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一分鐘完成驗證Quiet Map — global environmental noise atlas: computed Lden from roads, railways, aircraft, industry and buildings, as an interactive web map
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正在載入完整 README。 以下為已儲存的摘錄。
Global environmental noise atlas: computed sound levels (Lden) from roads,
railways, aircraft, industry, buildings and settlements, for the whole world
at about 12 m base resolution (with an optional ~6 m detail tier), served as an
interactive web map with per-point source
breakdowns. The acoustic model follows CNOSSOS-EU for surface sources with
ISO 9613-2 propagation and a Doc 29-inspired aircraft NPD; formulas, constants
and intentional simplifications are specified in engine/noise-compute/SPEC.md.
Requirements: Node.js 22 and the Rust toolchain pinned by
rust-toolchain.toml.檢視完整 README ↗Global environmental noise atlas: computed sound levels (Lden) from roads,
railways, aircraft, industry, buildings and settlements, for the whole world
at about 12 m base resolution (with an optional ~6 m detail tier), served as an
interactive web map with per-point source
breakdowns. The acoustic model follows CNOSSOS-EU for surface sources with
ISO 9613-2 propagation and a Doc 29-inspired aircraft NPD; formulas, constants
and intentional simplifications are specified in engine/noise-compute/SPEC.md.
Live instance: https://quietmap.org
engine/ Rust crates — noise-compute (the shared acoustic kernel),
tile-painter (batch tile builder + tile store), osm-extract and
aircraft-extract (OSM PBF / ADS-B → H3-res-4 arrow),
raster-reader, source-reader (NAPI addon for point queries),
noise-gpu (CUDA ports of the scatter kernels)
frontend/ The map — React 19 + MapLibre + deck.gl (Vite build)
server/ Fastify — tile serving, point noise queries, search
pipeline/ TypeScript enrichment — patches OSM defaults with
measured/registry data (traffic, industry, buildings) per country
scripts/ Product entry points: run-extraction.sh (rasters + OSM extract),
build-heatmap.sh (whole tile build), osm-to-h3r4.sh,
check-fast.sh, dataset-year.json
docs/ about/ (public About + methodology pages) · standards/
benchmarks/ Validation fixtures (popup/world point sets)
Requirements: Node.js 22 and the Rust toolchain pinned by
rust-toolchain.toml.
./start.sh
start.sh is standalone: it builds the engine native addon, the frontend and
an immutable compiled server release, activates the release, and serves on
$PORT (default 8520) — no external orchestration needed. Callers that own
the process lifecycle themselves (e.g. a systemd unit) build and activate
without serving:
QM_BUILD_ONLY=1 ./start.sh
./scripts/check-fast.sh [node|rust]
The required, data-free gate: server smoke/tests, frontend lint/build, offline pipeline tests, and rustfmt + Clippy + tests for the engine crates. The optional first argument runs only one side (CI split jobs). Keep it green before every commit.
The default dataset year is pinned in scripts/dataset-year.json
(current_year); the DATA_YEAR environment variable overrides it. The pin
controls which data/prepared/<year>/ and data/tiles/<year>/ trees a build
produces and the server reads.
data/ is gitignored and large. Expected shape:
data/prepared/dem/ 1°×1° DEM rasters, 30 m (shared across years)
data/prepared/rasters/ forest/IMD rasters (shared)
data/prepared/<year>/h3r4/ H3-res-4 source + vector-obstacle Arrow extracts
data/tiles/<year>/pmtiles/ built tile pyramids + manifest
H3R4_DIR / PMTILES_DIR env vars point a server at data living outside the
checkout. scripts/run-extraction.sh fetches and prepares the inputs, then
scripts/build-heatmap.sh computes the tiles.
This repo is the whole product: model, pipeline, tiles, web app. Deployment and orchestration of the author's own cluster (multi-checkout hosting, distributed world-build fleet) is intentionally out of scope here and lives in a separate private repository.
See docs/about/credits.md for data-source attribution (OSM, GLO-30, SRTM,
Overture, WorldCover, IMD, ADS-B) and terms. [email protected].