CALIBRATED ACTIVITY DETECTION IN SENTINEL-1 SAR TIME SERIES

Andrei-Toma STOICA, Simonel-Olimpiu DAVID, Rareș-Cristian BIȘAG

Abstract


This paper presents a method for facility-scale activity inference from Sentinel-1 SAR time series, emphasizing calibrated change detection under acquisition-geometry variability. Short-window composites are formed around two analysis dates and compared using (i) backscatter change in dB and (ii) standardized anomaly change derived from baseline mean and variance. Detection thresholds are learned from baseline null-pair comparisons via percentile calibration to quantify and control false-alarm behavior. Ascending and descending passes are processed separately to assess geometry-dependent stability. The approach is fully reproducible with open data and yields interpretable AOI-level activity indicators suitable for security monitoring.


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References


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