lidar2map

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lidar2map

Offline archaeological LiDAR maps, multi-country + IGN raster/vector + OSM, for Locus Map / OsmAnd / TwoNav

A self-contained Python tool that downloads public LiDAR data from several national portals (IGN France, AHN Netherlands, swisstopo Switzerland, Kartverket Norway), computes relief visualizations tuned for archaeological prospection, and generates maps usable offline on a smartphone (MBTiles, RMAP, SQLiteDB, Mapsforge formats). The IGN raster/vector maps remain France-only.

The same extent under three views: aerial imagery and the OSM map show nothing of the micro-relief — the Sky-View Factor computed from the HD LiDAR reveals it instantly.

⚠️ Status: personal project, publicly released. Heavily tested on Windows 10/11. Linux and macOS tested partially — known cases + cross-OS troubleshooting in the Troubleshooting section of BUILD.md. Feedback welcome via GitHub issues.

Note: the GUI auto-detects your language (English/French, with a manual toggle) and the CLI flags and --help are in English. The former French flag names still work as aliases, so older example commands keep working.

Who is it for?

Amateur archaeologists interested in LiDAR prospection — the tool works in France (IGN HD), the Netherlands (AHN4), Switzerland (swissALTI3D) and Norway (Nasjonal Høydemodell). The relief computations (multi, SVF, LRM, RRIM) are identical from one country to the next.
French hikers who want offline IGN topo maps on their phone (Locus Map Pro, OsmAnd+) — the IGN raster/vector tabs remain France-only.
Landscape surveyors who combine historical orthophotos (1950-1995, France) with a DEM to spot human remains before agricultural land abandonment erases them.
Cavers / explorers who need accurate base maps in areas not covered by mainstream apps.

The tool is not intended for metal detecting. The code strictly respects the open licenses involved (Etalab FR, CC BY 4.0 NO, CC-0 NL, BGDI CH).

What it produces

From a town, GPS coordinates, a bbox, a département or a whole region:

Archaeological relief from national LiDAR (0.5 m to 1 m resolution depending on source):
- Multidirectional hillshade (25° sun angle for micro-relief)
- Configurable SVF (Sky-View Factor) — reveals ditches, terraces, enclosures. flux convention (cos²γ, more visual contrast, default) or rvt (1−sin γ, the Kokalj/Hesse archaeology standard / openness); adjustable horizon distance (10–200 m, default 20 m); display gamma; sweep-horizon kernel. Flags: --svf-conv flux|rvt, --svf-dist M, --svf-gamma G, --svf-sweep / --no-svf-sweep (or the SVF panel in the GUI).
- LRM (Local Relief Model) — removes the natural terrain, keeps the anomalies
- RRIM (Red Relief Image Map) — color composite (slope + LRM)
Supported LiDAR sources (via the --provider <code> flag):
- France (fr-ign, default) — IGN LiDAR HD, 0.5 m, national coverage
- Netherlands (nl-ahn) — AHN4, 0.5 m, national coverage
- Switzerland (ch-swisstopo) — swissALTI3D, 0.5 m, national coverage
- Norway (no-kartverket) — Nasjonal Høydemodell, 1 m, national coverage
IGN raster maps (France only): Plan IGN, orthophotos (current + historical 1950, 1965, 1980), 19th-century État-Major, Pléiades satellite, CIR, etc.
Vector maps: OSM Mapsforge .map (international, via Geofabrik) or IGN BD TOPO (France only)
Outputs: MBTiles (universal), RMAP (CompeGPS / TwoNav), SQLiteDB (RMaps schema — Locus Map / OsmAnd), Mapsforge .map (OsmAnd / Locus)

Installation and usage

Two ways to use lidar2map:

	A. Python script	B. Standalone executable
Requirements	Python 3.12	None
First install	~5 min (deps bootstrap)	None
Updates	`git pull` + relaunch	Patch the 3 existing binaries on the GitHub release in one command: `python update_app.py --release` (see `update_app.py`)
Distributable	No — each user installs Python	Yes — `.exe` / `.app` / Linux binary + zip bundle side by side
Best for	dev / Linux / contributing code	end user / Windows / distributing

A. Python script

On first launch, the script creates ~/.lidar2map/venv and installs the critical dependencies there (Pillow, pyproj, numpy, rasterio, pywebview + PyQt6/QtWebEngine…). GDAL (Windows), the Temurin 21 JRE and osmosis are downloaded on demand. ~400 MB total, once.

Windows 10+

Install Python 3.12+

Get the code:

git clone https://github.com/nico579/lidar2map
cd lidar2map
python lidar2map.py

macOS 11+

brew install python@3.12
git clone https://github.com/nico579/lidar2map
cd lidar2map
python3.12 lidar2map.py

Linux (Debian / Ubuntu)

sudo apt install python3.12 python3.12-venv git
git clone https://github.com/nico579/lidar2map
cd lidar2map
python3.12 lidar2map.py

The script will ask permission to install GDAL via sudo apt install gdal-bin.

Troubleshooting: the Troubleshooting section of BUILD.md (including Linux/macOS-specific cases: PEP 668, Qt distro packages, Wayland, Gatekeeper on the JRE…).

B. Standalone executable

No Python for the end user to install. The deliverable carries its own runtime (embedded Python, deps, JRE, osmosis).

1. Get the deliverable

Option a — Download from Releases (if the version is published for your platform):

OS	Archive	Extract with
Windows 10/11 (x86_64)	`lidar2map-windows-x86_64.zip`	`Expand-Archive` (PowerShell) or double-click
Linux Ubuntu 24.04+ (x86_64)	`lidar2map-linux-x86_64.tar.gz`	`tar xzf`
macOS 12+ (Apple Silicon)	`lidar2map-macos-arm64.zip`	`unzip` then `xattr -dr com.apple.quarantine LIDAR2MAP.app`

The archive extracts into a lidar2map-<os>-x86_64/ folder containing the binary and its lidar2map_bundle.zip side by side. No system installation.

Option b — Build it yourself. Two scripts per platform: a machine setup (do once) then a build (re-run each time lidar2map.py is updated).

Windows

git clone https://github.com/nico579/lidar2map
cd lidar2map
.\setup_build_windows.ps1     # 1. Setup: Python 3.12, deps, JRE, osmosis, PyInstaller
.\lidar2map_win_build.ps1     # 2. Build: 3 steps -> dist\lidar2map.exe + dist\lidar2map_bundle.zip

macOS (Apple Silicon)

git clone https://github.com/nico579/lidar2map
cd lidar2map
bash setup_build_mac.sh       # 1. Setup
bash lidar2map_mac_build.sh   # 2. Build -> dist/LIDAR2MAP.app

Linux (Ubuntu / Debian)

Linux reuses the Windows specs (_win.spec produces an ELF on Linux — the name is misleading).

git clone https://github.com/nico579/lidar2map
cd lidar2map
bash setup_build_linux.sh       # 1. Setup
bash lidar2map_linux_build.sh   # 2. Build -> dist/lidar2map + dist/lidar2map_bundle.zip

Requirement: sudo apt install zip if missing. The produced binary depends on the build machine's libc (build on Ubuntu 22.04 → runs on Ubuntu ≥ 22.04 / Debian 12+).

Full build documentation (bundle architecture, updating without rebuild, troubleshooting): BUILD.md.

2. Run the deliverable

OS	Command
Windows	Double-click `lidar2map.exe` (or run from a terminal to see the log)
Linux	`chmod +x lidar2map && ./lidar2map` in the extracted folder
macOS	Double-click `LIDAR2MAP.app`. First launch blocked by Gatekeeper: `xattr -dr com.apple.quarantine LIDAR2MAP.app` then double-click
Linux	`chmod +x lidar2map && ./lidar2map`

The first launch extracts the bundle (~30-60 s, once — it contains Qt) into:

Windows: %LOCALAPPDATA%\lidar2map\
macOS: ~/Library/Application Support/lidar2map/
Linux: ~/.local/share/lidar2map/

Clean uninstall: lidar2map(.exe) --desinstaller.

Usage

Two modes, selected automatically based on the arguments (same logic as the twin project gpxsolar):

No argument → graphical interface (pywebview / Qt). The common mode.
With arguments → command-line computation (headless, no window). Handy for scripting, running on a server, or reproducing an exact render.

Everything below applies to the binary as well as the script — just replace python lidar2map.py with lidar2map.exe (Windows), ./lidar2map (Linux) or LIDAR2MAP.app (macOS).

Command-line examples

The flags below are English. The former French flag names still work as aliases, so older commands keep working.

SVF relief + IGN topo map over a town (1 km² zone around Garéoult, France):

python lidar2map.py --lidar --zone-city Gareoult --zone-radius 1 \
    --shadings multi svf --file-formats mbtiles --yes

Relief over Amsterdam (Netherlands, AHN4):

python lidar2map.py --provider nl-ahn --lidar --download \
    --zone-bbox 120000,486000,122000,488000 --zone-name amsterdam \
    --shadings multi --file-formats mbtiles --yes

Relief over Geneva (Switzerland, swissALTI3D):

python lidar2map.py --provider ch-swisstopo --lidar --download \
    --zone-city Geneve --zone-radius 1 \
    --shadings svf --file-formats mbtiles --yes

Relief over Oslo (Norway, Kartverket):

python lidar2map.py --provider no-kartverket --lidar --download \
    --zone-city Oslo --zone-radius 1 \
    --shadings multi --file-formats mbtiles --yes

Historical 1950-1965 orthophoto over an archaeological survey area:

python lidar2map.py --raster --zone-bbox 6.0,43.3,6.1,43.4 \
    --layer ortho_1950 --zoom-min 14 --zoom-max 18 --yes

OSM vector map (Mapsforge .map) for Locus, whole département:

python lidar2map.py --osm --zone-department 83 --file-formats map --yes

Whole region (--zone-region) — available for all modes:

# OSM: a single map for the whole region, no re-splitting
# (the Geofabrik PBF IS already regional — far faster than looping per département)
python lidar2map.py --osm --zone-region provence-alpes-cote-d-azur --yes

# IGN vector: paths/routes for the whole region as GeoJSON + Locus .map
python lidar2map.py --vector --zone-region provence-alpes-cote-d-azur \
    --layer chemins --file-formats gz map --yes

The slug is the one from Geofabrik France (old-style regions: provence-alpes-cote-d-azur, bretagne, corse, rhone-alpes…). In OSM the region is processed as one block (the Geofabrik file is already regional, no per-département geocoding); for the raster/vector/lidar modes the area is the bbox enclosing all the départements of the region. An unknown slug lists the available regions.

IGN BD TOPO map (roads + buildings) as compressed GeoJSON + Mapsforge .map:

python lidar2map.py --vector --zone-department 83 \
    --layer routes batiments --file-formats gz map --yes

The map format converts the IGN GeoJSON into a Mapsforge .map map (readable by Locus Map / OsmAnd).

LiDAR providers — adding a country

The provider abstraction lets you add a national LiDAR source without touching the core of the pipeline. Each provider lives in providers/<code>.py (~50-200 lines) and exposes:

NAME, CODE, COUNTRY, LICENSE          # metadata
CRS_NATIF, RESOLUTION_M, DALLE_KM     # geometry
discover_dalles(bbox_wgs, bbox_natif, cache)  # → {name: url}
# + helpers: dalle_filename, dalle_url, subdir_from_name, dalles_pour_bbox

The downstream pipeline (SVF, relief, EPSG:3857 warp, MBTiles) is provider-agnostic: it consumes the GeoTIFFs returned by discover_dalles, regardless of the native CRS or the index format used upstream.

Code	Country	Native CRS	Resolution	API paradigm
`fr-ign`	France	EPSG:2154 (Lambert-93)	0.5 m	Vector TMS PBF + WMS GetMap
`nl-ahn`	Netherlands	EPSG:28992 (RD New)	0.5 m	ATOM feed + JSON FeatureCollection
`ch-swisstopo`	Switzerland	EPSG:2056 (CH1903+/LV95)	0.5 m	STAC REST API
`no-kartverket`	Norway	EPSG:25833 (UTM33N)	1 m	ArcGIS ImageServer exportImage

Selection: --provider <code> flag (CLI), LIDAR2MAP_PROVIDER env var, or the dropdown at the top of the GUI.

To add a 5th country (e.g. UK Environment Agency, Spain PNOA-LiDAR, Italy PNRR): copy the provider closest in paradigm and adapt URLs/CRS/naming format. The first completed provider takes ~½ a day, the next ones ~1-2h each.

Main features

Auto-bootstrap: no pre-installed dependency required. The script downloads on demand: Python deps (Pillow, pyproj, numpy, scipy), GDAL (Windows) or asks for system install (Linux/macOS), Temurin 21 JRE, osmosis, mapwriter.
Memory streaming: département-scale processing without saturating RAM (ijson, rasterio windowed reads, tile-by-tile MBTiles generation).
Clean cancellation: Ctrl+C once → stops after the current chunk. Ctrl+C twice → immediate stop.
Resume after interruption: the same command resumes where it stopped, via a .json manifest that tracks completed chunks.
Up-front splitting: for large areas, split into an N×N grid — useful so you don't have to regenerate the whole area if something crashes.
Crash-safe history: each run is recorded at startup (status "running") then finalized to "ok" or "ko". A hard crash (kill -9, power loss) leaves the entry visible in the UI — the trace is kept for debugging.
Multi-provider LiDAR: a providers/<code>.py abstraction that lets you plug in any national LiDAR source. 4 providers shipped (FR/NL/CH/NO) covering 4 distinct API paradigms (TMS PBF, JSON FeatureCollection, STAC API, ArcGIS ImageServer). Adding a 5th country = ~50-150 lines in a new provider file.
Interactive GUI: 6 tabs (LiDAR, IGN raster, IGN vector, OSM, Merge, Splitting), provider selector at the top of the form (IGN Raster/Vector tabs hidden automatically for non-FR providers), history of the last 50 commands with status badges, parameter validation, live log, error modal.
Historical orthophoto maps: a unique combo for archaeology — SVF 2024 (current LiDAR) + 1950 ortho (before land abandonment) → reveals structures still legible 70 years later.

Screenshots

Graphical interface

Six tabs to drive LiDAR, IGN raster/vector, OSM, merge and splitting.

HD LiDAR (archaeological relief)	IGN raster (Plan / ortho / historical)	IGN vector (BD TOPO)

OSM vector (Mapsforge)	Vector merge	Raster splitting

Rendering in Locus Map

Archaeological LiDAR relief shown as an overlay on the terrain in Locus Map.

SVF (Sky-View Factor)	Multi-hillshade overlay

What SVF reveals — same area, three sources

Under tree cover, the aerial photo and OSM show nothing. The LiDAR SVF makes the terraces (dry-stone restanques) and old paths appear — invisible from above.

Satellite photo	OSM	SVF (HD LiDAR)

Opaque scrubland	Almost no detail	Crisp terraces + paths

Reproducing this render

The header SVF and the triptych above (Rougiers area, dép. 83, France) were computed with:

python lidar2map.py \
  --zone-gps <lat> <lon> --zone-radius 1 --zone-name hero \
  --lidar --download --workers 8 \
  --shadings svf --shading-elevation 25 \
  --svf-conv rvt --svf-dist 20 --svf-gamma 0.8 --svf-sweep \
  --file-formats mbtiles --zoom-min 8 --zoom-max 18 \
  --image-format jpeg --image-quality 85 --yes

Replace <lat> <lon> with your own area; the SVF parameters above are the ones used for the visual. The exact coordinates of a micro-relief are deliberately not published (ethics: do not guide anyone toward a specific site — see the anti-detecting disclaimer above).

Documentation

User README: this file
Build & deployment: BUILD.md — bundle architecture, per-OS build scripts, updating without rebuild, troubleshooting (including Linux- and macOS-specific cases)
Built-in help: python lidar2map.py --help (LiDAR), --raster --help (raster), --vector --help (vector), --osm --help, --merge --help

License

Code distributed under the GNU General Public License v3.0 — see LICENSE.

You are free to use, modify and redistribute this software under the terms of the GPL v3. In particular: if you redistribute a modified version, you must provide the modified source code under the same license.

Author

Designed and architected by Nicolas Martin (@nico579). Code developed with the assistance of Claude (Anthropic) as a development tool.

Acknowledgements

Data used:

IGN (French National Institute of Geographic and Forest Information) — LiDAR HD, BD ORTHO (including the historical 1950-1995 versions), BD TOPO, under the Etalab 2.0 license
OpenStreetMap — vector data under the ODbL license, distributed by Geofabrik
Apache JMapsforge / mapsforge-map-writer — offline vector rendering engine

Bundled tools: GDAL, osmosis, py7zr, pyproj, numpy, scipy, Pillow, ijson, pywebview.

Name		Name	Last commit message	Last commit date
Latest commit History 120 Commits
.github/workflows		.github/workflows
providers		providers
screenshots		screenshots
.gitignore		.gitignore
BUILD.md		BUILD.md
LICENSE		LICENSE
README.fr.md		README.fr.md
README.md		README.md
_loader.py		_loader.py
deploy.py		deploy.py
lidar2map.py		lidar2map.py
lidar2map_linux_build.sh		lidar2map_linux_build.sh
lidar2map_mac.spec		lidar2map_mac.spec
lidar2map_mac_build.sh		lidar2map_mac_build.sh
lidar2map_mac_launcher.spec		lidar2map_mac_launcher.spec
lidar2map_win.spec		lidar2map_win.spec
lidar2map_win_build.ps1		lidar2map_win_build.ps1
lidar2map_win_launcher.spec		lidar2map_win_launcher.spec
setup_build_linux.sh		setup_build_linux.sh
setup_build_mac.sh		setup_build_mac.sh
setup_build_windows.ps1		setup_build_windows.ps1
tagmapping-min.xml		tagmapping-min.xml
update_app.py		update_app.py

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lidar2map

Who is it for?

What it produces

Installation and usage

A. Python script

Windows 10+

macOS 11+

Linux (Debian / Ubuntu)

B. Standalone executable

1. Get the deliverable

Windows

macOS (Apple Silicon)

Linux (Ubuntu / Debian)

2. Run the deliverable

Usage

Command-line examples

LiDAR providers — adding a country

Main features

Screenshots

Graphical interface

Rendering in Locus Map

What SVF reveals — same area, three sources

Reproducing this render

Documentation

License

Author

Acknowledgements

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lidar2map

Who is it for?

What it produces

Installation and usage

A. Python script

Windows 10+

macOS 11+

Linux (Debian / Ubuntu)

B. Standalone executable

1. Get the deliverable

Windows

macOS (Apple Silicon)

Linux (Ubuntu / Debian)

2. Run the deliverable

Usage

Command-line examples

LiDAR providers — adding a country

Main features

Screenshots

Graphical interface

Rendering in Locus Map

What SVF reveals — same area, three sources

Reproducing this render

Documentation

License

Author

Acknowledgements

About

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