In this session we will explore the combined use of GRASS GIS and R following an example of habitat suitability modeling. We will use a daily time series of LST to extract relevant environmental variables for a mosquito species that transmits West Nile virus in Northern Italy. Particularly, we will use TGRASS to estimate bioclimatic variables such as those from Worldclim, autumnal cooling, spring warming, number of consecutive days with a certain LST value, number of potential mosquito generations, etc. We will then import our vector and raster maps into R and proceed with the habitat suitability modeling and prediction.
We will use GRASS GIS 7.8+. It can be installed either through standalone installers/binaries or through OSGeo-Live (a linux based virtual machine which includes all OSGeo software and packages).
There are two different options:
For Windows users, we strongly recommend installing GRASS GIS through the OSGeo4W package (second option), since it allows to install all OSGeo software. See this installation guide for details (Follow only the GRASS GIS part).
Install GRASS GIS 7.8.5 from the "unstable" package repository:
sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable
sudo apt-get update
sudo apt-get install grass grass-gui grass-dev
For other Linux distributions including Fedora and openSuSe, simply install GRASS GIS with the respective package manager. See also here
Have a look at: http://grassmac.wikidot.com/downloads
Install with g.extension extension=name_of_addon
Attention UNIX-like users: g.extension is currently failing in GRASS. See
alternative solutions
here or
download the addons
repo and use: g.extension extension=name_of_addon url=path/to/addon/folder.
Well, you know and you'll have it installed for sure 😄 The following packages should be installed beforehand:
install.packages(c("rgrass7","raster","sf","mapview","biomod2"))We will use the software MaxEnt to model habitat suitability. The software can be downloaded from: https://biodiversityinformatics.amnh.org/open_source/maxent/
Please, create a folder in your $HOME directory, or under Documents if in Windows, and name it grassdata_ogh. Then, download the following ready to use location and unzip within grassdata_ogh:
In the end, your grassdata folder should look like this:
grassdata/
└── eu_laea
├── italy_LST_daily
└── PERMANENT
Verónica Andreo is a biologist. She holds a PhD in Biological Sciences and an MSc in Remote Sensing and GIS applications. She works as a researcher for CONICET and lecturer at Gulich Institute - Argentinian Space Agency (CONAE) in Córdoba, Argentina. Her research is focused on uncovering environmental drivers of vector-borne disease outbreaks. She is mostly interested in those environmental features that can be derived by means of satellite image analysis, remote sensing time series and GIS-based techniques.
Verónica is part of the GRASS GIS Development team and has recently become the new PSC chair. She is a strong advocate for OSGeo and free and open source software for geo-spatial (FOSS4G), currently serving as Program Committee chair for FOSS4G 2021. Among other things, she has volunteered as a mentor for GRASS GIS in the Google Code-In contest introducing high school students into the Open Source world.
- Neteler, M. and Mitasova, H. (2008): Open Source GIS: A GRASS GIS Approach. Third edition. ed. Springer, New York. Book site
- Neteler, M., Bowman, M.H., Landa, M. and Metz, M. (2012): GRASS GIS: a multi-purpose Open Source GIS. Environmental Modelling & Software, 31: 124-130 DOI
- Gebbert, S. and Pebesma, E. (2014). A temporal GIS for field based environmental modeling. Environmental Modelling & Software, 53, 1-12. DOI
- Gebbert, S. and Pebesma, E. (2017). The GRASS GIS temporal framework. International Journal of Geographical Information Science, 31, 1273-1292. DOI
- Gebbert, S., Leppelt, T. and Pebesma, E. (2019). A Topology Based Spatio-Temporal Map Algebra for Big Data Analysis. Data, 4, 86. DOI
All the course material is under
Creative Commons Attribution-ShareAlike 4.0 International License