GIScience UK 2017

Today N/LAB attended the 25th GIScience Research UK Conference, presenting three papers. The first was by student Gregor Engelmann titled: Estimating activity-based land-use through unsupervised learning from mobile phone event series in emerging economies. The open access paper is available here.

The second, joint work between N/LAB (Dr. James Goulding & Dr. Bertrand Perrat) and the School of Computer Science (Dr. Mercedes Torres Torres & Dr. Michel Valstar), was titled Automatic Pixel-Level Land-use Prediction Using Deep Convolutional Neural Networks. The open access paper is available here.

The third, joint work between N/LAB (Dr. James Goulding & Prof. Andrew Smith) and Dr. Gary Priestnall from the University of Nottingham’s School of Geography, was titled Exploring the Capabilities of Projection Augmented Relief Models (PARM). The open access paper is available here.

Full citations:

Engelmann, G., Goulding, J., Golightly, D. (2017). Estimating activity-based land-use through unsupervised learning from mobile phone event series in emerging economies, In proceedings of GISRUK 2017 Conference, 21 April 2017, UK

Torres Torres, M., Goulding, J., Valstar, M., and Perrat, B. 2017, “Automatic Pixel-Level Land-use Prediction Using Deep Convolutional Neural Networks”, in GISRUK.

Priestnall, G., Goulding, J., Smith, A., and Arss, N. 2017, “Exploring the Capabilities of Projection Augmented Relief Models (PARM)”, in GISRUK.

Posted in NLab.