Open first, Pro when ready
Start with the 700+ tool library in Python or R. Then license Pro for bundle-level delivery, governance reporting, and QGIS analyst access to 41 decision-grade workflows.
One Platform, Python + R Interfaces
Whitebox Next Gen is a complete platform rewrite — modular Rust-backed backend libraries, major advances in raster, vector, and LiDAR format support, native projection workflows, and a new wbtopology vector-analysis core that adds network analysis and linear referencing. Whitebox for Python and Whitebox for R are two equal access surfaces to the same rebuilt platform. Start free, then upgrade to Pro bundles when governance and decision confidence become critical.
Whitebox Next Gen is a complete platform rewrite. The old monolith is replaced with modular backend libraries — wbgeotiff, wbraster, wbvector, wblidar, wbprojection, and wbtopology — all implemented in pure Rust and fully open-source.
Whitebox for Python and Whitebox for R give teams immediate access to 700+ tools on top of this new foundation. The platform philosophy is simple: open for capability breadth, Pro for accountability and governance. Transparent code, local execution, and reproducible results. When your organization needs standardized delivery and stakeholder-grade evidence, upgrade into Pro bundles.
Start free with Python and R. Add Whitebox Workflows Pro when your team needs bundle-level delivery, governance reporting, and decision-ready outputs — accessible from QGIS, Python, and R.
Start with the 700+ tool library in Python or R. Then license Pro for bundle-level delivery, governance reporting, and QGIS analyst access to 41 decision-grade workflows.
Use QGIS to run Pro workflows without scripting, while keeping the same workflow logic, contract format, and confidence outputs as Python and R.
Python and R for analysis and automation. QGIS for desktop teams. One platform, one engine, multiple ways to work.
Your Whitebox workflows are future-proof: build in Python or R, then deliver decision-grade outputs through QGIS, Python, or R with Pro.
Whitebox runs the same Rust-backed engine through Python and R. Choose the interface that matches your team's workflow. Both access the full tool library and have the same high-performance execution, local-first control, and reproducible results.
Best for scripting, Jupyter notebooks, automation, and production pipelines in the Python ecosystem.
Best for quantitative research, statistical modelling, and analysis workflows inside the R ecosystem.
The same core engine is available in both ecosystems, so teams can start from the interface they already know.
# Install
pip install whitebox_workflows
# Use in Python
import whitebox_workflows as wbw
wbe = wbw.WbEnvironment()
# Read a DEM, run hillshade, write output
dem = wbe.read_raster("dem.tif")
hs = wbe.terrain.general.hillshade(
dem,
azimuth=315.0,
altitude=45.0
)
wbe.write_raster(hs, "hillshade.tif")# Install
R CMD INSTALL whiteboxworkflows
# Use in R
library(whiteboxworkflows)
dem <- wbw_read_raster("dem.tif")
# Run hillshade
wbw_hillshade(
dem = dem$file_path(),
output = "hillshade.tif",
azimuth = 315.0,
altitude = 30.0
)Rust-backed execution for production-sized geospatial workloads. Process millions of pixels and points without compromise.
Run workflows in your environment with transparent inputs and outputs. All computation happens on your machine—no vendor lock-in.
Use Whitebox inside scripts, notebooks, automation pipelines, or analytical research workflows. Same engine, your choice of interface.
Process raster (GeoTIFF, Cloud-Optimized GeoTIFF), vector (GeoPackage, FlatGeobuf, GeoParquet, GeoJSON, Shapefile), and LiDAR (LAS, LAZ, COPC, E57). Substantially expanded format depth in Next Gen.
wbtopology introduces major new vector analysis depth in Next Gen: network analysis, route-event workflows, and linear referencing — capabilities not possible in the previous architecture.
Your Whitebox scripts and workflows are your foundation. As needs change, add Pro capability without starting over.
Whitebox development is guided by a small set of core priorities that make it meaningfully different from most geospatial software. These are not aspirational — they shape every architectural and implementation decision in the platform.
Whitebox aims to be a comprehensive general-purpose GIS and remote sensing toolset — raster, vector, CRS, and LiDAR — while maintaining particular depth in geomorphometry, spatial hydrology, and point-cloud processing. Most platforms specialize in one; Whitebox treats both as non-negotiable.
Most geospatial software is built on a common stack of external C/C++ libraries — GDAL, PROJ, GEOS — for I/O, projection, and geometry. Whitebox does not follow that model. All foundational plumbing is implemented in this codebase: GeoTIFF I/O, map projections, raster abstraction, vector I/O, LiDAR parsing, and topology. This enables end-to-end performance tuning, independent release control, and design decisions that general-purpose external libraries cannot accommodate.
The full-stack approach and pure Rust are deeply linked. Rust provides the performance headroom that makes it practical to implement LiDAR codecs, map projection engines, and raster I/O from scratch without sacrificing speed. It also brings memory safety without a garbage collector and excellent cross-platform compilation with no native toolchain requirements at build time.
Whitebox is a research vehicle as much as a production tool. New spatial analysis algorithms — particularly in geomorphometry and spatial hydrology — are developed, tested, and published through Whitebox first, then made available to the wider community. This is where new ideas enter the platform.
These principles are documented in full in the Whitebox Next Gen repository README.
Unlock Whitebox Workflows Pro to access six advanced proprietary workflow bundles for remote sensing, environmental monitoring, terrain siting, LiDAR analysis, precision agriculture, and network planning.