Testing a new satellite-derived vegetation index in a new biome

The last chapter of my PhD dissertation was published earlier this year in the International Journal of Applied Earth Observation and Geoinformation. From conception to publication, this paper took about two-and-a-half years of work. It signifies the end of my PhD era, so to speak. The idea came from my supervisor, who suggested that testing the relatively new Plant Phenology Index (PPI) in semi-arid biomes would be a worthwhile cause because its only been evaluated in the boreal biome.

Downward spiral of conflict and famine in Somalia is due to the absence of good governance, not climate

Somalia is mostly dry and semi-arid with the exception of few areas of greenery in the northern mountains or the riverine agricultural fields in the south. Since the acceleration of violence in the late 1980s that propelled it into civil war, two things have been occurring in Somalia on a more or less regular basis: conflicts and famines, and both have been linked, in one way or the other, to climate change

Test pixelwise correlation between two time series of raster data in R

Test pixelwise correlation between two time series of raster data in R

Satellite time series data are useful for studying biophysical how variables change over time and understanding what causes those changes. Recently, I was looking into correlating two time series datasets over Africa to look at the relationship between net primary production (NPP) and rainfall.After a futile attempt to find an “out-of-the-box” software package that does this, I created an R function to speed things up.