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Time series tutorials: Add a home page to collect them all (#67)
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---
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title: "Deep dive into time series analysis with GRASS"
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author: "Veronica Andreo"
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date: 2025-05-27
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date-modified: today
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image: images/tgrass_flowchart.png
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format:
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html:
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toc: true
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code-tools: true
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code-copy: true
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code-fold: false
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categories: [time series, raster, intermediate, advanced, Python]
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description: "A collection of tutorials demonstrating how to handle time series data in GRASS, from basic concepts to advanced spatiotemporal analysis."
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engine: jupyter
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execute:
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eval: false
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---
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**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.
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Whether you're just getting started or looking to perform advanced temporal algebra, you'll find a range of examples below.
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## 📚 Tutorial Collection
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Here are the available tutorials, ordered to guide you from basic to more advanced concepts:
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1. **[Introduction to Time Series in GRASS](./time_series_management_and_visualization.qmd)**
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Learn the basics of space-time datasets and time series visualization.
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2. **[Temporal aggregations](./time_series_aggregations.qmd)**
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Group and summarize time series data by week, month, or season.
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3. **[Temporal algebra](./time_series_algebra.qmd)**
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Use temporal algebra to query and analyze space-time datasets based on time relations.
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4. **[Temporal accumulation](./time_series_accumulations.qmd)**
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Compute cumulative temperature values over time and find suitable areas for mosquitoes.
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5. **[Temporal gap-filling](./time_series_gap_filling.qmd)**
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Fill missing values using temporal interpolation and smoothing techniques.
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6. **[Temporal query with vector data](./time_series_query_with_vector.qmd_)**
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Extract time series values at specific vector locations (e.g., points or polygons).
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7. **[Temporal subset, import and export](./time_series_extraction.qmd)**
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Subset time series by date, and learn how to import/export space-time datasets effectively.
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