I’m currently sitting at Chicago’s O’Hare airport waiting for my flight back home to Germany. In an attempt to both not forget too much of it too soon and at the same time to keep me awake so I can sleep well on the plane I will now try to craft a wrap-up of my AAG 2015. I’ll start with some details about the sessions I visited and will finish with a more general recap.
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Category / GIS
Setting up QGIS 2.8 on MacOS X 10.10 Yosemite
Upcoming Event: 2015 Annual Meeting of the Association of American Geographers (AAG)
While there’s still some time until the 2015 AAG Annual Meeting kicks off in Chicago next spring the deadline for submitting papers is approaching almost here: November 20th, 2014!
As for me, I will present an algorithm I developed as part of my PhD thesis and in the course of my related research of people’s movements in urban areas:
Konstantin Greger, University of Tsukuba
A Spatio-Temporal Betweenness Centrality Measure for the Micro-Scale Estimation of Pedestrian TrafficThe spatio-temporal mobile population estimation approach I introduce here can be used to calculate an index for the pedestrian traffic volume on street segments divided into deliberately chosen time steps. This is especially useful in the spatial context of highly urbanized areas, as it provides the populations in public space as a complementary element to building populations.
This was achieved by employing a graph theory methodology, namely that of betweenness centrality, and extending it by the temporal dimension. This new model was then applied using a number of datasets that provide information about building populations and train station passenger transfers segregated both spatially and by time.
The introduction of the temporal dimension to the estimation of populations in public space allows for a micro-scale analysis of the actual population figures according to the underlying human activities. I believe that this is the most interesting characteristic of the proposed estimation methodology, since for the first time it allows for a reliable estimation of mobile populations even for large study areas with justifiable requirements in terms of both necessary input data and computational expense.
The output result of the spatio-temporal model can be used to visualize the amount of pedestrians on the streets of a chosen study area. While the data do not represent the absolute numbers of pedestrians, they do reflect the traffic volume and allow for a comparison of crowdedness, which can be used for further quantitative analyses, such as population density calculations for certain points in time.
This year I made an effort to not being placed into some random session as has happened to me both in 2012 and 2014 – in 2013 I went all the way and organized my very own session. Therefore I browsed the (admittedly a wee bit confusing) “abstract and session submission console” on the AAG conference website. There I came across an effort by Prof. Diansheng Guo at the University of South Carolina, who proposed a session (or a series thereof?) labeled “Spatial Data Mining and Big Data Analytics”. I was more than happy to receive an almost instantaneous feedback from Prof. Guo, let alone a positive one!
Obviously I don’t have details about the “where and when”s of said session(s) and my presentation, but I will update this article accordingly once the information has become available. The details are:
Paper Session: Spatial Data Mining and Big Data Analytics (2)
Tuesday, 4/21/2015 10:00 AM – 11:40 AM
304 Classroom, University of Chicago Gleacher Center, 3rd Floor
In the meantime, Here’s the general conference information:
2015 AAG Annual Meeting
April 21 – 25, 2015
Hyatt Regency Chicago
http://www.aag.org/cs/annualmeeting
I’m already looking forward to my fourth AAG, and I would be happy to see you there!
Setting up QGIS 2.6 on MacOS X 10.10 Yosemite
It’s been awfully quiet here on the blog recently. This is owed to some major changes in my life, including the successful end of my PhD program, a successful job hunt, a move from Japan to Germany, and an interesting yet challenging start in my new job at a major German research institute.
But the recent release of MacOS 10.10 “Yosemite” together with the even more recent release of the new QGIS 2.6 “Brighton” was a brilliant opportunity to not only bring back some life here, but also to continue my mini-series of articles about installing and running QGIS and other rather scientific software packages on the latest versions of MacOS (see here, here, and here for example).
So I sat down on my freshly delivered sofa between unpacked boxes to try my luck. To make a long story short, in my case the installation ran smoothly and was done in about half an hour – downloading the necessary disk images took most of time. But before I updated my QGIS 2.4 to the new version 2.6 I first tried if 2.4 still runs on my freshly upgraded MacOS Yosemite. And there was a small surprise waiting for me here, as MacOS asked me to update my Java SE 6 runtime!
Luckily this was no big deal, since the error message provided a link to the download page at Apple.
After running this update QGIS 2.4 worked fine like before.
For the download of QGIS itself I decided once again for the packages provided by William Kyngesburye a.k.a KyngChaos – not only did I never have any problems with these, but to my best knowledge they are the only available pre-compiled QGIS packages for MacOS… The installation process follows the steps known from earlier releases:
1. GDAL
First is the new GDAL 1.11
. The installation is as easy as downloading the DMG
and installing GDAL
from the respective PKG
therein. Please ignore the NumPy
package also contained in the GDAL
disk image, since it’s an outdated version. Oh ya, and then there’s this thing that’s still annoying me:
Gatekeeper refuses to open applications and packages from “unidentified developers” (that is, developers that can’t afford a certificate by Apple) by double-clicking. Hence you need to right-click it and select Open
.
2. matplotlib
and NumPy
Before we can install matplotlib
we need to install NumPy
. There you can find the most recent version 1.8.0-1. As is stated on the website NumPy
is “included on the GDAL
Framework disk image, though it may not be up to date”. And indeed the GDAL
image mentioned above includes NumPy 1.6.2-1
from mid-2012…
Now that that’s out of the way we can install matplotlib 1.3.1-2
.
3. QGIS
And finally QGIS 2.6.0-1 itself. As in the other cases we open the DMG
file and install from the PKG
file therein. That’s it!
Now that everything was installed it was time to fire it up for the first time. And lo and behold, it works! Just like that. You can’t ask for more. Now it’s time to discover all the great new features QGIS 2.6 brings!
The Short Way to QGIS 2.4 Chugiak on MacOS
Today I finally found some breathing room in my projects to dare updating my MacBook Pro (running MacOS X 10.9.4 Mavericks) from QGIS 2.0 (Dufour) to the recently released version 2.4 (Chugiak). Well, to be honest I also realized that I should update to be able to use the QgsFeatureRequest.setFilterExpression()
method to make use of filtering expressions (introduced in version 2.2).
The first step was to download the installer images for QGIS 2.4 and GDAL 1.11
from KyngChaos.
The GDAL
disk image contains not only the complete GDAL
framework (including the GEOS
, PROJ
, SQLite
and UnixImageIO
frameworks), but also NumPy
. Since version 1.6.2-1
is dated from end of August 2012 I decided to skip installing, since I installed my NumPy
later than that and should therefore be up to date already. The GDAL
installation worked without a problem.
Next step was the installation of the actual QGIS 2.4. The readme files recommend to delete any existing QGIS.app
file from the Applications
folder, so that’s what I did. The installer then confronted me with this error message: "QGIS requires the Matplotlib python module (kyngchaos build)."
Luckily matplotlib 1.3.1-2
from early 2014 can also be found on the KyngChaos website, so I installed that from the disk image (root authorization necessary) and went back to the QGIS installer. When the installer presented me the readme file once again I realized that I had apparently just read over the hint that not only NumPy
but also the matplotlib
python module was required – classic user error on my end!
The QGIS installer also requires root authorization, takes few minutes and about half a gigabyte of hard disk space. After the small hickups earlier it finished without a problem, and I was presented first with the beautiful new splash screen and then the GUI itself. Side note: I love the fact that QGIS remembered all my settings regarding toolbars, window locations etc.!
Huge thanks and props have to go to the team behind QGIS – I can’t wait to look for reasons to try out all the new features. For a quick overview I can recommend Nyall Dawsons blog, whose most recent blog articles provide both an overview of and also some details about what’s new in QGIS 2.4.