Overview

This manual is the long-form user guide for the WbW-R API.

WbW-R (Whitebox Workflows for R) is the R frontend to Whitebox Next Gen, providing access to modern geospatial processing for raster, vector, lidar, and sensor-bundle data through an R-friendly API and workflow model.

Whitebox is a long-running geospatial project that originated in academia and has grown into a broad analysis platform with recognized strengths in geomorphometry, hydrology, lidar processing, and remote sensing. Whitebox Next Gen is the current Rust-based major iteration focused on performance, cross-platform reliability, and modern data formats.

Whitebox Next Gen is intentionally full-stack: core geospatial capabilities that are often delegated to external C/C++ dependencies in other GIS platforms (for example raster I/O, projections, geometry/topology operations, and lidar handling) are implemented in the Whitebox codebase itself. This architecture is unusual in GIS and provides practical benefits for users: consistent behavior across platforms, tighter control over correctness and performance, fewer system-level dependency issues during installation, and faster iteration when fixing bugs or introducing new capabilities.

In this architecture, WbW-R is the orchestration layer for R users who need both practical scripting ergonomics and backend-scale performance.

This manual is written to be both:

  • beginner friendly: clear progression and runnable examples,
  • canonical reference: explicit operational patterns, constraints, and validation guidance aligned with backend behavior.

How to Use This Manual

This guide is intended for analysts who want to move from one-off exploratory commands to stable, scriptable geospatial workflows. The examples are practical and executable, but each chapter also explains the operational intent behind the code: when to keep work in memory, when to persist outputs, and how to validate results between stages.

A good first pass is chapter-order reading. After that, use the script index as a task-oriented entry point for adapting workflows to your own projects.

When adapting examples, keep a consistent script shape:

  1. session setup,
  2. input loading,
  3. transformation chain,
  4. validation and output persistence.

This structure keeps scripts easier to review, test, and maintain.

Goals:

  • Comprehensive API coverage.
  • Script-first documentation style.
  • Chapter layout aligned with the project README.

Documentation style rules:

  • Every major concept includes runnable code snippets.
  • Each chapter includes at least one end-to-end workflow script.
  • Tool parameter specifics are linked to shared tool reference docs as needed.

Common Pitfalls and Validation

  • Confirm inputs exist and have the expected CRS/schema/metadata before running long workflows.
  • Prefer explicit output names and formats for reproducibility, especially in batch scripts.
  • Re-open and inspect outputs after major steps to validate assumptions before chaining more tools.
  • For performance-sensitive runs, start with a small representative subset, then scale to full data.

Write Option References

For quick access to output option tables: