Statistical Analysis of Changes in Sentinel-1 Time Series on the Google Earth Engine

• Published in: Remote sensing (Basel, Switzerland) Vol. 12; no. 1; p. 46
• Main Authors: Canty, Morton J., Nielsen, Allan A., Conradsen, Knut, Skriver, Henning
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2020
• Subjects: Algorithms; anthropogenic activities; Anthropogenic factors; Application programming interface; Archives & records; Cloud cover; computer software; Data analysis; Deforestation; Flash floods; floods; Hypotheses; Internet; mining; monitoring; Probability distribution; Remote sensing; shipping; Software; Source code; Statistical analysis; Statistics; Synthetic aperture radar; Temporal resolution; Time series; time series analysis; Uranium
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs12010046

Time series analysis of Sentinel-1 SAR imagery made available by the Google Earth Engine (GEE) is described. Advantage is taken of a recent modification of a sequential complex Wishart-based algorithm which is applicable to the dual polarization intensity data archived on the GEE. Both the algorithm and a software interface to the GEE Python API for convenient data exploration and analysis are presented; the latter can be run from a platform independent Docker container and the source code is available on GitHub. Application examples are given involving the monitoring of anthropogenic activity (shipping, uranium mining, deforestation) and disaster assessment (flash floods). These highlight the advantages of the good temporal resolution resulting from cloud cover independence, short revisit times and near real time data availability.