Integrating commercial and public imagery to accelerate deforestation alerts

Abstract

Generating satellite-based deforestation alerts with actionable latency requires frequent imaging, creating an imperative to use different sensors together. We introduce a simple and open-source framework called the Disturbance Index Alert System (DIAS), which is based upon transformation of imagery from different sources into an interoperable stream of Disturbance Index (DI) values. Whereas most alert systems target divergence of forested pixels from historical states, DIAS targets movement of a pixel’s Z-score position relative to the image-wide population of forest pixels along a forest-sensitive axis. This strategy provides the following practical benefits: (1) it reduces the need to process the historical archive; (2) it reduces dependence upon stable sensor calibration; (3) it allows Z-score-based DI values to be combined across sensors; and (4) it accommodates changes to the group of sensors providing measurements. We demonstrated in Madagascar that sensor integration through DIAS can provide more timely alerts than both conventional individual-sensor systems and additive combination of such systems. Across our study sites, using a commercial source of daily imaging (PlanetScope) in conjunction with imagery from public sources (Landsat, Sentinels-1 and -2) allowed high-confidence detection (false alert rate of approximately 20%) of two-thirds of deforestation occurring at 10 m reference pixels within one month; 40% were detected in that timeframe with public data alone. As commercial options for Earth observation proliferate, flexible and computationally lightweight approaches such as DIAS are needed to accommodate diverse and sometimes only loosely calibrated instruments in support of timely forest monitoring.

Citation

Yang, Zhiqiang; Bullock, Eric L.; Lindquist, Erik J.; Andrianirina, Carole; Healey, Sean P. 2026. Integrating commercial and public imagery to accelerate deforestation alerts. Remote Sensing. 18: 2221.