Paper Info
Title
Wetland Surface Water Detection from Multipath SAR Images Using Gaussian Process-Based Temporal Interpolation.
Abstract
Wetlands provide society with a myriad of ecosystem services, such as water storage, food sources, and flood control. The ecosystem services provided by a wetland are largely dependent on its hydrological dynamics. Constant monitoring of the spatial extent of water surfaces and the duration of flooding of a wetland is necessary to understand the impact of drought on the ecosystem services a wetland provides. Synthetic aperture radar (SAR) has the potential to reveal wetland dynamics. Multitemporal SAR image analysis for wetland monitoring has been extensively studied based on the advances of modern SAR missions. Unfortunately, most previous studies utilized monopath SAR images, which result in limited success. Tracking changes in individual wetlands remains a challenging task because several environmental factors, such as wind-roughened water, degrade image quality. In general, the data acquisition frequency is an important factor in time series analysis. We propose a Gaussian process-based temporal interpolation (GPTI) method that enables the synergistic use of SAR images taken from multiple paths. The proposed model is applied to a series of Sentinel-1 images capturing wetlands in Okanogan County, Washington State. Our experimental analysis demonstrates that the multiple path analysis based on the proposed method can extract seasonal changes more accurately than a single path analysis.
Year
DOI
Venue
2020
10.3390/rs12111756
REMOTE SENSING
Keywords
DocType
Volume
Synthetic aperture radar,wetlands,drought,Gaussian process,time series analysis
Journal
12
Issue
Citations 
PageRank 
11
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Yukio Endo101.01
Meghan Halabisky200.68
L Monika Moskal314020.24
Shunichi Koshimura42511.10