FAST-GC

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Fully Adaptive Self-Tuning Ground Classification (FAST-GC)

Sensor-adaptive ground classification, spatial LiDAR sampling, and LiDAR-derived geospatial products

FAST-GC is a Python-first framework for automated LiDAR ground classification and downstream geospatial analysis. It supports airborne laser scanning (ALS), UAV laser scanning (ULS), and terrestrial laser scanning (TLS), and integrates ground classification with digital terrain and surface modeling, height normalization, canopy modeling, terrain geomorphometry, continuous-domain hydrology, forest structure, individual-tree workflows, raster change analysis, and FAST-GIS plot sampling and clipping.

The core FAST-GC classifier adapts to acquisition geometry, point-cloud characteristics, and terrain conditions while minimizing scene-specific manual tuning. FAST-GC 0.2.1 also integrates optimized native execution for selected computational stages. Supported precompiled distributions use this automatically; normal users do not need to select or configure a computational backend.

Scientific Reference

The FAST-GC ground-classification methodology is documented in the public preprint:

Fareed, N.; Numata, I.; Silva, C. A.; Prichard, S. J. (2026).
FAST-GC: A Fully Adaptive Self-Tuning Ground Classification Algorithm for Multi-Platform LiDAR Sensors.
Preprints.org, Version 1.

https://www.preprints.org/manuscript/202609.1631

The manuscript is publicly available as a preprint and has been submitted for peer-reviewed publication. The citation will be updated when the final peer-reviewed article becomes available.

Key Capabilities

• Self-tuning ground classification across ALS, ULS, and TLS point clouds
• LAS/LAZ single-file, folder, plot-collection, and large-area tiled processing
• Buffered tiling, parallel processing, seam-aware merging, and downstream derivation
• FAST-GIS spatial sampling, plot import, clipping, buffering, and managed plot collections
• Digital elevation models (DEM) and digital surface models (DSM)
• Height-normalized LiDAR point clouds
• Multiple canopy-height-model (CHM) algorithms
• Terrain morphology, curvature, ruggedness, relief, and multiscale topographic metrics
• Continuous-domain D8/MFD hydrology, contributing area, flow length, streams, watersheds, and terrain-hydrology indices
• Raster and vector hydrology outputs
• Forest structural metrics
• Individual-tree detection and crown workflows
• Individual-tree point-cloud extraction
• Multi-temporal raster change analysis
• CRS-aware geospatial processing and reproducible manifests

Supported LiDAR Platforms

Sensor mode Platform

---

ALS Airborne Laser Scanning ULS UAV / drone Laser Scanning TLS Terrestrial Laser Scanning

The acquisition platform is supplied through --sensor_mode. FAST-GC routes the corresponding sensor-specific ground-classification workflow while downstream product interfaces remain consistent.

Installation

FAST-GC 0.2.1 supports Python 3.12-3.14.

PyPI --- Recommended

pip install fastgc

Verify:

fastgc --version
fastgc --help

Supported precompiled wheels include the optimized execution components required for normal operation. No separate computational-backend configuration is required.

GitHub Source

git clone https://github.com/nadeemfareed/FAST-GC.git
cd FAST-GC
pip install .

A source build may require a Rust toolchain because selected computational kernels use native acceleration.

Conda Development Environment

git clone https://github.com/nadeemfareed/FAST-GC.git
cd FAST-GC
conda env create -f environment.yml
conda activate fastgc
pip install -e .

See INSTALLATION.md for the complete development and environment policy.

Google Colab

!pip install fastgc

from google.colab import drive
drive.mount("/content/drive")

!fastgc \
  --in_path "/content/drive/MyDrive/input.laz" \
  --out_dir "/content/drive/MyDrive/FASTGC_output" \
  --sensor_mode ALS \
  --products FAST_GC

Quick Start

Ground classification:

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC

Ground classification plus terrain products:

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_TERRAIN \
  --terrain_products slope_degrees aspect hillshade multiscale_tpi

The default product is FAST_GC. Input can be a LAS/LAZ file, folder, managed FAST-GIS plot collection, or existing processed-product root depending on the selected workflow.

FAST-GIS --- Spatial Sampling and Plot Workflows

FAST-GIS is the spatial preparation layer integrated with FAST-GC. It is not an additional --products family. Instead, it prepares reproducible plot collections from LiDAR surveys and passes those collections into the normal FAST-GC processing system.

FAST-GIS supports:

• random sampling over observed LiDAR coverage
• continuous optimized-coverage sampling
• rough-height-stratified circular sampling using an existing DSM
• imported plot polygons
• survey-aware multi-file clipping
• core-plus-buffer point extraction
• CRS-aware geometry handling
• circle, hexagon, square, rectangle, and ellipse plot geometries
• continuous-layout width, height, overlap, rotation, and phase controls
• reproducible sampling and workspace manifests
• direct downstream processing through --workflow plots-run

FAST-GIS collections preserve the authoritative core geometry separately from the processing buffer. Buffered points can therefore support neighborhood-sensitive processing while final raster products can be masked back to the intended core plot footprint.

FAST-GIS Sampling Concepts

---

Sampling mode Purpose

---

random Reproducible random plots over observed LiDAR coverage

continuous Optimized continuous plot coverage with configurable geometry, overlap, and rotation

rough_height_stratified Circular plots stratified using rough DSM-relative height classes

imported Clip user-supplied polygon plots from vector/CSV definitions

Supported plot shapes are circle, hexagon, square, rectangle, and ellipse. Continuous sampling additionally supports explicit width, height, overlap, rotation, and phase-search controls.

The integrated FAST-GIS command implementation is exposed through the FAST-GIS entry path associated with the installed FAST-GC package. Use the installed command help for the authoritative syntax of the current build.

FAST-GIS → FAST-GC Processing

A FAST-GIS collection contains plot point clouds plus plots_manifest.json and plot metadata. Process the managed collection with:

fastgc \
  --in_path path/to/ALS_plots \
  --workflow plots-run \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_CHM FAST_TERRAIN

For managed FAST-GIS collections, the sensor mode can be read from plots_manifest.json. External independent plot LAS/LAZ collections can also use plots-run, but should provide --sensor_mode.

Conceptually:

LiDAR survey / survey tiles
          |
          v
       FAST-GIS
          |
          +--> survey catalog / CRS validation
          +--> sampling or imported plot geometry
          +--> core + processing buffer
          +--> clipped plot point clouds
          +--> plots_manifest.json + plot metadata
          |
          v
  fastgc --workflow plots-run
          |
          v
   normal FAST-GC products

FAST-GC Product Families

FAST-GC exposes ten integrated product families through --products. Products can be requested individually or combined according to their dependencies.

---

Product Purpose

---

FAST_GC Sensor-adaptive ground / non-ground classification

FAST_DEM Bare-earth digital elevation model

FAST_NORMALIZED Terrain-normalized LiDAR point cloud

FAST_DSM Upper-surface digital surface model

FAST_CHM Canopy height modeling

FAST_TERRAIN Terrain geomorphometry and continuous-domain hydrology

FAST_STRUCTURE Forest structural metrics

FAST_ITD Individual-tree detection / crown workflows

FAST_TREECLOUDS Individual-tree point-cloud extraction

FAST_CHANGE Multi-temporal raster change analysis

FAST_GC --- Ground Classification

FAST_GC is the core product: multi-stage, sensor-adaptive ground/non-ground classification for ALS, ULS, and TLS point clouds. Classified ground points provide the terrain reference used by downstream products.

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --workflow run \
  --products FAST_GC

FAST_DEM --- Digital Elevation Model

FAST_DEM generates a bare-earth terrain raster from classified ground points. Supported rasterization methods are min, max, mean, nearest, and idw; resolution is controlled with --grid_res.

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM \
  --grid_res 0.5 \
  --dem_method nearest

FAST_NORMALIZED --- Height-Normalized Point Cloud

FAST_NORMALIZED references point elevations to the local terrain surface, producing above-ground heights for canopy, structure, and tree-level analysis.

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_NORMALIZED

FAST_DSM --- Digital Surface Model

FAST_DSM represents the upper LiDAR surface and can be produced directly from the point cloud when ground classification is not otherwise required. Methods are min, max, mean, nearest, idw, and spikefree.

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_DSM \
  --grid_res 0.5 \
  --dsm_method max

FAST_CHM --- Canopy Height Models

FAST_CHM generates canopy-height surfaces from terrain-referenced LiDAR.

Method Processing concept

---

p2r Point-to-raster canopy surface p99 Percentile-based upper-canopy surface tin Triangulated canopy surface pitfree Pit-free canopy surface adaptive_pitfree Adaptive pit-free processing csf_chm Cloth-simulation-based CHM spikefree Spike-resistant surface processing percentile Percentile selector workflow percentile_top Upper-canopy percentile selection percentile_band Selected canopy-height-band workflow

Multiple CHMs can be generated in one run:

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_CHM \
  --chm_methods p2r p99 pitfree adaptive_pitfree

FAST_TERRAIN --- Terrain and Hydrology

FAST_TERRAIN is the integrated terrain-analysis family. It operates from FAST_DEM and contains both local terrain geomorphometry and continuous-domain hydrological analysis.

The release separates two concepts:

1. Established local/core terrain products --- selected individually or with --terrain_products all.
2. Continuous-domain hydrology products --- selected explicitly and derived from an authoritative continuous DEM.

This distinction is important. --terrain_products all intentionally refers to the established local/core terrain set; it should not be interpreted as automatically requesting every continuous hydrology product.

Terrain Morphometry

Available terrain descriptors include:

• slope_percent
• slope_degrees
• aspect
• hillshade
• curvature --- retained legacy Laplacian curvature
• profile_curvature
• tangential_curvature
• planform_curvature
• mean_curvature
• gaussian_curvature
• tpi
• multiscale_tpi
• positive_openness
• negative_openness
• tri
• roughness
• local_relief
• legacy-compatible twi
• legacy-compatible dtw
• tci

Example:

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_TERRAIN \
  --terrain_products slope_degrees aspect hillshade profile_curvature \
                     planform_curvature multiscale_tpi positive_openness \
                     negative_openness tri roughness local_relief

Default physical scales for multiscale TPI and openness can be overridden:

--multiscale_tpi_radii_m 5 10 25 50 100
--openness_radii_m 5 10 25 50 100

Continuous-Domain Hydrology

The expanded FAST_TERRAIN hydrology system includes:

DEM conditioning

• conditioned_dem
• depression_depth

D8 flow routing

• d8_flow_direction
• d8_flow_accumulation
• d8_contributing_area
• d8_specific_catchment_area
• d8_downslope_flow_length
• d8_longest_upslope_flow_length

Multiple-flow-direction routing

• mfd_flow_accumulation
• mfd_contributing_area
• mfd_specific_catchment_area

Stream network

• stream_mask
• strahler_stream_order
• stream_link_id

Catchments and drainage structure

• basin_id
• subcatchment_id
• watershed_boundary

Hydrologic / erosion-related indices

• topographic_wetness_index
• stream_power_index
• rusle_s_factor
• contributing_area_ls_factor

Continuous hydrology products are requested explicitly. For example:

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_TERRAIN \
  --terrain_products conditioned_dem depression_depth \
                     d8_flow_direction d8_flow_accumulation \
                     d8_contributing_area d8_specific_catchment_area \
                     mfd_flow_accumulation mfd_contributing_area \
                     stream_mask strahler_stream_order stream_link_id \
                     basin_id subcatchment_id watershed_boundary \
                     topographic_wetness_index stream_power_index \
                     d8_downslope_flow_length d8_longest_upslope_flow_length \
                     rusle_s_factor contributing_area_ls_factor

Raster and Vector Hydrology

FAST_TERRAIN supports:

--terrain_output raster
--terrain_output vector
--terrain_output both

The default is raster.

Vector hydrology is generated from the authoritative continuous DEM. Stream-network extraction can be controlled with:

--stream_threshold_area_m2 1000
--stream_min_order 1

--stream_threshold_area_m2 defines the minimum contributing area used for the analytical stream network. --stream_min_order controls the minimum Strahler order exported to vector stream layers and does not alter the complete analytical raster.

Example requesting terrain hydrology plus vector output:

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_TERRAIN \
  --terrain_products conditioned_dem d8_flow_direction \
                     d8_contributing_area stream_mask \
                     strahler_stream_order stream_link_id \
                     basin_id subcatchment_id watershed_boundary \
                     topographic_wetness_index stream_power_index \
  --terrain_output both \
  --stream_threshold_area_m2 1000 \
  --stream_min_order 1

Why FAST_TERRAIN Uses the Merged DEM

For tiled large-area workflows, ordinary products can be processed tile-by-tile and merged according to their product semantics. Hydrological terrain analysis is different because flow topology must remain continuous across tile boundaries.

FAST-GC therefore treats the final FAST_DEM mosaic as the authoritative continuous terrain surface for merged FAST_TERRAIN derivation. Final continuous-domain FAST_TERRAIN products are regenerated from the successfully merged DEM rather than being created by simply mosaicking independently derived hydrology tiles.

Conceptually:

Buffered LiDAR tiles
       |
       v
   FAST_GC tiles
       |
       v
   FAST_DEM tiles
       |
       v
  MERGED FAST_DEM
       |
       +--------------------------+
       |                          |
       v                          v
Terrain morphometry      Continuous hydrology
                                  |
                    +-------------+-------------+
                    |             |             |
                   D8            MFD        Streams /
                                             Basins /
                                           Watersheds

This continuous-domain rule is especially important for flow direction, accumulation, contributing area, stream topology, watersheds, flow length, and related indices.

FAST_STRUCTURE --- Forest Structure

FAST_STRUCTURE derives spatial forest-structure metrics from FAST_NORMALIZED, including canopy cover, mean height, maximum height, height standard deviation, foliage height diversity (FHD), vertical complexity index (VCI), and point count.

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_STRUCTURE \
  --structure_products all

FAST_ITD --- Individual Tree Detection

FAST_ITD provides individual-tree detection workflows using canopy-height or compatible surface information. The established public workflows include local-maxima filtering (lmf), watershed (watershed), adaptive watershed (adaptive_watershed), and the Yun et al. (2021) workflow (yun2021). Watershed-based workflows can support crown delineation, while lmf provides treetop detection.

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_CHM FAST_ITD \
  --chm_method pitfree \
  --itd_method watershed

The CLI may expose additional dispatcher method names for development or compatibility. A method should only be treated as an established workflow when its implementation is available and validated.

FAST_TREECLOUDS --- Individual-Tree Point Clouds

FAST_TREECLOUDS associates LiDAR points with tree/crown delineations and creates tree-level point-cloud products. The point source can be FAST_NORMALIZED or FAST_GC, with optional individual LAS writing.

fastgc \
  --in_path processed_FASTGC_workspace \
  --sensor_mode ALS \
  --workflow derive-only \
  --products FAST_TREECLOUDS \
  --treeclouds_las_source FAST_NORMALIZED \
  --treeclouds_write_individual

FAST_CHANGE --- Raster Change Analysis

FAST_CHANGE compares compatible FAST_DEM, FAST_DSM, FAST_CHM, or FAST_TERRAIN raster observations. Comparison modes are pairwise, sequential, and baseline, with threshold and level-of-detection controls.

fastgc \
  --in_path processed_FASTGC_workspace \
  --sensor_mode ALS \
  --workflow derive-only \
  --products FAST_CHANGE \
  --change_input_type FAST_CHM \
  --change_mode sequential

Overall Processing Architecture

FAST-GC separates spatial preparation, raw-LiDAR processing, terrain-referenced derivation, and specialized downstream analysis.

                    LiDAR survey / LAS / LAZ
                              |
              +---------------+---------------+
              |                               |
              | optional                      | direct
              v                               |
           FAST-GIS                           |
   sampling / imported plots                  |
   clipping / core + buffer                   |
   manifests / plot collections               |
              |                               |
              +---------------+---------------+
                              |
                              v
                           FAST_GC
                     ground classification
                              |
              +---------------+----------------+
              |                                |
              v                                v
           FAST_DEM                          FAST_DSM
              |                                |
      +-------+---------+                      |
      |                 |                      |
      v                 v                      |
FAST_NORMALIZED    FAST_TERRAIN                 |
      |            terrain + hydrology         |
      |                 |                      |
      |        authoritative merged DEM        |
      |        for continuous hydrology        |
      |                                        |
 +----+--------------+                         |
 |                   |                         |
 v                   v                         |
FAST_CHM       FAST_STRUCTURE                   |
 |                                             |
 v                                             |
FAST_ITD <-------------------------------------+
 |
 v
FAST_TREECLOUDS

Compatible DEM / DSM / CHM / TERRAIN rasters
                     |
                     v
                 FAST_CHANGE

Not every product requires every preceding stage. For example, FAST_DSM can operate directly on a point cloud, while FAST_NORMALIZED requires a terrain reference. FAST_TERRAIN depends on FAST_DEM; continuous-domain terrain hydrology uses the authoritative merged DEM in merged/tiled workflows.

Workflow Modes

---

Workflow Purpose

---

run Process an input file or collection directly

plots-run Process managed FAST-GIS plots or external independent plot point clouds

tile-only Create buffered processing tiles without deriving products

tile-run Tile and process without final merging

tile-run-merge Tile, process, merge, and derive final merged products

merge Merge previously processed tiled outputs

derive-only Derive downstream products from existing compatible FAST-GC outputs

Processing Scenarios

1. Single LAS/LAZ --- Ground Classification

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --workflow run \
  --products FAST_GC

Change ALS to ULS or TLS according to the acquisition platform.

2. Folder / Batch Processing

fastgc \
  --in_path lidar_folder \
  --out_dir output \
  --sensor_mode ULS \
  --workflow run \
  --products FAST_GC \
  --recursive

3. FAST-GIS Managed Plot Collection

fastgc \
  --in_path path/to/ULS_plots \
  --workflow plots-run \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_CHM

4. Large Dataset --- Tiling Only

fastgc \
  --in_path large_input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --workflow tile-only \
  --tile_size_m 250 \
  --buffer_m 5

5. Tile and Process

fastgc \
  --in_path large_input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --workflow tile-run \
  --tile_size_m 250 \
  --buffer_m 5 \
  --products FAST_GC FAST_DEM FAST_NORMALIZED

6. Complete Tile → Process → Merge

fastgc \
  --in_path large_input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --workflow tile-run-merge \
  --tile_size_m 100 \
  --buffer_m 5 \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_DSM FAST_CHM FAST_TERRAIN \
  --terrain_products all \
  --jobs 0

This produces the established local/core FAST_TERRAIN set. Add continuous hydrology products explicitly when they are required.

7. Large-Area Terrain + Hydrology

fastgc \
  --in_path large_input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --workflow tile-run-merge \
  --tile_size_m 100 \
  --buffer_m 5 \
  --products FAST_GC FAST_DEM FAST_TERRAIN \
  --terrain_products slope_degrees aspect hillshade multiscale_tpi \
                     conditioned_dem depression_depth \
                     d8_flow_direction d8_contributing_area \
                     mfd_contributing_area \
                     stream_mask strahler_stream_order stream_link_id \
                     basin_id subcatchment_id watershed_boundary \
                     topographic_wetness_index stream_power_index \
                     rusle_s_factor contributing_area_ls_factor \
  --terrain_output both \
  --stream_threshold_area_m2 1000 \
  --stream_min_order 1 \
  --jobs 0

The merged FAST_DEM becomes the authoritative surface for the final continuous-domain FAST_TERRAIN analysis.

8. Multiple CHMs in One Run

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_CHM \
  --chm_methods p2r p99 pitfree adaptive_pitfree

9. Derive Products Without Re-running Ground Classification

fastgc \
  --in_path processed_FASTGC_workspace \
  --sensor_mode ALS \
  --workflow derive-only \
  --products FAST_CHM \
  --chm_methods p2r p99 pitfree

Forest structure can similarly be derived from an existing compatible workspace:

fastgc \
  --in_path processed_FASTGC_workspace \
  --sensor_mode ALS \
  --workflow derive-only \
  --products FAST_STRUCTURE \
  --structure_products all

10. Merge Existing Tiled Results

fastgc \
  --in_path processed_FASTGC_workspace \
  --sensor_mode ALS \
  --workflow merge \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_DSM FAST_TERRAIN

11. Individual-Tree Workflow

fastgc \
  --in_path input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --products FAST_GC FAST_DEM FAST_NORMALIZED FAST_CHM FAST_ITD \
  --chm_method pitfree \
  --itd_method watershed

12. Raster Change Workflow

fastgc \
  --in_path processed_FASTGC_workspace \
  --sensor_mode ALS \
  --workflow derive-only \
  --products FAST_CHANGE \
  --change_input_type FAST_CHM \
  --change_mode sequential

13. Google Colab / Google Drive

!fastgc \
  --in_path "/content/drive/MyDrive/input.laz" \
  --out_dir "/content/drive/MyDrive/FASTGC_output" \
  --sensor_mode ALS \
  --workflow run \
  --products FAST_GC

Notebook environments are convenient for modest datasets. Large-area tiled processing is generally better suited to a workstation or dedicated compute environment.

Parallel and Large-Area Processing

FAST-GC supports tile-parallel execution. --jobs 0 allows FAST-GC to select the available CPU worker count automatically while reserving one logical CPU.

fastgc \
  --in_path large_input.laz \
  --out_dir output \
  --sensor_mode ALS \
  --workflow tile-run-merge \
  --tile_size_m 250 \
  --buffer_m 5 \
  --jobs 0 \
  --products FAST_GC FAST_DEM

Explicit worker counts can also be supplied with --jobs.

Typical Output Organization

Depending on requested products, an output workspace can contain:

FASTGC_output/
|
+-- FAST_GC/
+-- FAST_DEM/
+-- FAST_NORMALIZED/
+-- FAST_DSM/
+-- FAST_CHM/
+-- FAST_TERRAIN/
|   +-- slope_degrees/
|   +-- aspect/
|   +-- curvature/
|   +-- multiscale_tpi/
|   +-- positive_openness/
|   +-- negative_openness/
|   +-- conditioned_dem/
|   +-- d8_flow_direction/
|   +-- d8_contributing_area/
|   +-- stream_mask/
|   +-- strahler_stream_order/
|   +-- basin_id/
|   +-- watershed_boundary/
|   +-- ...
+-- FAST_TERRAIN_HYDROLOGY_VECTOR/
+-- FAST_STRUCTURE/
+-- FAST_ITD/
+-- FAST_TREECLOUDS/
+-- FAST_CHANGE/

Point-cloud products are written as LAS/LAZ outputs and raster products as geospatial raster outputs according to the selected workflow. FAST_TERRAIN vector hydrology is routed separately from raster terrain products.

A FAST-GIS workspace additionally maintains sampling/plot metadata such as:

FAST_GIS_workspace/
|
+-- workspace_manifest.json
+-- sampling_manifest.json
+-- sample_plots.geojson
+-- ALS_plots/  (or ULS_plots / TLS_plots)
    +-- plots_manifest.json
    +-- Plot_001/
    +-- Plot_002/
    +-- ...

Important Terrain/Hydrology Notes

• FAST_TERRAIN depends on FAST_DEM.
• --terrain_products all means the established local/core terrain set; continuous hydrology products are requested explicitly.
• Continuous hydrology is derived from an authoritative continuous DEM.
• In tiled merged workflows, final continuous-domain FAST_TERRAIN products are derived from the merged FAST_DEM rather than mosaicked from independently derived hydrology tiles.
• --terrain_output raster is the default.
• --terrain_output vector and --terrain_output both enable vector hydrology generation.
• --stream_threshold_area_m2 controls the analytical stream-network contributing-area threshold.
• --stream_min_order controls the minimum Strahler order exported to vector streams without changing the complete analytical raster.
• Multiscale TPI and openness use physical radii in metres.
• Categorical hydrology products preserve categorical raster semantics rather than being treated as ordinary continuous floating-point surfaces.

Command-Line Reference

The installed CLI is the authoritative reference for current processing options:

fastgc --help

Check the installed version with:

fastgc --version

Major option groups include:

• sensor and workflow selection
• product selection
• DEM / DSM rasterization
• CHM generation
• terrain and hydrology products
• raster/vector terrain output
• stream-network controls
• multiscale TPI and openness
• forest structure
• ITD
• tree-cloud extraction
• raster change analysis
• tiling and parallel execution

Release Validation

FAST-GC release development uses automated regression tests covering core routing, CLI contracts, CRS propagation, FAST-GIS behavior, terrain product registration, DEM dependencies, terrain raster semantics, D8 and MFD hydrology, DEM conditioning, flats, streams, Strahler ordering, stream links, watersheds, vector topology, flow length, TWI/SPI, RUSLE-related products, openness, and output routing.

Users developing from source should run:

python -m pytest -q

before packaging or publishing modified builds.

Citation

If FAST-GC contributes to your research, please cite:

Fareed, N.; Numata, I.; Silva, C. A.; Prichard, S. J. (2026).
FAST-GC: A Fully Adaptive Self-Tuning Ground Classification Algorithm for Multi-Platform LiDAR Sensors.
Preprints.org, Version 1.
https://www.preprints.org/manuscript/202609.1631

The manuscript has been submitted for peer-reviewed publication. Until the final article is available, the public preprint above is the current scientific reference. This README will be updated with the final journal citation and DOI when the peer-reviewed article is published.

Repository and Support

Source code: https://github.com/nadeemfareed/FAST-GC\ Issues and feature requests: https://github.com/nadeemfareed/FAST-GC/issues

Author

FAST-GC was conceived, developed, implemented, and is maintained by Nadeem Fareed.

Copyright © 2026 Nadeem Fareed.

License

FAST-GC is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0-or-later).

See LICENSE for the complete license terms.