Main page of this document: See https://neteler.gitlab.io/grass-gis-analysis/
Analysing environmental data with GRASS GIS
In this session "Analysing environmental data with GRASS GIS" we will start with a few GRASS GIS basics. We then focus on analysing the ECA&D climatic data, looking at data organization, data aggregation, univariate statistics, raster map algebra, and zonal statistics. This part is followed by classification with machine learning (RandomForest Classifier) and concluded with a quick glance at linear and multiple regression in GRASS GIS.
- Session overview
- A few GRASS GIS basics
- What you can do with GRASS GIS
- Concept of GRASS GIS database
- Concept of computational region
- Data management
- Workflow overview
- Startup of GRASS GIS
- Analysing the ECAD climatic data
- Data organization: First steps with an own mapset
- Data aggregation in GRASS GIS
- Univariate statistics in GRASS GIS
- Raster map algebra using map calculator
- Zonal statistics in GRASS GIS
- Classification with machine learning in GRASS GIS
- Variable preparation: raster map stacking
- RandomForest Classifier
- Linear and multiple regression in GRASS GIS
- Linear regression
- Multiple regression
- Using R within GRASS GIS
- Python and GRASS GIS
- Using GRASS GIS from "outside"
- Further useful links
Markus Neteler is partner and general manager at mundialis GmbH & Co. KG, Bonn, Germany. From 2001-2015 he worked as a researcher in Italy. Markus is co-founder of OSGeo and since 1998, coordinator of the GRASS GIS development (for details, see his private homepage).
In this session, we will go through the most commonly used spatial analysis techniques in GRASS GIS. The session is a hands-on with a set of exercises covering basic raster and vector processing capabilities of GRASS GIS.
- Some quick GRASS GIS basics
- Geospatial data import (aggregated ECA&D climatic data time series)
- Simple exploratory data analysis
- Zonal statistics: GRASS GIS and R with raster library
- Machine Learning analysis to classify the European climatic zones based on ECA&D climatic data
- Linear models in GRASS GIS and R
You need to have GRASS GIS 7.6 or later installed.
See here for an overview (GRASS GIS, R, QGIS for different operating systems)
Course data download
For this exercise, we will use a GeoTIFF file and the already prepared GRASS GIS location
- Download course ECA&D elevation GeoTIFF file here (or here)
- Download the GRASS GIS location here (or here)
- Unzip the file "ecad_elev_v17.zip" into the "$HOME/geodata/" folder (create folder if needed)
- Unzip the file "grassdata_ecad17_ll.zip" into the "$HOME/grassdata/" folder (create folder if needed)
A few GRASS GIS basics
This short section covers a few concepts you should know before continuing with the exercises. Please read on in 01_grass-gis-basics.md.
Analysing the ECAD climatic data
Please read on in 02_grass-gis_ecad_analysis.md.
Classification with machine learning in GRASS GIS
Please read on in 03_grass-gis_ecad_randomforest.md.
Linear and multiple regression in GRASS GIS
Please read on in 04_grass-gis_ecad_regression.md.
Python and GRASS GIS
Some tricks are shown in 05_grass_gis_python_session.md.
Further useful links
- GRASS GIS wiki: https://grasswiki.osgeo.org/wiki/GRASS-Wiki
- GRASS GIS and R for time series processing: https://grasswiki.osgeo.org/wiki/Temporal_data_processing/GRASS_R_raster_time_series_processing
- Related books: https://grass.osgeo.org/documentation/books/
- Related tutorials and articles: https://grass.osgeo.org/documentation/tutorials/
- 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)
Original data sources
- ECA&D V17 daily climatic data 1950-2017: aggregated in GRASS GIS to annual and monthly data of 30 years averages, 0.25° spatial resolution
- Related European elevation model
- NaturalEarth Admin0 country borders
- Köppen climate types for the period 1901-2010 on different time scales by Chen et al 2013
Last changed: 2 Sep 2019
"Analysing environmental data with GRASS GIS" by Markus Neteler, 2018
- Repository of this material on gitlab
- GRASS GIS manual main index | Topics index | Keywords Index | Full index | Raster index | Vector index | Temporal index
- Tutorial based on Hands-on to GIS and RS with GRASS GIS by Veronica Andreo, Sajid Pareeth and Paulo van Breugel (2017) which was adapted from Geostat 2015 exercises prepared by Markus Neteler.