A substantial part of my work over the years has been on crop and livestock systems, where I work to understand their functioning and response in East Africa, and how they can be transformed to be more productive. I have focused on how spatial modeling can contribute to decision making agricultural systems. My research is transforming! towards livestock systems. A year ago, I led the development of a new method to map and assess heat stress in pigs.
The unreasonable effectiveness of public work talk was given by David Robinson during rstudio::conf 2019, it’s still very relevant - Let’s collaborate and communicate more! First forward, the current COVID-19 pandemic led me into looking into publicly available data more closely and came up with a dashboard that was picked up by Locus Geosystems - a local Kenyan startup, with more hands on it now I am amazed at what they have done so far.
I am surprised by how often spreadsheets are used for things they are not really good for when there are better alternatives.
In a world experiencing climate change, good weather and climate data matters. It may be available but often hard to find, understand and apply to decision-making mainly because: There are no weather stations everywhere Weather stations are not in good condition (gaps) The data is not stored correctly The data does not pass the basic quality controls Access to data is restricted However, weather and climate data products derived from satellites and model-based reanalysis have been used in locations where station based observations are inadequate or incomplete.
Maps have been part of human history for a long time; representing the real world on paper and now via the web. The process should be simple, but it’s often challenging to non-GIS people. Software such as ArcGIS and QGIS have made map making an easy process, while you will need a license to use the former, the latter is a free and open-source software (FOSS). However, R - a statistical programming language has spatial capabilities that can be used for map making.