Spatial-temporal water area monitoring of Miyun Reservoir using remote sensing imagery from 1984 to 2020

TL;DR

This study presents an automated, long-term water mapping method using Landsat imagery from 1984 to 2020 to monitor Miyun Reservoir's changes with high accuracy, aiding ecological and water resource management.

Contribution

The paper introduces a novel automated water mapping approach that effectively handles cloud, shadow, ice, snow, and spectral variability over a 36-year period.

Findings

Achieved 98.2% overall accuracy in water mapping.

Revealed significant morphological changes in Miyun Reservoir.

Identified key driving factors of reservoir changes.

Abstract

Miyun Reservoir has produced huge benefits in flood control, agricultural irrigation, power generation, aquaculture, tourism, and urban water supply. Accurately water mapping is of great significance to the ecological environment monitoring of the Miyun Reservoir and the management of the South-to-North Water Diversion Project. On the 60th anniversary of the completion of the Miyun Reservoir, we took the Miyun Reservoir as the study area and collected all the Landsat-5 and Landsat-8 remote sensing images from 1984 to 2020 for water mapping. Based on the spectral, topographical and temporal-spatial characteristics of water, we proposed an automated method for long-term researvoir mapping, which can solve the problems caused by cloud, shadow, ice and snow pixels. Moreover, it can also deal with 'the same objects with different spectra' and spectral mixed problems. The overall accuracy is as high as 98.2% for the case with no cloud or snow/ice cover. The landscape division index is introduced to analyze the morphological changes of Miyun Reservoir. Based on the mapping results, we analyzed the changes of Miyun Reservoir from 1984 to 2020 and the driving factors of them.