Deep dive into time series analysis with GRASS

A collection of tutorials demonstrating how to handle time series data in GRASS, from basic concepts to advanced spatiotemporal analysis.

GRASS offers robust tools for working with spatiotemporal data, especially raster time series. This page collects all the tutorials that focus on time series workflows, from creating space-time datasets to performing time-aware analysis and visualizations.

Whether you’re just getting started or looking to perform advanced temporal algebra, you’ll find a range of examples below.

📚 Tutorial Collection

Here are the available tutorials, ordered to guide you from basic to more advanced concepts:

1. Introduction to Time Series in GRASS
   Learn the basics of space-time datasets and time series visualization.

2. Temporal aggregations
   Group and summarize time series data by week, month, or season.

3. Temporal algebra
   Use temporal algebra to query and analyze space-time datasets based on time relations.

4. Temporal accumulation
   Compute cumulative temperature values over time and find suitable areas for mosquitoes.

5. Temporal gap-filling
   Fill missing values using temporal interpolation and smoothing techniques.

6. Temporal query with vector data
   Extract time series values at specific vector locations (e.g., points or polygons).

7. Temporal subset, import and export
   Subset time series by date, and learn how to import/export space-time datasets effectively.