Large-Scale Street View Data Collection and Processing

Yes. The unit can be every fixed interval on a road network, a representative sample of roads, or a supplied list of locations across multiple countries. Before quoting, we run a coverage and access audit because platform quotas, image age, licensing and gaps determine the practical scale. The collection pipeline records status, retries, duplicates and QA outcomes so a large job remains reproducible rather than becoming an untraceable folder of images.

We collect across multiple street-view platforms, chosen per project and always within each platform's terms: Google Street View (Street View Static API) outside mainland China; Baidu panorama inside mainland China; Apple Maps Look Around where coverage and licence allow; and open imagery platforms such as KartaView and Mapillary, which publish under Creative Commons licences. We can also process imagery you already own or capture yourself, or commercially licensed imagery bought for the project. We do not bulk-download imagery from platforms that prohibit it, and we will say at the enquiry stage if the source you have in mind cannot be used the way you are imagining.

Yes, through Baidu's panorama API, which is the practical source there since Google has no coverage. The workflow is the same — sample points along the network, retrieve fixed headings, measure the same indicators — with two differences worth planning around. Coordinates need converting between WGS 84 and the BD-09 system the platform uses, which we handle and document. And historical vintages are far less consistently available than Google's, so change-over-time studies are something we scope against what the platform actually returns for your area rather than promise up front.

The indicators are always yours to keep. The imagery depends on where it came from: open-licensed and client-owned imagery can be delivered with the dataset, while imagery retrieved through a platform API is governed by that platform's caching and redistribution terms, so what you receive is the derived measurements plus a manifest identifying each source image. We confirm which case applies before work starts, in writing.

We validate every project against a manual sample scored by hand. On a typical greenery index the automated and manual scores agree within about three percentage points, which is sufficient for comparing streets against each other and not sufficient for treating any single value as an absolute truth. The validation result is delivered with the data rather than described in general terms.

As often as the underlying imagery is refreshed, which for platform sources is typically every one to three years in dense urban areas and less often elsewhere. Re-running the same sampling design against new imagery gives a genuine change measurement; we report which points actually have newer imagery rather than silently mixing vintages.

Yes, and it is often the better option. Dashcam footage, 360 camera runs or an existing image library can all be processed, provided positions and headings are recoverable. Your own capture removes licence restrictions on redistribution, fixes the capture date to a moment you chose, and lets you cover streets the platforms have not visited recently.