PINAS: connecting satellite maps with local knowledge

PINAS is PhilSA’s network for connecting institutions and people with space-enabled action. Its work includes understanding local government needs, sharing processing methods and supporting ground-data collection. Those activities help transform an available observation into a product suited to a particular place. PINAS is a network and capability effort, not the name of an imaging satellite.

Suppose a municipality wants to identify slopes that changed after prolonged rain. A satellite can provide wide-area context, but local staff may know which roads were blocked, where previous clearing occurred and which places can be checked safely. Combining the two kinds of evidence is more informative than treating a remote image as a replacement for everyone familiar with the landscape.

In September 2026, PhilSA published a comparison of Sentinel-2 observations from April 6 and September 13 around Subic, Zambales, following an August 30 landslide. The source map identifies Sentinel-2C imagery and marks a possible affected area of about 1.1 square kilometres. The analysis used vegetation change to identify candidate extent and explicitly stated that the map remained subject to ground validation — open definition.

One square kilometre contains one hundred hectares, so 1.1 square kilometres corresponds to about 110 hectares. This conversion changes the unit, not the certainty or meaning of the estimate. It also does not reveal the depth of moved material. Estimating a volume would need additional information, such as terrain change, rather than treating mapped surface area as if it were a three-dimensional measurement.

Area, interpretation and validation

Vegetation loss can indicate a landslide, but another disturbance can also alter a landscape. Field evidence and other records can test the interpretation. A useful report distinguishes the observed change, the inferred cause and what still needs checking. It can prioritize areas for investigation without pretending that every outlined pixel has already been verified on the ground.

For the fictional municipal project, keep the source dates, location accuracy, method and validation notes with each map version. If a field team corrects an outlined area, preserve why it changed instead of silently overwriting the history. That makes the product easier to improve and explain. PINAS-style collaboration is valuable because people who understand the local question can participate in producing and testing the information, rather than receiving an unexplained image at the end.