The Human Dimension to Drought Monitoring: Can Remote Sensing Data Corroborate the Lived Experience of Drought on the Ground?

Drought prediction methods are primarily effective to the extent that they accurately capture people’s lived experiences of drought on the ground. As such, this work analyzed whether or not a remotely sensed classification of drought based on vegetation corroborates the lived experience of eight different communities in Samburu County, Kenya. This was carried out by comparing two sets of data: first, with interview data from people on-the-ground, and second using satellite-derived Normalized Difference Vegetation Index data from the Global Inventory Monitoring and Modelling System (GIMMS), a NASA/NOAA product. These data allowed spatiotemporal instances of drought to be classified from both a “subjective” perspective and an “objective” remote sensing definition of drought. The results of this analysis led to the discovery of discrepancies between the two sets of data. We reveal an unexpected interplay between external violent conflict and perceived drought severity within the communities that only became evident through detailed analysis of the 2009 and 2011 droughts. This research concludes that (1) the lived experience of drought is culturally relative, (2) effective drought prediction methods must include both objective and subjective inputs, and (3) interdisciplinary collaboration is key in discovering systematic interplays and lags in drought processes.