GeoProfilerX is an open-source Python tool for extracting line and swath profiles from projected single-band raster datasets using LineString and MultiLineString vector geometries. It is designed for topographic, geophysical, remote sensing, environmental, and other geospatial applications, combining profile extraction, analysis, publication-quality visualization, and GIS-ready outputs in a single workflow.
GeoProfilerX is the next-generation evolution of my earlier GeoProfiler project.
While GeoProfiler was developed specifically for extracting topographic profiles from Digital Elevation Models (DEMs), GeoProfilerX extends the concept into a general-purpose raster profiling tool capable of extracting both line and swath profiles from a broad range of projected single-band raster datasets, including DEMs, InSAR displacement products, gravity and magnetic anomalies, terrain derivatives, environmental rasters, vegetation indices, and other geospatial datasets.
Compared with the original GeoProfiler, GeoProfilerX introduces:
- Compatibility with a broad range of projected single-band raster datasets
- Improved input validation, CRS handling, and error checking
- Export sampled profile points with profile attributes to ESRI Shapefile and GeoPackage formats
GeoProfilerX provides a streamlined workflow for extracting, analyzing, and visualizing profiles from projected raster datasets while automatically handling common geospatial preprocessing tasks.
- Extract line and swath profiles from projected single-band raster datasets
- Generate multiple profiles in a single workflow
- Maintain a consistent visual style across profile figures
- Create publication-ready profile plots with customizable formatting
- Export editable vector PDF and high-quality PNG figures
- Export sampled profile data as CSV
- Export sampled profile points to ESRI Shapefile and GeoPackage
- Support LineString and MultiLineString vector geometries
- Automatically validate CRS and reproject vectors when necessary
- Handle NoData values and optional profile smoothing
- Validate raster-vector overlap before processing
- Generate an input data preview with raster and profile overlay
- Organize outputs into dedicated directories
- Provide an execution summary with processing statistics
Raster data + vector profiles → publication-ready figures.
GeoProfilerX works with a broad range of projected single-band rasters, including:
- Digital Elevation Models (DEM)
- Gravity anomaly datasets
- Magnetic anomaly datasets
- InSAR displacement products
- Terrain derivatives
- Geophysical rasters
- Environmental and climate rasters
- Vegetation indices (e.g., NDVI)
- Other projected single-band raster datasets
- Python 3.10+
- numpy
- scipy
- pandas
- matplotlib
- rasterio
- geopandas
- shapely
Install dependencies using:
pip install -r requirements.txt- Single-band raster
- Projected Coordinate Reference System (CRS) (e.g., UTM or other projected CRS with metric units)
- Raster format readable by Rasterio/GDAL (e.g.,
.tif,.img)
The raster must contain valid georeferencing and CRS information. NoData values should be properly defined in the raster metadata when applicable.
- LineString or MultiLineString geometries; for MultiLineString geometries, the longest line component is used for profile extraction.
- Supported formats: ESRI Shapefile (
.shp,.shx,.prj,.dbf), GeoJSON (.geojson,.json), and GeoPackage (.gpkg) - Vector dataset must have a defined CRS; it is automatically reprojected to match the raster CRS if necessary
For ESRI Shapefiles, all required components (
.shp,.shx,.prj,.dbf) should be provided together. The.prjfile is required for CRS detection.
For each extracted profile, GeoProfilerX generates:
- Input data preview (PNG & PDF)
- Publication-quality line and swath profile plots (PNG & PDF)
- CSV export of sampled profile values with X/Y coordinates
- Export sampled points with attributes to ESRI Shapefile and GeoPackage formats
An execution summary is also printed after processing.
Generated outputs are automatically organized into dedicated directories:
outputs/
├── csv/
├── geopackage/
├── pdf/
├── png/
└── shapefiles/
GeoProfilerX can be used in two ways:
Use GeoProfilerX.ipynb in Google Colab, Jupyter Notebook/JupyterLab, or VS Code.
- Open the notebook.
- Update the User Settings with your input data.
- Run the cells.
Use GeoProfilerX.py as a standalone Python script in any Python environment.
- Open
GeoProfilerX.py. - Update the User Settings with your input data.
- Run the script.
Generated outputs are automatically organized into dedicated subdirectories within the outputs/ folder.
GeoProfilerX/
├── GeoProfilerX.py
├── GeoProfilerX.ipynb
├── README.md
├── requirements.txt
├── CITATION.cff
├── LICENSE
└── images/
Planned enhancements include:
- Interactive profile drawing
- Batch processing of multiple profile files
- Multi-raster profile extraction
This project is licensed under the MIT License.
Chandni Verma
LinkedIn: https://www.linkedin.com/in/chandni-verma-geo
GitHub: https://github.com/chandnivermageo
If you use GeoProfilerX in your research, please cite this tool using the citation information provided below.
Verma, C. (2026). GeoProfilerX: A Python Tool for Extracting Line and Swath Profiles from Projected Raster Datasets (Version v1.0.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.22013091