Water Level Change Monitoring Based on a New Denoising Algorithm Using Data from Landsat and ICESat-2: A Case Study of Miyun Reservoir in Beijing

Inland lakes or reservoirs are the main surface water resources, related to people’s survival and social development. On-site level data critical for resource management, while satellite laser remote sensing a significant tool long-term change monitoring. In this study, we took Miyun Reservoir, most important source of drinking in Beijing, as research area. We used Landsat images Ice, Cloud, Land Elevation Satellite (ICESat-2) small-scale monitoring inversion across unrecorded periods. First, proposed new two-step denoising method based on local statistics denoise ATL03 single photon from 2018 2020, extracted effective elevation information Reservoir. Second, 1984 MNDWI index was extract area generated percentage map occurrence. Finally, land boundary were selected according position under each generation graph, area, model (A–E model) established, values periods inverted. The results showed that accuracy all is higher than 95%. Reservoir has changed greatly past 37 years, especially northeast corner northern region. inverted had strong correlation with measured value, coefficient reached 0.97, root mean square error (RMSE) 0.553 m, estimated value highly consistent recorded fluctuated dramatically 2020. This complements traditional mapping method, provides idea changes without field records, also contributes timely management global lake reservoir time changes.