Spatial Data Analysis and Modeling for Agricultural Development, with R - Workshop

This is a 5 day hands-on workshop on data science for agricultural development. It covers an introduction to the R software, and using R for data analysis and modeling, with an emphasis on spatial data. Case studies include the use of climate, soils, crop, and health and remote sensing data. You will learn how to integrate various data types and analytical approaches (e.g. machine learning and simulation modeling) into a single work flow.

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The number of participants is limited. For full consideration apply by June 30, 2016.

Schedule

August 15 - August 19, 2016

Daily Schedule:
Day AM PM
1 Introduction to R Introduction to R
2 Spatial Data with R (Introduction) Spatial Data with R (Analysis)
3 Statistical Learning Methods Remote Sensing
4 Simulation models Projects
5 Projects Projects
Location

Arusha, Tanzania

Closest major airport is Kilamanjaro International Airport (JRO)

Costs
There is no cost for attending the workshop. Lodging and meals will be provided, and travel grants may be available upon request.
Preparations

You must bring your own computer (laptop).

Required software:
Contact
Please contact Ani Gosh (anighosh@ucdavis.edu) for additional information.
In Partnership With
The workshop is organized by the Geospatial and Farming Systems Research Consortium of the Feed the Future Sustainable Intensification Innovation Lab (SIIL) in collaboration with the African Soil Information Service (AfSIS) and International Center for Tropical Agriculture (CIAT).