<P>The Landsat TM and ETM+ images have been acquired for the long period from the 1980s until the present with the temporal resolution of a 16-day repeat cycle from the visible, near infrared (NIR), short wave infrared (SWIR) and thermal infrare...
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https://www.riss.kr/link?id=A107522119
2016
-
SCI,SCIE,SCOPUS
학술저널
37-46(10쪽)
0
상세조회0
다운로드다국어 초록 (Multilingual Abstract)
<P>The Landsat TM and ETM+ images have been acquired for the long period from the 1980s until the present with the temporal resolution of a 16-day repeat cycle from the visible, near infrared (NIR), short wave infrared (SWIR) and thermal infrare...
<P>The Landsat TM and ETM+ images have been acquired for the long period from the 1980s until the present with the temporal resolution of a 16-day repeat cycle from the visible, near infrared (NIR), short wave infrared (SWIR) and thermal infrared (TIR) bands. The Landsat multi-temporal images have been successfully used to monitor variations of the Earth surface during 27 years. In this paper, we observe the variations of (1) the snow cover area, (2) the snowline height and (3) the land surface temperature (LST) lapse rate at Mt. Kilimanjaro using a total number of 15 Landsat-5 TM and Landsat-7 ETM+ images from June 1984 July 2011. Segmentation of normalized difference snow index (NDSI) images with a threshold of 0.6 is used to extract snow cover. Snowline altitude is then determined by combining the snow cover classification maps with a digital elevation model (DEM). And the LST lapse rate is also calculated from the TIR band in the forest area. The results from this study show that (1) the snow cover area largely decreases from 10.1 km(2) to 2.3 km(2) during about 27 years, which corresponds to a 77.2% reduction, (2) the snowline height rose from 4760 m to 5020 m by about 260 m, and (3) the LST lapse rate shifted from -5.2 degrees C/km to 2.7 degrees C/km. This study demonstrates that multi-temporal Landsat images can be successfully used for the spatiotemporal analysis of long-term snow cover changes. (C) 2016 Elsevier Ltd. All rights reserved.</P>