Mapping Arctic Lake Ice Backscatter Anomalies Using Sentinel-1 Time Series on Google Earth Engine

Seepage of geological methane through sediments Arctic lakes might contribute conceivably to the atmospheric budget. However, abundance and precise locations such seeps are poorly quantified. For Lake Neyto, one largest on Yamal Peninsula in Northwestern Siberia, temporally expanding regions anomalously low backscatter C-band SAR imagery acquired late winter spring have been suggested be related seepage from hydrocarbon reservoirs. this hypothesis has not verified using in-situ observations so far. Similar anomalies also identified for other Yamal, but it is still uncertain whether or how many them seepage. This study aimed document similar lake ice a regional scale over four (the Tazovskiy Peninsulas; Lena Delta Russia; National Petroleum Reserve Alaska) during different years time series based approach Google Earth Engine (GEE) that quantifies changes σ0 Sentinel-1 sensor time. An algorithm assessing coverage takes number acquisitions maximum between into account presented, differences main operating modes evaluated. Results show better can achieved extra wide swath (EW) mode, interferometric (IW) mode data could useful smaller areas substantiate EW results. A classification Neyto Δσ0 images derived GEE showed good agreement with presented previous study. Automatic threshold-based per-lake counting where occurred was tested, issues were identified. example, effects grounding potentially emissions separated efficiently. Visualizations likely reflect temporal expansions expected particularly identifying target future field-based research. Characteristic clearly resemble ones observed solely visually regions. All algorithms produced framework openly provided scientific community studies aid our understanding upon progression corresponding evaluations formation hypotheses.