site_reconstruction

shallow

ai.greenlandai/greenlandai · Verify this server

A dated, georeferenced, textured 3D MODEL of a site (entity_type + id, or lat + lng) and its MEASUREMENTS as structured data. `measurements` (computed on the elevation source's own grid, every block with `source` and `accuracy`): site_extent (side, area, bbox, CRS); elevation (min, max, mean, relief, vertical datum); slope_deg (p10/p50/p90/max/mean + share per class 0–5/5–15/15–30/ 30–45/45–90°); pits (closed depressions filled to their spill level: area_m2, depth_max_m, depth_mean_m, volume_m3 ± volume_uncertainty_m3, spill and floor elevation, centre); heaps (closed mounds: area_m2, height_max_m, volume_m3 ± uncertainty above the highest separating saddle, base and top elevation, centre). Only features that CLOSE inside the extent are measured — 0 pits over a big open pit means the pit is larger than the square: widen radius_m. On a surface model a heap can be a stockpile, dump, building or rock: shape, not material. Tier follows the data: lidar_2m (USGS 3DEP lidar DSM 2 m, NAVD88, ~0.10 m) where it covers the extent, else dem_30m (Copernicus GLO-30, one epoch 2011–2015, EGM2008, < 4 m 90 %); texture NAIP (US) else Sentinel-2; the card states tier, sources, dates, datum, accuracy, dates_differ and what it is NOT (not a survey, not bare earth, not for volume certification). The MODEL is binary glTF 2.0 (+X east, +Y up, −Z north, metres; node extras carry the CRS, origin and base elevation); the card carries its sha256 and byte size. include_model=true adds `model_glb_base64` (a lidar model is about 4 MB, ~5 MB as base64); the raw file is GET /api/v1/site.reconstruction?…&format=glb on the API. radius_m 100..1000 (default 300; the square's side is 2 × radius); as_of YYYY-MM-DD picks the lidar collection and texture nearest that date. An entity whose coordinates are only a country centre is refused (409, not charged). Slow: about 15–60 s. AGENT KEYS ONLY (a browser session is refused BEFORE any charge). SIDE EFFECTS: none beyond the charge — read-only. ⚠ CHARGING: priced per tier, and the tier is decided BEFORE any charge (lidar_2m where 3DEP lidar covers the site, else dem_30m): the call reserves THAT tier's price — a 30 m site never needs the lidar price in the wallet. No model (no elevation source or no clear image) costs nothing. Price: lidar_2m 2,500 J, dem_30m 1,000 J, + the 0.5% rail fee (greenlandai-api look/reconstruct_build.RECONSTRUCTION_PRICE_JOULES). Quote the exact tier with `billing_quote("/api/v1/site.reconstruction", lat=…, lng=…, radius_m=…)` (or entity_type + id); the JSON carries `charged_joules` and a `price` block with tier_reserved and tier_delivered.

100.0/100

1 trials · measured 1 day ago

site_reconstruction scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against ai.greenlandai/greenlandai, measured 6 Oct 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
self-provisionable
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-10-06100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: site_reconstruction
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site_reconstruction — Vouch