Use imagery to spot new buildings and extensions

Use recent aerial, satellite, or drone imagery to flag new roofs and building extensions that are not yet on the roll. This works especially well in fast-growing or hard-to-reach areas and helps the city target follow-up checks rather than canvassing everywhere.

• Peri-urban growth is fast or terrain makes fieldwork costly.

• The city has at least basic GIS support or a partner who can provide it.

• The administration wants a repeatable change-detection tool rather than one-off enumeration.

• Access to recent imagery and a simple workflow for reviewing and verifying changes.

• A route to assign IDs and update the register once a building is confirmed.

• Do not start here if the city cannot validate flagged structures and update the roll.

• This is a poor first choice where imagery is poor or GIS support is effectively absent.

The political risk is usually low to moderate, but the city still needs to show that new records will be handled fairly and that residents are not being drawn into a process they do not understand.

The full card would help the city plan how to obtain usable imagery, how to spot likely new buildings, how to validate them on the ground, and how to integrate confirmed changes into the register.

• Put routine coverage audits on the calendar

• Give each property one ID in one register.

Imagery is most valuable when growth is happening faster than the register can keep up. It lets the city look for change systematically and revisit the same places over time. But imagery only creates value when the city can review likely changes, validate them where needed, and push confirmed changes into the live register.

Use aerial, satellite, or drone imagery to detect buildings and extensions that the register has missed or has not yet updated.

A city with visible peri-urban growth, difficult terrain, or strong pressure to create a repeatable change-detection tool rather than relying only on field enumeration.

A first verified list of new or changed structures in priority areas, feeding directly into the register update process.

Choose the imagery source, the pilot geography, and the minimum validation workflow so the exercise produces usable updates rather than just interesting maps.

Revenue administration with GIS or mapping support and a small validation team.

• Growth corridors, fringe settlements, or dense areas are changing too quickly for occasional field sweeps alone.

• The city has at least basic GIS support or can access it through a partner or contractor.

• Leadership wants a method that can be repeated every year or every few years, not just a one-off project.

• Decide how the city will get imagery first: existing satellite data, aerial photography, drone flights, or a partner institution.

• Define the review and validation workflow before analysing imagery, otherwise the city will generate leads it cannot process.

• Make sure confirmed changes can be linked to the property register and the city’s identifier system.

• Choose between a simple visual comparison method at the start or more automated change-detection methods later.

• Set thresholds for when a flagged change requires field verification and when desk validation may be enough.

• Decide whether the first use of imagery will focus on missing buildings, large extensions, or both.

First 90 days

• Secure the imagery source for a pilot area and confirm image quality.

• Overlay the imagery with current register or map information and define how likely changes will be flagged.

• Test the validation process on a small number of cases so the city learns how much follow-up work is really required.

6 to 12 months

• Run the first pilot comparison and validate the highest-confidence flags.

• Create or update records for confirmed changes and document false positives so the method improves.

• Estimate the staff time and costs required for scaling to more areas.

12 to 24 months and beyond

• Repeat the exercise in the same and then additional growth areas to create a regular rhythm of change detection.

• Integrate the imagery review into routine coverage audits rather than treating it as a one-off technical exercise.

• Use experience from the first cycles to decide whether more advanced analysis is worthwhile.

• Depending on the country context, the city may need clear permission to use imagery for tax-administration purposes, especially where drones are involved.

• Public messaging should make clear that the purpose is to keep the roll fair and current, not to create a surveillance programme.

• A small GIS function or trusted partner is enough to start; the city does not need a large geospatial unit at day one.

• Field validation and register update capacity matter just as much as the imagery itself.

• Stable property IDs or location references make imagery-based updates much easier.

• The city may overestimate what imagery can do and underinvest in validation and record maintenance.

• Poor image quality or weak georeferencing can create misleading leads.

• If communications are mishandled, the reform can attract unnecessary privacy concerns.

• Number of likely changes flagged through imagery.

• Share of flagged changes confirmed after review or field validation.

• Number of confirmed new or changed structures loaded into the register.

• Time from identification of a likely change to completion of the register update.

• This card is strongest when paired with PT-COV-09 on routine coverage audits, PT-COV-07 on one register and one ID, and PT-COV-03 where ground checks are still needed in harder areas.

• What imagery source is actually affordable and reliable for your city?

• Who will validate flagged structures before records are changed?

• Which geography should be piloted first to show value quickly?

• How will confirmed changes flow back into the live register?