Last week I went to GEOSTAT 2016. Given the amount of fun had at GEOSTAT 2015, expectations were high. The local organisers did not disappoint, with a week of lectures, workshops, spatial data competitions and of course lots of Geostatistics. It would be unwise to try to systematically document such a diverse range of activities, and the GEOSTAT website provides much further info. Instead this ‘miniwriteup’ is designed to summarise some of my memories from the event, and encourage you to get involved for GEOSTAT 2017.
Version 0.1.1 of the package
stplanr has been
released on CRAN. This is a major update with many new functions and a
new class definition,
SpatialLinesNetwork, for route planning and
network analysis using
This short post, by myself and package co-author Richard Ellison, describes how stplanr can be used for transport research with a few simple examples from the package documentation. We hope that stplanr is of use to transport researchers and practitioners worldwide and encourage contributions to the development version hosted on GitHub.
Open source software has caused a quiet revolution in computing since the creation of the GPL license by Richard Stallman back in 1989. Yet it has been slow to gain ascendency in many areas, including Civil Engineering. This short post discusses this issue in the context of the uptake of QGIS and R for spatial analysis work, with reference to a lecture delivered to undergraduate Civil Engineering students at the University of Leeds (see slides below and as a stand-alone html page here):
The week before last I attended the GEOSTAT summer school in Lancaster. GEOSTAT is an annual week-long meeting devoted to ‘geostatistics’ (or ‘spatial statistics’ - we’ll come on to the difference subsequently).
Having seen the impressive range of materials from previous ‘GEOSTATs’, I was greatly looking forward to the event as a hub of learning, research and community-building, organised by people at the cutting edge of the field. I was not disappointed. The purpose of this post is to say ‘heads up’ to people who are interested, not only in the field of geostatistics but also in free and open source software for geospatial applications (‘FOSS4G’) and research-focussed communities using and developing R more widely. For educators, this post also serves to highlight a cache of frankly amazing teaching materials that lie, largely undiscovered, online free for all to use.
A useful feature of R is its ability to implement a function differently depending on the ‘class’ of the object acted on. This article explores this behaviour with reference to a playful modification of the ‘generic’ function
plot() to allow plotting of cartoon bicycles. Although the example is quite simple and fun, the concepts it touches on are complex and serious.
The example demonstrates several of the programming language paradigms that R operates under. R is simultaneously object-orientated, functional and polymorphic. The example also demonstrates the paradigm of inheritance, through the passing of arguments from
plot() via the
... symbol. There has been much written about programming paradigms and R’s adherence to (or flouting of!) them. Two useful references on the subject are a Wikibook page on programming language paradigms and Hadley Wickham's Advanced R book. There is a huge amount of information on these topics. For the purposes of the examples presented here suffice to say that R uses multiple paradigms and is extremely flexible.
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