Tahmin, a student in our Geoinformatics for Urbanised society MSc programme, and I have been working hard over the last months to record, edit, and polish on our podcast project: a GIS-themed educational podcast from our Department of Geography (Geograafia osakond) here in Tartu, Estonia.
Introducing: Tartu Geo, a podcast about geography and geoinformatics related fields along with education, research, history, philosophy, ground breaking ideas and innovation. The show will also host guests from different sectors who will share insight about their research and work. We try to bring up new episodes every 15 days with exciting and newer topics of geoinformatics and geography. Stay tuned and happy listening.
Please bear with us, we are still amateurs :-D The sound quality in some guest interviews is not great, but overall it is getting better and better as we progress. We have already several episodes lined up, and the podcast can be loaded from all the convenient places like iTunes, Stitcher, Spotify and of course you can add the feed also directly to your podcast app.
Please let us know any suggestions or advice that can help us grow. Like always comment, like and subscribe.
I spontaneously filled an open slot for our regular PhD seminar in the Chair of Geoinformatics. As I described in an earlier blog post, I occasionally browse through latest published articles like scanning for headlines in the daily news. And with an app like Feedly or Inoreader you can tag interesting articles for later and group them. Now was the chance to re-iterate through some of the latest articles - literally aiming for only few months old to a maximum of 1-2 years old. I initially came up with a group of ca 30-35 articles, which was still too much for a single seminar.
GIScience is not a homogenous and strictly defined discipline, and there is no consensus among GIScience researchers about the relevant publication outlets.
Filip Biljecki (2016) “A scientometric analysis of selected GIScience journals”, International Journal of Geographical Information Science, 30:7, 1302-1335, DOI: 10.1080/13658816.2015.1130831
The original idea was to cover a few different topics that are also relevant for the teaching and research we do in the department, such as:
- cloud processing and Google Earth engine
- machine learning and GIS (statistical modelling)
- at least like European level/scale modelling
- some modern cartography/visualization topics
- terrain modelling
I'd then give a short overview of journals, and the selected papers hand out copies one each. 5 minutes reading/skimming and then one circulation, and another 5 minutes, and then discussion. The timing turned out to be too optimistic and we spent more time discussion the papers and interesting facts the participants found for themselves.
Comparison of FOSS4G Supported Equal-Area Projections Using Discrete Distortion Indicatrices, ISPRS Int. J. Geo-Inf. 2019, 8(8), 351; https://doi.org/10.3390/ijgi8080351
Performance Testing on Marker Clustering and Heatmap Visualization Techniques: A Comparative Study on JavaScript Mapping Libraries, ISPRS Int. J. Geo-Inf. 2019, 8(8), 348; https://doi.org/10.3390/ijgi8080348
Examining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change, International Journal of Geographical Information Science, 33:5, 1040-1061, DOI: 10.1080/13658816.2019.1568441
The scale effects of the spatial autocorrelation measurement: aggregation level and spatial resolution, International Journal of Geographical Information Science, 33:5, 945-966, DOI: 10.1080/13658816.2018.1564316
Comparative usability of an augmented reality sandtable and 3D GIS for education, International Journal of Geographical Information Science, DOI: 10.1080/13658816.2019.1656810
GIS&T pedagogies and instructional challenges in higher education: A survey of educators, Transactions in GIS 2019 https://doi.org/10.1111/tgis.12534
The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use, Earth Syst. Sci. Data, 11, 1385–1409, https://doi.org/10.5194/essd-11-1385-2019
Contemporary American cartographic research: a review and prospective, Cartography and Geographic Information Science, 46:3, 196-209, DOI: 10.1080/15230406.2019.1571441
Automated and semi-automated map georeferencing, Cartography and Geographic Information Science, DOI: 10.1080/15230406.2019.1604161
Today we broadcast a webinar info session about the new MSc programme in Geoinformatics for Urbanised Society at the University of Tartu.
One of the recurring core topics in this new MSc curriculum is Data and GIS use in Urban Planning.
Until just a decade ago spatial planning and analytics projects had problems with getting enough data. But nowadays there is so much data available, that it is increasingly hard to make sense of it – because of the 3 V’s of big data - volume, variety, velocity. The open data movement, government agencies, research institutes and citizen scientists alike make more and more data available publicly, mobile phones, sensor networks and satellites generate a multitude of datasets every day
In order solve the Interdisciplinary challenges of urban planning we want to empower you with skills and knowledge to analyse, visualise and understand processes and data. For that we teach the Full cycle of spatial data management, from the various methods of data acquisition, followed by efficient and practical processing techniques, to subsequent meaningful analysis and visualisation; in order to consequently make successful planning decisions for a sustainable future.
So what does it mean to study Geoinformatics for Urbanised Society with us in Tartu?
You will learn how to combine geography and IT in the age of BIG data. This is essentially what we believe modern Geoinformatics is representing. Mastering Geoinformatics will provide you with tools to analyse social and natural processes in space for interdisciplinary decision- and policy-making.
Which recent Geoscience related journal article has most influenced your work?
For me it was Laniak et al. (2013) "Integrated Environmental Modeling: A Vision and Roadmap for the Future". With a BSc in Computer Science I had worked in the IT industry before I started in academia. When I read Laniak et al. (2013) my Geography Master’s I knew that that was exactly how I would want to apply my computational background. Laniak et al. presented a vison for the future of integrated environmental modelling. They called to science and technology to work on standards for data sharing, and envisioned web-based platforms for transdisciplinary community interactions. I knew that science is not only about observations and theory. But it was then when I deeply understood how the capabilities of modern computers support research, make it reproducible and, thus, can accelerate research. The potential of linking people and knowledge from different disciplines in order to jointly understand natural processes and to make decisions together overwhelmed me. This landmark paper has since influenced me throughout my PhD and beyond.
Reference:
Laniak, Gerard F, Gabriel Olchin, Jonathan Goodall, Alexey Voinov, Mary Hill, Pierre Glynn, Gene Whelan, et al. 2013. “Integrated Environmental Modeling: A Vision and Roadmap for the Future.” Environmental Modelling & Software 39 (0):3–23. https://dx.doi.org/10.1016/j.envsoft.2012.09.006
As a scientist / researcher you have to stay informed about the latest research findings in your field. Typically, this means that you should follow the publications of the most important journals in your research domain. I found that many researchers (including myself so far) only conduct proper literature reviews when they work on a specific problem, when writing articles and grant applications. Often they wouldn't find the time to go to all the journal websites and scroll through the article lists etc.
I recently discovered the Feedly RSS reader. RSS is long-known internet feed syndication protocol that is used to subscribe to updates on websites and blogs. I found that many, if not all journals, more or less provide RSS feeds for their latest articles, often with an abstract provided. Feedly is a website application that helps you to organise RSS feeds and read them online. There is also an Android and an iPhone app. With these you can then read and manage your feeds on the phone. Now I quickly scroll through the latest articles every day via my mobile phone. This way it is just like scrolling through Facebook, Twitter or Instagram, but for journals. And the very few articles that you find relevant or that are of interest for you, you can save them in your Feedly backlog in order to read them later when you are in your office and take reading time :-)
Update: Inoreader is another very similar application to read your RRS feeds, and there are also the respective smartphone apps available.
One advantage of Feedly is that you can export and import lists of your RSS feed sources with so called OPML files. OPML is available in many RSS reader web sites and applications, so you can both import and export OPML files of RSS subscriptions.
I prepared an OPML Export file for you, a standard list format for your feed URLs, so you don't have to aggregate all the RSS URLs again. Happy reading and feel confident that you are not missing out on latest papers in your field.
Groundwater bodies are among the most important and valuable natural resources available, but at the same time they are also the least understood. To better understand the hydrological state of the environment and groundwater dynamics, data sets and measurements need to be made available and accessible to scientists, planners, and stakeholders to allow for proper decision making support. Information exchange via the internet has become faster, but at the same time data sets remain scattered both in location and formats. Present research in hydrogeology and freshwater resources management can be significantly supported and accelerated by relating, reusing and combining existing data sets, models and simulations in a streamlined, computer-aided and networked fashion and yield more new and reproducible insights.
In this thesis Design Science Research, Grounded Theory and Case Studies are applied in order to design a spatial data infrastructure that addresses the full data life cycle in the context of hydrogeology in New Zealand. This 'Hydrogeology Infrastructure' design was successfully implemented and evaluated via a networked and open standards-based prototype. Formerly disconnected and distributed data sets may now, for the first time, be used for hydrogeological data analysis, visualisation and modelling within one data portal.
My Supervisor(s)
Many thanks go out again to my supervisors who supported me continuously.
Assoc Prof Jacqueline Whalley (AUT, New Zealand); Assoc Prof Hermann Klug (Z_GIS, Salzburg University, Austria); Prof Philip Sallis (AUT, New Zealand)
