Characterizing and Detecting Multiscenario Degradation of the Maidika Alpine Wetland Nature Reserve in the Qinghai–Tibet Plateau Using Landsat Time Series

Monitoring alpine wetland degradation on the Qinghai–Tibet Plateau is crucial for understanding the responses to and resilience against climate change but has been challenging due to limited images in cloudy high-mountain areas. Based on 3 elements, spectral–temporal characterization, classification, and degradation detection for wetland covers, this study proposes a continuous classification and degradation detection algorithm for alpine wetlands (AW-CCD). This algorithm relates to water-related landscape change processes, including multiscenario detection of snowmelt, lake, and river shrinkage and the transition of a swampy meadow to an alpine meadow with decreased soil wetness. AW-CCD uses the spectral–temporal index features to classify wetlands on an annual basis and then capture wetland degradation processes to combine long-time-series inter-annual parameters and seasonal soil wetness. This study detected snow cover from clouds based on the Landsat Quality Assessment band and spectral changes during snow–bare rock transition. Through the meadow spectral ratio vegetation index and seasonal soil wetness frequency across years, swampy and alpine meadow dynamics are tracked by wetness loss and increasing grass signal. By effectively characterizing multiple surface changes through spectral–temporal analysis, AW-CCD provides annual wetland mapping and monitoring metrics for multiscenario degradation. Results show an improvement in snow and meadow mapping accuracy by 5% and 3%, respectively, with a mapping accuracy of 94.9% in the Maidika Wetland in 2022. Spatial–temporal patterns demonstrated multiscenario degradation during 2 decades, with snow and river areas decreasing by 5.04% and 16.74%, respectively, and 3.23% of swampy meadows transitioning to alpine meadows. Degradation was most pronounced before 2009, followed by stability until 2015 and renewed degradation thereafter. This study highlights the effectiveness of AW-CCD in capturing the multiscenario responses of alpine wetlands to climatic changes on the Qinghai–Tibet Plateau.