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Open AccessArticle

Application of Image Segmentation in Surface Water Extraction of Freshwater Lakes using Radar Data

1
Nelson Institute for Environmental Studies, University of Wisconsin-Madison, Madison, WI 53706, USA
2
Department of Computer Sciences, University of Wisconsin-Madison,Madison, WI 53706, USA
3
Department of Planning and Landscape Architecture, University of Wisconsin-Madison, Madison, WI 53706, USA
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(7), 424; https://doi.org/10.3390/ijgi9070424
Received: 22 May 2020 / Revised: 26 June 2020 / Accepted: 27 June 2020 / Published: 30 June 2020
(This article belongs to the Special Issue Geospatial Advances in Landscape Ecology)
Freshwater lakes supply a large amount of inland water resources to sustain local and regional developments. However, some lake systems depend upon great fluctuation in water surface area. Poyang lake, the largest freshwater lake in China, undergoes dramatic seasonal and interannual variations. Timely monitoring of Poyang lake surface provides essential information on variation of water occurrence for its ecosystem conservation. Application of histogram-based image segmentation in radar imagery has been widely used to detect water surface of lakes. Still, it is challenging to select the optimal threshold. Here, we analyze the advantages and disadvantages of a segmentation algorithm, the Otsu Method, from both mathematical and application perspectives. We implement the Otsu Method and provide reusable scripts to automatically select a threshold for surface water extraction using Sentinel-1 synthetic aperture radar (SAR) imagery on Google Earth Engine, a cloud-based platform that accelerates processing of Sentinel-1 data and auto-threshold computation. The optimal thresholds for each January from 2017 to 2020 are 14 . 88 , 16 . 93 , 16 . 96 and 16 . 87 respectively, and the overall accuracy achieves 92 % after rectification. Furthermore, our study contributes to the update of temporal and spatial variation of Poyang lake, confirming that its surface water area fluctuated annually and tended to shrink both in the center and boundary of the lake on each January from 2017 to 2020.
Keywords: Poyang lake; Otsu method; Google Earth Engine; water occurrence; hydrological dynamics; water area changes Poyang lake; Otsu method; Google Earth Engine; water occurrence; hydrological dynamics; water area changes
MDPI and ACS Style

Zhou, S.; Kan, P.; Silbernagel, J.; Jin, J. Application of Image Segmentation in Surface Water Extraction of Freshwater Lakes using Radar Data. ISPRS Int. J. Geo-Inf. 2020, 9, 424.

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