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RasterViz Release Note

08 May 07:00
@Defani Defani
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Release Note: RasterViz v1.1.0

Release Date: May 8, 2026

We are thrilled to announce the release of RasterViz v1.1.0! RasterViz is built to complement your QGIS workflow by providing a dedicated tool for crafting publication-ready scientific raster figures.

It brings the familiar aesthetics of Python script outputs (rasterio.show()) directly into your QGIS workspace. Now, you can easily generate maps with pointed colorbars, precise geographic coordinate formatting, domain-specific colormaps, and multi-map layout grids—all through a friendly graphical interface, without needing to write any code.

Key Features (Highlights)

  • Matplotlib Embedded Engine: Every map is rendered using the Matplotlib Qt5Agg backend embedded directly within the QGIS dialog.
  • Lightning-Fast Live Preview: Raster data is read once and cached as a NumPy array. All parameter adjustments (stretch, colormap, rotation) trigger an instant re-render from the cache without re-reading from the disk.
  • Advanced Stretch Control: Supports Actual min-max, Percentile (with configurable Pmin/Pmax), and Manual vmin/vmax input for reproducible figures across dates.
  • Geographic Coordinate Labels: Axis label formatting (DMS, DM, Decimal Degree, UTM) with independent text rotation for X and Y axes (0–360°) to gracefully handle dense tick intervals.
  • Publication-Style Colorbar: Full support for pointed colorbar styles (Both Pointed, Right/Max, Left/Min, or Box/Standard), along with precise controls for size, position, tick count, and labels.
  • Discrete / Classified Mode: Auto-scan gridcodes for classified data. Each class color (via UI swatch or Hex code), editable label, and decimal places can be configured and displayed as a clean patch legend.
  • RGB Composite: Full support for rendering 3-band composites (True color / False color) with independent stretch control for each R, G, and B channel.
  • Library of 80+ Colormaps: Features 24 custom domain-specific palettes (Vegetation, Mangrove, SAR Backscatter, Carbon Stock, etc.) plus access to the entire standard Matplotlib palette library (~60 named colormaps).
  • Multi-Map Layout Series (GridSpec): Build an N×M layout grid of maps from different layers or bands into a single export canvas simultaneously.
  • High-Resolution Export: Supports exporting to raster formats for journal submission (PNG/TIFF @ 300 DPI) and vector-preserving formats for posters/slides (SVG/PDF @ 150 DPI) with transparent background support.

Lightweight & Zero External Dependencies

RasterViz is built with efficiency in mind. It utilizes core libraries that are already seamlessly bundled with standard QGIS installations across Windows (OSGeo4W), Linux, and macOS: PyQGIS, PyQt5, NumPy, and Matplotlib. You do not need to run any additional pip installations to use all of its features.

📥 Installation Guide

  • Via Plugin Manager (Recommended - pending QGIS review): Once approved, search for "RasterViz" in the Plugins -> Manage and Install Plugins menu.
  • Via ZIP: Download the .zip archive from the GitHub Releases page. Open QGIS -> Plugins -> Manage and Install Plugins -> select the Install from ZIP tab -> browse to the downloaded .zip file. Access the plugin via the Raster → QRVIZ menu.

Bug reports, feature requests, and development contributions are always welcome. Please submit them via the [GitHub Issue Tracker](https://github.com/Defani/QRasterVIZ/issues).

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