Study on the Identification Method of Glacier in Mountain Shadows Based on Landsat 8 OLI Image
JI Xuan1, 2, CHEN Yun-fang3, LUO Xian1, 2, LI Yun-gang1, 2
1. Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650091, China
2. Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Kunming 650091, China
3. Yunnan Normal University,Kunming 650092, China
Abstract:Glaciers are extremely sensitive to climate change. And glacier changes have great impacts on the regional climate, ecology, water resources and so on. Remote sensing images are often used to study glacial changes. For plateau mountainous areas, the images usually have a larger area of the mountain shadows. Shadows cause loss or distraction of the information reflected by the ground target, making remote sensing image difficult to understand. Therefore, the identification of glaciers in the mountain shadow area based on remote sensing images becomes a technical difficulty. In this study, a large mountain glacier on the Qinghai-Tibet Plateau was chosen as experimental subject. Based on Landsat 8 OLI data, this study first analyzed the reflection characteristics of different bands for glacier and non-glacier in shadow area. The results showed that due to the fact that direct light is blocked and target objects in a shadow area are mainly irradiated by the scattered light, the blue band which has shorter wavelength and higher intensity of the scattered light is preferred band for glacier identification in shaded area. For longer wavelength band, the reflectance of ground target in the entire shadow region is very low, and it is difficult to distinguish between glaciers or non-glacial regions. On this basis, a shaded glacier information enhanced index is proposed. Compared with the conventional glacier information extraction methods, the proposed method can give a result to identify the segmentation threshold more clearly in the histogram; and get the best result both in accuracy of the extracted boundary and the total area. For large-scale glacier extractionin the plateau mountainous area, it is recommended to use the proposed method which can be helpful in improving the overall work efficiency.
Key words:Glacier; Landsat8 OLI; Plateau mountainous area; shadow region
季 漩,陈云芳,罗 贤,李运刚. Landsat 8 OLI影像的高原山地阴影区冰川识别方法[J]. 光谱学与光谱分析, 2018, 38(12): 3857-3863.
JI Xuan, CHEN Yun-fang, LUO Xian, LI Yun-gang. Study on the Identification Method of Glacier in Mountain Shadows Based on Landsat 8 OLI Image. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(12): 3857-3863.
[1] Paul F, Bolch T, Kaab A, et al. Remote Sensing of Environment, 2015, 162: 408.
[2] SUN Mei-ping, LIU Shi-yin, YAO Xiao-jun, et al(孙美平,刘时银,姚晓军, 等). Acta Geographica Sinica(地理学报), 2015, 70(9): 1402.
[3] Immerzeel W W, van Beek L P H, Bierkens M F P. Science, 2010, 328(5984):1382.
[4] YAN Li-li, WANG Jian(彦立利, 王 建). Journal of Glaciology and Geocryology(冰川冻土), 2013, 35(1): 110.
[5] ZHONG Zhen-wei, YE Qing-hua(仲振维, 叶庆华). Journal of Glaciology and Geocryology(冰川冻土), 2009, 31(4): 717.
[6] YAN Dong-hai, LI Zhong-qin, GAO Wen-yu, et al(颜东海, 李忠勤, 高闻宇, 等). Arid Zone Research(干旱区研究), 2012, 29(2): 245.
[7] Tielidze L G, Wheate R D. The Cryosphere, 2018, 12:81.
[8] Rastner P, Strozzi T,Paul F. Remote Sensing, 2017, 9:1122.
[9] HUANG Xiao-ran, BAO An-ming, GUO Hao, et al(黄晓然, 包安明, 郭 浩, 等). Arid Zone Research(干旱区研究), 2017, 34(4):870.
[10] Ke L H, Ding X L, Li W K, et al. Remote Sensing, 2017, 9: 114.
[11] NIE Yong, ZHANG Yi-li, LIU Lin-shan,at al(聂 勇, 张镱锂, 刘林山, 等). Acta Geographica Sinica(地理学报),2010, 65(1): 13.
[12] ZHOU Jian-min, LI Zhen, XING Qiang(周建民, 李 震, 邢 强). Journal of Glaciology and Geocryology(冰川冻土),2010, 32(1):28.
[13] HUAI Bao-juan, LI Zhong-qin, SUN Mei-ping, et al(怀保娟, 李忠勤, 孙美平, 等). Arid Zone Research(干旱区研究),2013年, 30(2): 372.
[14] LI Zhi-guo, YAO Tan-dong, YE Qing-hua,et al(李治国, 姚檀栋, 叶庆华, 等). Journal of Glaciology and Geocryology(冰川冻土),2010, 32(4): 650.
[15] XU Ai-wen, YANG Tai-bao, WANG Cong-qiang,et al(许艾文,杨太保,王聪强,等). Progress in Geography(地理科学进展), 2016, 35(7): 878.
[16] Paul F, KaabA, Maisch M, et al. Annals of Glaciology, 2002,34(1): 355.
[17] Shangguan D H, Liu S Y,Ding Y J, et al. Annals of Glaciology, 2006, 43(1): 79.
[18] Lin J H, Fang T, Li D R. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(12):5092.
[19] Du W B, Li J L, Bao A M, et al. Journal of Applied Remote Sensing, 2014, 8(1): 084683.
[20] Lindfors A V, Ylianttila L. Bulletin of the American Meteorological Society, 2016, 97(9): 1561.
[21] Wu S T, Hsieh Y T, Chen C T, et al. Canadian Journal of Remote Sensing, 2014, 40(4): 315.
[22] Gu L, Robles-Kelly A. Pattern Recognition Letters, 2014, 43: 89.