a string… it does a lot! You know how long it takes to implement something like this? Hours, not months. And you actually have more power than what is expressed by the OGC equivalent. Problem solved.

- XML/GML as a transport mechanism:

This is the mechanism of transport of choice for OGC standards. I have a two year old post about why I think this is far from ideal. Although there are some updates to be made to that answer, at the core, it still remains valid. If somebody tells you that the answer is to ‘gzip’ GML, then, they are wrong (a topic for a future post).

I am still baffled as to why do none of the standards, yet, refer to things like Protobuffers, MessagePack, Thrift, Avro - gosh - anything that we have learned to do better in the past decade!

Switching to any of these, or including them as serialization options would make all the implementations of these standards better/faster.

- “Reference Implementations” that cannot be referenced It is true that a “reference implementation” should be able to be, well, referenced. I cannot currently look at how the GeoServices REST reference implementation (I guess ArcGIS Server) is implemented internally, thus, the specification fails at having a valid reference implementation.

Does that mean that for a reference implementation to be useful it needs to be Open Source?

Maybe that is not enough.

Some people would argue that the reference implementations for the OGC GeoPackage spec, Spatialite, is arguably also not a good choice.

Why?

Because you cannot copy/paste or even create “derivative work” from it without also having to GPL/LGPL your work. Is looking at a reference implementation, seeing the internals, and copying how it works considered derivative work? Those are the type of questions that no developer wants to deal with, so IMHO, the OGC has the responsibility to pick reference implementation that in unencumbered by these issues. By picking Spatialite and a proprietary server (ArcGIS Server) as reference implementations to their respective specs, the OGC is showing that they are either 1) really clueless about these type of issues, or 2) don’t care. Either way, this is horrible.

- Websockets?

I wish! Where are the implementations that take advantage of full duplex communications? Server side push? Seriously, are we still assuming users are going to poll all the time and transfer state in every request? This is exactly why most real-time tracking implementations are done incorrectly. Why are we still stuck in a stateless architecture design? We can do server push now without Flash or Java (or Silverlight yikes!). Websockets exist. USE THEM.

I touched superficially around this topic in the last PyCon. The video is up if you are interested.

- [Https,] Authentication/authorization, security

I don’t even want to touch on authentication/authorization around all the OGC specs. OAuthv2, or even the first version of that are far better than what is expected of the current implementations of security. Most people rely on passing USERNAME/PASSWORD in the request. This is horrible.

But wait, I guess if I use [https] that means I am secure right? Hell no!

Look at this video from last year’s Blackhat (quite awesome actually) and then come back with a straight face and tell me this is fine.

** - SPDY** If you do not what SPDY is, then, you will definitely be surprised to tell you that all your [https] traffic to Google , Facebook and Twitter is not going over “traditional” SSL.

Yes, they use a special protocol called SPDY.

It is faster than traditional http (even though it is going over an encrypted channel!). Think about this for a sec.

Does the OGC use SPDY? Of course not. Does it make a difference? Check out this video of last year’s Google I/O about SPDY and you be the judge.

- Non-blocking servers.

The Mapbox guys get it. They use node.js for serving their tiles. Do you want to understand why this is a good thing? Check out this presentation by Ryan Dahl 3 years ago which gives an overview of why this is the case.

Anyway.

I can go on and ramble forever, but I want this to be more constructive.

**The discussion around OGC specs should be about what GIS is going to be like in 5 years in the future. **

• Why did the OGC not work with the W3C to push WebSQL through (now stalled)? Imagine spatial extensions in every browser on the client side?

• Why don’t we have a good spec about spatial replication, spatial changetsets, optimistic/pessimistic/long-transaction versioning, etc?

• Why don’t we have specs that take advantage of web stateful connections?

• Why don’t we have a spec for highly compressed geometries?

• Why don’t we have a spec that defines better editing capabilities? (hint: WFS-T is not enough for several editing workflows)

• Why don’t we have a spec that defines how to truly take advantage time-based datasets?

The list goes on.

Instead, the community as a whole is having long discussions analogous to the one about whether 3857, 3785 or 900913 was a better number for the Web Mercator definition.

Listen OGC, want to see a good standard definition? Check out MBTiles. Easy to implement, and to the point.

Want to change? Design/Define for the future - not for the present nor the past.

So Waze may be part of Facebook for a cool ”One Billion Dollars”.

After spending $1 billion on Instagram last year to keep pace with the mobile photo explosion, Facebook is now reportedly ready to spend a similar amount on popular social driving app Waze.

Waze is considered the second most popular navigation map in the USA so it’s not too much of a surprise. I do find it interesting though that Facebook would spend this money on the data. They don’t need the users, that’s for sure and they can buy engineers to solve the problem. I can only think it is better to own Waze than use OpenStreetMap data that you have to share. Are we seeing problems with the license? I hope this is a huge discussion at OSM PLUS next month.

UPDATE - Marc Prioleau has some great insight on his blog. His kicker at the end?

Why OSM isn’t a better option is another whole discussion. I suspect it revolves around ownership and data rights.

Some believe there is a lost city yet to be found in these jungles and that LiDAR may be the technology that will help them find it. Continue reading →



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In my daily search for new and exciting implementations of the Google Maps API I normally check Twitter mentions of 'Google Maps'. One of the problems with using Twitter for this kind of search is that the results are often over-run with lame Google Maps jokes.

Probably the lamest joke, and one that never seems to disappear from my Twitter search results, is this:

"I've never skydived but I have zoomed into Google Maps really fast."

Well now you can skydive for real on Google Maps - but only if you are attending Google I/O next week. Check out the video to see it in action and to learn a little more about how this game was developed.

So there is a ton of talk about Esri’s REST API trying to become an OGC standard on Twitter. We mentioned it on my hangout yesterday and it’s still a hot topic. Here are some bullet points.

• OGC exists to help software vendors, open source projects, contractors market to the federal government. There is no altruistic goal other than to make money.

• OGC standards are standard only in the world of contracts. Just because Esri gets their REST API “blessed” doesn’t make it worth using any more than it was before.

• Esri submitted their REST API to OGC so they could use it in federal contracts instead of existing OGC standards which nobody uses.

• Esri REST API won’t be used outside of Esri software so it really doesn’t matter.

• Esri’s consulting arm is competing with all of us. Beware as they’ll squeeze you out the minute they can.

• OGC standards suck so that’s why people are always proposing new ones. By next year there will be another “standard” coming up that will replace Esri’s.

• The simple fact that there is a proposal for ”OGCJSON” should tell you all you need to know about these standards.

• Esri exists to make money, that’s OK as I work for the same reasons. Just don’t wrap their business model up with saving the world.

• KML is the only OGC Standard people actually use. The rest are check boxes on a form.

Don’t get emotional about OGC standards. That’s what they want, people to actually start caring.

By Shawn Henderson

Recently a friend introduced me to a website called Reddit. For those who are unfamiliar with Reddit, it’s basically a forum message board on steroids. Redditors can post news articles, images, links, etc. in all different topic areas. Trust me; you can spend hours looking through the different stories and images many of which are amusing at times. Several days ago I was perusing one of the sections and ran across the picture below, which appears to be from a 1950’s magazine article. Ah yes the 1950’s, sock hops, soda fountains, drive-in movies… and DDT? I poked around a little more and found several You-Tube videos of DDT being applied to swimming pools with kids still in them and even one of a gentleman spraying DDT on a carrot and then proceeding to eat it portraying its relative safety. Needless to say we have learned a lot since the 50s.

EPA is responsible for regulating pesticides under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA). The beginnings of FIFRA actually date way back to a 1910 pesticide control law, with FIFRA itself being passed in 1947. In its earliest incarnation FIFRA was mostly concerned with labeling to ensure that folks were getting actual pesticides like DDT and not watered down ineffective products.

In 1972 FIFRA was re-written when it was amended by the Federal Environmental Pesticide Control Act (FEPCA) and has been amended numerous times since 1972, including some significant amendments in the form of the Food Quality Protection Act (FQPA) of 1996. In its current form, FIFRA mandates that EPA regulate the use and sale of pesticides to protect human health and preserve the environment. Under FIFRA, EPA is specifically authorized to: (1) strengthen the registration process by shifting the burden of proof to the chemical manufacturer, (2) enforce compliance against banned and unregistered products, and (3) promulgate a regulatory framework missing from the original law. You can learn more about EPA’s role with FIFRA at EPA’s Pesticide website.

Much has changed since the 1950s. DDT has been classified as a probable human carcinogen and has been found to be persistent in the environment. It is one chemical in a suite of pesticides that we look for when analyzing samples of water quality. In my role as EPA Region 7’s STORET (Water Quality Storage and Retrieval System), I get a chance to see all of the water quality data for the Region, and thankfully, we have noticed a downward trend in DDT concentrations over the years, especially in fish tissue. USGS’s National Water Quality Assessment Program has found the same thing.  However, the picture above should serve as a constant reminder of the need to continue to monitor for chemicals in our environment and study their relationship with human health.  Something we think of as great today, might not be so good thirty years from now.

 

Shawn Henderson is an Environmental Protection Specialist with the Environmental Assessment and Monitoring Branch of the Environmental Services Division. He is a part of the Aqua Team, and conducts water quality sampling around the Region’s four states.  He has a Computer Science degree from Park University and helped to develop the Region’s KCWaterBug app and kcwaters.org.

 

Google Maps, the U.S. Geological Survey, NASA and TIME have come together to release an awesome new interactive timelapse application for viewing satellite images of the Earth.

Timelapse allows you to create a timelapse sequence from satellite images (from 1984 to 2012) for anywhere on Earth.The application comes with a number of default views that allow you to view timelapse animations of satellite images showing the sprawling growth of Las Vegas, the building of Dubai, the shrinking of the Mendenhall Glacier and the drying-up of Lake Urmia.

The first thing you will probably want to do (after watching some of the default animations) is to view a timelapse from satellite images of your own town. When you've done that you might want to use the Google Map to centre on and view timelapse animations of Puning, China the World's fastest growing town) and Hong Kong (to view the reclamation of land from the sea).

A little user tip  The timelapse animations look much better when played back at a slower speed. So mouse-over the date (bottom-left of the app) and change the playback speed from 'fast' to 'slow'. 

The series of Landsat satellites has been collecting global imagery continuously since 1972.  A total of eight satellites and millions of pictures (and trillions of pixels) has resulted in a hugh amount of imagery which, when compiled, visualizes the massive amount of global change over the past thirty+ years.  Landsat satellites capture imagery of the [...]

The post Timelapse Satellite Imagery – View Changes on Earth over Time appeared first on GIS Lounge.

The developers behind the excellent OpenSignal map have released a new mobile phone app and crowd-sourced Google Map called WeatherSignal.

WeatherSignal takes advantage of the ever growing number of sensors built into modern smartphones. Using these sensors the WeatherSignal app is able to gather data about temperature, pressure and humidity. WeatherSignal is then able to use this crowd-sourced data to create a worldwide live updating map of weather conditions.

As you might have already discovered all our apps are optimized for all the tablets you can find on the market today.

Make sure to shoot us an email and leave us a comment on our twitter and facebook pages.

Oh yes, I love art… I also love music too, heck, who doesn’t right? Well, I know you GeoGeeks and music lovers will really dig this one as we stumble onto yet another amazing cartographic product that quite simply will … Continue reading →

Waze is back in the acquisition rumor mill.  In January, it was a rumor about Apple (propagated and debunked on successive days by TechCrunch).  Today, the rumored buyer is Facebook.  The one constant seems to be the price:  $1B.

Not sure if it’s true this time, but even if it’s not, it does raise the question: Is Waze a billion dollar company?

The comparable most often used is Instagram.  Given that Facebook is the subject of the rumors this time, that’s in every article I’ve seem so far.  The parallels are obvious, small company with limited revenue but growing user base bought for a $1B.

I don’t think the parallel holds.  IF Waze is being bought for that amount (and I think it could happen), it is not for the same reasons that Facebook bought Instagram.  If Waze is worth  $1B, it is not for the 40+M users of their traffic app.  It would be for the underlying map data that they are building.

Facebook bought Instagram because they had a fast growing user base in a space (photography) that was near and dear to Facebook’s heart.  Neither of those factors justify that sort of money for Waze.  Even considering their 44M users (and I suspect that the active users are a fraction of that), that barely shows as a blip on Facebook’s 1.1B users. And Facebook hasn’t shown any interest in maps and location, much less navigation, much less traffic. I doubt they’d buy Waze to get a traffic app.

What’s really valuable at Waze is what most people don’t see:  the underlying map data that they are building as a result of all those GPS traces collected from their users. By compiling millions of these traces overlaid on publicly available map data, they have been building a crowd-sourced road map database. And worldwide map data is very hard to build, which is why there are so few of them.

If the rumor is true (and the price is in that ballpark), it would indicate that Facebook wants to complement their moves into local search (Facebook Nearby) with their own mapping platform and their own mapping data underneath that. Waze gives them both, at least at some starting level. Said another way, if the price really is in the $1B range, it’s not for the revenue, or the team, or the 44M users or even the quirky traffic app.  It would have to be for the map data.

I have noticed that Waze management has been describing their company much more as a mapping platform in recent interviews (for instance, here with Liz Gannes).  A year ago, it was all about the app.  Not so much recently.  They seem to have focused on the maps and the data.

From the outside, it is hard to know how good this data is. I suspect it is good in some areas and not so good in others.  However, Waze’s map methodology gets much better if you extend it from their 44M user base to Facebook’s.  You get 1.1B users and much better geographic coverage. That could possibly combine to bring the quality of that map up very quickly.

I have no inside knowledge as to whether the rumors are true.  But if they are true, I think that you go down a wrong path by thinking about Waze as a second Instagram acquisition.  They would be valued for the underlying data, not the app.

And if it is true, advanced congratulations to Waze!

Addendum:  Why OSM isn’t a better option is another whole discussion. I suspect it revolves around ownership and data rights.

 

OpenSignal is the team that offers and app you run on your cell phone to crowdsource carrier coverage. Now it's launched WeatherSignal, which does the same thing, but for weather. Alas only the latest (Samsung Galaxy S4) phones have all the sensors the app can tap, but older ones can at... Continue reading

OpenSignal is the team that offers and app you run on your cell phone to crowdsource carrier coverage. Now it's launched WeatherSignal, which does the same thing, but for weather. Alas only the latest (Samsung Galaxy S4) phones have all the sensors the app can tap, but older ones can at... Continue reading

There’s no arguing that OpenStreetMap (OSM) has exploded in use and popularity, heck, just look at the basemap layer options in any online web mapping services and you’ll see OSM as an option. Often considered the wikipedia of the mapping … Continue reading →

At the Distributech 2013 conference, the largest electric power distribution conference in North America with attendance of about 9600, earler ths year in San Diego, if there was one consistent message, it was that smart grid has become mainstream - every utilty is doing something related to smart grid. 

I was interested in how gespatial was being used for smart grid applications by vendors at Distributech.  At the conference there were something on the order of 400 talks and panels.  Of these only a few explicitly mentioned geospatial or GIS so you might have concluded that geospatial was not playing a very important role in smart grid.  But the reality is quite different.  I talked directly to about 18 companies, mostly vendors, whom I asked about their use of geospatial technology.  All but two said that they were using geospatial technology in some capacity.

Geospatial analytics

One of the most interesting from the perspective of the application of geospatial technology for analytics was Tantalus Systems.  Tantalus provides utilities with an intelligent communications infrastructure supporting smart grid. Tantalus' network solutions rely on wired, wireless, or a combination for bidirectional communications.  Tantalus can integrate with well-known GISs like ArcGIS, or alternatively can provide an open source geospatial solution.

RF network analysis

Geospatial technology is used by Tantalus customers in several different capacities.  The first is to help identify problems or misalignment of resources in the radio frequency (RF) and electric grid network.  Visualizing the RF and distribution network geographically enables customers to identify and resolve problems in the RF network.   According to Dave Kauffman, Senior Product Manager for Applications and Interfaces at Tantalus, “GIS brings an entirely new dimension to problem solving for utilities. Before, our customers had to try to understand the source of problems by looking at tables and reports, but they found that with the geospatial view, the source of the problem, typically obstructions, became much easier to identify and correct."

Predictive maintenance

Tantalus customers also use geospatial analytics to look for patterns in outages by overlaying historical outage events on the distribution network and maps showing soil types, weather patterns, and traffic density patterns. Using this type of analytical approach can identify patterns that make it possible to identify equipment that is susceptible to failure and correct the problem before it actually fails.

Reducing risk in Volt/VAR

One of the new areas where GIS is just beginning to be be applied is voltage maps, a new application that Dave is very excited about. When a utility is implementing Volt/VAR at a substation to reduce load, voltages reported by smart meters can be mapped geographically in real-time across the entire distribution network in the form of isovolt maps. This makes it possible to identify areas of low voltage in real time, which is critical because the voltage cannot be allowed to drop below a tolerance mandated by the regulator in order to avoid potential damage to utility and consumer devices.

QGIS equals no need for ESRI anymore. Quantum GIS is replacing our ArcGIS platform. Simple Why, with the up and coming of QGIS 2.0 (currently at 1.9 alpha) Why the...



Map and GIS News finding blog. With so many Maps and GIS sites online now it is hard to find the good from the not so good. This blog tries to cut the cream and provide you with the newest, fastest, cleanest and most user friendly maps that are available online. News has location and it is mapped.

The Atlas of Ingenious Ireland is an Irish geek's dream map. The map helps you find Ireland’s ingenious places; from museums to hi-tech research institutions Ingenious Ireland shows you where great discoveries were made, and where great scientists and inventors were born and worked.

Using the map you can find great places to visit in Ireland. For example, why not visit the world's oldest astronomical observatory at Newgrange, made 5,000 years ago in the Stone Age. Or you could visit the spot at Broome Bridge where Sir William Rowan Hamilton, in 1843, invented a revolutionary new algebra. Hamilton's ‘quaternions’ describe things moving in 3D, and are now used to orient spacecraft, in 3D animations and in computer games.


Non-Irish geeks and nerds can use Nerdy Day Trips instead.

When nerds go to the beach they go to Marconi Beach, named after the Italian inventor Guglielmo Marconi. Or at least they do if they consult Nerdy Day Trips.

This Google Map is a great collection of interesting places to visit. Consulting the map for my own part of London I find that Edmund Halley's grave is nearby, there is a Cold War era nuclear bunker museum just down the road and numerous small museums nearby that I never knew existed.

Dodota is only the second Iranian Google Maps app that we have featured on Google Maps Mania. Dodota is a real estate search application that allows Iranians to search for property by location, price and by property features.

The results of each search are displayed on a Google Map. Users can click on each of the properties shown on the map to view the price of the property and click through to view the property's full details.

Dodata is a Persian language property search portal. Currently the site has coverage in Tehran, Mashad, Karaj, Isfahan, Tabriz, Rasht, Shiraz, Kish and other Persian speaking towns.

This past fall, NASA DEVELOP interns partnered with the U.S. Fish and Wildlife Service and the Oregon Department of Forestry to apply NASA EOS in understanding the impact of the 2012 wildfire season in Oregon on landscape and air quality. DEVELOP students combined VIIRS and Landsat 7 data to create burn scars and fire risk maps, and CALIPSO curtains and HYSPLIT modeling to visualize the extent of smoke plumes and particulate matter from the fires. 

Facebook is in the final stages of a deal to buy Waze per Israeli publication Calcalist (Hebrew only).  The Next Web cites Assaf Gilad, describing Facebook is in "advanced talks" to buy Waze for about $1 billion. Facebook and Waze are partners. Wazers can share their drives via the... Continue reading

Facebook is in the final stages of a deal to buy Waze per Israeli publication Calcalist (Hebrew only).  The Next Web cites Assaf Gilad, describing Facebook is in "advanced talks" to buy Waze for about $1 billion. Facebook and Waze are partners. Wazers can share their drives via the... Continue reading

The Massachussetts Bay Transportation Authority (MBTA) is essentially seeking new design ideas for its subway map - in the space of three weeks, for free, and with no rights retained by the cartographer. And if you win this contest? You get… um, fleeting glory, apparently. Andy Woodruff doesn't think this is such a great idea.

We had this big raster that we needed to chop up into tiles and only extract a portion of for load into PostGIS. raster2pgsql doesn't currently have an option to pull just a portion of a raster and also we don't have the windows raster2pgsql compiled with MrSID support. Luckily GDAL commandline gdal_translate has this switch that allows you to specify a chunk of a raster to grab based on a projected or unprojected box window. We wanted to grab just that portion that is part of boston and chunk it into bite size pieces. What we needed was a grid generator similar to what we described a while back in Map Dicing and other stuff that would chop our neighborhood into bite sized tiles we could then use to generate the relevant gdal_translate command. Instead of using temp tables and all that stuff, we decided to try with the ST_Tile raster function. Creating an empty raster and then tiling it.

Note the repurposing: Creating a raster with no bands to accomplish a task that has nothing to do with rasters, so that we can then apply it to something to do with rasters. Gridding is a surprisingly common step in a lot of spatial processing workflows.

Here is the SQL to do it and we'll explain in a separate article in more detail.

In a nutshell, we're using PostGIS raster technology (ST_Tile function introduced in PostGIS 2.1) that we demonstrated in Waiting for PostGIS 2.1 ST_Tile to create a grid because PostGIS geometry doesn't have cool gridding function like SpatiaLite has :). SpatialLite tesselation. Perhaps in PostGIS 2.2 we'll see some of these SpatiaLite niceties. However ST_Tile does the trick fairly nicely and quickly. For this example took under 600 ms to generate 1524 rows of GDAL commands.

Continue reading "Chopping rasters with gdal_translate"

I sometimes get surprised to find out that some people don’t know how easy is to get GIS packages on Ubuntu. UbuntuGIS is really one of the easiest ways to get up and running. You will notice that there are two repos.

UbuntuGIS “Stable” which has really old packages. You most likely don’t want that.

UbuntuGIS “Unstable” which is really not unstable at all. It just has newer packages. You do want that!

To get it working in your Ubuntu system add the ubuntugis-unstable repo:

sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable -y sudo apt-get update sudo apt-get upgrade

Now you can install all kinds of cool packages.

sudo apt-get install postgis gdal qgis

Is an example of how to get gdal, postgis and qgis ready to go.

Enjoy.

The Old Weather project is a crowdsourcing data gathering endeavor to understand and map historical weather variability.

The post Help Map Historical Weather From Ship Logs appeared first on GIS Lounge.

Our friends down under at All Things Spatial inform us that Geoscience Australia has released a new, Google Maps based, Discovery and Delivery System. The map has been created to provide public access to a diverse range of data, products and services available from the organisation.

The map includes a number of overlay layers, including topography, geology, landcover, gravity image and magnetic image. The map also includes access to over 100,000 historic Landsat-7 and Landsat-5 images of Australia captured between 2000 and 2010. These can be viewed as WMS overlays on the map or can be downloaded as data.

"We launched the ReCap Photo public trial yesterday… Its available to anybody with an Autodesk 360 account for the next few months." Continue reading →



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Some weeks ago I visualised the Swiss cantons (states) and their population numbers using what information visualization scientists call a linked view. You can click through to the actual, interactive visualization: here in German or here in French. In what follows I’ll describe the steps of data preparation for this visualization. I decided to keep the specifics on the implementation in D3.js for a third post in order to spare your scroll-wheel and -finger (so stay tuned for that one). 

Intro

Welcome to the second part of this series in which I describe the production of this linked view with a population cartogram (top right):

In case you missed it: in the first post of this series, you can read about the conceptual thinking that went into this visualization. But now let’s dive into some geodata-crunching:

Technically

GIS pre-processing

In what follows, I’ll try to give you a thorough description of my approach at data processing. I’ll include some screenshots of intermediate results. Obviously, I don’t know how familiar you are with GIS and spatial analysis terminology, so please bear with me if my description is too exhaustive. Conversely, speak up in the comments section, if I have forgotten something or something is not clear. I did all of the GIS analysis in Esri ArcGIS, however, any GIS that can handle vector data will do.

I started off with the following input data:

• Outlines of administrative units (cantons and cities)
• Spatially distributed population data from Swiss census

The preparation of the administrative units was quite straightforward: I applied a Union operation in GIS (ArcGIS Help Topic here). Then I did some tidying of the attributes and applied a set of geometric simplifications (polygon outline generalisations). The purpose of these is basically weeding out vertices from the geometries while preserving shape as well as possible. The bigger goal being, of course, simplifying the geometries enough for a fluid web experience down the line.

Swiss census data comes as a point grid at 100 meters resolution. Precise data characteristics don’t matter too much. And one could also use a thematic variable that comes at the same resolution as the display units – cantons and cities in this case. While the handling of canton/city level thematic data would be much easier, the spatially distributed thematic variable in this case allows for a more representative cartogram. If you wonder why, consider, for example, a US setting: Salt Lake City would cause a big local distortion in a cartogram using spatially distributed data, whereas its population would be spread out uniformly throughout all of Utah, if you use state-level data. This effect causes visible differences in the cartogram in regions where population distribution is not spatially uniform.

The GIS processing chain starts with these steps:

• Generation of a grid (in my case at 5 km resolution, but that number is a bit dependent on the resolution of your input data, your area of interest and maybe your application; as a rule of thumb, I’d suggest a grid resolution that is similar to the size of your hexagons). Any regular tesselation other than a rectangular grid will also do.
• Union operation on the grid cells and the administrative units. This yields smaller spatial analysis units, that follow the boundaries between administrative units.
• Spatial join of thematic variable to the new spatial units. A spatial join is a GIS operation where the spatial relationship of entities in two different datasets is evaluated. If a specified relationship is fulfilled, the characteristics of the features in the join dataset are joined to the features in the target dataset. The spatial relationship for this operation was containment (i.e. the criterion was: is a given census data point within the spatial unit at hand?). The join operation encompassed summing up the values. The overall process yields the sum of the population at all census data points which fall within a given spatial analysis unit – or, without the GIS lingo: the total population per unit).

 

For distortions you need a Scape… toad

The resulting data in Shapefile format was then transferred to the cartogram software Scapetoad. Scapetoad is a freely available Java software developed in the Choros Laboratory at EPFL in Lausanne. It employs the diffusion-based cartogram algorithm by Gastner–Newman. I did several model runs and iteratively tuned the algorithm parameters. That encompassed mainly striking an acceptable balance between subjective quality of the result and cartogram computation time. Unfortunately, I cannot give heuristics for this, you’ll really simply have to try with your data.

When I was happy with the result, I re-imported the cartogram dataset from Scapetoad into the GIS and used a Dissolve operation to aggregate the units back into regions (again, any GIS will do, but the precise name for the operation may vary).

Cartogram production part 1: (1) Preparation of cantons and cities dataset (2) Union of dataset with grid (3) Import into Scapetoad and distorting (4) Re-import into GIS and dissolving the geometries

Enter the hexagons

After these steps, I used a third-party add-on to ArcGIS to create a hexagonal grid (other GISs may have built-in support for creating hexagons). I chose the resolution of this grid to be similar to the one used for creating the spatial units before the spatial join and cartogram generation. I think that is an okay heuristic for dealing with resolution sensitivity or scale issues and MAUP (each of these can spark long discussions, but I’ll spare you).

Then I used another spatial join: this time on the distorted geometries and the hexagonal grid. Thus, I could automatically assign hexagons the respective region code, whenever the hexagons where located completely inside a distorted region. I did not use automatic conflict resolution on hexagons located on borders between distorted regions. While doing this would be perfectly possible in GIS, I actually wanted the wiggle room these unassigned hexagons gave me.

To conclude the cartogram generation, I manually assigned the border hexagons to adequate administrative units. In this subjective approach I employed two important cartographic principles:

• shape preservation
• topology preservation

It may seem odd to talk of shape preservation in the case of a cartogram (whose point are the distortions), but I hypothesise that, also for cartograms, preserving some key features helps people appreciate the geometries better. As an example, I maintained the small “antennae” of Grisons (near the right/eastern edge of below graphic) although I thus locally overestimated the population a bit (see graphic below). I also overemphasised the bays of the lakes bordering some cities (Geneva (bottom-left), Lucerne (below center) and Zurich (biggest city)). Features such as these are so well-known by people familiar with the geography, that they help those users recognise the unusual geometries.

Cartogram production part 2: (1) Overlay of hexagonal grid onto geometries (2) Spatial join and manual clean-up (3) Dissolving the hexagons into distorted administrative units

Examples for preservation of topology were cantons of Obwalden, Nidwalden and Uri (near the center). In an early iteration, these touched the border of Italy in the south, between Valais and Ticino. This is not the case in geographic space, though. I manually overrode that configuration in order to replicate the topology of the geographic regions closely, thus also fostering recognition.

Comparison between the conventional (Gastner-Newman) cartogram and one with the “hexagon treatment”

Quality checking and file format conversion

Throughout these manual interventions, I kept an eye on the quality of the representation using a simple, dynamically updated scatterplot that related the number of hexagons per distorted region with the total population of the respective region. The coefficient of correlation, R², started out high and with the end result I achieved a value greater than 0.99, that is the representation in the cartogram was very close to the actual population numbers: Nice!

For the visualization I couldn’t use the antiquated Shapefiles, but instead opted for the Topojson format by Mike Bostock (who also happens to be the creator of D3). Topojson of course plays well with Javascript and thus also D3. In my visualization, I wanted to display three datasets: the aggregated distorted geometries of cantons and cities, the tiny hexagons which they consist of as well as the undistorted geometries for my reference map. Thus, I converted all these datasets to Topojson files using an online service called shpescape. But other options do exist, such as GDAL/OGR (see Mike’s approach with that tool in his tutorial).

With the first visualization prototype, a problem became apparent: For the cartogram, the numerous small hexagons were supposed to be loaded and displayed first. Only after, the cantons and cities should be overlaid on them, with a slight transparency. But ever so often the considerably bigger hexagon Topojson file would be loaded and displayed in D3 only after the cantons and cities and thus the hexagons were on top of the latter instead of the other way around. An easy way to avoid this was the merging of all data files into one big file. To that end, I used the following syntax adapted from the afore-mentioned tutorial by Mike (topojson needs to be installed at this point):

topojson -o swiss_regions.json hexagons.json distorted_units.json undistorted_units.json

 

And with the first line of code: That’s it with data-processing. I started out from a “normal” official cantons and cities dataset and Swiss census data. Through various GIS processing steps, the use of Scapetoad for distorting, some more GIS including manual interventions and conversion, I obtained the Topojson file that would be at the core of my visualization.

The manual steps in the above process may seem tedious, but they took maybe an hour at most in my case. It’s really a question of your setting: complexity of the shapes you’re dealing with and the size of your hexagons, mostly (one of these you can choose ;).

In the next post, I will give some pointers regarding the actual implementation of my visualization using D3. Until then, stay tuned – via Twitter, RSS or email subscription (see top-right)!

iD is a new easy-to-use OpenStreetMap editor that allows anybody with minimal technical knowledge to contribute GIS data to this crowd sourced mapping project.

The post OpenStreetMap Editor Designed by MapBox Goes Live appeared first on GIS Lounge.

Steve Citron-Pousty joined me to talk about some of the latest trends in the spatial world. We hit on Google Glass, Esri, Frameworks, housing prices, travel, iD and OSM, naming stadiums and of course being in an airport. The IRC log is here

I stumbled onto some research findings recently and what got my attention was not the headline, but rather, what the headline didn’t say. The pitch was that according to a study, 66% of small business use mobile technology (smartphones, tablets) … Continue reading →

As a semi-keen cyclist the thing I hate most in the world (after cars, buses and trucks) is hills. I really, really hate hills.

Thankfully I can now use the Flat Route Finder to find cycling routes that avoid the steepest slopes. The Flat Route Finder uses the Google Maps elevation service to suggest the flattest possible cycling route. Two elevation graphs are also provided to show you the steepest parts of the route and the route itself is colour-coded to show you the easiest and most difficult stages of the journey.

If you don't like the look of the suggested route (or perversely you want to find the steepest route) you can drag the route around to view the elevation and difficulty of alternative routes.

The party is over. During the 1990s anything related to IT was expensive and fat profit margins were easily procured. Post-9/11 was very good for geospatial contracting with both the escalation of defense spending to support three wars as well as the mushrooming requirements of the Department of Homeland Security. But now sequestration–and its impacts [...]

YouTube unveiled this week their trending video map which is currently being overrun by Charles "dead giveaway" Ramsey. The trends are split out among location, age, sex, and views vs. shares across the United States. More countries are planned to be added soon. I'm hoping that being able to zoom into your own neighborhood will also be added. That feature is commonly found in Google's emergency response maps, so why not?



Check it out at [www.youtube.com] :

I have written all manor of data maintenance apps over the years. One of the first apps I worked on professionally was a cadastral data maintenance monstrosity written in AML (shudders). I have created enough of these types of apps to know that I absolutely hate making these types of apps.

It isn’t just that they’re hard to code. And by hard to code, I mean really hard. They’re like ferreting a snowflake across the Sahara while trying to figure out what The Fountain was about hard. It’s more this: it’s almost impossible to create a data maintenance app that people want to use. Data maintenance isn’t fun. By the time people open your app they are already pissed off. To create a data maintenance app that people actually want to use is something I had written off years ago¹.

Which is why what MapBox has accomplished with iD is so damn amazing. It makes you want to use it. It’s that good.

This is going to be a huge boon for OSM. After using iD, if I were king I’d dump any number of our layers and vendor maintenance packages and have our staff just start editing OSM via iD and using it as our basemap. It’s that good.

The iD editor itself is open source software (WTFPL licensed), and it is going to change the way we build web sites.

No jQuery. No Bootstrap. No Backbone. No Leaflet or OpenLayers or other mapping libraries.

It’s D3.

When I can free up some time I’m going to dig into the code and try to ferret out the genius. Mad props to MapBox. iD is freaking awesome.

¹By written off I mean relegated to vendors. Redirecting the bitching is worth the premium.

McKinsey Global Institute published a report Big data: The next frontier for innovation, competition, and productivity that analyzes the state of digital data, how it is used in different domains in both the private and public sectors, and offers suggestions for policy makers. In addition to looking at big data as a whole, the report examines five areas in detail including personal location data.



Real-time location data generated by mobile phones and other devices has created an entirely new set of location-based services from navigation to pricing property and casualty insurance. Personal location data is a new horizontal application domain that includes industry sectors from utilities to insurance to transportation. The growing smart phone market is creating an exponentially growing volume of location-aware data.  McKinsey sees this domain as a hotbed of innovation that has the potential to create significant value for consumers.  For example, use of real-time  traffic information for navigation will create a quantifiable consumer benefit by saving time spent traveling and fuel consumption. McKeinsey expects the economic value these innovations create to far exceed the revenue generated by service providers.



Economic value



Mobile phones with GNSS chips have created a revolution will continue over the next  decade. This personal location domain offers the potential for huge new value creation over the next ten years that McKinsey estimates at more than $100 billion/yr (about 0.14% of world GDP) in revenue to service providers and as much as $700 billion/yr (about 1% of world GDP) in value to consumer and business end users. Realizing this value will require investment in technology, infrastructure, and personnel as well as appropriate government action.



McKinsey's detailed analysis of the major applications of personal location data finds that, in ten years’ time, these applications could create value of $100 billion/yr or more for service providers  primarily from sales of navigation hardware and revenue from LBS, mobile LBS premiums, and geo-targeted advertising.



McKinsey estimates that by 2020 the benefits (difference between willingness to pay and the cost of applications) that customers, consumers and businesses, will enjoy from location-based applications will reach as as $700 billion/yr. Most of this, about 70 %, will be the consumer benefit from time and fuel saved by using GNSS navigation systems including those with real-time traffic information and mobile LBS applications. The remaining 30 % of the benefits will be through location-enabled applications such as geo-targeted mobile advertising.  Smart navigation applications are estimated to provide $500 billion in value to global consumers in time and fuel saved by 2020. Geo-targeted advertising could represent more than 5 percent of total global advertising spending by 2020.

For comparison, a recent study prepared for Google by Oxera Consulting Ltd in the UK estimated global revenues from geospatial products and services to be $150-$270 billion per year.  The geospatial industry is estimated to be growing by 13% per year through 2016.  These numbers were estimated using a different methodology to McKinsey's. The lower estimate of $150 billion/year was estimated using a bottom-up approach based on the Bloomberg BICS classification of companies worldwide and assumptions about allocating the revenue from companies that provide geospatial in addition to other services such as Trimble.  The $270 billion number was estimated by scaling up the US revenue estimated by Boston Consulting Group to come up with a world estimate.

Personal location data

McKinsey includes sources of personal location data that locate an individual to at least within a couple of city blocks in an urban settingin its analysis.

• Credit and debit card payments from cards processed at point-of-sale (POS) terminals and  automated teller machines. In 2008, there were 90 billion to 100 billion transactions of this type worldwide.
• Mobile phones - the location of such devices can be triangulated from cell-tower signals.  In 2011 there were about 6 billion of these.
• Smartphones with GPS - about 600 million devices in 2010 and the number is growing at about 20 % per year. Many smartphones also have Wi-Fi networking capability, which can be linked to a physical location of a Wi-Fi network.

In the future McKinsey expects indoor location to become more important.  They mention Shopkick, which allows merchants to track their customers from when they walk into a store, and Path Intelligence, which can track foot traffic within malls or amusement parks.

McKInsey's research estimates that the global pool of personal location data was at least 1 petabyte in 2009 and that this pool is growing by about 20 % a year. 

Location data generated by smartphones is growing at double the average rate of growth for all location data.  Asia is the leading region for the generation of personal location data because so many mobile phones are in use there. In 2010 the regions with the largest number of cell phone users were

• China 800 million
• India 650 million
• North America 300 million.

Applications of personal location data



McKInsey has identified three major categories of applications of personal location data.

• Location-based applications and services for individuals including smart routing, automotive telematics, and mobile-phone based location services
• Organizational use of individual personal location data that includes geo-targeted advertising, electronic toll collection, insurance pricing, and emergency response.
• Macro-level use of aggregate location data that includes urban planning and retail business intelligence.

Barriers to use of personal location data



Concerns about privacy and security was identified by McKinsey as a major barrier to future expansion of the use of personal location data. Laws are unclear about who owns that data and how it can be used.  McKinsey believes that a policy and legal framework that clearly describes the permissible and prohibited use of these data would be beneficial for all stakeholders.



For policy makers, McKinsey sees that a priority is incentives for innovation are in place including developing an up-to-date framework for intellectual property rules and rights, funding R&D in potential breakthrough areas, and ensuring that the infrastructure, including spectrum policies, is optimal.



Methodology



By looking at the value chain of location-based applications, McKinsey examined both the amount of data generation and the potential to create value.  McKInsey estimated the amount of personal location data generated in each category of application orsource device and in different geographic regions using the installed base of devices, usage behavior, and the frequency with which data are generated. To assess the potential value that data can generate, McKinsey estimated the economic value of each application to end users—individual consumers, enterprises, and government organizations.

Dear All,

we'd like to announce that GeoSolutions will be present at the GeoSpatial World Forum Conference which will be held in Rotterdam between the 13th amd 16th of May 2013.



GeoSolutions will be represented by its founder and director Ing. Simone Giannecchini as well as by its Director of Biz Dev & Sales Dott. Eleonora Fontana, In particular Simone Giannecchini will speak on the 16th during the Open Source session as well as during the session focused on SME and INSPIRE.



If you are at the conference and you'd like to network with us to talk about we could build a collaboration leveraging on our Open Source products, drop us a few lines!





The GeoSolutions team,

Google Operating System are reporting that Google are about to push out a radical new design for Google Maps.


Google Operating System surmise, probably correctly, that Google will announce and release the new look Google Maps next week at Google I/O. One of the major changes in the new design seems to be the removal of the sidebar. If you want to see more then have a look at the Google Operating System post, they have another screenshot of the new design in their report.

Z24 Luchtvaartkaart is a neat mapped based visualisation of European airport data. The map shows the ten largest European airports in three different categories: takeoffs and landings, passenger traffic and cargo traffic.

As well as displaying the largest airports in these categories in 2012 the sidebar contains a link to view the fastest growing airports in each category.

The markers on this Google Map are really well designed and I like the way that they are scaled to represent the data. The map has also been styled to strip out unnecessary features, leaving just the country borders.

When asked what types of mobile/social advertising they currently employ, 97 percent of respondents said social media like YouTube™, Pinterest®, Twitter®, Facebook®, and Instagram®. Location-based promotions (Foursquare® check-in, etc.) came in a distant second at 17 percent, and text... Continue reading