Hydrological Research Letters 7(3), 73–78 (2013)
Published online in J-STAGE (www.jstage.jst.go.jp/browse/hrl). doi: 10.3178/hrl.7.73

Supplement Information
Supplement Information S1. Mapping of MG&IC
Supplement Figure S1 shows the difference between the number of glacier grid cells
between our results and regions where the glacier inventory is complete in the GLIMS
Glacier Database. As illustrated in Supplement Figure S1, an uptrend means that too few
grid cells are marked as glacier, while a downtrend implies that too many grid cells are somarked. Overall, the error is smallest at the threshold TM4/TM5 of 3.6 compared to othervalues. The error was smallest at the threshold of 3.6 (19.4%), and other thresholds
resulted in more than 20% errors. Hence, glaciers can be best distinguished from othersurface types using the threshold value of 3.6.
Supplement Figure S2 shows that some non-glacier areas at the edge of the image
were identified as glaciers after the threshold TM4/TM5 > 3.6 was applied. Also, someforested areas were identified as glaciers (Supplement Figure S2b). Hence, an additional
threshold of TM3 (DN > 50) was applied to improve glacier mapping, exploiting the very
high reflectivity of ice and snow in the TM3 band. Supplement Figure S2c clearly
indicated that the errors at the edge of the image were removed.
After the two steps mentioned above, we applied a 9×9 pixel average filter toremove misclassification of pixels and noise. In this step, the central grid cell wasidentified as “glacier” when the area of glacier cells accounts for > 40% of thesurrounding 9 × 9 pixels and the area of non-glacier cells represents < 40%. Then,isolated pixels were removed and isolated gaps were filled (Supplement Figure S3). As
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mentioned above, we applied these steps to obtain glacier pixels from all satellite images
automatically. We then used the r.clump command of GRASS GIS to define individualglacier masses by cropping contiguous pixels where defined as glacier pixel. Finally, theedge of the mass of glacier pixels was used to define outlines of glaciers using the r.polycommand of GRASS GIS. Following these steps, the satellite-derived glacier outlines canbe extracted globally, which were stored as vector format.

22Supplement Figures

Supplement Figure S1. Difference between the number of mountain glacier grid cells inthis study and six regions where glacier inventories in the GLIMS Glacier Database arecomplete. British Columbia 1, 2, and 3 denotes satellite data acquired at different dates.

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Supplement Figure S2. Distribution of glaciers in (a) the true color image, (b) thresholdratio image where TM4/TM5 > 3.6 is used, and (c) where TM4/TM5 > 3.6 and additional
threshold in band 3 > 50 are used. The image is located at 128.43° W, 53.31° N.

44Supplement Figure S3. Glacier distribution (grey) in the part of British Columbia region
derived from (a) the GLIMS Glacier Database, (b) before applying 9 × 9 average filter,and (c) after applying a 9×9 average filter.

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Supplement Figure S4. Spatial distribution of MG&IC excluding glaciers in Greenlandand Antarctic. Red color denotes glaciers. Blue boxes show the regions and region
numbers from 1 to 10 are North America, South America, Iceland, Central Europe,Caucasus, High Mountain Asia, New Zealand, Scandinavia, North and East Asia and subAntarctic islands.

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Supplement Figure S5. Area-altitudinal distribution for a glacier in the Alps
(7.061635° E, 45.9195° N).

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