Aerial Imagery Import

Aerial Imagery Import refers to the ability of solar design software to pull in high-resolution satellite, aerial, or drone imagery directly into the design workspace. This feature allows solar designers, installers, EPCs, and engineering teams to build accurate system layouts based on real rooftop dimensions, shading patterns, vegetation, obstacles, and surrounding terrain—without requiring an on-site visit.

Modern platforms like SurgePV use aerial imagery import to automate roof detection, shading analysis, array placement, and 3D modeling. This improves design accuracy, reduces site visit costs, and accelerates sales-to-installation timelines.

Key Takeaways

Aerial imagery import allows solar designers to work from high-accuracy visuals for roof modeling, shading analysis, and array planning.
It eliminates many site visits and dramatically speeds up design turnaround time.
AI-driven tools can automatically detect roof geometry, panel placement zones, and obstructions.
Different imagery sources offer different resolutions; drone and aerial imagery provide the highest accuracy.
It is essential for precise shading analysis, permit design sets, and utility-scale planning.

What Is Aerial Imagery Import?

Aerial imagery import is the process of integrating geospatial images into solar design software for roof modeling and layout planning. These images typically originate from:

High-resolution satellite providers
Aerial survey aircraft
Drones
Government GIS datasets
LiDAR-assisted mapping

By importing imagery directly into a CAD or solar design interface, teams can view actual roof structures, measure dimensions, detect obstructions, and model solar access for optimal panel placement.

For roof measurements, designers often pair this with tools like the:

How Aerial Imagery Import Works in Solar Design

The workflow usually looks like this:

1. Software requests aerial imagery from mapping providers

This may include satellite imagery, GIS data, or drone scans.

2. The system overlays the image onto a geo-referenced map

Zoom levels, lat-long coordinates, and image tiles are aligned with map datasets.

3. Designers trace roof boundaries or use auto-detection

Some platforms use AI to automatically detect:

Roof edges
Planes and tilt angles
Obstructions like chimneys and vents
Trees and shading objects

4. The image becomes the base layer for array design

Solar modules, racking, setbacks, wiring paths, and shading studies all rely on the imported imagery.

5. Designers export or convert the layout into CAD, SLDs, proposals, or permit-ready drawings

SurgePV automates much of this for faster permit and proposal generation: Solar Proposal Software

Types / Sources of Aerial Imagery

1. Satellite Imagery

Widely available and updated frequently.

Resolution: 10–30 cm in premium datasets.

2. Aerial Imagery (Aircraft-Based)

Captured by low-flying planes for premium clarity.

Resolution: 5–10 cm

Used for detailed shading analysis.

3. Drone Imagery

Extremely precise for individual sites.

Resolution: 1–3 cm

Ideal for commercial roofs, complex structures, or shaded environments.

For supporting LiDAR-based workflows, see:

LiDAR Data Integration

LIDAR Roof Model

How Aerial Imagery Is Measured

Resolution (cm / pixel)

Lower numbers = higher clarity.

Geospatial Accuracy (RMSE / meters)

Indicates how closely the imagery aligns with real-world coordinates.

Date of Capture

Older imagery may not reflect roof changes, new trees, or construction.

Cloud Coverage / Clarity

Cloud-free imagery is ideal for shading studies and roof modeling.

Typical Values / Ranges

Practical Guidance for Solar Designers & Installers

1. Choose the right imagery type for your project

Residential: high-resolution satellite is typically enough.
Commercial: drone or aerial imagery is preferred for accuracy.

2. Verify the imagery capture date

Outdated imagery can misrepresent:

Tree heights
New HVAC units
Roof replacements
Extensions or remodels

3. Use AI-assisted roof detection where possible

SurgePV’s auto-roof segmentation improves design speed by >70%.

4. Pair with LiDAR when precise shading detail is required

Useful in forested or uneven terrain; available in many countries.

5. Use imagery integration with design automation

Tools like panel auto-fill, pitch detection, and setback generation save significant engineering time: Solar Design Software

Real-World Examples

Example 1 — Residential Rooftop Design

A designer imports satellite imagery into SurgePV, auto-detects the roof planes, and generates a complete shading report in under 2 minutes.

Example 2 — Commercial Warehouse Layout

Drone imagery provides accurate roof elevations and 3D obstacles, enabling PV designers to place modules precisely and avoid HVAC units.

Example 3 — Utility-Scale Site Mapping

Aerial flights capture high-resolution images that help engineers evaluate vegetation, terrain, access roads, and array boundaries before grading begins.