Last update : 20/06/2018
This post will sum up a few sources of information useful if you are interested in spatialization or development.
Spatialization and GIS
Definition : Spatialization or spatial interpolation creates a continuous surface from values measured at discrete locations to predict values at any location in the interest zone with the best accuracy.
The book Using ArcGIS Geostatistical Analyst will give you an efficient overview about spatialization.
The book Geocomputation with R will give you a lot of informations about what you can do with geographic data.
Geospatialization with sf and sp packages : Introduction to GIS with R.
Geospatialization tools on R with dplyr and ggmap : Geocoding with R.
Another source of knowledge about spatial data manipulation.
R tools
Use Rmarkdown to write your reports, your presentations or your HTML pages. Its reference guide is very useful ! Use Blogdown to create our own blog. Use Leaflet to generate maps. Have all the tools in hand to use efficiently R with these cheatsheets.
AGROMET project
If you are interested in the project led by CRA-W about providing hourly 1km² gridded datasets of weather parameters with the best accuracy, these links can give you more information about the context and the realisation of the project.
Presentation of the AGROMET project.
Here is a presentation that explains the methodological approach to assess the spatialization techniques
And here a presentation of the comparison of temperature of two stations from PAMESEB & RMI
All the results will be available on the platform developed for the project.
The following references are publications which inspired the AGROMET project :
Use of geographic information systems in warning services for late blight (Zeuner, 2007)
Decision Support Systems in Agriculture (Racca, 2011)
Spatial interpolation of ambient ozone concentrations in Belgium (Hooyberghs, 2006)
Spatial interpolation of air pollution measurements using CORINE land cover data (Stijn, 2008)