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Hyperspectral Characteristics and Quantitative Remote Sensing Inversion of Gravel Grain Size in the North Tibetan Plateau |
KONG Bo1, YU Huan2*, SONG Wu-jie2, 3, HOU Yu-ting2, XIANG Qing2 |
1. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
2. School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China
3. Unit 61287 of PLA, Chengdu 610036,China
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Abstract As grassland degradation and desertification are becoming more serious in the northern Tibetan plateau, estimating gravel grain size is important for desertification evaluation and dynamic monitoring. Based on hyperspectral remote sensing technology, this paper combines ground survey, GPS positioning, gravel spectroscopy and gravel grain size determination, preferably selecting the waveband with the highest correlation with gravel grain size, and establishes a linear fitting model between gravel grain size and sensitive waveband, and extracts the spatial distribution characteristics of gravel grain size in the experimental area using hyperspectral images of HMS-5. The results show that: the bands with better correlation are at 369.9, 371.5 and 910.5 nm, where the first-order derivative at 910.5 nm has the best fitting effect with gravel grain diameter (R2=0.738); the fitting comparison of different spectral absorption parameters with gravel grain diameter, the fitting accuracy of the fitted regression model established by the absorption area near 2 340 nm and the gravel grain diameter is The fitting accuracy of the fitted regression model is relatively high (R2=0.728); in the inversion of gravel grain size by spatial remote sensing, the accuracy reaches 70%, as well as briefly analyzing the spatial distribution characteristics of gravel grain size, which provides a reference basis for the desertification analysis of the northern Tibetan plateau.
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Received: 2021-09-25
Accepted: 2022-07-08
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Corresponding Authors:
YU Huan
E-mail: yuhuan0622@126.com
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[1] LIU Xing-yuan, FENG Qi-sheng(刘兴元, 冯琦胜). Acta Scientiae Circumstantiae(环境科学学报), 2012, 32(12): 3152.
[2] Hanson C T,Blevins R L. Soil Science Society of America Journal, 1979, 43(4): 819.
[3] Townsend T E. Journal of Geophysical Research: Solid Earth, 1987, 92: 1441.
[4] Maleki M R, Mouazen A M, Ramon H, et al. Biosystems Engineering, 2007,96(3): 427.
[5] TAN Bing-xiang, LI Zeng-yuan, CHEN Er-xue, et al(谭炳香, 李增元, 陈尔学, 等). Remote Sensing Information(遥感信息), 2005, (6): 36.
[6] Singer R B. Journal of Geophysical Research: Solid Earth, 1981, 86(B9): 7967.
[7] Wessman C A, Aber J D,Peterson D L. International Journal of Remote Sensing, 1989, 10(8): 1293.
[8] WANG Jin-nian, ZHENG Lan-fen, TONG Qing-xi(王晋年, 郑兰芬, 童庆禧). National Remote Sensing Bulletin(遥感学报), 1996, (1): 20.
[9] Kruse F A. Spectral Mapping With LANDSAT Thematic Mapper and Imaging Spectroscopy for Precious Metals Exploration. Proceedings of the Seventh Thematic Conference on Remote Sensing for Exploration Geology. Methods, Integration, Solutions, 1989, 17.
[10] Chen H, Tao P, Chen J, et al. Chemometrics and Intelligent Laboratory Systems, 2011, 107(1): 139.
[11] Steinier J, Termonia Y,Deltour J. Analytical Chemistry, 1972, 41(11): 1906.
[12] Wentworth Chester K. The Journal of Geology, 1922, 30(5): 377.
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