In this guest post King’s Geography PhD Student Jake Simpson describes some of his geocomputational work analysing data from tropical peat swamp forests to estimate carbon emissions.
On Monday 21st March 2016, Faith Taylor and I managed to organize a MissingMaps mapathon here at KCL.
What follows is not a mere report of the event (it’s been great fun, just look at the pictures!), but rather an attempt to cover certain aspects of a mapathon which usually might be overlooked, and that I instead consider to be of interest for an academic audience.
This week we started advertising a post-doctoral Research Associate position to work with James on a project looking at the global food system, local land use change and how they’re connected. The successful candidate will drive the development and application of an integrated computer simulation model that represents land use decision-making agents and food commodity trade flows as part of the Belmont Forum (NERC) funded project, ‘Food Security and Land Use: The Telecoupling Challenge’.
This afternoon’s seminar by CASA’s Dr. Elsa Arcaute will be of interest to a wide range of students and staff at King’s – with a background in theoretical physics and complexity, Elsa now studies how urban and regional systems scale and divide, and how these aspects are expressed in infrastructure and the built environment. To put it another way: where does London end? 4:30pm today in the Pyramid Room (K4U.04) and followed by wine and soft drinks.
Last week several members of King’s Geocomputation activity hub participated and contributed to a fieldwork mapping and monitoring party held at The Royal Geographical Society in London. Presentations and demos included crowdsourcing & OpenStreetMap, low-cost research drones and Arduino micro-controllers. This blog post summarises another presentation that explored the options for using mobile apps for fieldwork .
While working with Naru to design our new 2nd year GIS methods training course (with parallel QGIS and ArcGIS streams!), I came across a rather striking map on the ESRI blog that managed to combine both slope (steepness) and aspect (direction) in a single representation. This post explains both a problem with the way that the colour scheme was specified and how to replicate this type of map in QGIS (with style sheet).