Satellite Imagery for Roofing: The Complete Guide

Every "AI roofing" tool is downstream of one decision: which satellite imagery provider does it use? The provider determines what the tool can actually see. Different providers vary in resolution by 3-5x, in freshness by 12-36 months, and in coverage by entire regions. This post is the breakdown of which provider does what, so you can ask the right questions when evaluating any aerial roofing tool.

The four major imagery providers (and what each is good for)

Google Maps Static API

The most widely-used provider in the AI roofing space because it's the cheapest.

• Resolution: 5-15cm/pixel at maximum zoom (zoom 20)
• Freshness: Wildly variable — 6-24 months typical in major US metros, 2-4 years in suburban+rural
• Coverage: Global, US-comprehensive
• Pricing: $2 per 1000 image requests (essentially free at consumer scale)

What Google gets right:

• Coverage breadth (you can pull imagery for any US address)
• Cost (most AI tools can't afford anything else)
• Reasonable resolution for residential prospecting

What Google gets wrong:

• Freshness is unpredictable — you might be looking at the property's PREVIOUS owner's roof
• Resolution drops in rural areas
• No timestamp on imagery (vendors usually don't know when the image was captured)

Best for: consumer AI tools doing residential prospecting at scale.

Nearmap

The premium alternative most enterprise roofing tools use.

• Resolution: 5-7cm/pixel, sometimes finer
• Freshness: 3-6 month refresh in major US metros (much faster than Google)
• Coverage: US + a few international markets, but with gaps in rural areas
• Pricing: Enterprise contracts, $$$$ — typically $5k-25k+/year for contractor access

What Nearmap gets right:

• Best-in-class freshness for major US metros
• Consistent quality across the coverage area
• Available as direct API for AI tools to integrate

What Nearmap gets wrong:

• Cost makes it impractical for small-shop AI tools
• Coverage gaps in rural / smaller-market areas
• Smaller-shop AI tools that claim "Nearmap powered" often only have it for major metros

Best for: mid-to-large roofing contractors using EagleView or similar premium tools.

EagleView / Vexcel aerial imagery

The premium-of-premium tier. Uses planes (not satellites) for highest possible resolution.

• Resolution: under 5cm/pixel — near-survey quality
• Freshness: Variable, often custom-flight-on-demand for large jobs
• Coverage: US-comprehensive with regular flight schedules over major metros
• Pricing: Per-property reports ($30-100+) or annual subscriptions ($300-1500+/mo + per-property fees)

What EagleView gets right:

• Insurance-accepted reports
• Measurement accuracy under 1% error
• Custom flights for high-value insurance work

What EagleView gets wrong:

• Cost prohibits scaled prospecting (you can't economically score 500 candidate homes at $30-100/report)
• Designed for measurement-at-a-known-property, not prospect identification

Best for: insurance restoration, commercial work, post-storm damage documentation.

Drone imagery (on-demand)

Not a "provider" in the same sense, but increasingly used by AI tools for verification.

• Resolution: 1-2cm/pixel typical, finer with specialized equipment
• Freshness: Real-time (flight on request)
• Coverage: Anywhere you can legally fly
• Pricing: Per-flight, $50-200/property for contracted services

What drone gets right:

• Highest resolution available
• Oblique angles satellite can't capture
• On-demand timing (no waiting for satellite refresh)

What drone gets wrong:

• Cost-per-property prohibits scaled prospecting
• Regulatory constraints (FAA Part 107 license, no-fly zones)
• Weather-dependent

Best for: verifying high-priority AI-flagged properties before in-person inspection.

What resolution actually means for roof assessment

Resolution determines what the AI can detect. Practical breakdown:

Resolution	What's detectable	Use case
under 5cm/pixel	Granule loss patterns, individual missing shingles, fine cracking, hail bruise depth	Insurance-grade documentation
5-10cm/pixel	Material classification, damage signal detection, age estimation, condition scoring	Direct prospecting
10-15cm/pixel	Material type, large damage, tarp detection, structural features	Initial screening
15-25cm/pixel	Footprint, slope, basic structural features	Measurement only
over 25cm/pixel	Roof presence/absence	Useless for roofing

Most prospecting AI tools operate at 5-15cm at zoom 20 (Google range). Premium tools operate at finer resolution.

If a vendor doesn't tell you their resolution, ask. If they can't answer, treat the tool as Google-based until proven otherwise.

The freshness problem (most important variable)

Imagery freshness is the single most important variable nobody asks about.

Why it matters:

If a tool is scoring a roof from a 24-month-old image, you're potentially looking at the previous owner's roof. The current homeowner might have replaced it 18 months ago. You knock, embarrass yourself, lose credibility.

Typical freshness by region (Google-based tools):

• Major US metros (DFW, Phoenix, LA, NYC): 6-18 months
• Mid-sized metros: 12-24 months
• Suburban: 18-30 months
• Rural: 24-48 months

Typical freshness for premium-imagery tools:

• Nearmap in covered metros: 3-6 months
• EagleView in active flight schedules: 6-12 months
• Custom drone: real-time

The question to ask every vendor:

"What's the median image age in [my top zip code]?"

If they can't answer, they're not thinking about freshness — which means you'll be working with whatever Google has. Sometimes fine, sometimes a year and a half old.

When to trust the imagery, when to verify on ground

The rule of thumb:

Trust the AI screening when:

• The property is in a major metro with recent refresh
• The signal is high-contrast (visible tarp, missing shingle section)
• You're using AI for prospect prioritization, not insurance documentation

Verify on ground before action when:

• Imagery is older than 12 months in your area
• The signal is borderline (mild granule loss, possible curl)
• You're documenting for an insurance claim
• The property is high-value and worth the inspection time anyway

The screening + verification combo is faster and more accurate than either alone.

Manual vs AI-assisted satellite review

Manual review of satellite imagery (the Google Earth Pro approach) still has a place. It's slow — 5-10 addresses per hour — but it catches signals AI sometimes misses. Most useful for:

• Verifying AI-flagged borderline cases
• Reviewing historical changes (Google Earth Pro has timeline functionality)
• High-value insurance claims where you want human-confirmed signals

AI-assisted review is faster (every property in a service area in minutes) but isn't perfect. The best workflow uses AI for the 95% screening and manual for the 5% verification.

Cost models by use case

The pricing models tools use depend on what they're built for:

Per-image / per-report (EagleView, HOVER):

• Best for: low-volume measurement on already-qualified prospects
• Per-property cost: $30-100+
• Scales poorly to prospecting

Subscription with included scoring (Roofbird):

• Best for: high-volume prospecting across a service area
• Per-month cost: $99-299
• Effective per-property cost: $2-8 amortized

Enterprise-tier (Nearmap direct, EagleView annual):

• Best for: large multi-state contractors needing imagery API access
• Per-year cost: $5k-50k+
• Variable per-property cost depending on volume

Match the model to your use case. Don't buy per-image pricing for prospecting; don't buy subscription pricing for occasional one-off measurements.

Use cases by shop size

1-5 employees:

• Google-based AI prospecting (Roofbird or similar)
• Per-property EagleView only when needed for quotes
• Skip enterprise imagery entirely

5-15 employees:

• Subscription AI prospecting tool
• EagleView for measurements
• Consider drone services for high-value insurance work

15-50 employees:

• Multiple AI tools layered (prospecting + measurement)
• EagleView enterprise tier
• Begin drone integration for storm-chase

50+ employees:

• Enterprise contracts with Nearmap or similar
• EagleView premium tier
• Internal drone team or contracted services
• Custom AI integration

What to ask any "satellite imagery" vendor

A 5-question evaluation framework:

1. "Which imagery provider do you use?" (Google, Nearmap, EagleView, drone, custom?)
2. "What's the median image age in zip [your top zip]?" (If they can't answer, treat as Google-based)
3. "What resolution does your AI run against?" (Should be 5-15cm or finer for condition assessment)
4. "Have you published accuracy validation data?" (If yes, trust with skepticism; if no, treat as heuristic)
5. "Can I see sample output on properties I already know?" (Always pull 3-5 samples on known properties before signing up)

Vendors who answer all 5 confidently are usually the ones worth using.

Roofbird's DFW sample dashboard lets you run this evaluation in real-time on actual DFW properties. The 10 unlocked leads show exactly what Google-based AI scoring at 5-10cm resolution produces. Free trial in your own service area, no card required.

— Jake