Monthly Archives: September 2013

Presentation at FOSS4G Nottingham

Thanks to everyone who attended my talk last week at FOSS4G.

Here’s the presentation (pdf format). I’ll try to upload it to the FOSS4G site as well.


I really enjoyed myself, and there were some interesting questions. Here’s a quick summary of the questions and the answers I tried to give:

Q: How long does it take to run?

A: About 20 minutes on a fast-ish (4gb Ram) machine. Its fairly slow at present, due to the two loops and also I think the focal filter operation. I reckon it can be sped up quite alot if the inner loop can be removed (thanks for the tip Thomas), I’ll try to do this as soon as I can!

Q: Why did you present a single simulation for 2050 instead of a range of simulations showing the probability of land use change according to where it was located in each simulation?

A: Good question. I didn’t have much time. Certainly it would be much better (and more useful) to generate, say, 100 simulations, and then work out the probability of change. I wonder if it can be built into the script somehow?

Q: Have you run any tests against comparable commercial software?

A: Not yet, though I do intend to. The Ksim and fractal dimension results are within the realms of what one would get on a commercial system, and the cellular growth behaviour looks realistic. But I haven’t yet run a back-to-back comparison.  This is probably the most important priority. Thanks!

I can’t remember if there were any other questions. But feel free to write me an email and remind me!


A cellular-automata land use model for the R software environment

Though there are a number of Free and Open Source Software (FOSS) applications presently available for other types of land use models, such as Huang’s Change Analysis (logistic regression), and Purdue University’s Land Transformation Modeller (LTM) (Artificial Neural Networks), there are few fully operational implementations of true CA models for land use modelling in the Open Source community. In addition, stand alone model frameworks do not usually incorporate  appropriate statistical goodness-of-fit comparison techniques for model evaluation, something that is normally carried out externally in statistical software packages.

This website is dedicated to the development of SIMLANDER (SIMulation of LAnd use changE using R) , a CA land use model for the R software environment. The R platform, with its extensive developer and user community, and its clear relevance for model building and scientific computing, seems to present an ideal environment for geographical land use modelling.


Batty, M., and Xie, Y. (1994). From cells to cities. Environment and Planning B: Planning and Design 21 Supplement, 31–48.

Tobler, W. (1979), Cellular Geography, S. Gale & G. Olsson, eds., Philosophy in Geography, Reidel, Dortrecht; pp 379-386.

White, R., and Engelen, G. (1993). Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A, 25(8), 1175–1199.