Sentinel‐Based Inventory of Thermokarst Lakes and Ponds Across Permafrost Landscapes on the Qinghai‐Tibet Plateau

Abstract

AbstractThermokarst lakes and ponds (hereafter referred to as thaw lakes) play an important role in the permafrost regions by regulating hydrology, ecology, and biogeochemistry. However, detailed quantitative information on thaw lake extent and distribution remains poorly resolved across the entire permafrost regions on the Qinghai‐Tibet Plateau (QTP). Here, we applied the random forest (RF) model and manual visual vectorization methods to extract thaw lake boundaries on the QTP based on Sentinel‐2 images. Accuracy assessment was comprehensively demonstrated regarding the inherent spatial resolution of imagery and RF model performance. The results showed that the accumulated uncertainty of the total thaw lake area was ±5.75 km2, and the mean accuracy (91.9%) from field‐measured boundaries of 132 thaw lakes supported the accuracy of this inventory. A total of ∼161,300 thaw lakes with sizes ranging from 500 m2 to 3 km2 were detected, with a total area of ∼2,825.45 ± 5.75 km2. Most thaw lakes were detected in the continuous permafrost type (94.1%) and within the elevations of 4,500–5,000 m (68.4%). The small thaw lakes (<10,000 m2) predominated the total lake number (78.9%) but contributed to a small portion of the total lake area (12.7%). Spatial distributions of thaw lakes in terms of different climatic and environmental conditions were also comprehensively explored, including temperature, precipitation, ground thermal stability, active layer thickness, vegetation, soil properties, and underground ice content. This inventory is expected to be incorporated into Earth system models for a more comprehensive projection of the large‐scale biogeochemical feedback of thermokarst landforms on the QTP under continued global warming.