PRISMPRISMLiDAR & Remote Sensing
Spatial Ecology and Conservation Lab (SPECLab)University of Florida IFASUSDA Forest ServiceFAMU Center for Spatial Ecology and Restoration (CSER)

A browser-based research environment

LiDAR analysis.
Across platforms.
On your computer.

Inspect point clouds, measure forest structure and compare acquisitions in one browser workspace.

PRISM runs entirely online, requires no installation, and is accessible through modern web browsers across major operating systems.

Open PRISM workspaceRead the methods

Version 2.3 Research preview

Project origins

Project initiated in September 2021.

PRISM was initiated through the U.S. Forest Service Partnership for Remote Inventory and Stand Management (PRISM) project in September 2021.

Versions, dates & release notes

A real-data starting point

One forest. Two acquisitions.

Explore the Hurricane Michael study landscape west of Sumatra, in Apalachicola National Forest, with measured USGS 3DEP returns and a shared analysis grid.

Scientific comparison figure showing earlier and later canopy-height maps and their difference for the Sumatra example
Before and after the storm. The earlier acquisition is from April 2018; the later acquisition is from December 2019. The scientific figure shows derived canopy-height products on the shared analysis grid. A pixel difference alone does not identify whether change came from hurricane damage, salvage logging, growth, acquisition conditions or processing effects. Read the comparison method.
Location figure identifying the selected example area west of Sumatra within Apalachicola National Forest
Example location and study-area context. Source records and the exact analysis boundary accompany the demo.

Work through the example

Inspect, compare, then reproduce.

Use the point viewer to examine returns, review terrain and canopy products, and compare the two dates. Read the original acquisition references before interpreting the difference.

The prepared example makes the workflow visible on arrival. A local rerun retrieves and processes the accepted source returns; a point-preview sample is never substituted for those metrics.

Follow the step-by-step manual

The current toolset

From returns to forest structure.

Maps, point inspection, raster analysis and GIS-ready outputs share one professional workspace.

01

Terrain & canopy

Create terrain, surface and canopy-height grids, then inspect height, cover and return-density products.

02

Height distributions

Review declared percentiles, mean, sample variation and return-based cover with explicit height thresholds.

03

Individual trees

Detect canopy peaks, inspect approximate crown regions and exact pixel-support polygons, and colour matching point previews.

04

Dated acquisitions

Process two or three sources on a shared grid, review comparability and calculate later-minus-earlier products.

05

Large-area tiles

Process buffered windows to a local folder and resume work from verified, checksummed completed tiles.

06

Reproducible exports

Save rasters, cell tables, tree vectors, AOI and provenance that identify data sources, units, settings and method versions.

A numbered starting workflow

Five steps through the available analyses.

The compact workflow strip keeps the common path visible while retaining advanced controls.

  1. Choose a study area. Draw a polygon, import an area file, or select the prepared Sumatra example from the step 1 menu. Begin with two measured 3DEP acquisitions, or load your own supported source.
  2. Choose data and review dates. For a new polygon, select Use this source in the catalog and confirm its elevation units. Check acquisition references, units and the study area before interpreting results.
  3. Run the analysis. For a new polygon, step 3 downloads the selected source and computes area metrics; Add tree analysis is then available. The example reuses prepared full-resolution area metrics, calculates seven exact-grid change products, and runs tree detection locally on both full CHMs. It does not silently download and reprocess millions of raw returns.
  4. Inspect change and trees. Review source counts, canopy peaks, crown regions and any explicit omissions. A single-acquisition analysis does not invent a comparison.
  5. Download completed results. Save the supported area/tree/change outputs with provenance in one bounded ZIP. Cancelled or limited steps remain explicitly identified.

Advanced controls remain available for metric settings, source reprocessing, individual-tree parameters, tiled jobs and individual exports. The suite orchestrates current capabilities; it does not add unimplemented fire/fuels models or establish reference-tool parity.

Open the numbered workflow

A traceable workflow

Keep the data, method and result connected.

Review source references and parameters before computing. Keep the exported provenance beside the products you use.

From a study area to reproducible outputsChoose a study area and source, retrieve and clip all accepted source returns, calculate declared terrain and height metrics locally, then inspect and export results with provenance. Viewer sampling follows a separate display path.01 / DEFINE02 / RETRIEVE03 / COMPUTE LOCALLY04 / REVIEW & SAVEStudy area & sourceDecode & clipTerrain & structureMaps & provenanceAOI · acquisition · unitsComplete spatial hierarchyDeclared grid & definitionsGeoTIFF · CSV · GIS vectorsAll accepted returnsA bounded point sample supplies the viewer; it does not supply processing metrics.
Workflow diagram. The display sample and the full-resolution metric path remain separate.

Full accepted data for metrics

EPT hierarchy levels and COPC ranges are selected spatially. Returns are decoded locally and clipped to the exact study polygon within explicit resource budgets.

Useful across operating systems

The workspace opens in modern browsers. Large tiled jobs need desktop Chrome or Edge features for directory access and locks. Browser/device checks describe available capabilities.

Scientific interpretation remains explicit

Current outputs use preliminary declared definitions. Source alignment, vertical reference, acquisition conditions and field context determine how a result can be interpreted.

Research preview

Current capabilities and remaining work.

Implementation, engineering verification and scientific validation are tracked separately.

Implemented

Structure, trees & change

Area metrics, canopy-peak/crown analysis, exact-grid differences, buffered tiling, export and provenance are available within documented limits.

Planned

Dedicated fire & fuels

Vertical strata, qualified ladder-fuel indicators and calibrated fuel models are future work. Current structure products do not estimate fuel mass or fire spread.

Validation in progress

Broader reference & field checks

Independent numerical engineering checks cover declared definitions and selected real datasets. FUSION/lidR parity and field accuracy remain separate acceptance work.

Evidence, limits & interpretation

Release & attribution

Cite PRISM

Record the software version alongside the original acquisition, method definitions and analysis settings.

Broadbent, E. N., Drake, J. B., Medley, P., & Almeyda Zambrano, A. M. (2026). PRISM: A browser-based, cross-platform environment for LiDAR and remote-sensing analysis (Version 2.3) [Computer software]. https://prismlidar.app

BibTeXCFF

Developed with support from the Apalachicola Regional Restoration Initiative (ARRI) and the Partnership for Remote Inventory and Stand Management (PRISM) of the U.S. Department of Agriculture, Forest Service and SPECLab internal research funds. Portions of the software development and documentation were completed with assistance from AI tools under the direction of the PRISM development team. The team is responsible for reviewing and verifying these contributions. Validation status and remaining limits are described in the Methods. Development continues with support through ARRI and SPECLab internal research funds.

Project initiated
September 2021
Software
Version 2.3 · Research preview
Release date
November 11, 2026
Project lead
Eben N. Broadbent
Website
prismlidar.app