土壤星地传感技术现状与发展趋势

doi:10.18306/dlkxjz.2018.01.009

Abstract

Abstract:

Soil as an important study object of physical geography, acts as the essential link between geographical elements such as water, atmosphere, organisms, and so on. Therefore, research on accurate and efficient acquisition of soil information has great significance in the development of modern geography. In this article, the operation principles of various sensors equipped on satellite, aviation, and unmanned aerial vehicle platforms and ground devices for soil information acquisition were introduced. Then the authors summed up the findings on the methods and techniques of rapid acquisition of soil information based on remote sensing and proximal soil sensing and their applications in soil mapping and soil attribute prediction. Applications of soil information acquisition in soil geography were also explained. Finally, this article discussed the prospect of development of remote and proximal soil sensing.

Key words: soil information, remote sensing, proximal soil sensing, soil geography

Zhou SHI, Dongyun XU, Hongfen TENG, Yueming HU, Xianzhang PANG, Ganlin ZHANG. Soil information acquisition based on remote sensing and proximal soil sensing: Current status and prospect[J].PROGRESS IN GEOGRAPHY, 2018, 37(1): 79-92.

Figures/Tables 3

References 122

[1]	陈颂超, 冯来磊, 李硕, 等. 2015. 基于局部加权回归的土壤全氮含量可见-近红外光谱反演[J]. 土壤学报, 52(2): 312-320.
	[Chen S C, Feng L L, Li S, et al.2015. Vis-NIR spectral inversion for prediction of soil total nitrogen content in laboratory based on locally weighted regression[J]. Acta Pedologica Sinica, 52(2): 312-320.]
[2]	崔凡, 刘杰, 吴志远, 等. 2014. 探地雷达功率谱模型在砂壤含水率和紧实度探测中的应用[J]. 农业工程学报, 30(16): 99-105.
	[Cui F, Liu J, Wu Z Y, et al.2014. Application of ground penetrating radar power spectrum model in detection of water content and degrees of compactness in sandy loam[J]. Transactions of the Chinese Society of Agricultural Engineering, 30(16): 99-105.]
[3]	傅伯杰. 2014. 地理学综合研究的途径与方法: 格局与过程耦合[J]. 地理学报, 69(8): 1052-1059. doi: 10.11821/dlxb201408002
	[Fu B J.2014. The integrated studies of geography: Coupling of patterns and processes[J]. Acta Geographica Sinica, 69(8): 1052-1059.] doi: 10.11821/dlxb201408002
[4]	侯晓冬, 郭秀军, 贾永刚, 等. 2008. 基于探地雷达回波信号获取污染土壤中污染物含量的研究进展[J]. 地球物理学进展, 23(3): 962-968.
	[Hou X D, Guo X J, Jia Y G, et al.2008. Progress on detection of contamination content in the contaminated soilbased on ground penetrating radar[J]. Progress in Geophysics, 23(3): 962-968.]
[5]	胡振琪, 陈宝政, 陈星彤. 2005. 应用探地雷达检测复垦土壤的分层结构[J]. 中国矿业, 14(3): 73-75. doi: 10.3969/j.issn.1004-4051.2005.03.020
	[Hu Z Q, Chen B Z, Chen X T.2005. Study on layer structure of rehabilitated soil using ground-penetrating radar[J]. China Mining Magazine, 14(3): 73-75.] doi: 10.3969/j.issn.1004-4051.2005.03.020
[6]	纪文君, 李曦, 李成学, 等. 2012. 基于全谱数据挖掘技术的土壤有机质高光谱预测建模研究[J]. 光谱学与光谱分析, 32(9): 2393-2398, 2408.
	[Ji W J, Li X, Li C X, et al.2012. Using different data mining algorithms to predict soil organic matter based on visible-near infrared spectroscopy[J]. Spectroscopy and Spectral Analysis, 32(9): 2393-2398, 2408.]
[7]	亢庆, 张增祥, 赵晓丽. 2008. 基于遥感技术的干旱区土壤分类研究[J]. 遥感学报, 12(1): 159-167. doi: 10.3321/j.issn:1007-4619.2008.01.021
	[Kang Q, Zhang Z X, Zhao X L.2008. A study of soil classification based on remote sensing in arid area[J]. Journal of Remote Sensing, 12(1): 159-167.] doi: 10.3321/j.issn:1007-4619.2008.01.021
[8]	李洪义, 史舟, 唐惠丽. 2010. 基于三维普通克立格方法的滨海盐土电导率三维空间变异研究[J]. 土壤学报, 47(2): 359-363. doi: 10.11766/trxb200805090222
	[Li H Y, Shi Z, Tang H L.2010. Research on three-dimension spatial variability of soil electrical conductivity of coastal saline land using 3D ordinary kriging method[J]. Acta Pedologica Sinica, 47(2): 359-363.] doi: 10.11766/trxb200805090222
[9]	刘恒柏, 张佳宝, 朱安宁. 2008. 砂壤土中目标物的GPR图像解译及土壤含水量反演[J]. 灌溉排水学报, 27(4): 55-57.
	[Liu H B, Zhang J B, Zhu A N.2008. Ground penetrating radar imagery interpretation of target in sand loamy soil and soil water content inversion[J]. Journal of Irrigation and Drainage, 27(4): 55-57.]
[10]	刘宁, 李新举, 郭斌, 等. 2016. 基于修正介电常数模型的煤矿区复垦土壤压实评价[J]. 水土保持学报, 30(4): 318-322.
	[Liu N, Li X J, Guo B, et al.2016. Compaction evaluation of reclamation soil in coal mining district based on modified dielectric constant model[J]. Journal of Soil and Water Conservation, 30(4): 318-322.]
[11]	冉景, 王德建, 王灿, 等. 2014. 便携式X射线荧光光谱法与原子吸收/原子荧光法测定土壤重金属的对比研究[J]. 光谱学与光谱分析, 34(11): 3113-3118.
	[Ran J, Wang D J, Wang C, et al.2014. Comparison of soil heavy metals determined by AAS/AFS and portable X-ray fluorescence analysis[J]. Spectroscopy and Spectral Analysis, 34(11): 3113-3118.]
[12]	邵芸, 吕远, 董庆, 等. 2002. 含水含盐土壤的微波介电特性分析研究[J]. 遥感学报, 6(6): 416-423. doi: 10.11834/jrs.20020604
	[Shao Y, Lu Y, Dong Q, et al.2002. Study on soil microwave dielectric characteristic as salinity and water content[J]. Journal of Remote Sensing, 6(6): 416-423.] doi: 10.11834/jrs.20020604
[13]	史舟, 等. 2014. 土壤地面高光谱遥感原理与方法[M]. 北京: 科学出版社.
	[Shi Z, et al.2014b. Turang dimian gaoguangpu yaogan yuanli yu fangfa[M]. Beijing, China: Science Press.]
[14]	史舟, 王乾龙, 彭杰, 等. 2014. 中国主要土壤高光谱反射特性分类与有机质光谱预测模型[J]. 中国科学: 地球科学, 44(5): 978-988.
	[Shi Z, Wang Q L, Peng J, et al.2014a. Development of a national VNIR soil-spectral library for soil classification and prediction of organic matter concentrations[J]. Science China Earth Sciences, 57(7): 1671-1680.]
[15]	王人潮, 王深法, 苏海萍. 1985. MSS卫片目视土壤解译与制图技术研究[J]. 科技通报, 1(1): 39-41.
	[Wang R C, Wang S F, Su H P.1985. MSS weipian mushi turang jieyi yu zhitu jishu[J]. Bulletin of Science and Technology, 1(1): 39-41.]
[16]	王瑞燕, 尹涛, 胡盈盈, 等. 2017. 基于低频探地雷达的土壤累积入渗量的探测方法研究[J]. 土壤学报, 54(4): 885-893.
	[Wang R Y, Yin T, Hu Y Y, et al.2017. Method for measurement of soil cumulative infiltration based on low frequency GPR[J]. Acta Pedologica Sinica, 54(4): 885-893.]
[17]	余克强, 赵艳茹, 刘飞, 等. 2017. 应用激光诱导击穿光谱对土壤中多元素同时定量分析[J]. 光谱学与光谱分析, 37(9): 2879-2884.
	[Yu K Q, Zhao Y R, Liu F, et al.2017. Laser-induced breakdown spectroscopy for simultaneous quantitative analysis of multi-elements in soil[J]. Spectroscopy and Spectral Analysis, 37(9): 2879-2884.]
[18]	张甘霖, 史学正, 龚子同. 2008. 中国土壤地理学发展的回顾与展望[J]. 土壤学报, 45(5): 792-801. doi: 10.3321/j.issn:0564-3929.2008.05.005
	[Zhang G L, Shi X Z, Gong Z T.2008. Retrospect and prospect of soil geography in China[J]. Acta Pedologica Sinica, 45(5): 792-801.] doi: 10.3321/j.issn:0564-3929.2008.05.005
[19]	周银, 刘丽雅, 卢艳丽, 等. 2015. 星地多源数据的区域土壤有机质数字制图[J]. 遥感学报, 19(6): 998-1006. doi: 10.11834/jrs.20154257
	[Zhou Y, Liu L Y, Lu Y L, et al.2015. Regional scale mapping of soil organic matter using remote sensing and visible-near infrared spectroscopy[J]. Journal of Remote Sensing, 19(6): 998-1006.] doi: 10.11834/jrs.20154257
[20]	Bartholomeus H, Kooistra L, Stevens A, et al.2011. Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy[J]. International Journal of Applied Earth Observation and Geoinformation, 13(1): 81-88. doi: 10.1016/j.jag.2010.06.009
[21]	Bell D, Menges C, Ahmad W, et al.2001. The application of dielectric retrieval algorithms for mapping soil salinity in a tropical coastal environment using airborne polarimetric SAR[J]. Remote Sensing of Environment, 75(3): 375-384. doi: 10.1016/S0034-4257(00)00180-2
[22]	Bowers S A, Hanks, R J.1965. Reflection of radiant energy from soils[J]. Soil Science, 100(2): 130-138. doi: 10.1097/00010694-196508000-00009
[23]	Brown D J, Shepherd K D, Walsh M G, et al.2006. Global soil characterization with VNIR diffuse reflectance spectroscopy[J]. Geoderma, 132(3-4): 273-290. doi: 10.1016/j.geoderma.2005.04.025
[24]	Bushnell T M.1929. Aerial photography and soil survey[J]. Soil Science Society of America Journal, (2001): 23-28. doi: 10.2136/sssaj1929.036159950B1020010004x
[25]	Chakraborty S, Weindorf D C, Li B, et al.2015. Development of a hybrid proximal sensing method for rapid identification of petroleum contaminated soils[J]. Science of the Total Environment, 514: 399-408. doi: 10.1016/j.scitotenv.2015.01.087 pmid: 25681776
[26]	Chang C W, Laird D A, Mausbach M J, et al.2001. Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties[J]. Soil Science Society of America Journal, 65(2): 480-490. doi: 10.2136/sssaj2001.652480x
[27]	Chappell A, Baldock J, Sanderman J.2016. The global significance of omitting soil erosion from soil organic carbon cycling schemes[J]. Nature Climate Change, 6: 187-191. doi: 10.1038/nclimate2829
[28]	Chen K S, Wu T D, Tsang L, et al.2003. Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method simulations[J]. IEEE Transactions on Geoscience and Remote Sensing, 41(1): 90-101. doi: 10.1109/TGRS.2002.807587
[29]	Christy C D.2008. Real-time measurement of soil attributes using on-the-go near infrared reflectance spectroscopy[J]. Computers and Electronics in Agriculture, 61(1): 10-19. doi: 10.1016/j.compag.2007.02.010
[30]	Ciucci A, Palleschi V, Rastelli S, et al.1996. Trace pollutants analysis in soil by a time-resolved laser-induced breakdown spectroscopy technique[J]. Applied Physics B, 63(2): 185-190. doi: 10.1007/BF01095271
[31]	Colliander A, Fisher J B, Halverson G, et al.2017. Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15[J]. IEEE Geoscience and Remote Sensing Letters, 14(11): 2107-2111. doi: 10.1109/LGRS.2017.2753203
[32]	De Jong E, Ballantyne A K, Cameron D R, et al.1979. Measurement of apparent electrical conductivity of soils by an electromagnetic induction probe to aid salinity surveys[J]. Soil Science Society of America Journal, 43(4): 810-812. doi: 10.2136/sssaj1979.03615995004300040040x
[33]	Doolittle J A, Brevik E C.2014. The use of electromagnetic induction techniques in soils studies[J]. Geoderma, 223-225: 33-45. doi: 10.1016/j.geoderma.2014.01.027
[34]	El Haddad J, Villot-Kadri M, Ismaël A, et al.2013. Artificial neural network for on-site quantitative analysis of soils using laser induced breakdown spectroscopy[J]. Spectrochimica Acta Part B: Atomic Spectroscopy, 79-80: 51-57. doi: 10.1016/j.sab.2012.11.007
[35]	Fung A K, Li Z, Chen K S.1992. Backscattering from a randomly rough dielectric surface[J]. IEEE Transactions on Geoscience and Remote Sensing, 30(2): 356-369. doi: 10.1109/36.134085
[36]	Gogé F, Joffre R, Jolivet C, et al.2012. Optimization criteria in sample selection step of local regression for quantitative analysis of large soil NIRS database[J]. Chemometrics and Intelligent Laboratory Systems, 110(1): 168-176. doi: 10.1016/j.chemolab.2011.11.003
[37]	Goglio P, Grant B B, Smith W N, et al.2014. Impact of management strategies on the global warming potential at the cropping system level[J]. Science of the Total Environment, 490: 921-933. doi: 10.1016/j.scitotenv.2014.05.070 pmid: 24911772
[38]	Goldshleger N, Ben-Dor E, Lugassi R, et al.2010. Soil degradation monitoring by remote sensing: Examples with three degradation processes[J]. Soil Science Society of America Journal, 74(5): 1433-1445. doi: 10.2136/sssaj2009.0351
[39]	Gomez C, Viscarra Rossel R A, McBratney A B.2008. Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: An Australian case study[J]. Geoderma, 146(3-4): 403-411. doi: 10.1016/j.geoderma.2008.06.011
[40]	Grunwald S, McSweeney K, Rooney D J, et al.2001. Soil layer models created with profile cone penetrometer data[J]. Geoderma, 103(1-2): 181-201. doi: 10.1016/S0016-7061(01)00076-3
[41]	Grunwald S, Vasques G M, Rivero R G.2015. Fusion of soil and remote sensing data to model soil properties[J]. Advances in Agronomy, 131: 1-109. doi: 10.1016/bs.agron.2014.12.004
[42]	Guerrero C, Zornoza R, Gómez I, et al.2010. Spiking of NIR regional models using samples from target sites: Effect of model size on prediction accuracy[J]. Geoderma, 158(1-2): 66-77. doi: 10.1016/j.geoderma.2009.12.021
[43]	Hahn C, Gloaguen R.2008. Estimation of soil types by non linear analysis of remote sensing data[J]. Nonlinear Processes in Geophysics, 15(1): 115-126. doi: 10.5194/npg-15-115-2008
[44]	Hengl T, Heuvelink G B M, Kempen B, et al.2015. Mapping soil properties of Africa at 250 m resolution: Random forests significantly improve current predictions[J]. PLoS One, 10(6): e0125814. doi: 10.1371/journal.pone.0125814 pmid: 4482144
[45]	Horta A, Malone B, Stockmann U, et al.2015. Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review[J]. Geoderma, 241-242: 180-209. doi: 10.1016/j.geoderma.2014.11.024
[46]	Hu B F, Chen S C, Hu J, et al.2017. Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution[J]. PLoS One, 12(2): e0172438. doi: 10.1371/journal.pone.0172438 pmid: 5325278
[47]	Huang J, Taghizadeh-Mehrjardi R, Minasny B, et al.2015. Modeling soil salinity along a hillslope in Iran by inversion of EM38 data[J]. Soil Science Society of America Journal, 79(4): 1142-1153. doi: 10.2136/sssaj2014.11.0447
[48]	Huisman J A, Hubbard S S, Redman J D, et al.2003. Measuring soil water content with ground penetrating radar: A review[J]. Vadose Zone Journal, 2(4): 476-491. doi: 10.2136/vzj2003.0476
[49]	Ito A, Wagai R.2017. Global distribution of clay-size minerals on land surface for biogeochemical and climatological studies[J]. Scientific Data, 4: 170103. doi: 10.1038/sdata.2017.103 pmid: 5667577
[50]	Jabbar M, Chen X L.2008. Land degradation due to salinization in arid and semi-arid regions with the aid of geo-information techniques[J]. Geo-spatial Information Science, 11(2): 112-120. doi: 10.1007/s11806-008-0013-z
[51]	Jackson T J, O'neill P E.1987. Salinity effects on the microwave emission of soils[J]. IEEE Transactions on Geoscience and Remote Sensing, GE-25(2): 214-220.
[52]	Ji W, Viscarra Rossel R A, Shi Z.2015. Accounting for the effects of water and the environment on proximally sensed vis-NIR soil spectra and their calibrations[J]. European Journal of Soil Science, 66(3): 555-565. doi: 10.1111/ejss.12239
[53]	Keen B A, Haines W B.1925. Studies in soil cultivation. I. The evolution of a reliable dynamometer technique for use in soil cultivation experiments[J]. The Journal of Agricultural Science, 15(3): 375-386. doi: 10.1017/S002185960000681X
[54]	Kim K R, Kim G, Kim J Y, et al.2014. Kriging interpolation method for laser induced breakdown spectroscopy (LIBS) analysis of Zn in various soils[J]. Journal of Analytical Atomic Spectrometry, 29(1): 76-84. doi: 10.1039/c3ja50233c
[55]	Knadel M, Deng F, Thomsen A, et al.2012. Development of a Danish national Vis-NIR soil spectral library for soil organic carbon determination[C]//Digital soil assessments and beyond: Proceedings of the 5th global workshop on digital soil mapping. Sydney, Australia: CRC Press: 403-408.
[56]	Kristof S J, Baumgardner M F, Johannsen C J.1973. Spectral mapping of soil organic matter[R]. LARS Technical Reports. Purdue, IN: Laboratory for Applications of Remote Sensing: 26.
[57]	Kruse F A, Boardman J W, Huntington J F.2003. Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping[J]. IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1388-1400. doi: 10.1109/TGRS.2003.812908
[58]	Kuang B, Mahmood H S, Quraishi M Z, et al.2012. Sensing soil properties in the laboratory, in situ, and on-line: A Review[J]. Advances in Agronomy, 114: 155-223. doi: 10.1016/B978-0-12-394275-3.00003-1
[59]	Li H Y, Shi Z, Webster R, et al.2013. Mapping the three-dimensional variation of soil salinity in a rice-paddy soil[J]. Geoderma, 195-196: 31-41. doi: 10.1016/j.geoderma.2012.11.005
[60]	Li H Y, Webster R, Shi Z.2015b. Mapping soil salinity in the Yangtze delta: REML and universal kriging (E-BLUP) revisited[J]. Geoderma, 237-238: 71-77. doi: 10.1016/j.geoderma.2014.08.008
[61]	Li S, Shi Z, Chen S C, et al.2015a. In situ measurements of organic carbon in soil profiles using vis-NIR spectroscopy on the Qinghai-Tibet Plateau[J]. Environmental Science & Technology, 49(8): 4980-4987. doi: 10.1021/es504272x pmid: 25828919
[62]	Li Y Y, Zhao K, Zheng X M, et al.2014. Identification of saline-alkali soil based on target decomposition of full-polarization radar data[J]. Journal of Applied Remote Sensing, 8(1): 083511. doi: 10.1117/1.JRS.8.083511
[63]	Liu F, Geng X Y, Zhu A X, et al.2012. Soil texture mapping over low relief areas using land surface feedback dynamic patterns extracted from MODIS[J]. Geoderma, 171-172: 44-52. doi: 10.1016/j.geoderma.2011.05.007
[64]	Liu Y, Pan X Z, Shi R J, et al.2015. Predicting soil salt content over partially vegetated surfaces using non-negative matrix factorization[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(11): 5305-5316. doi: 10.1109/JSTARS.2015.2478490
[65]	Liu Y, Pan X Z, Wang C K, et al.2015. Predicting soil salinity with Vis-NIR spectra after removing the effects of soil moisture using external parameter orthogonalization[J]. PLoS One, 10(10): e0140688. doi: 10.1371/journal.pone.0140688 pmid: 4607364
[66]	Macdonald H C, Waite W P.1971. Soil moisture detection with imaging radars[J]. Water Resources Research, 7(1): 100-110. doi: 10.1029/WR007i001p00100
[67]	Martínez G, Vanderlinden K, Giráldez J V, et al.2010. Field-scale soil moisture pattern mapping using electromagnetic induction[J]. Vadose Zone Journal, 9(4): 871-881. doi: 10.2136/vzj2009.0160
[68]	Melendez-Pastor I, Navarro-Pedreño J, Koch M, et al.2010. Applying imaging spectroscopy techniques to map saline soils with ASTER images[J]. Geoderma, 158(1-2): 55-65. doi: 10.1016/j.geoderma.2010.02.015
[69]	Metternicht G I.1998. Fuzzy classification of JERS-1 SAR data: An evaluation of its performance for soil salinity mapping[J]. Ecological Modelling, 111(1): 61-74. doi: 10.1016/S0304-3800(98)00095-7
[70]	Miller B A, Koszinski S, Wehrhan M, et al.2015. Impact of multi-scale predictor selection for modeling soil properties[J]. Geoderma, 239-240: 97-106. doi: 10.1016/j.geoderma.2014.09.018
[71]	Minasny B, McBratney A B.2016. Digital soil mapping: A brief history and some lessons[J]. Geoderma, 264: 301-311. doi: 10.1016/j.geoderma.2015.07.017
[72]	Minasny B, McBratney A B, Bellon-Maurel V, et al.2011. Removing the effect of soil moisture from NIR diffuse reflectance spectra for the prediction of soil organic carbon[J]. Geoderma, 167-168: 118-124. doi: 10.1016/j.geoderma.2011.09.008
[73]	Minet J, Bogaert P, Vanclooster M, et al.2012. Validation of ground penetrating radar full-waveform inversion for field scale soil moisture mapping[J]. Journal of Hydrology, 424-425: 112-123. doi: 10.1016/j.jhydrol.2011.12.034
[74]	Moore I D, Gessler P E, Nielsen G A, et al.1993. Soil attribute prediction using terrain analysis[J]. Soil Science Society of America Journal, 57(2): 443-452. doi: 10.2136/sssaj1993.03615995005700020026x
[75]	Moran M S, Peters-Lidard C D, Watts J M, et al.2004. Estimating soil moisture at the watershed scale with satellite-based radar and land surface models[J]. Canadian Journal of Remote Sensing, 30(5): 805-826. doi: 10.5589/m04-043
[76]	Mouazen A M, De Baerdemaeker J, Ramon H.2005. Towards development of on-line soil moisture content sensor using a fibre-type NIR spectrophotometer[J]. Soil and Tillage Research, 80(1-2): 171-183. doi: 10.1016/j.still.2004.03.022
[77]	Mulder V L, De Bruin S, Schaepman M E, et al.2011. The use of remote sensing in soil and terrain mapping: A review[J]. Geoderma, 162(1-2): 1-19. doi: 10.1016/j.geoderma.2010.12.018
[78]	Muñoz J D, Kravchenko A.2011. Soil carbon mapping using on-the-go near infrared spectroscopy, topography and aerial photographs[J]. Geoderma, 166(1): 102-110. doi: 10.1016/j.geoderma.2011.07.017
[79]	Nanni M R, Dematte J A M, Chicati M L, et al.2012. Soil surface spectral data from Landsat imagery for soil class discrimination[J]. Acta Scientiarum. Agronomy, 34(1): 103-112. doi: 10.4025/actasciagron.v34i1.12204
[80]	Nocita M, Stevens A, Van Wesemael B, et al.2015. Soil Spectroscopy: An alternative to wet chemistry for soil monitoring[J]. Advances in Agronomy, 132: 139-159. doi: 10.1016/bs.agron.2015.02.002
[81]	Oh Y, Sarabandi K, Ulaby F T.1992. An empirical model and an inversion technique for radar scattering from bare soil surfaces[J]. IEEE transactions on Geoscience and Remote Sensing, 30(2): 370-381. doi: 10.1109/36.134086
[82]	O'Rourke S M, Angers D A, Holden N M, et al.2015. Soil organic carbon across scales[J]. Global Change Biology, 21(10): 3561-3574. doi: 10.1111/gcb.12959 pmid: 25918852
[83]	O'Rourke S M, Stockmann U, Holden N M, et al.2016. An assessment of model averaging to improve predictive power of portable vis-NIR and XRF for the determination of agronomic soil properties[J]. Geoderma, 279: 31-44. doi: 10.1016/j.geoderma.2016.05.005
[84]	Petropoulos G P, Ireland G, Barrett B.2015. Surface soil moisture retrievals from remote sensing: Current status, products & future trends[J]. Physics and Chemistry of the Earth, Parts A/B/C, 83-84: 36-56. doi: 10.1016/j.pce.2015.02.009
[85]	Piles M, Sánchez N, Vall-llossera M, et al.2014. A downscaling approach for SMOS land observations: Evaluation of high-resolution soil moisture maps over the Iberian Peninsula[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(9): 3845-3857. doi: 10.1109/JSTARS.2014.2325398
[86]	Ouerghemmi W, Gomez C, Naceur S, et al.2011. Applying blind source separation on hyperspectral data for clay content estimation over partially vegetated surfaces[J]. Geoderma, 163(3-4): 227-237. doi: 10.1016/j.geoderma.2011.04.019
[87]	Quraishi M Z, Mouazen A M.2013. Calibration of an on-line sensor for measurement of topsoil bulk density in all soil textures[J]. Soil and Tillage Research, 126: 219-228. doi: 10.1016/j.still.2012.08.005
[88]	Ristori G, Bruno V.1969. Metallic microelements of soil determined by X-ray fluorescence[J]. Agrochimica, 13(4-5): 367.
[89]	Scheinost A C, Kretzschmar R, Pfister S, et al.2002. Combining selective sequential extractions, x-ray absorption spectroscopy, and principal component analysis for quantitative zinc speciation in soil[J]. Environmental Science& Technology, 36(23): 5021-5028. doi: 10.1021/es025669f pmid: 12523415
[90]	Scudiero E, Skaggs T H, Corwin D L.2015. Regional-scale soil salinity assessment using Landsat ETM + canopy reflectance[J]. Remote Sensing of Environment, 169: 335-343. doi: 10.1016/j.rse.2015.08.026
[91]	Shanahan P W, Binley A, Whalley W R, et al.2015. The use of electromagnetic induction to monitor changes in soil moisture profiles beneath different wheat genotypes[J]. Soil Science Society of America Journal, 79(2): 459-466. doi: 10.2136/sssaj2014.09.0360
[92]	Shi J C, Guo P, Zhao T J, et al.2014. Soil moisture downscaling algorithm for combining radar and radiometer observations for SMAP mission[C]//Proceedings of the 31th URSI general assembly and scientific symposium (URSI GASS). Beijing, China: IEEE: 1-4.
[93]	Shi J C, Jiang L M, Zhang L X, et al.2005. A parameterized multifrequency-polarization surface emission model[J]. IEEE Transactions on Geoscience and Remote Sensing, 43(12): 2831-2841. doi: 10.1109/TGRS.2005.857902
[94]	Shi J C, Wang J, Hsu A Y, et al.1997. Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data[J]. IEEE Transactions on Geoscience and Remote Sensing, 35(5): 1254-1266. doi: 10.1109/36.628792
[95]	Shi T Z, Liu H Z, Wang J J, et al.2014. Monitoring arsenic contamination in agricultural soils with reflectance spectroscopy of rice plants[J]. Environmental Science & Technology, 48(11): 6264-6272. doi: 10.1021/es405361n pmid: 24804926
[96]	Shonk J L, Gaultney L D, Schulze D G, et al.1991. Spectroscopic sensing of soil organic matter content[J]. Transactions of the ASAE, 34(5): 1978-1984. doi: 10.13031/2013.31826
[97]	Shrestha R P.2006. Relating soil electrical conductivity to remote sensing and other soil properties for assessing soil salinity in northeast Thailand[J]. Land Degradation & Development, 17(6): 677-689. doi: 10.1002/ldr.752
[98]	Skidmore A K, Watford F, Luckananurug P, et al.1996. An operational GIS expert system for mapping forest soils[J]. Photogrammetric Engineering and Remote Sensing, 62(5): 501-511.
[99]	Stenberg B, Viscarra Rossel R A, Mouazen A M, et al.2010. Visible and near infrared spectroscopy in soil science[J]. Advances in Agronomy, 107: 163-215. doi: 10.1016/S0065-2113(10)07005-7
[100]	Stevens A, Nocita M, Tóth G, et al.2013. Prediction of soil organic carbon at the European scale by visible and near infrared reflectance spectroscopy[J]. PLoS One, 8(6): e66409. doi: 10.1371/journal.pone.0066409 pmid: 23840459
[101]	Stevens A, Van Wesemael B, Bartholomeus H, et al.2008. Laboratory, field and airborne spectroscopy for monitoring organic carbon content in agricultural soils[J]. Geoderma, 144(1-2): 395-404. doi: 10.1016/j.geoderma.2007.12.009
[102]	Teng H F, Viscarra Rossel R A, Shi Z, et al.2016. Assimilating satellite imagery and visible-near infrared spectroscopy to model and map soil loss by water erosion in Australia[J]. Environmental Modelling & Software, 77: 156-167. doi: 10.1016/j.envsoft.2015.11.024
[103]	Terra F S, Demattê J A M, Viscarra Rossel R A.2015. Spectral libraries for quantitative analyses of tropical Brazilian soils: Comparing vis-NIR and mid-IR reflectance data[J]. Geoderma, 255-256: 81-93. doi: 10.1016/j.geoderma.2015.04.017
[104]	Tran A P, Bogaert P, Wiaux F, et al.2015. High-resolution space-time quantification of soil moisture along a hillslope using joint analysis of ground penetrating radar and frequency domain reflectometry data[J]. Journal of Hydrology, 523: 252-261. doi: 10.1016/j.jhydrol.2015.01.065
[105]	USDA (United States Department of Agriculture). 2016. Rapid Carbon Assessment (RaCA): Methodology, Sampling, and Summary[EB/OL]. [2018-01-16]. .
[106]	Viscarra Rossel R A, Behrens T.2010. Using data mining to model and interpret soil diffuse reflectance spectra[J]. Geoderma, 158(1-2): 46-54. doi: 10.1016/j.geoderma.2009.12.025
[107]	Viscarra Rossel R A, Behrens T, Ben-Dor E.2016. A global spectral library to characterize the world's soil[J]. Earth-Science Reviews, 155: 198-230. doi: 10.1016/j.earscirev.2016.01.012
[108]	Viscarra Rossel R A, Lobsey C R, Sharman C, et al.2017. Novel proximal sensing for monitoring soil organic C stocks and condition[J]. Environmental Science & Technology, 51(10): 5630-5641. doi: 10.1021/acs.est.7b00889 pmid: 28414454
[109]	Viscarra Rossel R A, McBratney A B.1998. Laboratory evaluation of a proximal sensing technique for simultaneous measurement of soil clay and water content[J]. Geoderma, 85(1): 19-39. doi: 10.1016/S0016-7061(98)00023-8
[110]	Viscarra Rossel R A, Walvoort D J J, McBratney A B, et al.2006. Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties[J]. Geoderma, 131(1-2): 59-75. doi: 10.1016/j.geoderma.2005.03.007
[111]	Viscarra Rossel R A, Webster R.2012. Predicting soil properties from the Australian soil visible-near infrared spectroscopic database[J]. European Journal of Soil Science, 63(6): 848-860. doi: 10.1111/j.1365-2389.2012.01495.x
[112]	Viscarra Rossel R A, Webster R, Bui E N, et al.2014. Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change[J]. Global Change Biology, 20(9): 2953-2970. doi: 10.1111/gcb.12569 pmid: 24599716
[113]	Wang C K, Pan X Z.2016. Improving the prediction of soil organic matter using visible and near infrared spectroscopy of moist samples[J]. Journal of Near Infrared Spectroscopy, 24(3): 231-241. doi: 10.1255/jnirs.1184
[114]	Wang J R, Choudhury B J.1981. Remote sensing of soil moisture content, over bare field at 1.4 GHz frequency[J]. Journal of Geophysical Research: Oceans, 86(C6): 5277-5282. doi: 10.1029/JC086iC06p05277
[115]	Wu C Y, Jacobson A R, Laba M, et al.2009. Alleviating moisture content effects on the visible near-infrared diffuse-reflectance sensing of soils[J]. Soil Science, 174(8): 456-465. doi: 10.1097/SSL.0b013e3181b21491
[116]	Wu Y Z, Chen J, Wu X M, et al.2005. Possibilities of reflectance spectroscopy for the assessment of contaminant elements in suburban soils[J]. Applied Geochemistry, 20(6): 1051-1059. doi: 10.1016/j.apgeochem.2005.01.009
[117]	Xu D Y, Ma W Z, Chen S C, et al.2018. Assessment of important soil properties related to Chinese Soil Taxonomy based on vis-NIR reflectance spectroscopy[J]. Computers and Electronics in Agriculture, 144: 1-8. doi: 10.1016/j.compag.2017.11.029
[118]	Zeng C Y, Zhu A X, Liu F, et al.2017. The impact of rainfall magnitude on the performance of digital soil mapping over low-relief areas using a land surface dynamic feedback method[J]. Ecological Indicators, 72: 297-309. doi: 10.1016/j.ecolind.2016.08.023
[119]	Zhao T J, Shi J C, Bindlish R, et al.2015. Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval[J]. Physics and Chemistry of the Earth, Parts A/B/C, 83-84: 65-74. doi: 10.1109/URSIGASS.2014.6929685
[120]	Zhao Y C, Wang Z G, Sun W X, et al.2010. Spatial interrelations and multi-scale sources of soil heavy metal variability in a typical urban-rural transition area in Yangtze River Delta region of China[J]. Geoderma, 156(3-4): 216-227. doi: 10.1016/j.geoderma.2010.02.020
[121]	Zhou Y, Biswas A, Ma Z Q, et al.2016. Revealing the scale-specific controls of soil organic matter at large scale in Northeast and North China Plain[J]. Geoderma, 271: 71-79. doi: 10.1016/j.geoderma.2016.02.006
[122]	Zhou Y, Guo B, Wang S X, et al.2015. An estimation method of soil wind erosion in Inner Mongolia of China based on geographic information system and remote sensing[J]. Journal of Arid Land, 7(3): 304-317. doi: 10.1007/s40333-015-0122-0

传感器类型	测量指标	平台	传感器设备
光学与辐射型	质地、有机质、CEC、pH,水分、盐分、温度、土壤粗糙度、矿物等	卫星、航空、近地	光学遥感、微波遥感地面光谱仪、探地雷达、激光诱导光谱等
电与电磁型	质地、有机质、盐分、水分等	近地	大地电导率仪、Veris3100、时域反射仪、频谱反射仪
机械式型	紧实度、耐旱力、水分等	近地	指针式土壤紧实度仪
电化学型	pH、硝酸盐、营养元素等	近地	pH计、离子敏感晶体管传感器

Soil information acquisition based on remote sensing and proximal soil sensing: Current status and prospect

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 3

References 122

Related Articles 15

Metrics

Comments

Recommended 0

[1]	SHI Xiao, WANG Guojie, SUN Ming, LI Yvtao, WANG Boni, SHEN Jie. Evaluation of the long-term high-resolution infrared radiation sounder land surface temperature during 1980-2009 in Jiangsu Province, China [J]. PROGRESS IN GEOGRAPHY, 2020, 39(8): 1283-1295.
[2]	LIAO Xiaohan. Advance of geographic sciences and new technology applications [J]. PROGRESS IN GEOGRAPHY, 2020, 39(5): 709-715.
[3]	HU Xu, NIE Yong, XU Xia, JIANG Sheng, ZHANG Yili. Monitoring land-use change in Hetian Tarim Basin, China using satellite remote sensing observation between 1990 and 2016 [J]. PROGRESS IN GEOGRAPHY, 2020, 39(4): 577-590.
[4]	TANG Yin, WANG Zhonggen, WANG Wanqing, HUANG Huojian, YUAN Yong. Multifunctional classification of aquatic habitats for remote sensing data [J]. PROGRESS IN GEOGRAPHY, 2020, 39(3): 454-460.
[5]	JIANG Kaisi,LIU Zhengjia,LI Yurui,WANG Yongsheng,WANG Yu. Land use change of typical villages in the loess hilly and gully region and implications for regional rural transformation and development [J]. PROGRESS IN GEOGRAPHY, 2019, 38(9): 1305-1315.
[6]	DUAN Hongtao,LUO Juhua,CAO Zhigang,XUE Kun,XIAO Qitao,LIU Dong. Progress in remote sensing of aquatic environments at the watershed scale [J]. PROGRESS IN GEOGRAPHY, 2019, 38(8): 1182-1195.
[7]	MA Mingguo,TANG Xuguang,HAN Xujun,SHI Weiyu,SONG Lisheng,HUANG Jing. Research progress and prospect of observation and simulation of carbon cycle in the karst areas of Southwest China [J]. PROGRESS IN GEOGRAPHY, 2019, 38(8): 1196-1205.
[8]	Yingbiao CHEN, Zihao ZHENG, Zhifeng WU, Qinglan QIAN. Review and prospect of application of nighttime light remote sensing data [J]. PROGRESS IN GEOGRAPHY, 2019, 38(2): 205-223.
[9]	WU Qihui, LI Changyou, SUN Biao, SHI Xiaohong, ZHAO Shengnan, HAN Zhiming. Change of ice phenology in the Hulun Lake from 1986 to 2017 [J]. PROGRESS IN GEOGRAPHY, 2019, 38(12): 1933-1943.
[10]	Hongyuan ZHANG, Yanhong WU, Yanjun LIU, Linan GUO. Water storage variation of the Qinghai Lake in recent decades based on satellite observation [J]. PROGRESS IN GEOGRAPHY, 2018, 37(6): 823-832.
[11]	Tianjie ZHAO. Recent advances of L-band application in the passive microwave remote sensing of soil moisture and its prospects [J]. PROGRESS IN GEOGRAPHY, 2018, 37(2): 198-213.
[12]	Guoqing ZHANG. Changes in lakes on the Tibetan Plateau observed from satellite data and their responses to climate variations [J]. PROGRESS IN GEOGRAPHY, 2018, 37(2): 214-223.
[13]	Hui LIN, Hongsheng ZHANG, Yinyi LIN, Shan WEI, Zhifeng WU. Spatiotemporal changes of gridded urban population in the Guangdong-Hong Kong-Macao Greater Bay Area based on impervious surface-population correlation [J]. PROGRESS IN GEOGRAPHY, 2018, 37(12): 1644-1652.
[14]	Xiuling ZUO, Fenzhen SU, Huanting ZHAO, Yue FANG, Juan YANG. Development of a geomorphic classification scheme for coral reefs in the South China Sea based on high-resolution satellite images [J]. PROGRESS IN GEOGRAPHY, 2018, 37(11): 1463-1472.
[15]	Zhen ZHANG, Shiyin LIU, Junfeng WEI, Zongli JIANG. Monitoring a glacier surge in the Kungey Mountain, eastern Pamir Plateau using remote sensing [J]. PROGRESS IN GEOGRAPHY, 2018, 37(11): 1545-1554.