Multispectral Imagery
Take special aerial imagery that sees beyond what the human eye can see – especially plant health.
Measures:
- Tree health & stress
- Chlorophyll activity
- Early signs of decline
- Canopy vigor
Photogrammetry
High-resolution aerial imagery stitched together to create detailed maps and 3D models.
Measures:
- Tree location
- Canopy spread (top-down)
- Visual Condition Indicators
- Surrounding Infrastructure Context
LiDAR
Laser-based 3D scanning that measures the exact shape and height of trees and terrain.
Measures:
- Tree height
- Canopy volume
- Crown width
- Ground elevation
- Utility conflicts
- Biomass estimates
Tailored Solutions
From canopy analysis to sustainability metrics, our deliverables provide the data needed to make strategic, defensible urban forestry decisions with confidence. Support smarter urban forestry management with risk reduction, sustainability tracking, canopy equity analysis, and data-driven planning.
Multispectral Imagery
Visual & Mapping Intelligence: Get precise measurements for planning budgeting and risk mitigation using:
• Tree location layers
• Planimetric feature extraction (roads, sidewalks, buildings)
• High-Resolution Orthomosaic Maps
• 3D Surface Models
Photogrammetry
Measurement & Risk Intelligence: Get high-detailed imagery for mapping, planning, and stakeholder communication through:
• Urban Canopy Coverage Maps
• Clearance & Encroachment Analysis
• Canopy Height Models
• Digital Terrain Models
LiDAR
Health Intelligence: Know where to prioritize which trees need attention before problems become visible with:
•Tree vitality rankings
• Change detection reports (year-over-year health)
•Tree Health Maps (color-coded by condition)
• Vegetation Index Maps
Case Studies & Stories
Our remote sensing services help organizations inventory, analyze, and manage trees more efficiently than traditional field methods alone. Leveraging drone-based LiDAR, multispectral imagery, photogrammetry, digital twins, and machine learning, we deliver accurate data on tree location, structure, health, and canopy conditions to support urban forestry, environmental planning, and long-term landscape management.
Laguna Woods Village
Using Drone LiDAR, this project identified trees within five feet of buildings and canopy encroachment over rooftops. Manual measurement would have been time-intensive and difficult across the full area. Still, remote sensing enabled efficient classification of 35,995 trees with minimal ground crews, delivering accurate data to support risk management and maintenance planning.
Drone LiDAR
35,995 Digitally Captured Trees
Reduced Maintenance Planning Time
Lancaster
Using drone multispectral imagery, this project mapped Joshua trees across eight square miles of desert terrain. Traditional field surveys would have required extensive labor and would not have been feasible on private properties beyond City control. Remote sensing enabled the identification of more than 1,000 Joshua trees across both public and private lands, providing precise location data to support long-term monitoring, conservation, and management efforts.
Drone Multispectral
1,000+ Digitally Captured Trees That Otherwise Would Not Have Been Feasible.
Reduced Fieldwork Time
Hudson County
Using drone LiDAR, this project estimated the number of trees across a densely forested area where traditional field inventory methods would have been time-consuming and difficult to perform. The dense canopy and challenging terrain limited efficient ground-based assessments. With just a few hours of data collection and processing, remote sensing provided an accurate tree count along with key metrics such as tree height and crown size, supporting efficient planning and resource management.
Drone LiDAR
Enabled the Identification of Trees in a Heavily Forested Area
Reduced Data Collection Time