Analysis on the spectral reflectance response to snow contaminants in Northeast China

doi:10.7523/j.issn.2095-6134.2011.5.007

Abstract

Abstract:

We have analyzed the relationship between the snow spectrum and snow contaminants. It is found that from 350nm to 850nm snow reflectance dramatically decreases with increase in concentrations of contaminants in snow. The results show that snow reflectance at 384nm logarithmically decreases with increase in the snow contaminants while the reflectance at 1495nm exponentially increases with the snow contaminants. Besides, we have selected six bands according to the center wavelength of TM to analyze the relation between snow reflectance and snow contaminants, and we come to the same conclusion as from the hyperspectral analysis. Therefore, this method can be used in combination with TM image to forecast the contaminants in snow.

Key words: hyperspectral remote sensing, snow reflectivity, snow contaminants, TM

CLC Number:

TP753

LEI Xiao-Chun, SONG Kai-Shan, DU Jia, WU Yan-Qing, WANG Yuan-Dong, TANG Xu-Guang, ZENG Li-Hong. Analysis on the spectral reflectance response to snow contaminants in Northeast China[J]. , 2011, 28(5): 611-616.

References

[1] Yan H. Comparison of MODIS and passive microwave snow mappings
[J]. Journal of Glaciology and Geocryology,2005,27(4):515-519(in Chinese). 延昊. 利用MODIS和AMSR-E进行积雪制图的比较分析
[J]. 冰川冻土,2005,27(4):515-519.

[2] Kelly R, Hall D K. Remote sensing of terrestrial snow and Ice for global change studies
[J]. Earth Observation of Global Change, 2008:189-219.

[3] Jiang X. Progress in the research of snow and ice albedo
[J].Journal of Glaciology and Geocryology, 2006, 28(5):728-738(in Chinese). 蒋熹. 冰雪反照率研究进展
[J]. 冰川冻土,2006,28(5):728-738.

[4] Franz T P, Eisenreich S. Snow scavenging of polychlorinated biphenyls and polycyclic aromatic hydrocarbons in Minnesota
[J]. Environ Sci Technol, 1998, 32: 1771-1778.

[5] Cao M S, Feng X Z, Jin D H. Preliminary research on some characteristies of the spectral reflection of snow cover
[J]. Journal of Glaciology and Geocryology,1984,6(3):15-26(in Chinese). 曹梅盛,冯学智,金德洪. 积雪若干光谱反射特征的初步研究
[J]. 冰川冻土,1984,6(3):15-26.

[6] Kay J E, Gillespie A R, Gary B, et al. Spatial relationships between snow contaminant content, grain size, and surface temperature from multispectral images of Mt. Rainier, Washington (USA)
[J]. Remote Sensing of Environment, 2003, 86:216-231.

[7] Jiang T L, Zhao S H, Xiao P F, et al. Spectral analysis of different snow grain sizes based on field measurement
[J].Journal of Glaciology and Geocryology, 2009, 31(2): 227-232(in Chinese). 姜腾龙, 赵书河,肖鹏峰,等. 基于实测数据的不同雪粒径光谱分析
[J]. 冰川冻土,2009,31(2):227-232.

[8] Painter T H, Dozier J, Dar A Roberts, et al. Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data
[J]. Remote Sensing of Environment, 2003 (85):64-77.

[9] Casacchia R, Salvatori R, Cagnati A,et al. Field reflectance of snow/ice covers at Terra Nova Bay, Antarctica
[J]. Remote sensing, 2002, 23(21):4653- 4667.

[10] 赵英时. 遥感应用分析原理与方法
[M]. 北京:科学出版社, 2003:78-79.

[1]	TANG Siqi, HAN Congying, GUO Tiande. Point matching algorithm based on machine learning method [J]. , 2020, 37(4): 450-457.
[2]	ZHANG Zhen, HUANG Qiang, SHENG Xianlei, ZHENG Qingrong. First-principle quantum transport simulations of a fully spin-polarized device TiCl₃/RhCl₃/TiCl₃ [J]. , 2020, 37(4): 458-464.
[3]	LAI Xunfei, LIANG Xuwen, XIE Zhuochen, LI Zongwang. Intrusion detection method based on entity embedding and long short-term memory networks [J]. , 2020, 37(4): 553-561.
[4]	LI Yingrui, XU Jing, LIU Xiang, YI Huiyue. TMRC-Filter: a subband filter design method for Filtered OFDM system [J]. , 2020, 37(1): 120-127.
[5]	SONG Xuming, SHEN Yifei, SHI Yuanming. Intelligent mobile edge network caching based on deep learning [J]. , 2020, 37(1): 128-135.
[6]	WU Changjiang, LEI Liping, ZENG Zhaocheng. Spatio-temporal analysis of differences among atmospheric CO₂ concentrations retrieved from different satellite observations [J]. , 2019, 36(3): 331-337.
[7]	LI Wen, ZHAO Yongchao. The improvement in solar position calculations in the ellipsoid model of the earth [J]. , 2019, 36(3): 363-375.
[8]	ZHANG Shenghu, ZHU Jiayan, ZHANG Sanguo. A powerful procedure for multiple outcomes comparison with covariate adjustment and its application to genomic data [J]. , 2019, 36(2): 155-161.
[9]	REN Jiamin, MA Yanji. Spatial-temporal evolution characteristics of decoupling relationship between industrial growth and industrial atmospheric pollution in Jilin Province [J]. , 2019, 36(1): 72-81.
[10]	WEI Wenfei, LIU Lichao, CHEN Bin, TAN Saichun, SHI Guangyu, XIE Min. Research on bioaerosol and its climate effects [J]. , 2018, 35(3): 320-326.
[11]	DING Zhiyong, GE Yongxiao, ABUDUWAILI Jilili, PU Jia. Trends of extreme temperature and precipitation in Ebinur Lake basin in Xinjiang during the period from 1957 to 2012 [J]. , 2018, 35(2): 160-171.
[12]	SUN Chuan, SONG Xiaoning, ZHOU Fangcheng, LI Zhaoliang. Effects of cloudy atmosphere on microwave signals in channels of AMSR-E [J]. , 2018, 35(1): 42-49.
[13]	WANG Lijuan, WU Dalei, ZHANG Zhisheng. Characterization of typical biomass burning tracers among atmospheric particles in urban Guangzhou [J]. , 2017, 34(5): 567-572.
[14]	YANG Kunhao, XIA Zanyu, HE Peng, WU Li, GONG Lingling, QIAN Yueying, HOU Yanlin, HE Yujian. Correlation of fuel quality and emissions of motor vehicle with atmospheric pollution in Beijing [J]. , 2017, 34(3): 304-317.
[15]	TAO Yuequn, CAI Jun, LIU Bin, HUAI Xiulan. Bubble dynamic analysis and hydroxyl radical production calculation at bubble collapse in turbulence flow [J]. , 2017, 34(2): 191-197.