MacroscopeVR Technical Specification and Project Report
Published: February 11, 2026Version: 1
Abstract
MacroscopeVR is a web-based Participatory Planetary Observatory that transforms consumer 360° photography into interactive three-dimensional structural models of ecological environments. The platform applies SHARP monocular Gaussian splatting — a neural network that reconstructs 1.18 million 3D ellipsoids from a single photograph — to panoramic imagery captured at biological field stations, producing explorable terrariums that preserve the geometric and spectral characteristics of vegetation, terrain, and built structures. A 25-position spherical sampling grid (CNL-SP-2026-013) decomposes each equirectangular panorama into perspective views spanning horizon, upper canopy, lower canopy, zenith, and nadir, yielding comprehensive structural coverage from a single capture point.
The current dataset encompasses 33 ecological research stations, 457 panoramas, and 11,425 individual views totaling approximately 258GB of Gaussian splat and point cloud data. Analysis of SHARP output reveals three distinct Gaussian populations — physical surfaces, atmospheric fill, and reconstruction artifacts — separable through opacity and scale thresholds, enabling GPU-accelerated interactive filtering in a browser-based quad-view analysis laboratory.
The platform's contribution model parallels iNaturalist's democratization of species identification: where iNaturalist compressed taxonomic expertise into smartphone-accessible AI classification, MacroscopeVR compresses structural ecology — traditionally requiring specialized instruments, plot mensuration, and forestry training — into a single 360° photograph processed through an automated pipeline. The system accepts geotagged input from multiple device types (360° cameras, smartphones, LiDAR scanners) and derives geographic and ecosystem classification from iNaturalist APIs using coordinates alone, requiring no manual metadata entry. Species observations and three-dimensional habitat context are captured simultaneously by the same observer at the same location, linking organism and environment in a unified, explorable record.
MacroscopeVR represents the convergence of a forty-year research program — spanning LaserDisc interactive video, desktop Qt applications, Google Earth integration with SketchUp 3D visualization, CENS wireless sensor networks, EcoView/econode environmental monitoring with ArcGIS, and the VeLEA ecological array — with contemporary advances in neural 3D reconstruction. Each generation pursued the same cognitive journey from planetary context to organism-level detail; MacroscopeVR is the first to make that journey participatory, computationally active, and accessible to anyone with a consumer camera.
@techreport{cnl2026macroscopevr,
author = {},
title = {MacroscopeVR Technical Specification and Project Report},
institution = {Canemah Nature Laboratory},
year = {2026},
number = {CNL-TN-2026-021},
month = {february},
url = {https://canemah.org/archive/document.php?id=CNL-TN-2026-021},
abstract = {MacroscopeVR is a web-based Participatory Planetary Observatory that transforms consumer 360° photography into interactive three-dimensional structural models of ecological environments. The platform applies SHARP monocular Gaussian splatting — a neural network that reconstructs 1.18 million 3D ellipsoids from a single photograph — to panoramic imagery captured at biological field stations, producing explorable terrariums that preserve the geometric and spectral characteristics of vegetation, terrain, and built structures. A 25-position spherical sampling grid (CNL-SP-2026-013) decomposes each equirectangular panorama into perspective views spanning horizon, upper canopy, lower canopy, zenith, and nadir, yielding comprehensive structural coverage from a single capture point.
The current dataset encompasses 33 ecological research stations, 457 panoramas, and 11,425 individual views totaling approximately 258GB of Gaussian splat and point cloud data. Analysis of SHARP output reveals three distinct Gaussian populations — physical surfaces, atmospheric fill, and reconstruction artifacts — separable through opacity and scale thresholds, enabling GPU-accelerated interactive filtering in a browser-based quad-view analysis laboratory.
The platform's contribution model parallels iNaturalist's democratization of species identification: where iNaturalist compressed taxonomic expertise into smartphone-accessible AI classification, MacroscopeVR compresses structural ecology — traditionally requiring specialized instruments, plot mensuration, and forestry training — into a single 360° photograph processed through an automated pipeline. The system accepts geotagged input from multiple device types (360° cameras, smartphones, LiDAR scanners) and derives geographic and ecosystem classification from iNaturalist APIs using coordinates alone, requiring no manual metadata entry. Species observations and three-dimensional habitat context are captured simultaneously by the same observer at the same location, linking organism and environment in a unified, explorable record.
MacroscopeVR represents the convergence of a forty-year research program — spanning LaserDisc interactive video, desktop Qt applications, Google Earth integration with SketchUp 3D visualization, CENS wireless sensor networks, EcoView/econode environmental monitoring with ArcGIS, and the VeLEA ecological array — with contemporary advances in neural 3D reconstruction. Each generation pursued the same cognitive journey from planetary context to organism-level detail; MacroscopeVR is the first to make that journey participatory, computationally active, and accessible to anyone with a consumer camera.}
}