Gen 4 is powered by a new raster model with the addition of eight new AI Layers for roof condition and construction. Gen 4 also improves existing layers already available in Gen 3. Open World vectorisation has been expanded, enhancing some existing AI Packs and adding new ones. Gen 4 processing includes every survey from mid 2020 to present, and coverage now extends beyond Australia and the USA to include Canada and New Zealand.

Showcasing some of the new roof condition AI Layers

Gen 4 AI Layers

The Gen 4 model (gen4-building_storm-1.0) introduces a new raster model with eight new layers to the AI Layer Glossary.

Some of these have not yet been included in generally available AI Packs from the first release of Gen 4, but will be subsequently added to existing and new AI Packs:

Roof Condition layers:

Construction layers:

New AI Packs

AI Pack: Roof Condition

The Roof Condition AI Pack includes these 5 layers visualised in MapBrowser, and AI Feature API + AI Offline vectorised data that intersects these with our building footprints. See the pack link for more details.

Roof Condition layers:

Enhanced AI Packs

AI Pack: Surfaces

AI Pack: Construction

AI Pack: Swimming Pool

AI Pack: Solar Panels


Note that Gen 4 content is currently available via three methods:

Gen 4 is NOT yet available for export through MapBrowser. If you wish to access Gen 4 data and have existing Nearmap AI credits, you may either do so via the AI Feature API (which can be added to your subscription), or by asking your Account Manager to organise an offline delivery of Gen 4 data.


The big new change to coverage with Gen 4 is adding New Zealand and Canada to our coverage footprints. Initial coverage for Gen 4 is every survey captured in all four capture countries from mid 2020 until launch in May 2021 (and ongoing).

The one key caveat to New Zealand and Canadian data is that AI Offline Parcel is not yet available (that is, raster and vector can be provided, but summary information trimmed to property boundaries and address information are not yet available).

Version History


The first production data released, as per the specifications above.


Adds new "unclippedAreaSqm" and "unclippedAreaSqft" fields to connected classes behind AI Feature API (vegetation and surfaces AI Packs). "areaSqm" and "areaSqft" will continue to give the area of the feature returned from the API. The "unclippedArea" includes the full area of the connected feature, which may be very large. This is to make it easier to determine if e.g. a property borders on a small stand of trees vs a large forest, or a pond vs an ocean.

This upgrades all previously processed data from gen4-building_storm-1.0 to gen4-building_storm-1.1


Enhanced AI Packs

AI Pack: Construction update - new AI Layers included in MapBrowser, and new feature classes in AI Feature API corresponding to:

API Data

In this release, a response includes all children of any feature that intersects with the query AOI, whether or not each child feature intersects with the parcel boundary. Previously, a response returned only features (children and parents) that intersected with the parcel.

This upgrades all previously processed data from gen4-building_storm-1.x to gen4-building_storm-2.0


gen4_lightning_bolt uses the same raster model and vectorisation process, such that results will be identical to gen4-building_storm, with the following exceptions. It will typically be available on surveys processed from July 2021 onwards.

New AI Packs

AI Pack: Poles introduces a new feature in the data that captures the location of both power and light poles as a point feature with attached metadata. See the pack page for more details.

Enhanced AI Packs

AI Pack: Building Footprints introduces a new fidelity score for both building footprints and roof outlines along with confidence as a measure of quality. Where confidence gives the probability that an object is real, the fidelity score measures how well we believe the shape of the polygon matches the true shape. See the pack page for more details.

AI Pack: Roof Condition now includes a "low confidence roof condition" attribute for each of the five roof condition layers. This is in addition to the existing, unchanged standard roof condition vectors and attributes. The low confidence roof condition will describe a larger area, and a lower confidence than the standard one. Given roofs typically degrade gradually, this makes it easier to identify new roofs with no weathering at all (e.g. for tile and shingle staining), but has a much higher rate of false positives. See the pack page for more details.