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Water 2018, 10(4), 455; https://doi.org/10.3390/w10040455

Glacial Lake Detection from GaoFen-2 Multispectral Imagery Using an Integrated Nonlocal Active Contour Approach: A Case Study of the Altai Mountains, Northern Xinjiang Province

1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Beijing 100094, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Hainan Key Laboratory of Earth Observation, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Sanya 572029, China
*
Author to whom correspondence should be addressed.
Received: 15 March 2018 / Revised: 4 April 2018 / Accepted: 6 April 2018 / Published: 10 April 2018
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Abstract

Due to recent global climate change, glacial lake outburst floods (GLOFs) have become a serious problem in many high mountain areas. Accurately and rapidly mapping glacial lakes is the basis of other glacial lake studies that are associated with water resources management, flood hazard assessment, and climate change. Most glacial lake detection studies have mainly used medium to coarse resolution images, whose application is limited to large lakes. Because small glacial lakes are abundant and because changes in these lakes are small and occur around the lake shores, fine-resolution satellite imagery is required for adequate assessments. In addition, the existing detection methods are mainly based on simply applying a threshold on various normalized difference water indices (NDWIs); this cannot give appropriate results for glacial lakes that have a wide range of turbidity, mineral, and chlorophyll content. In the present study, we propose a region-dependent framework to overcome the spectral heterogeneity of glacial lake areas using a nonlocal active contour model that is integrated with the NDWI. As the first trial, the glacial lakes were detected using high-resolution GaoFen-2 multispectral imagery in the test site of Altai Mountains (northern Xinjiang Province). The validation of the results was carried out using the manually digitized lake boundaries. The average probabilities of false positives P F P and false negatives P F N were found to be 0.0106 and 0.0039, respectively. After taking into consideration the spectral features of the water and making slight NDWI threshold adjustments, this method can also be used for lake detection in any glaciated environment elsewhere in the world. View Full-Text
Keywords: nonlocal active contour; glacial lakes; Altai Mountains; high resolution; GaoFen-2 nonlocal active contour; glacial lakes; Altai Mountains; high resolution; GaoFen-2
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Zhang, M.; Chen, F.; Tian, B. Glacial Lake Detection from GaoFen-2 Multispectral Imagery Using an Integrated Nonlocal Active Contour Approach: A Case Study of the Altai Mountains, Northern Xinjiang Province. Water 2018, 10, 455.

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