Upload a survey that would crash most workstations, and get survey-grade bare-earth DEMs, surface and canopy models, and classified point clouds back fast — even the largest clouds run in parallel, in one automated cloud run, reproducible to the byte, at a quality that meets and exceeds the federal standard (USGS 3DEP).
If you process LiDAR for a living, none of this is news — it's the standard toolchain, and everyone fights it. If these sound like your week, you're who we built this for.
The desktop pipeline is the bottleneck — not flying. Field crews collect faster than legacy tools can process.
The capable tools are expensive and license-locked — seats, dongles, maintenance, and one machine that can run the job.
Conventional DEMs round off the banks, scarps and breaklines your clients are actually paying you to capture.
Legacy desktop pipelines won't reproduce their own surface — rerun the same data and get a slightly different DEM, which is hard to defend in review.
In the desktop stack, classification is a separate manual step — another tool, another license, another day of cleanup.
You don't have to be a surveyor. If you can get a LiDAR point cloud, PRISM·lidarcloud turns it into a clean, bare-earth ground surface and matching deliverables — no GIS license, no desktop software, no jargon.
A LiDAR point cloud is a .las or .laz file — millions of
measured 3D points of a place. If you fly a LiDAR-equipped drone, your mapping app
produces one for you; if you hired a pilot or bought data, your provider hands you
one. That file is all you upload — we do the rest.
Sign in with your email, drag the .las/.laz in, and click run.
PRISM·lidarcloud separates the bare ground from trees and buildings, builds the terrain, surface and
canopy models, and hands back a download with maps, a 3D view and an accuracy report —
often within minutes (larger surveys take longer).
A bare-earth ground surface (the shape of the land with vegetation and structures removed), a top-of-everything surface, a canopy-height layer, the labeled point cloud, and a plain-language accuracy report — ready to view in the browser or hand to a client.
Who it's for: land surveyors; civil and site engineers; drone-mapping services; foresters and natural-resource teams; researchers; solar, agriculture and small businesses; and anyone who just needs the bare-earth surface under the trees without becoming a LiDAR expert first.
Four steps from raw flight data to client-ready files — all in the browser, every result reviewed by Metria™, our geomatics-tuned AI.
Send your LAS/LAZ securely to the cloud with WarpStream™ — multi-stream, direct-to-cloud upload up to ~10× faster than your system's normal transfer speeds. No conversion, no preprocessing on your side. Upload survey control points for a Verus™ accuracy report following ASPRS Positional Accuracy Standards, cross-checked independently against USGS 3DEP.
Our Stratum™ ground engine produces the bare-earth DEM, DSM, canopy height model at 25 cm (~10 in), a classified point cloud, and per-cell uncertainty — at any size, via HyperScale™ fan-out. Aligning to a prior survey or the integrated USGS 3DEP? Change detection runs automatically — erosion and deposition volumes, canopy damage and growth — with the maps and statistics as report pages.
Review everything in the browser — 2D map, 3D point cloud, elevation profiles, click-to-identify on any surface, and difference layers in one common frame: you pick the reference (a prior survey, an existing dataset, or USGS 3DEP) and AutoSnap™ registers your survey and the 3DEP model into it, so every comparison is truly apples-to-apples. Clouds flown without a camera can be viewed in true color using public imagery — and that color can be embedded directly into your LiDAR points.
Export the SurveyPack™ — CAD-ready DXF / LandXML / GeoTIFF with FGDC metadata. Metria™ reviews every run and writes the plain-English findings — point density, coverage gaps and accuracy caveats — into your Verus™ accuracy report.
One upload returns a complete, ready-to-deliver package — terrain and surface models, a classified point cloud, per-cell uncertainty, an accuracy report, CAD/survey files, metadata and change products. The images below are rendered directly from real PRISM·lidarcloud output rasters — coastal mangrove and creek-cut forest sites, real data.
Bare earth recovered beneath heavy coastal canopy — with the subtle relief intact, not flattened into a guess.
The same run that strips canopy from your DEM hands it back as a 25 cm (~10 in) canopy height model, ready for habitat, forestry, and carbon work.
The terrain model with vegetation, buildings and noise removed — banks, scarps and grade breaks preserved, not rounded off.
GeoTIFF · 25 cm (~10 in)The top-of-canopy / top-of-structure surface — everything the sensor saw, gridded to a clean raster.
GeoTIFF · 25 cm (~10 in)Vegetation height above bare earth — ready for habitat, forestry, biomass and carbon work, from the same run.
GeoTIFF · 25 cm (~10 in)Every point labeled — ground, low / medium / high vegetation, building, water, road and power line — in the same run, with per-class accuracy measured against independent USGS 3DEP reference classifications on urban, suburban, forest and coastal benchmark sites.
LAS / LAZA raster co-registered to the DEM that says, cell by cell, how well-supported the surface is — where data is dense and where canopy forced interpolation.
GeoTIFF · per cellA client-ready document with ASPRS-convention statistics from your surveyed control points (USGS 3DEP as an always-on cross-check), datum lineage, and a full registration table — the exact horizontal and vertical shift applied to your survey and to the 3DEP reference, round by round, with the final fit — plus a plain-language interpretation.
Word (DOCX)Standards-compliant geospatial metadata accompanying the rasters — provenance, datum and lineage a reviewer can cite.
FGDC CSDGM · XMLSurveyPack™ — breakline-ready 3D polylines, points and TIN surfaces in US State Plane — nationwide, county-aware (NAD83(2011)) — with NAVD88 heights, with FGDC metadata and survey exports — rebuilds correctly in Civil 3D-class software.
DXF · LandXMLThe USGS national elevation model, registered into your chosen reference frame and compared apples-to-apples — we fetch the 3DEP point cloud and run it through the same engine, then bring it into the same frame as your survey. It's the always-on independent cross-check; your surveyed control points stay the authority for the formal accuracy grade. Spin the 3DEP cloud next to your own in the 3D browser; the 3DEP rasters and point cloud ship in your export package, so the national reference travels with your deliverable.
GeoTIFF + report page · 3DEP cloud overlayThe processed area-of-interest footprint as ready-to-share vector boundaries for GIS and your client's records.
KML · ShapefilePick a reference — an existing survey, a prior survey you upload, or USGS 3DEP — and once everything is in that one frame the engine quantifies what moved: erosion / deposition volumes with a printed minimum level of detection, plus canopy damage and growth, as map and statistics report pages.
Your existing survey and/or USGS 3DEPFlown without a camera? Drape the cloud in natural color — sub-metre US NAIP aerial preferred when captured near your flight, a detail-preserving NAIP + Sentinel-2 fusion, near-flight-time Sentinel-2, and a cloud-free quarterly Sentinel-2 mosaic as the final fallback, so color is available virtually anywhere on Earth, even where every satellite pass was cloudy. Each produced source is included and viewable as its own dated raster layer in the 2D map, so you always know exactly what — and when — you're looking at — and that color can optionally be baked into your uploaded LiDAR points themselves.
colorized LAS / LAZ · dated source imageryEvery deliverable from a real benchmark run — bare-earth DEM, DSM, canopy height model, per-cell uncertainty, the ASPRS-classified point cloud, CAD/survey files (DXF + LandXML), FGDC metadata, the AOI boundary and the accuracy report — exactly what each job returns. No sign-up.
One upload, one click, the complete package. The rasters, the classified cloud, the uncertainty, the report, the CAD/survey files, the metadata and the change products — all in one product zip, with no extra steps.
Screenshots of the PRISM·lidarcloud workspace on the sites shown above. Every layer, panel and tool is on tap — during and after processing — when you want to dig in; or ignore them entirely and take the one-click result. Prefer code? Everything here also runs headless from the API — same jobs, same products, no browser.
Everything you can do in the browser is also a one-line command. A REST API and a Python / CLI
client (pip install prism-lidarcloud) upload, process and download the product zip —
same jobs, same deliverables, no browser — so you can wire LiDAR straight into your own automation.
$ pip install prism-lidarcloud $ prism run survey.las -o products.zip uploading survey.las … WarpStream™ · 100 parallel streams job 5e96f2 · est. $94 (2.4 km² · ~593 ac · $39/km²) # price up front — the ceiling processing … HyperScale™ fan-out → merge → Verus™ report ✓ products.zip · DEM · DSM · CHM · classified.laz · report.docx · FGDC $ prism jobs ID STATUS AREA POINTS COST 5e96f2 done 2.4 km² 234.7 M $94 a17c9b done 0.42 km² 38.1 M $75
pip install prism-lidarcloud, then prism run to upload, process and download in one line. prism jobs lists your runs — area, points and cost shown illustratively — so you can wire LiDAR into your own automation and budgets. (Example output; figures illustrative.)Upload as many sites as you like, then track them all from your account — no emailing yourself job IDs, no guessing whether a run finished. Each job shows exactly where it is and what it will cost, on a page built for the desk and the field alike.
Reproducible to the byte, validated against USGS 3DEP, and delivered as a complete, client-ready package.
Banks, scarps and grade breaks are preserved, not smoothed away — in calibration testing, PRISM held an erosion-scarp crest to within ~1 cm (~0.4 in) of the raw returns, the sharp detail conventional interpolation tends to round off.
The same input produces the byte-identical deliverable, run after run. When it's questioned in audit, you can prove it.
Every run labels eight standard ASPRS classes per point — ground, low / medium / high vegetation, buildings, water, roads and power lines — in the same pass, at no extra step. Shape-aware gates avoid the classic blunders: mangrove canopy isn't a building, a dry field isn't a lake.
U.S. outputs default to NAVD88 orthometric heights (rigorous per-cell GEOID18) on NAD83(2011) State Plane coordinates — county-correct Florida zones. Outside CONUS, products default to EGM2008 orthometric heights (global geoid) where the grid is available, with WGS84 ellipsoidal heights as a clearly labeled fallback; WGS84 ellipsoidal is also available anywhere when explicitly selected.
Verus™ ships defensible accuracy on every job — accuracy statements following ASPRS Positional Accuracy Standards (2014 & 2023 conventions) from your checkpoints, plus an independent cross-validation against USGS 3DEP — in a client-ready report with a plain-language interpretation.
Nothing to install, nothing to maintain, no seats to count. Open the browser, upload, and pay for what you process.
Access the full power through the browser GUI and / or the API, whichever fits your workflow. Drive the whole pipeline from code — a REST API and a one-line Python / CLI client (pip install prism-lidarcloud) upload, poll, and download the product zip. Wire LiDAR into your own automation; the desktop incumbents can't.
Scanned without a camera? PRISM drapes your cloud in true color from near-flight-time public imagery for a natural 3D view — a visual layer only, so it never touches the DEM or the classification you sign off on.
Send a client the interactive result, not just a zip. One click turns any finished job into a shareable link — they open the maps, 3D cloud and profiles in the browser with no account and no sign-in. You choose the tier: view-only (let them review before the products are signed off) or view + download (also release the full deliverable package). Your account, other jobs and settings always stay private; links expire automatically.
Every deliverable PRISM·lidarcloud ships is backed by a validation chain: cross-validation against a commercial survey-grade workflow, optional control-point checks, independent national references, a public benchmark, and bit-level reproducibility.
PRISM runs on a self-contained, in-house engine — no third-party GIS licenses anywhere in the chain. Every run is fully versioned and records the exact configuration that produced it, and jobs of any size run as one job via HyperScale™. You get audit-ready provenance without touching a single processing knob.
PRISM adapts automatically to your terrain and your sensor — from sparse aerial collections to dense drone surveys, coastal mangrove to open agricultural ground. There's nothing to tune: the engine reads the site and configures itself.
Our Stratum™ engine delivers a clean bare-earth surface that holds the terrain features generic tools smooth away — bank tops, erosion scarps, ditch inverts, grade breaks — and keeps legitimate sparse ground returns under canopy.
Bare-earth, surface, and canopy-height models at 25 cm (~10 in). The ground surface preserves crest lines and scarp lips that conventional interpolation rounds off — so banks and grade breaks survive into the DEM. Every DEM ships with a per-cell uncertainty raster, so you can see exactly where the model is well-supported and where canopy occlusion forced interpolation.
The delivered cloud carries eight ASPRS classes — ground, low/medium/high vegetation, buildings, water, roads, and power lines — and we measure them: per-class accuracy is validated against independent USGS 3DEP reference classifications across urban, suburban, forest and coastal benchmark sites, from dense downtown cores to suburban rooftops, rivers and coastal water. The classifier keeps its accuracy where generic tools break down — mangrove canopy is not a building; a dry field is not a lake. Anyone can claim a class list; we publish how well it actually performs.
Clouds flown without a camera can be draped in natural color from public imagery, picked by a source ladder that prefers the sharpest recent option: sub-metre US aerial (NAIP) when captured within about six months of your flight, a detail-preserving fusion of aerial sharpness with flight-time satellite color, then cloud-masked near-flight-time Sentinel-2 — and when the satellite view was cloudy, a cloud-free quarterly Sentinel-2 mosaic, so your survey gets color virtually anywhere on Earth. Every produced source ships as its own dated 2-D layer. It is a visual layer only — strictly decoupled from the engine, so it never changes the DEM, the surfaces, or the classification you sign off on, and every color is a measured imagery pixel (nothing is invented).
Your surveyed checkpoints produce a Verus™ accuracy assessment following ASPRS Positional Accuracy Standards (both the 2014 edition and the 2023 second edition conventions). An independent cross-check against the USGS 3DEP national elevation model runs automatically, and you can render signed difference layers against 3DEP or a prior dataset in the browser. Deliverables export with FGDC metadata, and the accuracy report is a client-ready Word document whose plain-language interpretation is written by Metria™, our geomatics-tuned AI. AutoSnap™ adds automatic co-registration to your chosen reference on stable ground and two-epoch change detection — erosion/deposition volumes with a printed minimum level of detection, canopy damage and growth — rendered as report pages. Comparisons against the coarse national raster are explicitly labeled screening-grade in the report.
One upload starts the whole chain. The only decision you make is which reference your survey is aligned to — an existing processed survey, a prior survey you upload, the USGS 3DEP national model fetched automatically, or none. That reference becomes the single frame: your survey and the 3DEP model are registered into it, so change and accuracy are apples-to-apples. Everything else runs without you.
Your change maps show real change on the ground — not alignment noise — with the alignment residual printed next to the result. Validation runs against references you don't control: checkpoints you surveyed and a national model we can't tune. And the report discloses everything that was applied — every offset, every comparison, every skipped step — so a reviewer can retrace the run.
The manual tools are for verification and refinement; the pipeline has already done these steps automatically. Upload control points, run the independent 3DEP cross-check, re-run the alignment or apply a vertical adjustment whenever you want to see the evidence yourself — the deliverables never depend on you doing any of it.
Calibration runs on full-scale sites spanning the toughest cover types — coastal mangrove, dense creek-cut forest, and agricultural research plots, 66 to 342 million points each — processed end-to-end and compared against a commercial survey-grade workflow and national reference data.
| What was measured | Result | Reference |
|---|---|---|
| Bare-earth DEM agreement across terrain regimes | within 2–5 cm (~0.8–2 in) mean differencemangrove coast, creek-cut forest, agricultural plots | commercial survey-grade workflow |
| Coastal erosion-scarp crest elevation | within ~1 cm (~0.4 in) of the raw returnsthe sharp crest conventional interpolation tends to round off | raw LiDAR returns |
| Reproducibility of every raster & cloud | byte-identical (MD5-verified)same input ⇒ same output, independent of machine load or core count | repeated end-to-end runs |
| Agreement with the national elevation model | σ ≈ 0.4–0.5 m (~1.3–1.6 ft) on dense-forest terrainsurface-to-surface check dominated by the reference's own uncertainty and collection-epoch differences — not PRISM checkpoint accuracy | USGS 3DEP |
| Public benchmark — forest & rural ground filtering | median ≈5% total error (2–11% per sample)terrain-matched configuration, documented; in the range of the best published filters of its class | ISPRS ground-filter test (independent labels) |
| Building removal from the bare-earth DEM | all reference buildings correctly removedroof points classified, ground interpolated from true surrounding terrain | ag research site with known structures |
The engine's development discipline: no change ships unless it is quality-up, or provably neutral — verified on full-scale calibration sites before promotion, every time.
Coastal mangrove, dense creek-cut forest, and agricultural plots — chosen because each terrain breaks a different assumption. Every engine change re-validates against all of them.
Hillshade review from above — and from below. Underside relief exposes classification artifacts that hide in a top-down view. If it isn't clean from both sides, it doesn't ship.
Candidate changes must reproduce the locked production output byte-for-byte wherever they claim no effect. Drift of a single byte fails the gate.
Every DEM ships with a per-cell uncertainty raster showing where the model is well-supported. Supply your own surveyed checkpoints and it is calibrated against them — so "how good is the DEM here?" gets a numeric answer, not just a color ramp.
Every processed site can be compared against the USGS national elevation model in one click — an outside reference we don't control.
Accuracy statements follow ASPRS Positional Accuracy Standards (Ed. 1 2014 and Ed. 2 2023 conventions), with FGDC metadata on exports. Built to support a licensed surveyor's review — never to replace it.
U.S. outputs default to NAVD88 orthometric heights via rigorous per-cell GEOID18 undulation — not a single site-wide constant — the convention geomatics and commercial-survey clients expect. Outside CONUS, products default to EGM2008 orthometric heights (the global geoid) where the grid is available, falling back to WGS84 ellipsoidal heights only where no geoid coverage exists. A datum is never silently downgraded — any fallback is stated in the report. Vertical adjustment from your control points is applied with full before/after disclosure in the report.
NAD83(2011) on State Plane coordinate systems with county-correct zone selection (Florida's zone boundaries follow counties, not latitude — we resolve them the way a surveyor would), US survey feet handled exactly.
DXF (3D breakline-ready polylines, points, TIN faces) and LandXML 1.2 surfaces that rebuild correctly in Civil 3D-class software — northing/easting order and all the ingest foot-guns handled.
Every output carries the exact engine and module versions that produced it. Two years from now, you can state precisely how a deliverable was made — and regenerate it.
PRISM·lidarcloud produces deliverables conformant to the USGS Lidar Base Specification (LBS) / 3DEP requirements, and reports vertical accuracy in the ASPRS Positional Accuracy Standards conventions — both the 2014 first edition and the 2023 second edition.
The product set is structured to the USGS 3DEP / Lidar Base Specification requirements — bare-earth DEM, classified cloud, metadata and reporting. 3DEP is a requirements-based program (it publishes specifications, not an algorithm), so we describe the deliverables as conformant to the specification. The default 25 cm (~10 in) DEM exceeds the USGS QL1 grid-cell size (a 50 cm QL1-cell DEM is also available).
The report computes ASPRS Positional Accuracy against your surveyed checkpoints — the vertical accuracy class is the RMSEz in cm (Edition 2; the Edition 1 NVA = 1.96 × RMSEz is also reported) with VVA at the 95th percentile — and states which accuracy class the data supports. We report the class the data earns: the engine reports the 10 cm (~3.9 in) RMSEz class where the data supports it, backed by ≥30 surveyed checkpoints — never a class asserted without the control to back it.
A calibrated uncertainty raster shipped with every DEM. 3DEP delivers nothing like it — you get a single project-level statement, not a per-cell answer.
A 25 cm (~10 in) DSM and CHM in the same run. 3DEP delivers a bare-earth DEM; the surface and canopy products here have no 3DEP equivalent.
Semantic point-cloud classes plus DXF / LandXML surfaces — neither is a 3DEP deliverable, and both arrive without a separate manual pass.
Honest about the line: we process delivered point clouds — we don't fly the sensor, so we make no acquisition or boresight-calibration claims. We deliver on top of the bare-earth DEM: per-cell uncertainty, surface and canopy models, semantic classification, and CAD/LandXML interchange. A specific accuracy class is only ever stated when it is backed by ≥30 of your surveyed checkpoints.
Most tools stop at a classified cloud. PRISM·lidarcloud carries each job through the steps a survey practice bills time for — CAD interchange, datum bookkeeping, accuracy statistics, and the documentation a reviewing professional expects — in the same one-click run.
DXF and LandXML surfaces in NAD83(2011) State Plane coordinates with NAVD88 (GEOID18) heights, ready for Civil 3D-class software — scale factor and full datum lineage stamped on every file, so nothing arrives ambiguous. State Plane zones: nationwide, county-aware (NAD83(2011)).
Accuracy statistics following ASPRS Positional Accuracy Standards, computed against your surveyed control points — plus an independent cross-check against the USGS 3DEP reference surface. Residuals disclosed, not summarized away.
Automatic horizontal and vertical alignment to control and datum — co-registered to NAVD88 (GEOID18) and national control in the same one-click run, with every offset and the alignment residual disclosed in the report.
Re-fly a site and the engine co-registers the epochs and quantifies what moved — erosion and deposition volumes with a printed minimum level of detection — turning a repeat flight into a monitoring deliverable.
An AI-assisted report formatted for a licensed professional's review workflow: methodology, datum lineage, residuals, and limitations stated up front, with a plain-language interpretation your client can read.
Where the licensed professional comes in: every PRISM deliverable is clearly stamped DRAFT — not a sealed survey. Outputs are intended for review and adoption by your firm's — or your client's — licensed surveyor or geomatics professional. PRISM does not provide licensed surveying services.
An American-built platform that keeps your survey data under your control — processed securely on encrypted U.S. machines, fully owned by you, with access restricted to you and the people you select.
Operated in the United StatesPRISM is built and run by a U.S.-based team — an American company, American operators, and your work is handled entirely in the United States.
Your data is stored and processed entirely in the United States, replicated across multiple U.S. regions for durability. From upload to delivery, it never leaves the country.
Your point clouds and deliverables stay yours. We process your data only to produce the products you asked for. The confidentiality and security of your data is paramount.
Each job runs in its own isolated, single-tenant environment that exists only for that job and is torn down the moment it finishes — so your data stays fully isolated to your own job.
Once your products are built, the uploaded point cloud is deleted. Stored job products follow a clear per-plan retention window with automatic irrevocable deletion — and you can extend retention if you need the files to live longer.
All uploads, downloads and account traffic move over TLS/HTTPS. Sign-in is passwordless — a fresh, single-use magic link signs you in each time, with short-lived, individually-revocable sessions.
Your account sees only your own jobs — one account can't see another's work. Share links are per-job, expire automatically, and never expose your other jobs or settings. Administrative actions are recorded to an append-only audit trail, and customer reports carry clean, branded provenance.
Our security program is designed to align with recognized federal security practices (NIST SP 800-53 / 800-171). Detailed security documentation is available to qualified clients on request.
Run your hardest site through it yourself — free trial, full engine, next to your current tool's output and your checkpoints if you have them.
Start your free trial Launch LidarCloud AppUpload and process in the browser — no seats, no license. Every run ships a survey‑grade DEM / DSM / CHM, a classified point cloud, an ASPRS accuracy report and a USGS 3DEP cross‑check. Billing is per area under the hood; small jobs start at a $75 minimum. Start with a free trial — 3 runs, no credit card.
BETA ACCESS · plans & pricing subject to change
Every run is a finished, audit‑ready deliverable set — priced by area under the hood (per km², 1 km² ≈ 247 acres), with a $75 job minimum so small high‑value sites are still a complete work‑product. Pro adds a subscription that lowers your per‑km² rate and unlocks the API + advanced Geomatics formats; Business adds team accounts and an SLA · advanced analytics available.
Individuals & occasional surveys — pay only for what you run, no commitment.
from $75 / survey
pay‑as‑you‑go · no monthly · $39/km² (~$0.16/acre) · $75 job minimum
Surveyors & firms running LiDAR every week — the production product.
$899 / mo
$899/mo includes 15 km²/mo (~3,707 acres/mo); extra area bills only after that's used, at $30/km² (~$0.12/acre, vs $39 pay‑as‑you‑go) · annual $8,990 (~17% off)
Multi‑crew survey, civil & DOT teams running LiDAR at scale — with an SLA.
$2,500 / mo
$2,500/mo includes 75 km²/mo (~18,533 acres/mo); extra area bills only after that's used, at $25/km² (~$0.10/acre) · annual $25,000
Everything in Starter and Pro, free — on a small area, no credit card.
Free · 3 runs in 30 days
full Pro features · small areas (≤ ~2 km² · ~494 acres/job) · 7‑day job retention · sign in with your email
No card to start| Feature | Starter | Pro | Business | Free Trial |
|---|---|---|---|---|
| Price | from $75/survey · $39/km² | $899/mo · 15 km²/mo incl. | $2,500/mo · 75 km²/mo incl. | Free · 3 runs / 30 days |
| Per‑km² rate | $39/km² (~$0.16/acre) | $30/km² above 15 km²/mo | $25/km² above 75 km²/mo | — (free, capped) |
| Getting started | $75 job minimum | $899/mo, or annual $8,990 (~17% off) | $2,500/mo, or annual $25,000 | magic‑link sign‑in · no card |
| Max area / job | any size | any size | any size | small (~2 km² · ~494 ac) |
| Runs | unlimited · pay per area | unlimited · pay per area | unlimited · pay per area | 3 runs / 30 days |
| WarpStream™ fast upload & download | ✓ | ✓ | ✓ | ✓ |
| HyperScale™ any‑size fan‑out | ✓ | ✓ | ✓ | ✓ (within cap) |
| DEM · DSM · CHM + classified cloud | ✓ | ✓ | ✓ | ✓ |
| AutoSnap™ datum/control alignment | ✓ | ✓ | ✓ | ✓ |
| Change‑detection + true‑color | ✓ | ✓ | ✓ | ✓ |
| Verus™ accuracy + USGS 3DEP | ✓ | ✓ | ✓ | ✓ |
| SurveyPack™ (CAD / LandXML / FGDC) | — | ✓ | ✓ | ✓ |
| API access (Python / CLI) | — | ✓ | ✓ | ✓ |
| Priority processing | — | ✓ | ✓ | — |
| Team accounts & SLA | — | — | ✓ | — |
| Analytics — subsurface / forestry / LULC | available | available | available | — |
| No‑surprise‑bill spend caps | ✓ | ✓ | ✓ | n/a (free) |
| Retention | 14 days | 30 days | 90 days | 7 days |
| Keep online longer | $0.15/GB‑mo | $0.12/GB‑mo | $0.10/GB‑mo | — |
| Support | priority email | named support | ||
| Academic / gov / partner | 25% off the per‑km² rate ($29.25 Starter ~$0.12/acre · $22.50 Pro ~$0.09/acre) | |||
You stay in control of spend. Every job shows its exact price up front — that price is the ceiling — and runs one‑click. You're only asked to confirm a job that would exceed a spend cap you've set (optional per‑job, daily and monthly caps), with alerts at 50/80/100% of any cap; caps stop runaway spend, not your wallet. On accuracy & sealing: PRISM produces the survey‑grade deliverable and an independent USGS 3DEP QA cross‑check; your licensed surveyor reviews and seals the final product. NAVD88 (GEOID18) is the default vertical datum in the CONUS; outside CONUS products default to EGM2008 orthometric heights where the geoid grid is available (WGS84 ellipsoidal otherwise, always labeled). Beta access — pricing not final: all plans and prices are proposed and subject to change before general availability.
Run your hardest site through it yourself — free trial, full engine, no card. All it takes to start is your email. Put our deliverables next to your current tools.
* Individual file uploads are capped at 25 GB (5 GB on the free trial).
Questions before you start? Write to us — happy to help.
Where PRISM·lidarcloud is heading — capabilities in active development, building on the same one-click run you use today.
These are additions to a complete, shipping, validated pipeline — not gaps in it. Everything above already runs in production today; the items below extend it.
PRISM is expanding into forest-structure analytics, storm-impact and change assessment, and richer point-cloud classification — all built on the same one-click run you use today. Talk to us about early access.
A published validation of canopy-height accuracy against field-measured reference plots — the CHM ships today; the formal accuracy statement for it is in progress.
Push notifications when a job finishes, so you don't have to poll — today the API
reports status by polling /api/v1/jobs/{job_id}; webhooks are on the way.
An optional per-area add-on (on by default): PRISM pulls authoritative USDA soil-survey data for your area — drainage, depth to restrictive layers, hydric & prime-farmland indicators — and Metria™ works it into your report, connecting the surface model to what lies beneath. Delivered as downloadable data, too.
An optional per-area add-on (on by default): national land-cover for your area from 2001 versus the epoch closest to your flight — cover by class then and now, plus the change between them — assessed in your Metria™ report and delivered as downloadable layers.
The team
Built by the team behind a decade of airborne-LiDAR research from the University of Florida and Florida Agricultural and Mechanical University.
Associate Professor of forest ecology and geomatics in the School of Forest, Fisheries, and Geomatics Sciences. He co-directs the Spatial Ecology and Conservation (SPEC) Lab and the drone-borne LiDAR program at the heart of this work. His research spans spatial scales from the globe to the leaf, carrying him from the Amazon to Hawaii and back to the New England forests he grew up in.
Research faculty in the Center for Latin American Studies and co-director of the Spatial Ecology and Conservation (SPEC) Lab, where she also co-directs the drone-borne LiDAR program behind this platform. Her work centers on the human side of landscape change — how people and ecosystems shape each other across the tropics. She is core faculty in UF's Tropical Conservation and Development program.
A restoration ecologist and remote-sensing scientist focused on ecosystem and hydrologic restoration across the Gulf Coast, working with federal, state, and private partners. Co-founder and co-director of the Center for Spatial Ecology and Restoration at Florida A&M University. His expertise runs through remote sensing, LiDAR, and ecological modeling of southern forests.
A GIS and geospatial specialist and co-director of the Center for Spatial Ecology and Restoration at Florida A&M University. He brings more than two decades of hands-on geospatial experience to applied LiDAR and forest-mapping work across the Southeast.
The PRISM app family builds on more than a decade of proprietary drone-LiDAR algorithmic development by Broadbent & Almeyda Zambrano.
The underlying technology was developed at the University of Florida; commercialization proceeds through UF’s technology-licensing process (UF Innovate | Tech Licensing).
Our mission is simple: take the rigorous kind of LiDAR processing that used to demand a specialist, a high-end workstation, and days of work — and put it one click away in the cloud, for anyone who needs to know the exact shape of the earth.
Recommended citation. If PRISM·lidarcloud output supports a publication, please cite the platform and the engine version that produced your deliverable (the exact version is stamped in every output's provenance file and shown in the manual's Engine badge):
Broadbent, E. N., Almeyda Zambrano, A. M., Drake, J., & Medley, P. PRISM·lidarcloud (PRISM LiDAR Cloud), engine version <version>. University of Florida. https://lidarcloud.app [DOI: pending]
Method, in plain English. Bare earth is separated from vegetation and structures by the Stratum™ ground engine, which preserves banks, scarps and grade breaks that generic tools smooth away. Surfaces are gridded to a DEM, DSM and canopy-height model, each with a per-cell uncertainty raster. U.S. heights are reported as NAVD88 orthometric via rigorous per-cell GEOID18 undulation on NAD83(2011) State Plane coordinates. Accuracy is reported following the ASPRS Positional Accuracy Standards against your surveyed control, with an independent USGS 3DEP cross-check. The pipeline is built on a decade of airborne-LiDAR research at the University of Florida. PRISM produces a draft deliverable for review and sealing by a licensed surveyor; it does not assert an accuracy class without ≥30 surveyed checkpoints.
Everything PRISM·lidarcloud does in the browser — upload & options, inspect, validate, datums & CAD, change detection, true-colour, downloads, and read-only client share links. Looking to script it instead? Jump to the REST API.
Engine: PRISM·lidarcloud
Enter your email and we send a one-time sign-in link — no password to manage. The link signs you into your account on any device; your jobs and usage stay private to your account. Open your account page any time to see usage, manage API keys, and review past jobs.
Drop a .las or .laz on Upload — no conversion or
preprocessing needed. The one-click defaults run the full suite; open Options to change any of:
| Option | Default | What it does |
|---|---|---|
| Alignment | USGS 3DEP | automatic co-registration to a reference: 3DEP (auto-fetched national model, default), a second cloud you upload (paired), an existing dataset, or none. |
| Change detection + 3DEP cloud | on | with a reference, compute erosion / deposition / canopy change. Against 3DEP it runs our engine on the raw 3DEP point cloud by default for a same-engine, apples-to-apples DEM & canopy comparison; opt out only for faster screening-grade DEM-only change. |
| Semantic classification | on | label the cloud into the 8 ASPRS classes. |
| DEM resolution | 25 cm | 25 cm by default; auto / 50 cm / 1 m are available for larger or lighter-weight runs. |
| Vertical datum | NAVD88 | NAVD88 orthometric heights (GEOID18, rigorous per-cell) by default in CONUS; outside CONUS products default to EGM2008 orthometric heights (global geoid) where the grid is available, with WGS84 ellipsoidal as the clearly labeled fallback. Choose WGS84 ellipsoidal explicitly for ellipsoidal products anywhere. |
| Visual colorization | auto | for clouds with no camera RGB, drape natural colour from public imagery (see True-colour). Visual only. |
| Accuracy report | on | Verus™ Word report (ASPRS 2014/2023) with a plain-language interpretation by Metria™, our geomatics-tuned AI. |
| CAD bundle | on | DXF contours + LandXML surface (State Plane ftUS / NAVD88) in the download. |
| Email me | on | close the tab — we email you when the job finishes. |
Processing runs in the cloud; a progress bar tracks the stages. You can keep the tab open to watch, or close it — if “Email me” is on, we notify you (and the link signs you back in to the result on any device). Typical jobs finish in minutes; very large clouds take longer.
The right panel is a numbered step list — Process · Explore · Validate · Align · Report · Export — with a single detail pane for the selected step and a Run summary that lists the pipeline stages with their status. The list advances as a job runs and tracks which steps you have completed.
Verus™ is the accuracy deliverable: an ASPRS-standard accuracy assessment cross-checked independently against USGS 3DEP. From the Accuracy panel:
lon, lat, height file in WGS84 decimal degrees with height in metres, one point per line (e.g. -82.601, 29.652, 12.34; commas or spaces, a header row and # comments are ignored). Native projected UTM / State Plane support is coming; for now convert to lon/lat degrees. PRISM compares them to the DEM and reports residuals + an ASPRS accuracy statement (2014 NVA/VVA and 2023 conventions), with a datum-mismatch guard. Surveyed control points are the authority for the formal accuracy grade.The uncertainty raster ships with every DEM: low values = well-supported bare ground; high values = where canopy occlusion forced interpolation. Use it to know which parts of the surface to trust most. It is a relative confidence map by default; it is calibrated to an absolute ±cm answer only when you supply surveyed control points (above), which tie the surface to a known datum and yield a numeric vertical accuracy statement.
Alignment vs validation: co-registration (AutoSnap™) runs automatically on upload — a two-round horizontal + vertical fit that brings your survey, the USGS 3DEP model, and the PRISM-derived 3DEP products into your chosen reference frame on stable ground. The report prints a registration table: the exact per-round shift each dataset needed and the final fit. Your aligned (in-frame) products are the primary download, with the untouched engine-frame products included alongside. Validation (see Accuracy) is the separate accuracy check — surveyed control points give the formal grade, 3DEP the cross-check. Re-run alignment manually from the Align step against a different reference, then re-validate.
Datums/CAD: the horizontal datum is NAD83(2011); choose NAVD88 (GEOID18) for orthometric heights; the CAD bundle exports DXF contours + a LandXML surface in the correct US State Plane zones (NAD83(2011), county-aware) for direct ingest into civil/survey software.
Change detection & apples-to-apples 3DEP: the default comparison is against the USGS 3DEP reference. Alignment and validation use the raw 3DEP DEM (USGS’s own product, built by their algorithm) — an honest external cross-check. Change detection runs OUR engine on the raw 3DEP point cloud, producing a same-engine DEM (and canopy surface) so the change — erosion/deposition volumes (with a printed minimum level of detection) and canopy loss/gain — is truly apples-to-apples rather than confounded by differing processing. (When the 3DEP point cloud is unavailable for the area, the job records that condition and uses the screening-grade 3DEP DEM comparison.) You can also process against a prior survey of your own (paired upload). 3DEP comparisons are labelled screening-grade (coarse grid, unknown collection epoch). Results render as maps + stats + report pages.
LiDAR is often flown without a camera, so the cloud has no colour. PRISM can drape it in natural colour from public imagery — date-matched and cloud-masked — for an intuitive 3D view and a colourised cloud in your download.
*_colorized.las and never changes the DEM, surfaces, or classification. The canonical deliverable stays colour-free.The product zip contains the DEM, DSM, CHM, and uncertainty rasters (GeoTIFF), the AOI boundary, the classified cloud, the accuracy report (Word), and the CAD bundle (DXF + LandXML) — plus alignment + change products and the colourised cloud when those ran.
Everything above is scriptable: create an API key on your
account page, install
the client (pip install prism-lidarcloud), then
prism run scan.las -o out.zip, or use the Python Client / plain
REST. Full reference: REST API below.
Reference + imagery come from open, commercially-usable public sources: USGS 3DEP (US public domain), Sentinel-2 (Copernicus — free and open, commercial use permitted), and NAIP aerial where available (USDA public domain). Your uploaded data is private to your account and retained for 14 days, then purged.
Process LiDAR programmatically: upload a point cloud, poll until done, download the survey-grade product zip — the same endpoints behind the terminal example above. Prefer the browser? See the user manual.
https://app.lidarcloud.app. All endpoints are versioned
under /api/v1 and authenticate with a Bearer API key. API jobs use the same engine,
quota and billing as the web app and appear in your usage console tagged API.Create a key in the app: sign in → click your email → API access →
Create API key. The key (prism_live_…) is shown once — store it like
a password. Send it as a Bearer token on every request:
Authorization: Bearer prism_live_xxxxxxxxxxxxxxxxRevoke a key any time from the same panel; revocation takes effect immediately.
The client is published on PyPI: pypi.org/project/prism-lidarcloud — zero dependencies (pure Python standard library).
Windows PowerShell
py -m pip install --upgrade prism-lidarcloud
$env:PRISM_API_KEY = "prism_live_xxxxxxxxxxxx"
prism run "C:\surveys\scan.las" --out products.zipIf PowerShell says prism is not recognized, your Python
Scripts folder isn't on PATH (pip prints a warning about this during install). Either run the
module form — py -m prism_lidarcloud.cli run "C:\surveys\scan.las" --out products.zip —
or add the Scripts folder pip named to your PATH and reopen the terminal.
macOS / Linux
python3 -m pip install --upgrade prism-lidarcloud
export PRISM_API_KEY="prism_live_xxxxxxxxxxxx"
prism run ./scan.las --out products.zipIf prism is not found, use the module form:
python3 -m prism_lidarcloud.cli run ./scan.las --out products.zip (or add
~/.local/bin to your PATH).
from prism_lidarcloud import Client
c = Client() # reads PRISM_API_KEY
out = c.run("scan.las", out="products.zip")
print("saved", out)macOS / Linux
KEY="prism_live_xxxxxxxxxxxx"
# 1) submit
curl -sS -X POST https://app.lidarcloud.app/api/v1/jobs \
-H "Authorization: Bearer $KEY" \
-F file=@scan.las
# -> {"job_id":"<id>","status":"queued","status_url":"...","download_url":"..."}
# 2) poll
curl -sS https://app.lidarcloud.app/api/v1/jobs/<id> -H "Authorization: Bearer $KEY"
# 3) download when status == "done"
curl -sS -L https://app.lidarcloud.app/api/v1/jobs/<id>/download \
-H "Authorization: Bearer $KEY" -o products.zipWindows PowerShell
$KEY = "prism_live_xxxxxxxxxxxx"
curl.exe -sS -X POST "https://app.lidarcloud.app/api/v1/jobs" `
-H "Authorization: Bearer $KEY" `
-F "file=@C:\surveys\scan.las"
# replace <id> with the returned job_id
curl.exe -sS "https://app.lidarcloud.app/api/v1/jobs/<id>" `
-H "Authorization: Bearer $KEY"
curl.exe -sS -L "https://app.lidarcloud.app/api/v1/jobs/<id>/download" `
-H "Authorization: Bearer $KEY" `
-o products.zip/api/v1/jobsSubmit a point cloud for processing. multipart/form-data:
| field | default | notes |
|---|---|---|
file | — | required — .las/.laz |
align | 3dep | none · 3dep (USGS reference, default) · upload (send a reference file) · existing (ref_site). Co-registration to the chosen reference runs automatically. |
reference | — | second cloud for paired change detection (with align=upload) |
change | 1 | run change detection vs the reference. |
dep3_cloud | 1 | with align=3dep, also run our engine on the raw 3DEP point cloud for same-engine DEM + canopy change. Pass 0 for faster screening-grade DEM-only 3DEP change. |
classify | 1 | semantic point classification (8 ASPRS classes) |
dem_res | 25cm | auto · 25cm · 50cm · 100cm · 250cm · 5m · 10m |
vdatum | navd88 | navd88 (rigorous per-cell GEOID18 orthometric heights, default) · egm2008 (global orthometric, where the geoid grid is available) · ellipsoidal (WGS84 ellipsoidal, explicit only). Outside CONUS, navd88 jobs fall back to EGM2008 orthometric heights (global geoid), then to WGS84 ellipsoidal only where no geoid coverage exists — a labelled fallback stated in the report, never a silent downgrade. |
colorize | auto | visual true-colour drape for no-RGB clouds (public imagery): auto (on when the cloud has no RGB) · on · off. Visual layer only — never affects the DEM/classification; shipped as a separate *_colorized.las |
colorize_source | auto | which public-imagery source becomes the composite colour + 2-D layer: auto (sub-metre NAIP preferred when acquired within ~6 months of the flight → fusion → Sentinel-2 scene → cloud-free quarterly Sentinel-2 mosaic) · sentinel · naip · fusion (NAIP detail + Sentinel colour). Every produced source also ships as its own dated toggleable 2-D layer. If a forced source is unavailable for the AOI, auto source selection is used and recorded. |
report | 1 | include the accuracy report (Word) |
narrate | 1 | include the Metria™ AI interpretation in the report when available |
cad | 1 | include the CAD bundle (DXF + LandXML) |
notify | 1 | email the signed-in account when the job finishes |
confirm | 0 | set to 1 only when re-submitting after a 402 confirm_required response |
max_usd | — | optional per-job ceiling; the job is refused if the estimate exceeds it |
Returns 202 with {job_id, status, status_url, download_url, quota_jobs}.
A job consumes your account quota exactly like a web upload.
/api/v1/jobs/{job_id}Poll a job. Returns {job_id, status, stage, pct, error, download_url} where
status ∈ queued · running · done · error.
download_url is non-null once done.
/api/v1/jobs/{job_id}/downloadStream the finished product zip (404 until the job is done). Optional ?clouds=0
omits the classified point clouds. The zip holds the bare-earth DEM, DSM, CHM,
DEM-uncertainty rasters (GeoTIFF), the AOI boundary, the classified cloud, and — unless
disabled — the accuracy report (Word) + CAD bundle (DXF + LandXML). When colorization runs, a
separate *_colorized.las + a colorize.json provenance sidecar are included
(the canonical cloud stays RGB-free). Paired/3DEP runs add alignment + change products.
/api/v1/jobs/{job_id}/download_urlsReturn short-lived signed URLs for the finished product files so clients can download the
complete deliverable package in parallel — rasters, clouds,
report, CAD, FGDC metadata, alignment, change products, and colorization sidecars. Optional
?clouds=0 omits classified point clouds. Response shape:
{presigned, complete, files:[{name,url,size}], expires_in}. This is the default fast
download path; use /download only when you want the serial server-built zip.
/api/v1/jobsList your account’s jobs: {jobs:[{job_id, name, status, source, …}], count}.
| code | meaning |
|---|---|
401 | missing/invalid/revoked API key |
403 | account suspended, or key-management attempted via the API |
404 | job not found / not visible to this account |
402 | job requires confirmation before it can run (e.g. it would exceed a spend cap you set) — re-submit with the confirm flag |
409 | a spend cap (per-job, daily or monthly) would be exceeded — raise the cap or reduce the job |
413 | file exceeds the current account upload or automated processing limit |
429 | rate limit — back off and retry |
/api/v1 programmatic surface. Documented here for
completeness./api/dep3cloud?site={id}Render the PRISM-3DEP DEM (the bare-earth raster our engine builds from the raw
USGS 3DEP point cloud) as a 2D hillshade map overlay. With ?probe=1 it does
not render — it returns {exists, cloud}, where cloud (when present)
carries the supplementary 3D point-cloud metadata
{count, origin, zspan, classes, hasrgb, url} and url points at
/api/dep3cloud_bin. The GUI uses the probe to decide whether to reveal the “Show
3DEP cloud” (3D) toggle and the “3DEP DEM (2D)” map button. 404 when
the dataset has no PRISM-3DEP product (option off / fell back to the screening-grade DEM).
/api/dep3cloud_bin?site={id}Stream the decimated raw USGS 3DEP point cloud (cloud_3dep.bin) in the same packed
[xyz f32][rgb u8][class u8] format the user cloud uses, co-registered into the user
cloud’s local frame, so the 3D viewer can overlay it (amber) for an “ours vs 3DEP”
comparison. When the PRISM-3DEP products haven’t been built for the dataset yet, returns
409 with a machine-readable {prereq} block whose run_url builds
them on demand — the app does this automatically and retries, so a missing prerequisite never
requires re-processing the upload.
Keys carry your account’s quota, visibility and billing. Never embed a key in client-side code or a public repo. Questions? hello@lidarcloud.app