Real estate portfolios span dozens or hundreds of properties spread across metros, and no inspection schedule can put a person on every roof, lot, and parcel line before a quarterly decision is due.
Aerial and satellite imagery answer that by capturing the same rooftops, lots, and blocks on a repeating schedule, turning a portfolio-wide condition check into something a desk analyst can run without a single site visit.
This guide breaks down how real estate teams put overhead imagery to work, which resolution and revisit each task actually needs, and which providers are matched to the job, so you can find the right data and provider for your property program.
Table of Contents
Key takeaways
- Real estate portfolios need repeatable, wide-area imagery no site-visit schedule can match across dozens of properties
- Roof detail favors aircraft-based aerial imagery, while satellites earn their place scanning many locations
- The shortlist narrows fast once you know whether the job is one property or a whole portfolio
Before any provider enters the picture, a real estate program has to settle what it actually needs from the data. The summary below sets out the resolution, cadence, and constraints that overhead property imagery works within.
| Primary sensors | Aerial VHR optical, satellite VHR optical |
|---|---|
| Working resolution | 2.5-15 cm aerial, 30 cm-1.5 m satellite |
| Typical revisit | Annual aerial refresh, tasked satellite capture |
| Core indices | Building footprints, roof and property attributes |
| Entry cost | Demo request, or published rates on UP42 |
| Main constraint | Imagery shows the exterior only, not the inside |
Those figures cover the baseline most property programs run on. Programs built around a single high-value asset or a nationwide portfolio pull on different sensors entirely, covered next.
How satellite data is used in real estate
Overhead imagery enters a real estate program at five distinct points, from a single roof to an entire portfolio, each pulling on a different sensor and a different scale.
Rooftop condition and property attributes
Assessing a roof at scale starts with resolution fine enough to separate a shingle tab from a vent stack, which is well beyond what any satellite delivers. Nearmap’s AI Insights stack reads roof condition, material, and peril risk out of its own aerial capture at 4.4 to 7.5 cm, refreshed up to three times a year across its covered North American metros.
Vexcel’s Elements AI works the same problem from four angles at once. Its oblique imagery, captured from each cardinal direction at 7.5 cm alongside a top-down orthomosaic at 7.5 to 15 cm, extracts more than 40 AI-derived building and property attributes, including roof shape, pools, and solar panels, features a single top-down pixel can miss.
EagleView runs a comparable program at 1-inch, 2.54 cm, ground sample distance on an annual capture cycle, extracting 125 or more property attributes per structure and packaging them into measurement reports a contractor or appraiser can order one property at a time. All three programs work at a resolution class no satellite in this market matches.
Portfolio screening across many locations
A portfolio manager reviewing hundreds of addresses cannot read a hundred separate images by eye, which is the problem Ecopia AI’s building data solves. It applies its own AI-based feature extraction to imagery sourced from its partner network rather than flying anything itself, turning aerial and satellite captures into a queryable footprint layer.
The resulting US layer covers more than 180 million building footprints tied to over 270 million address points, updated annually and guaranteed above 97 percent accuracy under contract. Access runs through a Data Portal that grants entry by request rather than an open self-serve option.
For a single continuously updated view of dispersed assets, Vantor’s Vivid Mosaic basemap covers 135 million square kilometers at 30 cm-class resolution, letting an analyst scan a scattered set of properties against one current image rather than tasking each site individually.
New construction and infill tracking
Tracking how fast a market is building is a change-detection problem, not a single snapshot. Vantor sells its imagery into housing-market monitoring platforms that classify construction stages automatically, which gives a developer or analyst visibility into a competitor’s pipeline without a site visit.
Airbus has published a case study in which 50 cm Pleiades imagery identifies cleared land and classifies each phase of residential construction from groundbreaking to completion, with roughly 90 percent accuracy, for US Census Bureau reporting. Note the resolution: half a meter was enough, and the sharper 30 cm product was not what the job required.
Neighborhood context and risk exposure
A property’s surroundings matter as much as the structure itself. Ecopia AI pre-appends FEMA flood zone data to its US building footprint layer, giving a zone-level exposure read for every mapped structure without a separate lookup against a flood map.
Nearmap folds a near-infrared band into its capture alongside standard RGB, supporting vegetation and impervious-surface analysis around a parcel, useful for reading tree overhang, green space, and runoff risk as part of the same property review that covers roof condition.
Long-term change and value history
A property’s history informs its valuation as much as its current condition does. Nearmap’s US archive reaches back to 2014, and Vexcel and EagleView hold comparably deep records, giving a reviewer a timestamped, third-party view of when an addition, a pool, or a renovation actually appeared.
Airbus extends that record furthest: its optical archive runs back to 1986, when the first SPOT satellite launched. That depth matters less for a single transaction than for tracking a neighborhood’s development pace across the multi-year cycles that actually drive value. The same aerial imagery underwrites property risk, as set out in our guide to satellite data for insurance.
What satellite data you need for real estate
Different real estate tasks call for different sensor types, resolutions, and revisit frequencies. The table below maps each common task to the data specification it requires.
| Task | Sensor modality | Resolution | Revisit | Key index / band |
|---|---|---|---|---|
| Roof condition assessment | Very high-resolution aerial optical | 2.5-8 cm | Annual to 3x/year | Roof material and condition flags |
| Property attribute extraction | Aerial optical plus AI/ML | 3-15 cm | Annual | Building and roof attributes |
| Portfolio-wide building inventory | Aerial or satellite optical | 15 cm-1 m | Annual | Building footprint count |
| New construction and infill tracking | VHR satellite optical | 30-50 cm | Weekly to on-demand | Footprint change detection |
| Neighborhood and land-cover context | Multispectral optical (NIR/CIR) | 10-30 cm | Annual | NDVI, impervious surface |
| Flood and hazard zone overlay | Optical plus reference layers | 30 cm-1 m | Annual | Flood zone, peril flags |
| International portfolio screening | VHR satellite optical, tasked | 30 cm-1.5 m | On-demand | Single-date capture |
| Historical value verification | Aerial or satellite optical archive | Varies by provider | Multi-year archive | Time-stamped comparison |
With data requirements mapped, the next step is identifying which providers can supply them. The section below covers the most relevant options for real estate programs, from aerial capture to satellite tasking.
Satellite data providers for real estate
The providers below have documented real estate use cases and data products that map to the tasks in the table above. The mix spans three aerial imagery operators, an analytics platform built on partner imagery, and two VHR satellite operators.
| Provider | Type | Best for | Key real estate spec | Entry point |
|---|---|---|---|---|
| Nearmap | Aerial imagery provider | Metro portfolio and roof scoring | 4.4-7.5 cm GSD, up to 3x/year | Contact sales |
| Vexcel | Aerial imagery provider | Portfolio property attributes | 7.5-15 cm ortho and oblique | Demo request |
| EagleView | Aerial imagery provider | Property measurement reports | 125+ AI property attributes | Per-report or subscription |
| Ecopia AI | Analytics platform | Nationwide building footprints | 180M+ US building footprints | Data Portal by request |
| Vantor | Optical satellite operator | New-build and portfolio tracking | Vivid Mosaic, 30 cm-class basemap | Quote or UP42 marketplace |
| Airbus | Satellite operator | International portfolio tasking | Pléiades Neo, 30 cm optical | Quote or UP42 marketplace |
For a wider shortlist across the high-resolution imagery market, our guide to the best high-resolution satellite imagery providers covers additional operators beyond this real estate-focused set.
How to choose satellite data for real estate
Real estate imagery purchases are not steered by a filing deadline or a compliance mandate. The decision comes down to portfolio economics and what a program actually needs to prove, which puts cost, coverage, and resolution ahead of any regulatory date.
Scale decides the model first. A single acquisition or a one-off appraisal review is well served by a single tasked image or a one-time aerial report, while a portfolio spanning dozens of assets is cheaper to run on an aerial subscription or a standing building-footprint license than on repeated one-off orders.
Coverage decides the field quickly after that. Nearmap, Vexcel, and EagleView each cover specific metros and countries rather than the whole globe, while Vantor’s and Airbus’s tasked satellites reach any address on the planet on a quote or an UP42 order. A portfolio concentrated in a few metro areas is well served by an aerial program; one spread across countries is not.
Overhead imagery, aerial or satellite, does not appraise a property. It shows what the roof, footprint, and surroundings look like from above and how they changed, not the condition of the furnace, the terms of a lease, or the finish inside.
In dense urban cores, aircraft-based imagery from Nearmap, Vexcel, or EagleView, captured at a few centimeters, resolves far more roof and site detail than any satellite. For one address, a walk-through inspection usually costs less than tasking a satellite, and the satellite only earns its place once a program is screening many locations at once.
Licensing matters more for portfolio-wide analytics than for a single image. Confirm whether redistribution to a lender, an investor, or a public filing is permitted under a provider’s standard commercial terms before a dataset becomes part of due diligence documentation.
Verdict
Real estate is a volume vertical for overhead imagery. The technology itself is mature, and most programs are choosing between an aerial subscription and a tasked satellite rather than deciding whether to use imagery at all.
Programs assessing roof condition or extracting property attributes at scale should evaluate Nearmap, Vexcel, and EagleView first, since a few centimeters of aerial detail beats anything a satellite in this market delivers. Teams building a nationwide footprint inventory get more from Ecopia AI’s building data, and portfolios with international exposure or new-construction tracking needs turn to Vantor and Airbus.
For a shortlist across the wider high-resolution imagery market, see our guide to the best high-resolution satellite imagery providers, which covers additional operators beyond this real estate-focused set.
Frequently asked questions
Below are answers to the questions real estate buyers most commonly ask. Each answer points to the section where the full detail lives.
How is satellite and aerial data used in real estate?
Overhead imagery covers five jobs: roof and property attribute extraction, portfolio-wide building screening, new-construction and infill tracking, neighborhood and risk context, and long-term value history. Most programs draw on aerial imagery for detail and satellite tasking for reach. The detail is in “How satellite data is used in real estate“.
Can satellite imagery replace a property inspection?
No. Overhead imagery shows the roof, footprint, and surroundings from above, not the condition of the mechanicals, the lease terms, or the interior finish. For a single address a walk-through inspection is usually cheaper than tasking a satellite. The trade-off is covered in “How to choose satellite data for real estate“.
What resolution do I need to assess a roof from above?
Roof condition and property attribute work runs on aerial imagery at 2.5 to 15 cm, the resolution range Nearmap, Vexcel, and EagleView all capture at. Portfolio-wide building counts and neighborhood context work fine at 30 cm to 1 meter from tasked satellites. The full task-to-resolution mapping is in “What satellite data you need for real estate“.
Which satellite data providers are best for real estate?
Nearmap, Vexcel, and EagleView lead on aerial roof and property detail across their covered metros, Ecopia AI supplies the nationwide building footprint layer portfolio teams query instead of surveying, and Vantor and Airbus cover new-construction tracking and international tasking. Provider details are in “Satellite data providers for real estate“.
Does satellite or aerial imagery show flood risk for a property?
Not directly, but Ecopia AI pre-appends FEMA flood zone data to its US building footprint layer, giving a zone-level read for every mapped structure without a separate lookup. Nearmap’s near-infrared band adds vegetation and impervious-surface context around a site. Both are covered in “How satellite data is used in real estate“.
How far back do real estate imagery archives go?
Nearmap’s US archive reaches back to 2014, and Airbus’s optical archive runs back to 1986, when the first SPOT satellite launched. Both function as an independent record of when a structure or an improvement actually appeared. Archive depth by provider is discussed in “How satellite data is used in real estate“.
My passions are Earth Observation and Satellites, and my profession is Data Analysis. I combine both within ObservationData.com to show you the use cases of Earth Observation, to help you find the right provider, and to share your experiences.
