Investigating the potential use of Sentinel-1 data for monitoring wetland water level changes in China’s Momoge National Nature Reserve

Abstract

Background Interferometric Synthetic Aperture Radar (InSAR) has become a promising technique for monitoring wetland water levels. However, its capability in monitoring wetland water level changes with Sentine-1 data has not yet been thoroughly investigated. Methods In this study, we produced a multitemporal Sentinel-1 C-band VV-polarized SAR backscatter images and generated a total of 28 interferometric coherence maps for marsh wetlands of China’s Momoge National Nature Reserve to investigate the interferometric coherence level of Sentinel-1 C-VV data as a function of perpendicular and temporal baseline, water depth, and SAR backscattering intensity. We also selected six interferogram pairs acquired within 24 days for quantitative analysis of the accuracy of water level changes monitored by Sentinel-1 InSAR. The accuracy of water level changes determined through the Sentinel-1 InSAR technique was calibrated by the values of six field water level loggers. Results Our study showed that (1) the coherence was mainly dependent on the temporal baseline and was little affected by the perpendicular baseline for Sentinel-1 C-VV data in marsh wetlands; (2) in the early stage of a growing season, a clear negative correlation was found between Sentinel-1 coherence and water depth; (3) there was an almost linear negative correlation between Sentinel-1 C-VV coherence and backscatter for the marsh wetlands; (4) once the coherence exceeds a threshold of 0.3, the stage during the growing season, rather than the coherence, appeared to be the primary factor determining the quality of the interferogram for the marsh wetlands, even though the quality of the interferogram largely depends on the coherence; (5) the results of water level changes from InSAR processing show no agreement with in-situ measurements during most growth stages. Based on the findings, we can conclude that although the interferometric coherence of the Sentinel-1 C-VV data is high enough, the data is generally unsuitable for monitoring water level changes in marsh wetlands of China’s Momoge National Nature Reserve.

Mapping Wetland Plant Communities Using Unmanned Aerial Vehicle Hyperspectral Imagery by Comparing Object/Pixel-Based Classifications Combining Multiple Machine-Learning Algorithms

“…1). It was established in 1981 and listed in the National Nature Reserves of China in 1997 and the Ramsar site in 2013 [32]. There are 193 recorded bird species, and over 10 species of national class I protected birds in the MNNR.…”

Assessment of Surface Hydrological Connectivity in an Ungauged Multi-Lake System with a Combined Approach Using Geostatistics and Spaceborne SAR Observations

“…The Momoge National Nature Reserve (45 • 42 25 -46 • 18 00 N, 123 • 27 00 -124 • 04 33.7 E) covering an area of 1440 km 2 is located in Zhenlai County, west Jilin Province, Northeast China ( Figure 1). The reserve is known as the main stopover site for rare and endangered migratory birds, such as the Siberian crane (Grus leucogeranus) and oriental white stork (Ciconia ciconia) and was included on the List of Wetlands of International Importance (Ramsar sites) in 2013 [28]. Two large rivers flow through the reserve, the Nenjiang River in the east and the Tao'er River in the south.…”

“…The second latest C-band VV polarized SAR mission, Sentinel-1, was launched in 2014. It provides free SAR datasets with a repeat cycle as short as 6-12 days, a coverage range as wide as 250 km, and a spatial resolution as high as 10 m [28], which can greatly improve the spatial and temporal resolution of hydrological connectivity detection, at least relative to MODIS and Landsat. However, so far, few studies have investigated the potential use of backscattering coefficient information of SAR data (e.g., Sentinel-1) in observing surface hydrological connectivity.…”

Using InSAR to identify hydrological connectivity and barriers in a highly fragmented wetland

“…Wetland InSAR is the use of the InSAR technology to detect changes in elevation of aquatic surfaces. This technique works where vegetation emerges above the water surface due to the double bounce effect in which radar pulse is backscattered twice from the water surface and vegetation (Chen et al, 2020; Richards, Woodgate, & Skidmore, 1987). Since interferogram observations are not absolute but relative in value, absolute changes of water level in wetlands can only be computed when combined with stage monitoring or altimeter observations (Hong & Wdowinski, 2014; Kim et al, 2009).…”

“…A remote sensing technique termed Wetland interferometric synthetic aperture radar (Wetland InSAR; Wdowinski, Amelung, Miralles-Wilhelm, Dixon, & Carande, 2004) is a complementary radar-based tool of high spatial resolution used to monitor surface hydrological processes in wetlands. Water level changes, sheet flow and water flow have been studied in different regions of the world with this methodology (Chen et al, 2020;Hong, Wdowinski, & Kim, 2010;Kim et al, 2014;Lee, Yuan, Jung, & Beighley, 2015;Palomino-Angel, Anaya-Acevedo, Simard, Liao, & Jaramillo, 2019;Xie, Shao, Xu, Wan, & Fang, 2013;Zhou, Bin, & Li, 2009). Wetland InSAR generates maps representing changes in the water surface, over time, from differences in the phase-path length of two satellite acquisitions, taken from the same orbital position, at the same resolution and over the same region.…”