土壤含水量高光谱遥感定量反演研究进展

doi:10.11924/j.issn.1000-6850.casb15090128

摘要/Abstract

摘要： 高光谱遥感因其光谱信息丰富，在土壤含水量的反演中得到了广泛的应用。通过对土壤含水量遥感监测方法进行了归纳总结，对比分析了微波法、热红外法、光学法和高光谱法监测土壤含水量的优缺点以及适用范围；重点分析总结了土壤含水量高光谱遥感定量方法，简要阐述了统计模型和机理模型反演土壤含水量的研究进展，特别对辐射传输模型和几何光学模型等两个机理模型进行了说明，将近年来国内外学者在基于机理模型的土壤含水量遥感反演研究中获得的成果进行了归纳总结，并提出了存在的问题以及今后的研究方向。

关键词: 木材, 木材, 吸湿, 脱抽提物, 脱木质素, 含水率, 尺寸

Abstract: Hyperspectral remote sensing has been widely used in soil moisture inversion because of abundant spectral information. Through summarizing the remote sensing monitoring methods of soil moisture content, the advantages, disadvantages and scope of application of microwave method, thermal infrared method, optical method and hyperspectral remote sensing method were analyzed, the quantitative method of hyperspectral remote sensing was emphatically analyzed, the research process of statistical model and mechanism model were elaborated, radiated transfer model and geometric optics model were described particularly, the research results of soil moisture content based on the mechanism of remote sensing inversion model in recent years were summarized and the existing problems and future research direction were put forward.

刘影,姚艳敏. 土壤含水量高光谱遥感定量反演研究进展[J]. 中国农学通报, 2016, 32(7): 127-134.

刘影 and . Research Progress of Soil Moisture Quantitative Inversion by Hyperspectral Remote Sensing[J]. Chinese Agricultural Science Bulletin, 2016, 32(7): 127-134.

参考文献

[1] Dobson M, Ulaby F T, Active microwave soil moisture research[J]. IEEE Transactions Remote Sensing of Environment,1986,24(1):23-36.
[2] Oh Y, Sarabandi K, Ulaby F T. An empirical model and an inversion technique for radar scattering from bare soil surface[J]. IEEE Transactions on Geoscience and Remote Sensing,1992,30(2):370-381.
[3] Shi J C, Wang J, Hsu A Y, et al. Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1997,35(5):1254-1266.
[4] Roger D, De R, Yang D. A semi-empirical backscattering model at L-band and C-band for a soybean canopy with soil moisture inversion[J]. IEEE Transactions on Geoscience and Remote Sensing,2001,39(4):864-872.
[5] 鲍艳松,刘良云,王纪华.综合利用光学、微波遥感数据反演土壤湿度研究[J].北京师范大学学报(自然科学版),2007,43(3):228-233.
[6] Njoku E G, Li L. Retrieval of 1and surface parameters using passive microwave measurements at 6-18 GHz[J].IEEE Trans Geoscience Remote Sensing,1999,37(1):79-93.
[7] 乔平林,张继贤,王翠华.基于星载被动微波遥感的地表土壤湿度反演[J]. 辽宁工程技术大学学报, 2005,25(3):342-344.
[8] Jackson T J, Le Vine D M, Hsu A Y, et al. Soil moisture mapping at regional scales using microwave radiometry: The southern great plains hydrology experiment[J].IEEE Trasactions on Geoscience and Remote Sensing,1999,37(5):2136-2151.
[9] 余涛,田国良.热惯量法在监测土壤表层水分变化中的研究[J].遥感学报,1997,1(1):24-31,80.
[10] 吴黎,张有智,解文欢,等.改进的表观热惯量法反演土壤含水量[J].国土资源遥感,2013,25(1):44-49.
[11] 张春桂,李文.福建省干旱灾害卫星遥感监测应用研究[J].气象,2004,30(3):22-24.
[12] 姚春生,张增祥,汪潇.使用温度植被干旱指数法(TVDI)反演新疆土壤湿度[J].遥感技术与应用,2004,19(6):473-478.
[13] 隋洪智,田国良,李付琴.农田蒸散双层模型及其在干旱遥感监测中的应用[J].遥感学报,1997,1(3):220-224.
[14] Galvao L S, Formaggio A R, Couto E G, et al. Relationships between the mineralogical and chemical composition of tropical soils and topography from hyperspectral remote sensing data [J]. ISPRS Journal of Photogrammetry and Remote Sensing,2008,63(2):259-271.
[15] Selige T, Bhner J, Schmidhalter U. High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures[J].Geoderma,2006,136(1/2):235-244.
[16] Gomez C, Rossel R A V, Mc Bratney A B. Soil organic carbon prediction by hyperspectral remote sensing and field VIS-NIR spectroscopy: An Australian case study [J]. Geoderma,2008,146(3/4):403-411.
[17] 张婷婷.基于PLS模型的农业土壤成分高光谱遥感反演研究[D].吉林大学, 2010.
[18] 吴见,刘民士,李伟涛.基于高光谱影像分解的土壤含水量反演技术[J].水土保持通报,2013,(5):156-160.
[19] 魏娜.土壤含水量高光谱遥感监测方法研究[D].中国农业科学院,2009.
[20] 刘伟东,F.Baret,张兵,等.应用高光谱遥感数据估算土壤表层水分的研究(英文)[J].遥感学报, 2004,(5):434-442.
[21] Liu D S, Wang Z S. A modeling study of potential evapotranspiration and the estimation of Chinese soil moisture regimes[J]. Pedosphere,1996,6(3):193-200.
[22] 吉别克?哈力克巴义.基于实测高光谱数据的地表土壤水分含量反演研究[D].新疆大学,2011.
[23] Bowers S A, SMITH S J. Spectrophotometric determination of soil water content [J]. Soil Science Society of America,1972,36: 978- 980.
[24] 朱永豪,邓仁达,卢亚非,等.不同湿度条件下黄棕壤光谱反射率的变化特征及其遥感意义[J].土壤学报,1984,21(2):194-202.
[25] Stoner E R, Baumgardner M F. Characteristic variations in reflectance of surface soils [J]. Soil Science Society,1981,45:1161-1165.
[26] 司海青,姚艳敏,王德营,等. 含水率对土壤有机质含量高光谱估算的影响[J].农业工程学报,2015,31(9):114-120.
[27] Cloutis E. A., Hyperspectral geological remote sensing: evaluation of analytical techniques. [J]. Remote Sensing,1996,17(12):2215-2242.
[28] 何挺. 土地质量高光谱遥感监测方法研究[D].武汉大学,2003.
[29] 王晓. 土壤含水量高光谱特性与估测模型研究[D].山东农业大学,2012.
[30] Bach, M. Mauser, W. Modeling and model verification of the spectral reflectance of soils under varying moisture conditions[J]. Proceedings of IEEE IGARSS’,1994,(4):2354-2356.
[31] 姚艳敏,魏娜,唐鹏钦,等.黑土土壤水分高光谱特征及反演模型[J].农业工程学报,2011,27(8):95-100.
[32] 王昌佐,王纪华,王锦地,等.裸土表层含水量高光谱遥感的最佳波段选择[J].遥感信息,2003,(4):33-36.
[33] Hummel J W, Sudduth K A, Hollinger S E. Soil moisture and organic matter prediction of surface and subsurface soil using an NIR soil sensor[J]. Computer and Electronic in Agriculture, 2001,32(2):149-165.
[34] Sorensen L K, Dalsgaard S. Determination of clay and other soil properties by near infrared spectroscopy[J]. Soil Science society of America Journal, 2005,69(1):159-167.
[35] 沈润平,丁国香,魏国栓,等.基于人工神经网络的土壤有机质含量高光谱反演[J].土壤学报,2009,46(3):391-397
[36] 王静,何挺,李玉环.基于高光谱遥感技术的土地质量信息挖掘研究[J].遥感学报,2005,9(4):438-445.
[37] Hapke B. Bidirectional Reflectance Spectroscopy 1.Theory [J]. Journal of Geophyscial Research,1981,86(84):3039-3054.
[38] Pinty, B., Verstraete, M. M., Dickinson, R. E. A physical model for predicting bidirectional reflectances over bare soil[J]. Remote Sensing of Environment,1989,27:273-288.
[39] Wu, Y. Z., Peng, G., Qiang, L., et al. Retrieving photometric properties of desert surfaces in China using the Hapke model and MISR data[J]. Remote Sensing of Environment,2009,113(1):213-223.
[40] 程街亮,纪文君,周银,等.土壤二向反射特性及水分含量对其影响研究[J].土壤学报,2011,48(2):255-262.
[41] Jacquemoud S, Baret F, Hanocq J F. Modeling spectral and bidrectional soil reflectance [J]. Remote Sensing of Environment,1992:41-123.
[42] Hapke, B. Bidirectional reflectance spectroscopy[J]. Correction for macroscopic roughness. Icarus,1984,59:41-59.
[43] Chappell, A.., Zobeck, T., Brunner, G. Using bi-directional soil spectral reflectance to model soil surface changes induced by rainfall and wind-tunnel abrasion[J]. Remote Sensing of Environment,2006,102(3-4):328-343.
[44] Hapke, B. Bidirectional reflectance spectroscopy. 4. The extinction coefficient and the opposition effect. Icarus,1986,67:264-280.
[45] Pinty, B., Verstraete, M M. Extracting information on surface properties from bidirectional reflectance measurements[J]. Journal of Geophysical Research,1991,96:2865-2874.
[46] 吕云峰,孙仲秋,赵云升.基于野外双向反射信息利用反射模型反演土壤含水量研究[J].光学学报,2015,(3):352-358.
[47] 程街亮.土壤高光谱遥感信息提取与二向反射模型研究[D].浙江大学,2008.
[48] G. J. Yang, C.J. Zhao, W. J. Huang, et al. Extension of the Hapke bidirectional reflectance model to retrieve soil water content[J]. Hydrology and Earth System Sciences,2011,(15):2317-2326.
[49] D Segelstein. The Complex Refractive Index of Water[D]. Kansas City: University of Missouri-Kansas City,1981.
[50] 张仁华,覃汉文.中国北方主要农作物双向反射光谱数据集[M].北京:科学出版社,1991.
[51] Irons, J R., Campbell, G S., Norman, J M., et al. Prediction and measurement of soil bidirectional reflectance[J]. IEEE Transactions on Geoscience and Remote Sensing,1992,30:249-260.