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 across many machines, 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.
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™ — a multi-stream, direct-to-cloud upload up to ~10× faster than your system's normal upload speeds. No conversion, no preprocessing on your side.
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 across machines. Aligning to a prior survey or 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 — auto-aligned with AutoSnap™ — against USGS 3DEP or a prior survey. Clouds flown without a camera can be shown in true color from public imagery — and that color can be embedded directly into your LiDAR points.
Upload survey control points for a Verus™ accuracy report following ASPRS Positional Accuracy Standards, cross-checked independently against USGS 3DEP, and 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 that 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 · 50 cm (~20 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.
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, datum lineage, alignment residuals and 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 Florida State Plane (ftUS) with NAVD88 heights, with FGDC metadata and survey exports — rebuilds correctly in Civil 3D-class software.
DXF · LandXMLAn independent cross-check against the USGS national elevation model — signed difference layer and agreement statistics, labeled screening-grade. We also fetch the 3DEP point cloud and run it through the same engine, so the comparison is apples-to-apples — and you can spin the 3DEP cloud next to your own in the 3D browser. The 3DEP rasters and point cloud ship in your export package too, 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 · ShapefileAlign to USGS 3DEP — the default national reference — or a prior survey of your own, and 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.
3DEP default · or your prior surveyFlown without a camera? Drape the cloud in natural color from near-flight-time NAIP aerial (US) or Sentinel-2 imagery — a visual layer only, decoupled from the DEM and classification. The source aerial is included and viewable as a 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 imagery
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 --align 3dep --report -o products.zip uploading survey.las … WarpStream™ · 16 parallel streams job 5e96f2 · est. $4.20 (1.32 km² · ~326 ac · $3.18/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 1.32 km² 234.7 M $4.20 a17c9b done 0.42 km² 38.1 M $1.33
pip install prism-lidarcloud, then prism run to upload, process and download in one line. prism jobs lists area, points and the exact cost per run — 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.
Polished enough to deliver. Rigorous enough to defend.
Banks, scarps and grade breaks are preserved, not smoothed away — measured: scarp crest preserved to ~1 cm (~0.4 in), where the reference workflow rounds the same crest off by ~26 cm (~10 in).
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 State Plane coordinates — county-correct Florida zones — with WGS84 ellipsoidal optional and EGM2008 fallback outside CONUS.
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 the industry-reference workflow, optional control-point checks, independent national references, a public benchmark, and bit-level reproducibility.
The engine is a proprietary, self-contained scientific pipeline — no third-party GIS licenses anywhere in the chain. Each stage is versioned, every run records the exact configuration that produced it, and the whole chain fans out across machines via HyperScale™ so any-size cloud runs as one job.
Before any classification, the cloud is profiled — point density, canopy structure, ground visibility, terrain roughness. Processing parameters adapt to the regime (coastal mangrove behaves nothing like an open ag field), including automatic adaptation across two orders of magnitude in point density, from sparse aerial collections to dense drone surveys.
Bare earth is separated from vegetation, buildings, and noise by our Stratum™ engine — engineered to keep the terrain features generic tools smooth away: bank tops, erosion scarps, ditch inverts, grade breaks. Legitimate sparse ground returns under canopy are preserved.
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 — tuned to avoid the classic false positives (mangrove canopy is not a building; a dry field is not a lake).
Clouds flown without a camera can be draped in natural color from near-flight-time public satellite imagery (higher-resolution aerial over the US where available), date-matched to the survey and cloud-masked. 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 double-round co-registration on outlier-excluded 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 and compared against — a prior survey you upload, the USGS 3DEP national model fetched automatically, or none. Everything else runs without you.
Co-registration runs before differencing, so what the change maps show is change — not misregistration; the alignment residual is 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 the industry-reference commercial 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 | industry-reference commercial workflow |
| Coastal erosion-scarp crest elevation | within ~1 cm (~0.4 in) of the raw returnsthe reference workflow rounds the same crest off by ~26 cm (~10 in) | 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. WGS84 ellipsoidal heights are available as an option, and outside CONUS the engine falls back to the EGM2008 global geoid. Vertical adjustment from your control points is applied with full before/after disclosure in the report.
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 50 cm (~20 in) DEM matches the QL1 grid-cell size.
The report computes ASPRS Positional Accuracy against your surveyed checkpoints — NVA = 1.96 × RMSEz and VVA at the 95th percentile — and states which accuracy class the data supports. We report the class the data earns: the engine meets the 10 cm (~3.9 in) RMSEz class where the data supports it, demonstrated against ≥20 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 ≥20 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 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.
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 on its own network of freshly-created machines that exist only for that job and are destroyed the moment it finishes. Unique ephemeral machines per job — your data stays fully isolated to your own job.
Once your products are built, the worker deletes the uploaded point cloud. 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 — no internal method or IP leakage.
Our security program is designed to align with recognized federal security practices (NIST SP 800-53 / 800-171). We'll tell you in writing exactly what we do and don't do. 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 PRISM·lidarcloudUpload and process in the browser — you pay only for the area you run, with an ASPRS accuracy report and a USGS 3DEP cross‑check on every job. Start with a free trial — 5 runs, no credit card.
BETA ACCESS · plans & pricing subject to change
Pricing is area‑based, always — you pay per km² (1 km² ≈ 247 acres), not per machine, so multi‑machine fan‑out costs you the same, just faster, on both tiers. Pro adds a base subscription that lowers your per‑km² rate and unlocks the API + advanced Geomatics formats.
Individuals & occasional surveys — pay only for what you run, no commitment.
$35 / km² (~$0.14/acre)
pay‑as‑you‑go · no monthly · minimum job bill of $15
Surveyors & firms running LiDAR every week — the production product.
$599 / mo — 15 km²/mo included, then $28/km² (~$0.11/acre)
$599/mo includes 15 km²/mo (~3,707 acres/mo); above that, $28/km² (~$0.11/acre, down from $35) · annual $5,990 (~17% off)
Everything in Starter and Pro, free — on a small area, no credit card.
Free · 5 runs in 14 days
full Pro features · small areas (≤ ~2 km² · ~494 acres/job) · 3‑day job retention · sign in with your email
No card to start| Feature | Starter | Pro | Free Trial |
|---|---|---|---|
| Price | $35/km² (~$0.14/acre) PAYG | $599/mo · 15 km²/mo incl., then $28/km² | Free · 5 runs / 14 days |
| Per‑km² rate | $35/km² (~$0.14/acre) | $28/km² (~$0.11/acre) above 15 km²/mo incl. | — (free, capped) |
| Getting started | $15 billing floor | $599/mo, or annual $5,990 (~17% off) | magic‑link sign‑in · no card |
| Max area / job | any size | any size | small (~2 km² · ~494 ac) |
| Runs | unlimited · pay per area | unlimited · pay per area | 5 runs / 14 days |
| DEM · DSM · CHM + classified cloud | ✓ | ✓ | ✓ |
| Verus™ accuracy + USGS 3DEP | ✓ | ✓ | ✓ |
| HyperScale™ any‑size fan‑out | ✓ | ✓ | ✓ (within cap) |
| WarpStream™ fast upload | ✓ | ✓ | ✓ |
| Change‑detection + true‑color | ✓ | ✓ | ✓ |
| AutoSnap™ datum/control alignment | ✓ | ✓ | ✓ |
| API access (Python / CLI) | — | ✓ | ✓ |
| SurveyPack™ (CAD / LandXML / FGDC) | — | ✓ | ✓ |
| Priority processing | — | ✓ | — |
| No‑surprise‑bill spend caps | ✓ | ✓ | n/a (free) |
| Retention | 14 days | 30 days | 3 days |
| Keep online longer | $0.15/GB‑mo (area‑based) | $0.12/GB‑mo (area‑based) | — |
| Support | priority email | ||
| Academic / gov / partner | 25% off the per‑km² rate ($26.25 Starter ~$0.11/acre · $21 Pro ~$0.085/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; EGM2008 orthometric and WGS84 ellipsoidal are available for other regions. 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.
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.
Individual-tree segmentation and tree-level 3D structural metrics, derived from the same one-click run that produces your terrain and surface models.
Automated tree-level and stand-level assessment of storm impact and forest-health change between flights — extending the change detection that ships today.
Additional ASPRS feature classes in the delivered point cloud, widening the semantic detail available straight out of the automated run.
The team
Built by the team behind a decade of airborne-LiDAR research from the University of Florida, Florida Agricultural and Mechanical University, and the United States Forest Service.
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 GatorEye Unmanned Flying Laboratory, 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 GatorEye Unmanned Flying Laboratory. 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.
Biological scientist and Gulf restoration program specialist with the USDA Forest Service, working with federal, state, and private partners to plan and carry out ecosystem and hydrologic restoration across the Gulf Coast. He is co-founder and co-director of FAMU's Center for Spatial Ecology and Restoration, a USDA Forest Service–Florida A&M partnership. His expertise runs through remote sensing, LiDAR, and ecological modeling of southern forests.
GIS program manager for the USDA Forest Service's National Forests in Florida and co-director of FAMU's Center for Spatial Ecology and Restoration. He brings more than two decades of hands-on geospatial experience to applied LiDAR and forest-mapping work across Florida's public lands.
The PRISM app family builds on more than a decade of proprietary GatorEye 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.
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 | auto double-round co-registration (H→V→H→V) to a reference: 3DEP (auto-fetched national model, default), a second cloud you upload (paired), an existing dataset, or none. |
| Change detection | on | with a reference, compute erosion / deposition / canopy change (post-processing — 0 extra jobs). Against 3DEP it runs our engine on the raw 3DEP point cloud for a same-engine, apples-to-apples DEM & canopy comparison. |
| Semantic classification | on | label the cloud into the 8 ASPRS classes. |
| DEM resolution | auto | auto / 25 cm / 50 cm / 1 m. |
| Vertical datum | NAVD88 | NAVD88 orthometric heights (GEOID18, rigorous per-cell) by default; or keep WGS84 ellipsoidal. Outside the contiguous US (no GEOID18 coverage) it falls back to ellipsoidal with a note. |
| 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 on its own cloud machine; 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; PRISM compares them to the DEM and reports residuals + an ASPRS accuracy statement (2014 NVA/VVA and 2023 conventions), with a datum-mismatch guard.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 runs automatically on upload — a double round that solves horizontal then vertical, repeated twice (H→V→H→V), on stable ground. The second round verifies the residual from the first. Validation (see Accuracy) is the separate post-alignment accuracy check: it measures how well the co-registered product agrees with the reference. Re-run alignment manually from the Align step against a different reference, then re-validate.
Datums/CAD: choose NAVD88 (GEOID18) for orthometric heights; the CAD bundle exports DXF contours + a LandXML surface in the correct Florida State Plane ftUS zone (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, change falls back to the screening-grade 3DEP DEM.) 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 flight-time 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 --align 3dep -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).
# install the client
pip install prism-lidarcloud
export PRISM_API_KEY=prism_live_xxxxxxxxxxxx # PowerShell: $env:PRISM_API_KEY="prism_live_..."
# upload, wait, download in one step
prism run scan.las --align 3dep --out products.zipfrom prism_lidarcloud import Client
c = Client() # reads PRISM_API_KEY
out = c.run("scan.las", out="products.zip", align="3dep", change=True)
print("saved", out)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 -F align=3dep
# -> {"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.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 is an automatic double round (horizontal→vertical, ×2). |
reference | — | second cloud for paired change detection (with align=upload) |
change | 1 | run change detection vs the reference. With align=3dep it runs our engine on the raw 3DEP point cloud (same-engine apples-to-apples DEM + canopy change); alignment/validation still use the raw 3DEP DEM. Falls back to the screening-grade 3DEP DEM where the 3DEP cloud is unavailable. |
classify | 1 | semantic point classification (8 ASPRS classes) |
dem_res | auto | auto · 25cm · 50cm · 100cm |
vdatum | navd88 | navd88 (rigorous per-cell GEOID18 orthometric heights, default) · ellipsoidal (WGS84). Outside the contiguous US (no GEOID18 coverage) navd88 falls back to ellipsoidal with a note. |
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 (NAIP sharp-swap when eligible, else Sentinel-2) · sentinel · naip · fusion (NAIP detail + Sentinel colour). Every produced source also ships as its own dated toggleable 2-D layer. A forced source unavailable for the AOI falls back to auto. |
report | 1 | include the accuracy report (Word) |
cad | 1 | include the CAD bundle (DXF + LandXML) |
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/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 |
413 | file exceeds the maximum upload size (3 GB) or 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. 404 when the dataset has no 3DEP cloud.
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