Optimal Threshold Selection for Water Bodies Mapping from Sentinel-L Images Based On Sentinel-2 Water Masks

Kavats, Olena; Khramov, Dmitriy; Sergieieva, Kateryna; Puputti, Julia; Joutsenvaara, Jari; Kotavaara, Ossi

doi:10.1109/igarss46834.2022.9883600

Cited by 2 publications

(2 citation statements)

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“…Based on the idea presented by Uddin et al [39,40] of constructing a SAR water mask corresponding to an optical mask, this study proposes a method for determining the optimal threshold value σ 0 according to the criterion of maximum similarity between optical and SAR masks [59]. The optimum is based on finding the extremum of the quality functional-the maximum of the binary mask-matching criterion:…”

Section: Sar: Proposed Methodsmentioning

confidence: 99%

“…The value of σ 0 is a function of the radar observation parameters: frequency, polarization, the incidence angle of the emitted electromagnetic waves, and the physical (roughness and the area relief) and dielectric properties of the investigated surface [26,56,57]. Sentinel-1 GRD data are preprocessed in the Golden-AI platform according to the following main stages [58,59]:…”

Section: Satellite Datamentioning

confidence: 99%

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Surface Water Mapping from SAR Images Using Optimal Threshold Selection Method and Reference Water Mask

Kavats¹,

Khramov²,

Sergieieva³

2022

Water

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Water resources are an important component of ecosystem services. During long periods of cloudiness and precipitation, when a ground-based sample is not available, the water bodies are detected from satellite SAR (synthetic-aperture radar) data using threshold methods (e.g., Otsu and Kittler–Illingworth). However, such methods do not enable to obtain the correct threshold value for the backscattering coefficient (σ0) of relatively small water areas in the image. The paper proposes and substantiates a method for the mapping of the surface of water bodies, which makes it possible to correctly identify water bodies, even in “water”/“land” class imbalance situations. The method operates on a principle of maximum compliance of the resulting SAR water mask with a given reference water mask. Therefore, the method enables the exploration of the possibilities of searching and choosing the optimal parameters (polarization and speckle filtering), which provide the maximum quality of SAR water mask. The method was applied for mapping natural and industrial water bodies in the Pohjois-Pohjanmaa region (North Ostrobothnia), Finland, using Sentinel-1A and -1B ground range detected (GRD) data (ascending and descending orbits) in 2018–2021. Reference water masks were generated based on optical spectral indices derived from Sentinel-2A and -2B data. The polarization and speckle filtering parameters were chosen since they provide the most accurate σ0 threshold (on average for all observations above 0.9 according to the Intersection over Union criterion) and are resistant to random fluctuations. If a reference water mask is available, the proposed method is more accurate than the Otsu method. Without a reference mask, the σ0 threshold is calculated as an average of thresholds obtained from previous observations. In this case, the proposed method is as good in accuracy as the Otsu method. It is shown that the proposed method enables the identification of surface water bodies under significant class imbalance conditions, such as when the water surface covers only a fraction of a percent of the area under study.

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Section: Sar: Proposed Methodsmentioning

confidence: 99%