Monitoring Dynamic Evolution of the Glacial Lakes by Using Time Series of Sentinel-1A SAR Images

Bo Zhang,Xiaowen Wang,Guoxiang Liu,Zhilin Li,Rui Zhang,Qiao Liu,Jialun Cai,Yin Fu

doi:10.3390/rs13071313

Abstract

As an approach with great potential, the interpretation of space-borne synthetic aperture radar (SAR) images has been applied for monitoring the dynamic evolution of the glacial lakes in recent years. Considering unfavorable factors, such as inherent topography-induced effects and speckle noise in SAR images, it is challenging to accurately map and track the dynamic evolution of the glacial lakes by using multi-temporal SAR images. This paper presents an improved neighborhood-based ratio method utilizing a time series of SAR images to identify the boundaries of the glacial lakes and detect their spatiotemporal changes. The proposed method was applied to monitor the dynamic evolution of the two glacial lakes with periodic water discharge at the terminus of the Gongba Glacier in the southeastern Tibetan Plateau by utilizing 144 Sentinel-1A SAR images collected between October of 2014 and November of 2020. We first generated the reference intensity image (RII) by averaging all the SAR images collected when the water in the glacial lakes was wholly discharged, then calculated the neighborhood-based ratio between RII and each SAR intensity image, and finally identified the boundaries of the glacial lakes by a ratio threshold determined statistically. The time series of areas of the glacial lakes were estimated in this way, and the dates for water recharging and discharging were accordingly determined. The testing results showed that the water of the two glacial lakes began to be recharged in April and reached their peak in August and then remained stable dynamically until they began to shrink in October and were discharged entirely in February of the following year. We observed the expansion process with annual growth rates of 3.19% and 12.63% for these two glacial lakes, respectively, and monitored a glacial lake outburst flood event in July 2018. The validation by comparing with the results derived from Sentinel-2A/B optical images indicates that the accuracy for identifying the boundaries of the glacial lakes with Sentinel-1A SAR images can reach up to 96.49%. Generally, this contribution demonstrates the reliability and precision of SAR images to provide regular updates for the dynamic monitoring of glacial lakes.

Highlights

Over the past decades, climate warming has exacerbated the melting of glaciers in most of High Mountain Asia [1,2,3,4]
We computed the areas of Xiaogongba Glacial Lake (XGL) and Dagongba Glacial Lake of 21 (DGL) derived from each period of synthetic aperture radar (SAR) images, respectively
We developed and showed the use of a simple but effective data processing method for classifying glacial lakes and monitoring their dynamic evolution using time series of SAR images acquired by the Sentinel-1 A satellite for two glacial lakes at the terminus of Gongba Glacier

Summary

Introduction

Climate warming has exacerbated the melting of glaciers in most of High Mountain Asia [1,2,3,4]. The glaciers in the southeastern Tibetan Plateau and its vicinity have been observed with the most negative mass balances [3,4]. Monitoring the dynamic evolution of glacial lakes is essential. Current and accurate mapping of the glacial lakes is the basis for monitoring dynamic evolution and further research. With the emergence of many earth observation satellites, such as the Landsat series and Sentinel-2 A/B constellation, remote sensing technology has been widely used for the inventory and dynamic monitoring of glacial lakes [6,7,8,10,11,12,13]

Methods

Results

Discussion

Conclusion