Some recent papers of mine
I’ve just realised that I haven’t posted about the last few papers that I’ve authored. Some of these came from before I stopped paid work due to ill-health, and some were based on work that was done before I stopped work, but have only been published since. Anyway, on with the papers:
Rapid and near real-time assessments of population displacement using mobile phone data following disasters: the 2015 Nepal earthquake
I am first author of this paper, alongside over a dozen others from the Flowminder Foundation. It details work that we did in response to the 2015 Nepal earthquake, where we used mobile phone data to analyse population movements resulting from the disaster. I led this project, and – a while after we’d finished providing data to the aid agencies in Nepal – I co-ordinated the writing of the paper.
Rather than repeat things, I’ll point you to the detailed write-up on the Flowminder website, and suggest that you watch the video below:
https://www.youtube.com/watch?v=hY9g0kPi8BA
This video was part of our submission to the Global Mobile Awards 2016, and I’m very proud to say that we won in the Mobile in Emergency or Humanitarian Situations category. The judges commented that this was ‘A brilliant example of how the application of big data analysis to mobile technologies can be used to accelerate emergency aid, and provide intelligence to help prepare for future disasters.’ I’m also pleased to say that this paper has 26 citations (at the time of writing) – tying for first place with my Py6S paper.
Reference: Wilson, R., zu Erbach-Schoenberg, E., Albert, M., Power, D., Tudge, S., Gonzalez, M., Guthrie, S., Chamberlain, H., Brooks, C., Hughes, C. and Pitonakova, L. et al., 2016, Rapid and near real-time assessments of population displacement using mobile phone data following disasters: the 2015 Nepal Earthquake. PLoS currents, 8.
Predictors of Daily Mobility of Adults in Peri-Urban South India
This paper came out of a collaboration with the London School of Hygiene and Tropical Medicine. The collaboration actually started with me providing some satellite-derived estimates of air pollution over a study area near Hyderabad, India for a project they were working on there. Alongside these I also provided some other satellite products, including satellite-derived night-time lights intensity data. They were interested in this for a number of other analyses that were taking place in that study area, and so I did some more work on the night-time lights data, calibrating it and providing data over the villages in the Andhra Pradesh Children and Parents Study (APCAPS). This night-time light data was then used as a measure of ‘urbanicity’ (the extent to which an area is urban) for each village, something which has been found to have a significant impact on health. In this study, villages which had a higher urbanicity were associated with more mobility in and around home for both women and men.
Although night-time lights data has been used as a measure of urbanicity before, it is still relatively novel – and it has not been applied as a predictor for mobility before. This has potentially useful implications for predicting mobility of populations – and this is important because mobility has a significant impact on health (for example, affecting exposure to sources of disease).
Reference: Sanchez, M., Ambros, A., Salmon, M., Bhogadi, S., Wilson, R.T., Kinra, S., Marshall, J.D. and Tonne, C., 2017. Predictors of daily mobility of adults in peri-urban South India. International journal of environmental research and public health, 14(7), p.783.
Is increasing urbanicity associated with changes in breastfeeding duration in rural India? An analysis of cross-sectional household data from the Andhra Pradesh children and parents study
This paper is another resulting from my collaboration with the London School of Hygiene and Tropical Medicine – and again it uses the night-time light intensity data that I processed for them. It is used as a measure of urbanicity again – although this time urbanicity is categorised as low, medium or high, and used as a predictor of breastfeeding duration. It was found that higher urbanicity was linked with a shorter duration of breastfeeding – something which is important, as longer breastfeeding duration is linked to many health benefits. Interestingly, this paper was published in the year that my son was born – so I was observing a lot of breastfeeding (and the issues associated with it) in my personal life.
Reference: Oakley, L., Baker, C.P., Addanki, S., Gupta, V., Walia, G.K., Aggarwal, A., Bhogadi, S., Kulkarni, B., Wilson, R.T., Prabhakaran, D. and Ben-Shlomo, Y., 2017. Is increasing urbanicity associated with changes in breastfeeding duration in rural India? An analysis of cross-sectional household data from the Andhra Pradesh children and parents study. BMJ open, 7(9), p.e016331.
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This post originally appeared on Robin's Blog.
Categorised as: Academic, GIS, Publications, Remote Sensing
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