TY - JOUR
T1 - Towards automated mapping and monitoring of potentially dangerous glacial lakes in Bhutan Himalaya using Sentinel-1 Synthetic Aperture Radar data
AU - Wangchuk, Sonam
AU - Bolch, Tobias
AU - Zawadzki, Jarosław
N1 - Funding Information:
Sonam Wangchuk acknowledges ESKAS – Swiss Government Excellence Scholarships for Foreign Scholars. The Rufford Foundation is thanked for granting permission to use field photograph and information to partially reflect in this paper. We thank the National Centre for Hydrology & Meteorology, Bhutan, for providing the meteorological data. ASTER GDEM is a product of METI and NASA. The study is also supported by the project “Recent and future EVOlution of Glacial LAkes in China (EVOGLAC): Spatio-temporal diversity and hazard potential” funded by the Swiss National Science Foundation (Grant No. IZLCZ2_169979/1) and the Dragon 4 project funded by the European Space Agency (No. 4000121469/17/I-NB). Much appreciation goes to the editor and anonymous reviewers for their constructive comments which helped to improve the manuscript. Benjamin A. Robson and Owen King are thanked for polishing the English.
Funding Information:
This work was supported by the European Space Agency [4000121469/17/I-NB]; Swiss National Science Foundation [IZLCZ2_169979/1]. Sonam Wangchuk acknowledges ESKAS–Swiss Government Excellence Scholarships for Foreign Scholars. The Rufford Foundation is thanked for granting permission to use field photograph and information to partially reflect in this paper. We thank the National Centre for Hydrology & Meteorology, Bhutan, for providing the meteorological data. ASTER GDEM is a product of METI and NASA. The study is also supported by the project “Recent and future EVOlution of Glacial LAkes in China (EVOGLAC): Spatio-temporal diversity and hazard potential” funded by the Swiss National Science Foundation (Grant No. IZLCZ2_169979/1) and the Dragon 4 project funded by the European Space Agency (No. 4000121469/17/I-NB). Much appreciation goes to the editor and anonymous reviewers for their constructive comments which helped to improve the manuscript. Benjamin A. Robson and Owen King are thanked for polishing the English.
Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/6/18
Y1 - 2019/6/18
N2 - The majority of glacial lakes around the world are located in remote and hardly accessible regions. The use of remote sensing data is therefore of high importance to identify and assess their potential hazards. However, the persistence of cloud cover, particularly in high mountain areas such as the Himalayas, limits the temporal resolution of optical satellite data with which we can monitor potentially dangerous glacial lakes (PDGLs). The ability of Synthetic Aperture Radar (SAR) satellites to collect data, irrespective of weather and at day or night, facilitates monitoring of PDGLs by without compromising temporal resolution. In this study, we present a semi-automated approach, based on a radar signal intensity threshold between water and non-water feature classes followed by post-processing including elevations, slopes, vegetation and size thresholds, to delineate glacial lakes in Sentinel-1 SAR images in Bhutan Himalaya. We show the capability of our method to be used for delineating and monitoring glacial lakes in Bhutan Himalaya by comparing our results to 10 m resolution Sentinel-2 multispectral data, field survey data, meteorological data, and a time series of monthly images from January to December 2016 of two lakes. Sentinel-1 SAR data can, moreover, be used for detecting lake surface area changes and open water area variations, at temporal resolution of six days, providing substantial advantages over optical satellite data to continuously monitor PDGLs.
AB - The majority of glacial lakes around the world are located in remote and hardly accessible regions. The use of remote sensing data is therefore of high importance to identify and assess their potential hazards. However, the persistence of cloud cover, particularly in high mountain areas such as the Himalayas, limits the temporal resolution of optical satellite data with which we can monitor potentially dangerous glacial lakes (PDGLs). The ability of Synthetic Aperture Radar (SAR) satellites to collect data, irrespective of weather and at day or night, facilitates monitoring of PDGLs by without compromising temporal resolution. In this study, we present a semi-automated approach, based on a radar signal intensity threshold between water and non-water feature classes followed by post-processing including elevations, slopes, vegetation and size thresholds, to delineate glacial lakes in Sentinel-1 SAR images in Bhutan Himalaya. We show the capability of our method to be used for delineating and monitoring glacial lakes in Bhutan Himalaya by comparing our results to 10 m resolution Sentinel-2 multispectral data, field survey data, meteorological data, and a time series of monthly images from January to December 2016 of two lakes. Sentinel-1 SAR data can, moreover, be used for detecting lake surface area changes and open water area variations, at temporal resolution of six days, providing substantial advantages over optical satellite data to continuously monitor PDGLs.
UR - http://www.scopus.com/inward/record.url?scp=85061607625&partnerID=8YFLogxK
U2 - 10.1080/01431161.2019.1569789
DO - 10.1080/01431161.2019.1569789
M3 - Article
AN - SCOPUS:85061607625
VL - 40
SP - 4642
EP - 4667
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
SN - 0143-1161
IS - 12
ER -