Updated on April 20, 2017
Updated on November 22, 2016
March 30, 2012
Japan Aerospace Exploration Agency (JAXA)
Earth Observation Research Center

Description of Glacier and Glacial Lake Inventory of Bhutanusing ALOS (Daichi) Data (Version 17.04)
Abstract
This document aims to develop and publish the glacier and glacial lake inventory in the Bhutan Himalayas using
optical instruments onboard the Advanced Land Observing Satellite (ALOS, nicknamed “Daichi”), which wasoperated from January 2006 to April 2011. The Glacial Lake Outburst Flood (GLOF) is exposing to a risk forpeoples living in downstream regions. A glacial lake inventory was developed using ALOS data under “Study on
GLOFs in the Bhutan Himalayas”*1 project supported by Japan Science and Technology Agency (JST) and Japan
International Cooperation Agency (JICA) under the “Science and Technology Research Partnership for
Sustainable Development (SATREPS)” (Fujita et al., 2012). The field survey has been conducted in 2010 and2011, and the location accuracy of 9.5 m (average) and 11.9 m (RMS) has been achieved at a lake in the inventory.
In addition, a glacier inventory was generated using the same ALOS images to integrate with the lake inventory(Nagai et al. 2016). Integrating them, we are cordially announcing public release of “Glacier and Glacial Lake
Inventory of Bhutan using ALOS Data (Version 17.04)”.
Keywords: Glacial lake inventory, Glacier inventory, ALOS, PRISM, AVNIR-2, DSM
Update on April 20, 2017:
A part of "GLACIER" column in the attribute tables was corrected as follows.
- 2 lakes mistaken number corrected- 2 lakes corrected to no relation to any glacier- 90 lakes corrected to be related to glaciers

1. Introduction
Failures of glacial lake dams terminated by natural moraines can cause outburst floods and represents aserious hazard damages in downstream regions. The development and expansion of glacial lakes issometime saying due to the recent global warming, on the other hand other researchers are saying nocorrelation between them. The fact is peoples living in such regions are exposing to a risk by glacial lake
outburst floods (GLOFs). According to a study coordinated by the International Centre for Integrated
Mountain Development (ICIMOD) there are 44 potentially dangerous glacial lakes in risk of GLOFs inNepal and Bhutan (Mool et al., 2001). However, it may relatively be old and should be update to monitor
existing conditions and re-evaluate a potential of GLOF objectively.
This study aim to develop and publish of new glacier and glacial lake inventory using the Panchromatic
Remote sensing Instrument for Stereo Mapping (PRISM) and the Advanced Visible and Near Infrared
Radiometer type 2 (AVNIR-2) onboard the Advanced Land Observing Satellite (ALOS, nicknamed“Daichi”). ALOS was operated from January 2006 to April 2011 (Shimada et al., 2010).
2. Data processing and status
PRISM has 2.5 m spatial resolution, and performs along-track stereo observation by a forward-, nadir-,and backward-looking radiometer to extract precise Digital Surface Model (DSM) or Digital Elevation
Model (DEM). AVNIR-2 has 10 m resolution by four radiometric bands from visible to near infrared.
Firstly, ortho-rectified image is processed for both of them using own developed software (Takaku andTadono, 2009). The PRISM DSM can be simultaneously generated with ortho image. Secondly,
pan-sharpened image is generated using them to obtain 2.5 m resolution with color composite image.
Thirdly, water bodies are extracted manually using pan-sharpened image. If it is not available yet due tocloud covers in the image, the ortho-rectified AVNIR-2 image is used for this processing instead of it.
Finally, glacial lakes are screened from extracted water bodies based on the following definitions:1Glacial lakes in our definition are bodies of water that lay between the terminus of the mother glacier andthe Little Ice Age moraine. Lakes located within 2 km of the Little Ice Age moraine down-valley are also
included to take into account a possible flooding event with multiple lakes being involved. In addition,
supraglacial lakes on debris- covered glaciers are included. We also set 0.01 km2 as the minimum lakesize considering small lakes contribute a less amount of GLOFs’ risk. More detail of methodology isgiven by Ukita et al. (2011) and Tadono et al. (2012).
Figure 1 show a pan-sharpened mosaic image for the Bhutan Himalayas as of July 2011 with bands 3, 2,
and 1 assigned as red, green, and blue, respectively, and overlaid boundaries of river basins with a redline. The color dots show extracted glacial lakes. The image covers almost the entire state of Bhutan,
except for some cloudy areas. Hence, it can be used not only as a base image for the ALOS period butalso as a reference to other satellite imageries from fine resolution and precise geolocation. Figure 2
shows enlarged image around upper stream of the Mangde Chu basin as example.

Figure 1: Pan-sharpened mosaic image by PRISM and AVNIR-2 in the Bhutan Himalayas as of July 2011 (R, G, B =Band 3, 2, 1 as true color composite). The red lines show boundaries of river basin and the color dots show extracted
glacial lakes in this study.

2Figure 2: Enlarged image around upper stream of the Mangde Chu basin with glacial lake inventory (red polygons).

3. Glacial lake inventory
ALOS-based glacial lake inventory in the Bhutan Himalayas consists of shape file, which includes
mostly follow the ICIMOD convention, ID, coordinates in terms of latitude and longitude of the lake
center, area, and elevation. Each lake has its own ID based on the name of the river basin and latitude andlongitude of the lake center. In addition we provide a cross-reference with respect to the ICIMOD code
whenever available.

Figure 3: Comparison of polygons among our inventory (yellows), ground-based measurement (green) and ICIMOD
inventory (reds) at Metatshota Lake.

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As the validation of our inventory, we conducted the ground-based GPS measurements on Sep. to Oct.
2010 at Metatshota Lake in Mangde Chu basin. Figure 3 shows comparison of polygons among
ALOS-based inventory (yellows), ground-based GPS measurement (green), and ICIMOD inventory(reds) overlaid AVNIR-2 image. Unfortunately, there has not been a synchronous set of clear PRISM andAVNIR-2 images covering the area. Therefore, ALOS-based inventory was used here on AVNIR-2image. In statistically, we confirmed that ALOS-based inventory has 9.5m of averaged error, and 11.9mof root mean square (RMS) error compared with ground-based GPS measurement, which was applied
post processing with base station GPS data and selected 40 points out of about 4,500 points with a nearly
equal spacing (Ukita et al., 2011).
4. Glacier inventory
We manually delineated glaciers and debris-covered areas in PRISM and other satellite imagery (Fig. 4)(Nagai et al. 2016). Our Bhutanese study follows the definition of a glacier proposed by Global Land Ice
Measurements from Space (GLIMS) (Raup and Khalsa, 2007), with the sole exception that we excluded
adjacent snow-covered slopes on which glacier flow is not expected. Glacier outlines were generated as
vector-format polygons traced onto the PRISM images, over which ASTER GDEM2-derived contourlines (20-m interval) were laid using GIS software. Having delineated the outer line, internal bedrockand nunataks were removed from the polygon domain. PRISM data were unavailable for 32 glaciers
located in the northernmost part of the study site, for which AVNIR-2 imagery alone was used.
Delineated outlines smaller than 0.01 km2 in area were removed to minimize the risk of including snow
patches. This study does not delineate rock glaciers because they are not defined as a type of glacier(Raup and Khalsa, 2007). Snow-covered rock walls adjacent to the ice surface were also excluded. Any
detached ice masses located just above a glacier were included in the delineation if ice redistribution wasexpected. Shapes for these features are recorded and registered in the inventory as a single row in theattribute table with contains used ALOS-scene IDs, longitude and latitude of glacier centroids, glacierarea, debris-covered area, and glacier ID. Upon delineation of glacier outlines and debris-covered areas,
outlines were corrected by review of exported glacier polygons into Google Earth, which includes three
dimensional high-resolution satellite images.

Figure 4: Example of manually delineated outlines of glacier and debris-covered area (an edited figure from Nagai et al.,2016).

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5. Public release of “Glacier and Glacial Lake Inventory of Bhutan using ALOS Data”
We are cordially releasing “Glacier and Glacial Lake Inventory of Bhutan using ALOS Data” with freeof charge only for research and education purposes and not in commercial purpose. The motivation forthis release is to support the research community and various domestic and international projects.
When the inventory is used in any publications, please indicate that “The ALOS-based glaciallake inventory was prepared under the international project ‘Study on Glacial Lake Outburst Floodsin the Bhutan Himalayas’ supported by the Japan Science and Technology Agency (JST) and theJapan International Cooperation Agency (JICA)” and send copy of the publication to ZGLOFST@jaxa.jp by e-mail. It is also welcome your valuable comments.
References
Fujita, K., Nishimura, K., Komori, J., Iwata, S., Ukita, J., Tadono, T., and Koike, T. (2012): Outline of
Research Project on Glacial Lake Outburst Floods in the Bhutan Himalayas, Global
Environmental Research, 16(1), 3-12.
Mool, P.K., Bajracharya, S.R., and Joshi, S.P. (2001): Inventory of glaciers, glacial lakes and glacial lake
outburst floods: monitoring and early warning systems in the Hindu Kush–Himalayan region,
International Centre for Integrated Mountain Development.
Nagai, H., Fujita, K., Sakai, A., Nuimura, T., and Tadono, T. (2016): Comparison of multiple glacierinventories with a new inventory derived from high-resolution ALOS imagery in the Bhutan
Himalaya, The Cryosphere, 10, 65-85.
Raup, B. and Khalsa, S. J. S.: GLIMS analysis tutorial. Boulder, CO, University of Colorado, National
Snow and Ice Data Center, 2007.
Shimada, M., Tadono, T., and Rosenqvist, A. (2010): Advanced Land Observing Satellite (ALOS) andMonitoring Global Environmental Change, Proc. the IEEE, 98, 5, 780-799.
Tadono, T., Kawamoto, S., Narama, C., Yamanokuchi, T., Ukita, J., Tomiyama, N., and Yabuki, H.
(2012): Development and Validation of New Glacial Lake Inventory in the Bhutan Himalayas Using
ALOS ‘DAICHI’. Global Environmental Research, 16(1), 31-40.
Takaku, J. and Tadono, T. (2009): PRISM On-Orbit Geometric Calibration and DSM Performance,
Trans. Geoscience and Remote Sensing, IEEE, 47, 12, 4060-4073.
Ukita, J., Narama, C., Tadono, T., Yamanokuchi, T., Tomiyama, N., Kawamoto, S., Abe, C., Uda, T.,
Yabuki, H., Fujita, K., and Nishimura, K. (2011): Glacial Lake Inventory of Bhutan using ALOS,
Part I: Methods and Preliminary Results, Annals of Glaciology, 52(58), 65-71.
*1 The project is a collaborative work of Nagoya University, Rikkyo University, Hokkaido University,
National Research Institute for Earth Science and Disaster Prevention (NIED), Hiroshima Instituteof Technology, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), RemoteSensing Technology Center of Japan (RESTEC), Niigata University, Research Institute for Humanityand Nature (RIHN), Earth System Science Co.,Ltd. (ESS), Hirosaki University, Nihon University,Teikyo Heisei University, Gunma University, Keio University and the Department of Mineral andGeology (DGM) of the Royal Government of Bhutan supported by JST and JICA under “SATREPS”.
Related Links
Japan Aerospace Exploration Agency (JAXA)
http://www.jaxa.jp/index_e.html
ALOS (Daichi) Research and Application Project, JAXA
http://www.eorc.jaxa.jp/ALOS/en/index.htm“Bhutan GLOF Project”, Nagoya University
http://www.cryoscience.net/index_e.html
SATREPS, Japan Science and Technology Agency (JST)
http://www.jst.go.jp/global/english/index.html
http://www.jst.go.jp/global/english/kadai/h2008_bhutan.html
Japan International Cooperation Agency (JICA)
http://www.jica.go.jp/english/index.html
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