IEEE Geoscience and Remote Sensing Magazine - March 2023 - 98

(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)
FIGURE 2. A time series of satellite data (a)-(e), along with its predicted class labels (f)-(j), to monitor a glacial lake formation over Chitral,
Pakistan. (a) and (f) Lake birth observed on 19 June 2019. (b) and (g) Lake covered with clouds as observed on 23 June 2019. (c), (d), (h), and
(i) Lake size significantly increased as observed on 28 June 2019 [(c) and (h)] and 03 July 2019 [(d) and (i)]. (e) and (j) Lake caused a GLOF and
water has been drained as observed on 08 July 2019.
learning techniques can be used to automatically classify
glacial lakes in remote sensing data. Towards this end, a
glacial lakes inventory covering the entire high mountain
Asia region is used to locate glacial lakes. It contains 30,121
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98
glacial lakes, covering an approximate area of 2,080 km2.
After that, true color (red, green, and blue bands) imagery,
acquired by the Sentinel-2 mission, is collected from
the ESA's Sentinel hub's EO browser, a cloud platform for
visualizing and downloading satellite data. It
provides data every five days with a fine resolution
of 10 m. For preparation of the glacial lakes
detection dataset, nearly 400 cloud-free acquisitions
are used. These data are further processed to
prepare 1,200 crops of size 320 by 320, with each
crop containing at least one lake. Each image is
associated with its binary ground measurements
mask with two classes: lake and no lake. The dataset
contains sufficient training examples of
glacial lakes with different shape, size, and radiometric
signature. For glacial lakes classification,
an encoder-decoder based a convolutional neural
network is used. It is trained on the labeled dataset
for semantic segmentation of true color images.
The performance of the proposed model is
evaluated using an intersection over union (IoU)
score. It classifies glacial lakes accurately with an
IoU score of 79.90%, which is quite good as far as
the complexity of the lake classification problem
is concerned.
We want to thank all of the entrants to this
year's contest! It has been an honor to witness the
work of each of you. Please check the IEEE GRSS
home page regularly-because we will launch the
next competition in 2023 May-and do not miss
the competition opportunity.
GRS
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE MARCH 2023
IMAGE LICENSED BY INGRAM PUBLISHING

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IEEE Geoscience and Remote Sensing Magazine - March 2023

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