- Building footprint extraction at city scale — High-resolution optical and SAR imagery can delineate individual building outlines across entire cities. The accuracy ceiling depends on pixel size, roof geometry, and how honestly the method accounts for SAR distortion.
- Cadastral boundary verification using sub-metre imagery — Sub-metre commercial imagery lets land registries check registered parcel boundaries against physical reality at scale, flagging encroachments and area discrepancies before they become disputes. Accuracy requirements are strict and the legal status of satellite-derived boundaries is not equivalent to a ground survey.
- Construction activity monitoring and project-stage tracking — Satellite imagery and SAR coherence time-series can track individual construction sites from ground-break to topping-out, independent of cloud cover. The method underpins permit compliance, infrastructure investment verification, and economic nowcasting in cities where ground inspection is slow or politically fraught.
- Impervious surface mapping for urban flood and runoff modelling — Sealed surfaces drive flash-flood risk, yet most cities lack current maps of their true impervious fraction. Spectral unmixing of Sentinel-2 and Landsat imagery, checked against SAR backscatter, produces impervious-fraction grids that feed directly into hydrological models.
- Informal settlement detection from satellite imagery — Sub-metre optical imagery and spectral analysis can distinguish informal settlements from formal low-rise housing by roof material, street geometry, and building density. The method is powerful but not infallible: dense formal housing creates genuine ambiguity that honest analysis must flag.
- Land-use change detection for planning enforcement — Satellite change detection exposes unauthorised construction, green-belt encroachment and agricultural conversion before enforcement windows close. This page covers sensor choice, minimum detectable change size, and what courts and planning tribunals actually accept as evidence.
- Night-lights mapping of urban economic activity — Calibrated night-light radiance from VIIRS and DMSP-OLS reveals electrification extent, relative wealth gradients, and economic activity patterns. The signal is real but indirect: physics, saturation, and mixed light sources all require careful handling before any GDP inference is defensible.
- Population distribution modelling from built-environment data — Dasymetric mapping disaggregates census totals onto fine spatial grids by weighting them against satellite-derived proxies: building footprints, roof area, settlement extent, and night-light intensity. The method is powerful and the uncertainty is compounding. Both facts matter.
- Property tax base mapping from satellite data — Satellite imagery can count, measure, and roughly value taxable structures even where ground records are absent or decades out of date. This page explains which sensors do what, where the method breaks down, and what a municipality can realistically expect from a first survey.
- Urban expansion and boundary mapping — Satellite imagery from Sentinel-2, Landsat and Sentinel-1 SAR can track the outward spread of built-up areas with annual or sub-monthly cadence, exposing where urban boundaries on official maps have fallen behind reality.
- Urban green-space audit and canopy mapping — Satellite multispectral and LiDAR data can quantify urban green space with far more rigour than ground surveys alone, but separating canopy layers and correcting for seasonal bias demands careful method choices. This page explains what the sensors can and cannot resolve.
- Urban heat island mapping from thermal infrared — Thermal infrared satellites measure land surface temperature across urban fabrics, revealing heat-island cores, cool corridors, and the stark contrast between asphalt and tree canopy. Resolution limits are real and matter for city planning.