数字土壤制图研究综述与展望

doi:10.18306/dlkxjz.2018.01.008

Abstract

Abstract:

The spatial distribution of soil reflects its formation and development. Digital soil mapping is a new and efficient technique to represent the spatial distribution of soil, which has experienced a rapid development over the last three decades. The theoretical bases are the soil forming factor theory and the first law of geography. Researchers have done significant work on the generation of environmental covariates, soil sampling methods, mapping methods, and production and evaluation of soil maps. The application cases are from small areas to big regions, even at the global scale. Future directions for digital soil mapping include: new techniques for depicting environmental covariates, especially for expressing human activities; efficient use of new data and legacy data; the reconciling of pedometric knowledge and mathematic models; and new computation ways supporting the use of big data.

Key words: spatial distribution of soil, digital soil mapping, environmental covariates, soil-environment relationship

A-Xing ZHU, Lin YANG, Naiqing FAN, Canying ZENG, Ganlin ZHANG. The review and outlook of digital soil mapping[J].PROGRESS IN GEOGRAPHY, 2018, 37(1): 66-78.

References 91

[92]	Qin C Z, Zhu A-X, Qiu W L, et al.2012. Mapping soil organic matter in small low-relief catchments using fuzzy slope position information[J]. Geoderma, 171-172: 64-74. doi: 10.1016/j.geoderma.2011.06.006
[93]	Qin C Z, Zhu A-X, Shi X, et al.2009. Quantification of spatial gradation of slope positions[J]. Geomorphology, 110(3-4): 152-161. doi: 10.1016/j.geomorph.2009.04.003
[94]	Reza Pahlavan Rad M, Toomanian N, Khormali F, et al.2014. Updating soil survey maps using random forest and conditioned Latin hypercube sampling in the loess derived soils of northern Iran[J]. Geoderma, 232-234: 97-106. doi: 10.1016/j.geoderma.2014.04.036
[95]	Rossel R A V, Fouad Y, Walter C.2008. Using a digital camera to measure soil organic carbon and iron contents[J]. Biosystems Engineering, 100(2): 149-159. doi: 10.1016/j.biosystemseng.2008.02.007
[96]	Roudier P, Hewitt A E, Beaudette D E.2012. A conditioned Latin hypercube sampling algorithm incorporating operational constraints[M]//Minasny B, Malone B P, McBratney A B. Digital soil assessments and beyond: Proceedings of the 5th global workshop on digital soil mapping. London, UK: CRC Press, 227-232.
[97]	Russo D.1984. Design of an optimal sampling network for estimating the variogram[J]. Soil Science Society of America Journal, 48(4): 708-716. doi: 10.2136/sssaj1984.03615995004800040054x
[98]	Sacks J, Schiller S.1988. Spatial designs//Gupta S S, Berger J O. Statistical decision theory and related topics IV: Vol. 2. New York: Springer Verlag: 385-399.
[99]	Shi Z, Ji W, Viscarra Rossel R A, et al.2015. Prediction of soil organic matter using a spatially constrained local partial least squares regression and the Chinese vis-NIR spectral library[J]. European Journal of Soil Science, 66(4): 679-687. doi: 10.1111/ejss.12272
[100]	Simbahan G C, Dobermann A.2006. Sampling optimization based on secondary information and its utilization in soil carbon mapping[J]. Geoderma, 133(3-4): 345-362. doi: 10.1016/j.geoderma.2005.07.020
[101]	Song X D, Brus D J, Liu F, et al.2016. Mapping soil organic carbon content by geographically weighted regression: A case study in the Heihe River Basin, China[J]. Geoderma, 261: 11-22. doi: 10.1016/j.geoderma.2015.06.024
[102]	Song X D, Liu F, Ju B, et al.2017. Mapping soil organic carbon stocks of northeastern China using expert knowledge and GIS-based methods[J]. Chinese Geographical Science, 27(4): 516-528. doi: 10.1007/s11769-017-0869-7
[103]	Stein A, Hoogerwerf M, Bouma J.1988. Use of soil-map delineations to improve (co-) kriging of point data on moisture deficits[J]. Geoderma, 43(2-3): 163-177. doi: 10.1016/0016-7061(88)90041-9
[104]	Stoorvogel J J, Bakkenes M, Temme A J A M, et al.2017. S-world: A Global soil map for environmental modelling[J]. Land Degradation & Development, 28(1): 22-33. doi: 10.1002/ldr.2656
[105]	Stumpf F, Schmidt K, Behrens T, et al.2016. Incorporating limited field operability and legacy soil samples in a hypercube sampling design for digital soil mapping[J]. Journal of Plant Nutrition and Soil Science, 179(4): 499-509. doi: 10.1002/jpln.201500313
[1]	邓红眉. 2013. 江汉平原土壤中、小尺度下的空间分异研究[D]. 武汉: 华中师范大学.
	[Deng H M.2013. Study on spatial heterogeneity of soil in mesoscale and small scale in Jianghan Plain[D]. Wuhan, China: Central China Normal University.]
[2]	郭龙, 张海涛, 陈家赢, 等. 2012. 基于协同克里格插值和地理加权回归模型的土壤属性空间预测比较[J]. 土壤学报, 49(5): 1037-1042.
	[Guo L, Zhang H T, Chen J Y, et al.2012. Comparison between Co-Kriging model and geographically weighted regression model in spatial prediction of soil attributes[J]. Acta Pedologica Sinica, 49(5): 1037-1042.]
[106]	Tobler W R.1970. A computer movie simulating urban growth in the Detroit region[J]. Economic Geography, 46(S1): 234-240. doi: 10.2307/143141
[107]	Trochim W M K. 2006. The qualitative debate: Research methods knowledge base[R/OL]. New York, NY: Cornell University, .
[3]	韩宗伟, 黄魏, 张春弟, 等. 2014. 基于土壤养分—景观关系的土壤采样布局合理性研究[J]. 华中农业大学学报, 33(1): 56-61.
	[Han Z W, Huang W, Zhang C D, et al.2014. Rationality of sampling strategies based on soil-landscape relationships[J]. Journal of Huazhong Agricultural University, 33(1): 56-61.]
[108]	van Groenigen J W, Stein A.1998. Constrained optimization of spatial sampling using continuous simulated annealing[J]. Journal of Environmental Quality, 27: 1078-1086. doi: 10.2134/jeq1998.00472425002700050013x
[109]	Wang D C, Zhang G L, Pan X Z, et al.2012. Mapping soil texture of a plain area using fuzzy-c-means clustering method based on land surface diurnal temperature difference[J]. Pedosphere, 22(3): 394-403. doi: 10.1016/S1002-0160(12)60025-3
[4]	黄魏, 罗云, 汪善勤, 等. 2016. 基于传统土壤图的土壤—环境关系获取及推理制图研究[J]. 土壤学报, 53(1): 72-80. doi: 10.11766/trxb201503260023
	[Huang W, Luo Y, Wang S Q, et al.2016. Knowledge of soil-landscape model obtain from a soil map and mapping[J]. Acta Pedologica Sinica, 53(1): 72-80.] doi: 10.11766/trxb201503260023
[110]	Wang J F, Li L F, Christakos G.2009. Sampling and kriging spatial means: Efficiency and conditions[J]. Sensors, 9(7): 5224-5240. doi: 10.3390/s90705224 pmid: 22346694
[111]	Wang J F, Robert H, Liu T J, et al.2013. Sandwich estimation for multi-unit reporting on a stratified heterogeneous surface[J]. Environment and Planning A, 45(10): 2515-2534. doi: 10.1068/a44710
[112]	Wang K, Zhang C R, Li W D.2013. Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging[J]. Applied Geography, 42: 73-85. doi: 10.1016/j.apgeog.2013.04.002
[113]	Warrick A W, Myers D E.1987. Optimization of sampling locations for variogram calculations[J]. Water Resources Research, 23(3): 496-500. doi: 10.1029/WR023i003p00496
[5]	李天杰, 赵烨, 张科利, 等. 2004. 土壤地理学[M]. 3版. 北京: 高等教育出版社.
	[Li T J, Zhao Y, Zhang K L, et al.2004. Turang dilixue[M]. 3rd ed. Beijing, China: Higher Edudation Press.]
[6]	刘峰, 朱阿兴, 李宝林, 等. 2009. 利用陆面反馈动态模式来识别土壤类型的空间差异[J]. 土壤通报, 40(3): 501-508.
[114]	Webster R.1977. Quantitative and numerical methods in soil classification and survey[M]. Oxford, England: Oxford University Press.
[115]	Webster R, Oliver M A.1990. Statistical methods in soil and land resource survey[M]. Oxford, England: Oxford University Press.
[6]	[Liu F, Zhu A X, Li B L, et al.2009. Identification of spatial difference of soil types using land surface feedback dynamic patterns[J]. Chinese Journal of Soil Science, 40(3): 501-508.]
[7]	刘京, 朱阿兴, 张淑杰, 等. 2013. 基于样点个体代表性的大尺度土壤属性制图方法[J]. 土壤学报, 50(1): 12-20.
[116]	Webster R, Oliver M A.1992. Sample adequately to estimate variograms of soil properties[J]. European Journal of Soil Science, 43(1): 177-192. doi: 10.1111/j.1365-2389.1992.tb00128.x
[117]	Wilding L P, Jones R B, Schafer G M.1965. Variation of soil morphological properties within miami, Celina, and Crosby mapping units in West-Central Ohio[J]. Soil Science Society of America Journal, 29(6): 711-717. doi: 10.2136/sssaj1965.03615995002900060033x
[7]	[Liu J, Zhu A X, Zhang S J, et al.2013. Large-scaled soil attribute mapping method based on individual representativeness of sample sites[J]. Acta Pedologica Sinica, 50(1): 12-20.]
[8]	秦承志, 卢岩君, 邱维理, 等. 2010. 模糊坡位信息在精细土壤属性空间推测中的应用[J]. 地理研究, 29(9): 1706-1714. doi: 10.11821/yj2010090016
[118]	Yang L, Brus D J, Zhu A X, et al.2018. Accounting for access costs in validation of soil maps: A comparison of design-based sampling strategies[J]. Geoderma, 315: 160-169. doi: 10.1016/j.geoderma.2017.11.028
[119]	Yang L, Jiao Y, Fahmy S, et al.2011. Updating conventional soil maps through digital soil mapping[J]. Soil Science Society of America Journal, 75(3): 1044-1053. doi: 10.2136/sssaj2010.0002
[8]	[Qin C Z, Lu Y J, Qiu W L, et al.2010. Application of fuzzy slope positions in predicting spatial distribution of soil property at finer scale[J]. Geographical Research, 29(9): 1706-1714.] doi: 10.11821/yj2010090016
[9]	瞿明凯, 李卫东, 张传荣, 等. 2014. 地理加权回归及其在土壤和环境科学上的应用前景[J]. 土壤, 46(1): 15-22.
	[Qu M K, Li W D, Zhang C R.2014. Geographically weighted regression and its application prospect in soil and environmental sciences[J]. Soils, 46(1): 15-22.]
[10]	史舟, 郭燕, 金希, 等. 2011. 土壤近地传感器研究进展[J]. 土壤学报, 48(6): 1274-1281.
[120]	Yang L, Qi F, Zhu A X, et al.2016. Evaluation of integrative hierarchical stepwise sampling for digital soil mapping[J]. Soil Science Society of America Journal, 80(3): 637-651. doi: 10.2136/sssaj2015.08.0285
[121]	Yang L, Zhu A X, Qi F, et al.2013. An integrative hierarchical stepwise sampling strategy for spatial sampling and its application in digital soil mapping[J]. International Journal of Geographical Information Science, 27(1): 1-23. doi: 10.1080/13658816.2012.658053
[10]	[Shi Z, Guo Y, Jin X, et al.2011. Advancement in study on proximal soil sensing[J]. Acta Pedologica Sinica, 48(6): 1274-1281.]
[11]	宋敏, 杨琳, 朱阿兴, 等. 2017. 轮作模式在农耕区土壤有机质推测制图中的应用[J]. 土壤通报, 48(4): 778-785.
[122]	Yang Q Y, Luo W Q, Jiang Z C, et al.2016. Improve the prediction of soil bulk density by cokriging with predicted soil water content as auxiliary variable[J]. Journal of Soils and Sediments, 16(1): 77-84. doi: 10.1007/s11368-015-1193-4
[123]	Zeng C Y, Yang L, Zhu A X, et al.2016. Mapping soil organic matter concentration at different scales using a mixed geographically weighted regression method[J]. Geoderma, 281: 69-82. doi: 10.1016/j.geoderma.2016.06.033
[11]	[Song M, Yang L, Zhu A X, et al.2017. Mapping soil organic matter in farming areas with crop rotation[J]. Chinese Journal of Soil Science, 48(4): 778-785.]
[12]	王会肖, 张超. 2007. 利用MATLAB研究土壤水分空间变异初探[J]. 中国生态农业学报, 15(1): 127-130.
[124]	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
[125]	Zhang C S, Tang Y, Xu X L, et al.2011. Towards spatial geochemical modelling: Use of geographically weighted regression for mapping soil organic carbon contents in Ireland[J]. Applied Geochemistry, 26(7): 1239-1248. doi: 10.1016/j.apgeochem.2011.04.014
[126]	Zhang S J, Zhu A X, Liu J, et al.2016. An heuristic uncertainty directed field sampling design for digital soil mapping[J]. Geoderma, 267: 123-136. doi: 10.1016/j.geoderma.2015.12.009
[127]	Zhao M S, Rossiter D G, Li D C, et al.2014. Mapping soil organic matter in low-relief areas based on land surface diurnal temperature difference and a vegetation index[J]. Ecological Indicators, 39: 120-133. doi: 10.1016/j.ecolind.2013.12.015
[12]	[Wang H X, Zhang C.2007. Studies on spatial variability of soil water with Matlab[J]. Chinese Journal of Eco-Agriculture, 15(1): 127-130.]
[13]	王劲峰, 姜成晟, 李连发, 等. 2009. 空间抽样与统计推断[M]. 北京: 科学出版社.
[128]	Zhu A X.1997. A similarity model for representing soil spatial information[J]. Geoderma, 77(2-4): 217-242. doi: 10.1016/S0016-7061(97)00023-2
[129]	Zhu A X.2000. Mapping soil landscape as spatial continua: the neural network approach[J]. Water Resources Research, 36(3): 663-677. doi: 10.1029/1999WR900315
[13]	[Wang J F, Jiang C S, Li L F, et al.2009. Kongjian chouyang yu tongji tuiduan[M]. Beijing, China: Science Press.]
[14]	杨琳. 2006. 基于模糊c均值聚类提取土壤—环境系知识的方法研究[D]. 北京:北京师范大学.
[130]	Zhu A X, Band L E.1994. A knowledge-based approach to data integration for soil mapping[J]. Canadian Journal of Remote Sensing, 20(4): 408-418. doi: 10.1080/07038992.1994.10874583
[131]	Zhu A X, Band L, Vertessy R, et al.1997. Derivation of soil properties using a soil land inference model (SoLIM)[J]. Soil Science Society of America Journal, 61(2): 523-533. doi: 10.2136/sssaj1997.03615995006100020022x
[14]	[Yang L.2006. Jiyu mohu c junzhi julei tiqu turang: Huanjingxi zhishi de fangfa yanjiu[D]. Beijing, China: Beijing Normal University.]
[15]	杨琳. 2009. 目的性采样下样本设计与制图精度的关系研究: 以数字土壤制图为例[D]. 北京: 中国科学院地理科学与资源研究所.
[132]	Zhu A X, Hudson B, Burt J E, et al.2001. Soil mapping using GIS, expert knowledge, and fuzzy logic[J]. Soil Science Society of America Journal, 65(5): 1463-1472. doi: 10.2136/sssaj2001.6551463x
[133]	Zhu A X, Liu F, Li B L, et al.2010. Differentiation of soil conditions over low relief areas using feedback dynamic patterns[J]. Soil Science Society of America Journal, 74(3): 861-869. doi: 10.2136/sssaj2008.0411
[15]	[Yang L.2009. Mudexing caiyang xia yangben sheji yu zhitu jingdu de guanxi yanjiu: Yi shuzi turang zhitu weili[D]. Beijing, China: Institute of Geographical Sciences and Natural Resources Research, CAS.]
[16]	杨琳, 朱阿兴, 秦承志, 等. 2010. 基于典型点的目的性采样设计方法及其在土壤制图中的应用[J]. 地理科学进展, 29(3): 279-286. doi: 10.11820/dlkxjz.2010.03.004
	[Yang L, Zhu A X, Qin C Z, et al.2010. A purposive sampling design method based on typical points and its application in soil mapping[J]. Progress in Geography, 29(3): 279-286.] doi: 10.11820/dlkxjz.2010.03.004
[17]	杨琳, 朱阿兴, 秦承志, 等. 2011. 一种基于样点代表性等级的土壤采样设计方法[J]. 土壤学报, 48(5): 938-946.
[134]	Zhu A X, Liu J, Du F, et al.2015. Predictive soil mapping with limited sample data[J]. European Journal of Soil Science, 66(3): 535-547. doi: 10.1111/ejss.12244
[135]	Zhu A X, Yang L, English E, et al.2008. Purposive sampling for digital soil mapping under fuzzy logic[C]//Proceedings of 2007 International Annual Meeting. New Orleans, Louisiana: ASA.
[17]	[Yang L, Zhu A X, Qin C Z, et al.2011. A soil sampling method based on representativeness grade of sampling points[J]. Acta Pedologica Sinica, 48(5): 938-946.]
[18]	杨奇勇, 杨劲松, 刘广明. 2011. 土壤速效养分空间变异的尺度效应[J]. 应用生态学报, 22(2): 431-436.
	[Yang Q Y, Yang J S, Liu G M.2011. Scale-dependency of spatial variability of soil available nutrients[J]. Chinese Journal of Applied Ecology, 22(2): 431-436.]
[19]	张黎明, 林金石, 史学正, 等. 2011. 中国水稻土氮密度变异性的幅度效应研究[J]. 生态环境学报, 20(1): 1-6. doi: 10.3969/j.issn.1674-5906.2011.01.001
	[Zhang L M, Lin J S, Shi X Z, et al.2011. The effect of different extents on variation of nitrogen density of paddy soils in China[J]. Ecology and Environmental Sciences, 20(1): 1-6.] doi: 10.3969/j.issn.1674-5906.2011.01.001
[20]	朱阿兴, 李宝林, 裴韬, 等. 2008. 精细数字土壤普查模型与方法[M]. 北京: 科学出版社.
	[Zhu A X, Li B L, Pei T, et al.2008. Jingxi shuzi turang pucha moxing yu fangfa[M]. Beijing, China: Science Press.]
[21]	朱鹤健, 陈健飞, 陈松林, 等. 2010. 土壤地理学[M]. 2版. 北京: 高等教育出版社.
	[Zhu H J, Chen J F, Chen S L, et al.2010. Turang dilixue[M]. 2nd ed. Beijing, China: Higher Education Press.]
[22]	Behrens T, Schmidt K, Ramirez-Lopez L, et al.2014. Hyper-scale digital soil mapping and soil formation analysis[J]. Geoderma, 213: 578-588. doi: 10.1016/j.geoderma.2013.07.031
[23]	Bell J C, Cunningham R L, Havens M W.1992. Calibration and validation of a soil-landscape model for predicting soil drainage class[J]. Soil Science Society of America Journal, 56(6): 1860-1866. doi: 10.2136/sssaj1992.03615995005600060035x
[24]	Bell J C, Cunningham R L, Havens M W.1994. Soil drainage class probability mapping using a soil-landscape model[J]. Soil Science Society of America Journal, 58(2): 464-470. doi: 10.2136/sssaj1994.03615995005800020031x
[25]	Besson A, Cousin I, Richard G, et al.2010. Changes in field soil water tracked by electrical resistivity[M]//Viscarra Rossel R A, McBratney A B, Minasny B. Proximal soil sensing. Dordrecht, Netherlands: Springer.
[26]	Bezdek J C.1981. Cluster validity[M]//Bezdek J C. Pattern recognition with fuzzy objective function algorithms. Boston, MA: Springer.
[27]	Bishop T F A, McBratney A B, Laslett G M.1999. Modelling soil attribute depth functions with equal-area quadratic smoothing splines[J]. Geoderma, 91(1-2): 27-45. doi: 10.1016/S0016-7061(99)00003-8
[28]	Blaszczynski J S.1997. Landform characterization with geographic information systems[J]. Photogrammetric Engineering and Remote Sensing, 53(2): 183-191. doi: 10.1016/S0031-0182(97)81130-3
[29]	Boettinger J L.2010. Environmental covariates for digital soil mapping in the Western USA[M]//Boettinger J L, Howell D W, Moore A C, et al. Digital soil mapping: Bridging research, environmental application, and operation. Dordrecht, Netherlands: Springer.
[30]	Brus D J.1994. Improving design-based estimation of spatial means by soil map stratification: A case study of phosphate saturation[J]. Geoderma, 62(1-3): 33-246. doi: 10.1016/0016-7061(94)90038-8
[31]	Brus D J, Bogaert P, Heuvelink G B M.2008. Bayesian maximum entropy prediction of soil categories using a traditional soil map as soft information[J]. European Journal of Soil Science, 59(2): 166-177. doi: 10.1111/j.1365-2389.2007.00981.x
[32]	Brus D J, Heuvelink G B M.2007. Optimization of sample patterns for universal kriging of environmental variables[J]. Geoderma, 138(1-2): 86-95. doi: 10.1016/j.geoderma.2006.10.016
[33]	Brus D J, Kempen B, Heuvelink G B M.2011. Sampling for validation of digital soil maps[J]. European Journal of Soil Science, 62(3): 394-407. doi: 10.1111/j.1365-2389.2011.01364.x
[34]	Burgess T M, Webste R.1980. Optimal interpolation and isarithmic mapping of soil properties[J]. Journal of Soil Science, 31(2): 333-341. doi: 10.1111/j.1365-2389.1980.tb02085.x
[35]	Burrough P A, 1989. Fuzzy mathematical methods for soil survey and land evaluation[J]. European Journal of Soil Science, 40(3): 477-492. doi: 10.1111/j.1365-2389.1989.tb01290.x
[36]	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
[37]	Clifford D, Payne J E, Pringle M J, et al.2014. Pragmatic soil survey design using flexible Latin hypercube sampling[J]. Computers & Geosciences, 67: 62-68. doi: 10.1016/j.cageo.2014.03.005
[38]	Davies B E, Gamm S A.1970. Trend surface analysis applied to soil reaction values from Kent, England[J]. Geoderma, 3(3): 223-231. doi: 10.1016/0016-7061(70)90022-4
[39]	de Gruijter J J, Bierkens M F P, Brus D J, et al.2006. Sampling for natural resource monitoring[M]. Berlin, Germany: Springer-Verlag: 331.
[40]	Dobos E, Montanarella L, Nègre T, et al.2001. A regional scale soil mapping approach using integrated AVHRR and DEM data[J]. International Journal of Applied Earth Observation and Geoinformation, 3(1): 30-42. doi: 10.1016/S0303-2434(01)85019-4
[41]	Dunn J C.1973. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters[J]. Journal of Cybernetics, 3(3): 32-57. doi: 10.1080/01969727308546046
[42]	Fayyad U, Piatetsky-Shapiro G, Smyth P.1996. From data mining to knowledge discovery in databases[M]//Piatetsky-Shapiro G. Advances in knowledge discovery and data mining. Menlo Park: AAAI Press, 37.
[43]	Gao B B, Pan Y C, Chen Z Y, et al.2016. A spatial conditioned Latin hypercube sampling method for mapping using ancillary data[J]. Transactions in GIS, 2016, 20(5): 735-754. doi: 10.1111/tgis.12176. doi: 10.1111/tgis.12176
[44]	Godinho Silva S H, Owens P R, De Menezes M D, et al.2014. A technique for low cost soil mapping and validation using expert knowledge on a watershed in Minas Gerais, Brazil[J]. Soil Science Society of America Journal, 78(4): 1310-1319. doi: 10.2136/sssaj2013.09.0382
[45]	Godinho Silva S H, Owens P R, Silva B M, et al.2015. Evaluation of conditioned Latin hypercube sampling as a support for soil mapping and spatial variability of soil properties[J]. Soil Science Society of America Journal, 79(2): 603-611. doi: 10.2136/sssaj2014.07.0299
[46]	Goovaerts P.1999. Geostatistics in soil science: State-of-the-art and perspectives[J]. Geoderma, 89(1-2): 1-45. doi: 10.1016/S0016-7061(98)00078-0
[47]	Goulard M, Voltz M.1992. Linear coregionalization model: Tools for estimation and choice of cross-variogram matrix[J]. Mathematical Geology, 24(3): 269-286. doi: 10.1007/BF00893750
[48]	Gray J M, Bishop T F A, Wilford J R.2016. Lithology and soil relationships for soil modelling and mapping[J]. CATENA, 147: 429-440. doi: 10.1016/j.catena.2016.07.045
[49]	Grimm R, Behrens T, Märker M, et al.2008. Soil organic carbon concentrations and stocks on Barro Colorado Island: Digital soil mapping using Random Forests analysis[J]. Geoderma, 146(1-2): 102-113. doi: 10.1016/j.geoderma.2008.05.008
[50]	Guo S X, Meng L K, Zhu A-X, et al.2015. Data-gap filling to understand the dynamic feedback pattern of soil[J]. Remote Sensing, 7(9): 11801-11820. doi: 10.3390/rs70911801
[51]	Guo S X, Zhu A-X, Meng L K, et al.2016. Unification of soil feedback patterns under different evaporation conditions to improve soil differentiation over flat area[J]. International Journal of Applied Earth Observation and Geoinformation, 49: 126-137. doi: 10.1016/j.jag.2016.02.002
[52]	Hallema D W, Lafond J A, Périard Y, et al.2015. Long-term effects of peatland cultivation on soil physical and hydraulic properties: Case study in Canada[J]. Vadose Zone Journal, 14(6): 1-12. doi: 10.2136/.vzj14.10.0147
[53]	Hengl T, de Jesus J M, Heuvelink G B M, et al.2017. SoilGrids250m: Global gridded soil information based on machine learning[J]. PLoS One, 12(2): e0169748, doi: 10.1371/journal.pone.0169748. doi: 10.1371/journal.pone.0169748 pmid: 5313206
[54]	Hengl T, de Jesus J M, MacMillan R A, et al.2014. SoilGrids1km: Global soil information based on automated mapping[J]. PLoS One, 9(8): e105992. doi: 10.1371/journal.pone.0105992
[55]	Hengl T, Gruber S, Shrestha D P.2004. Reduction of errors in digital terrain parameters used in soil-landscape modelling[J]. International Journal of Applied Earth Observation and Geoinformation, 5(2): 97-112. doi: 10.1016/j.jag.2004.01.006
[56]	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
[57]	Hengl T, Heuvelink G B M, Rossiter D G.2007. About regression-kriging: From equations to case studies[J]. Computers & Geosciences, 33(10): 1301-1315. doi: 10.1016/j.cageo.2007.05.001
[58]	Hudson B D.1992. The soil survey as paradigm-based science[J]. Soil Science Society of America Journal, 56(3): 836-841. doi: 10.2136/sssaj1992.03615995005600030027x
[59]	Hughes J P, Lettenmaier D P.1981. Data requirements for kriging: Estimation and network design[J]. Water Resources Research, 17(6): 1641-1650. doi: 10.1029/WR017i006p01641
[60]	Hutchinson M F.1995. Interpolating mean rainfall using thin plate smoothing splines[J]. International Journal of Geographical Information Systems, 9(4): 385-403. doi: 10.1080/02693799508902045
[61]	Isaaks E H, Srivastava R M.1989. Applied geostatistics[M]. New York, NY: Oxford University Press.
[62]	Jenny H.1941. Factors of soil formation: A system of quantitative pedology[M]. New York, NY: McGraw-Hill.
[63]	Juang K W, Liao W J, Liu T L, et al.2008. Additional sampling based on regulation threshold and Kriging variance to reduce the probability of false delineation in a contaminated site[J]. Science of the Total Environment, 389(1): 20-28. doi: 10.1016/j.scitotenv.2007.08.025 pmid: 17888495
[64]	Kempen B, Brus D J, Heuvelink G B M, et al.2009. Updating the 1:50,000 Dutch soil map using legacy soil data: A multinomial logistic regression approach[J]. Geoderma, 151(3-4): 311-326. doi: 10.1016/j.geoderma.2009.04.023
[65]	Knotters M, Brus D J, Oude Voshaar J H.1995. A Comparison of kriging, co-kriging and kriging combined with regression for spatial Interpolation of horizon depth with censored observations[J]. Geoderma, 67(3-4): 227-246. doi: 10.1016/0016-7061(95)00011-C
[66]	Kumar S, Lal R, Liu D S.2012. A geographically weighted regression kriging approach for mapping soil organic carbon stock[J]. Geoderma, 189-190: 627-634. doi: 10.1016/j.geoderma.2012.05.022
[67]	Lagacherie P, McBratney A B.2006. Chapter 1 Spatial soil information systems and spatial soil inference systems: Perspectives for digital soil mapping[J]. Developments in Soil Science, 31: 3-22. doi: 10.1016/S0166-2481(06)31001-X
[68]	Li J, Heap A D.2011. A review of comparative studies of spatial interpolation methods in environmental sciences: Performance and impact factors[J]. Ecological Informatics, 6(3): 228-241. doi: 10.1016/j.ecoinf.2010.12.003
[69]	Li J, Heap A D.2014. Spatial interpolation methods applied in the environmental sciences: A review[J]. Environmental Modelling & Software, 53: 173-189. doi: 10.1016/j.envsoft.2013.12.008
[70]	Li Y, Zhu A-X, Shi Z, et al.2016. Supplemental sampling for digital soil mapping based on prediction uncertainty from both the feature domain and the spatial domain[J]. Geoderma, 284: 73-84. doi: 10.1016/j.geoderma.2016.08.013
[71]	Loague K.1992. Soil water content at R-5: Part 1. Spatial and temporal variability[J]. Journal of Hydrology, 139(1-4): 233-251. doi: 10.1016/0022-1694(92)90204-9
[72]	MacMillan R A, Pettapiece W W, Nolan S C, et al.2000. A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic[J]. Fuzzy Sets and Systems, 113(1): 81-109. doi: 10.1016/S0165-0114(99)00014-7
[73]	Malone B P, de Gruijter J J, McBratney A B, et al.2011. Using additional criteria for measuring the quality of predictions and their uncertainties in a digital soil mapping framework[J]. Soil Science Society of America Journal, 75(3): 1032-1043. doi: 10.2136/sssaj2010.0280
[74]	Matheron G.1963. Principles of geostatistics[J]. Economic Geology, 58(8): 1246-1266. doi: 10.2113/gsecongeo.58.8.1246
[75]	McBratney A B, Hart G A, McGarry D.1991. The use of region partitioning to improve the representation of geo statistically mapped soil attributes[J]. Journal of Soil Science, 42(3): 513-532. doi: 10.1111/j.1365-2389.1991.tb00427.x
[76]	McBratney A B, Mendonça Santos M L, Minasny B.2003. On digital soil mapping[J]. Geoderma, 117(1-2): 3-52. doi: 10.1016/S0016-7061(03)00223-4
[77]	McBratney A B, Odeh I O A, Bishop T F A, et al.2000. An overview of pedometric techniques for use in soil survey[J]. Geoderma, 97(3-4): 293-327. doi: 10.1016/S0016-7061(00)00043-4
[78]	McBratney A B, Webster R.1983. Optimal interpolation and isarithmic mapping of soil properties: V. Co-regionalization and multiple sampling strategy[J]. Journal of Soil Science, 34(1): 137-162. doi: 10.1111/ejs.1983.34.issue-1
[79]	McKenzie N J, Ryan P J.1999. Spatial prediction of soil properties using environmental correlation[J]. Geoderma, 89(1-2): 67-94. doi: 10.1016/S0016-7061(98)00137-2
[80]	McSweeney K, Slater B K, Hammer R D, et al.1994. Towards a new framework for modeling the soil-landscape continuum[M]//Amundson R R, Harden J, Singer M. Factors of soil formation: A fiftieth anniversary retrospective. Madison, WI: Soil Science Society of America, 127-145.
[81]	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
[82]	Minasny B, McBratney A B.2006. Latin hypercube sampling as a tool for digital soil mapping[J]. Developments in Soil Science, 31: 153-165, 606. doi: 10.1016/S0166-2481(06)31012-4
[83]	Mondal A, Khare D, Kundu S, et al.2017. Spatial soil organic carbon (SOC) prediction by regression kriging using remote sensing data[J]. The Egyptian Journal of Remote Sensing and Space Science, 20(1): 61-70. doi: 10.1016/j.ejrs.2016.06.004
[84]	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
[85]	Mulder V L, de Bruin S, Schaepman M E.2013. Representing major soil variability at regional scale by constrained Latin Hypercube Sampling of remote sensing data[J]. International Journal of Applied Earth Observation and Geoinformation, 21: 301-310. doi: 10.1016/j.jag.2012.07.004
[86]	Myers D B, Kitchen N R, Sudduth K A, et al.2010. Combining proximal and penetrating soil electrical conductivity sensors for high-resolution digital soil mapping[M]//Viscarra Rossel R A, McBratney A B, Minasny B. Proximal soil sensing. Dordrecht, Netherlands: Springer.
[87]	Nemes A, Rawls W J, Pachepsky Y A.2006. Use of the nonparametric nearest neighbor approach to estimate soil hydraulic properties[J]. Soil Science Society of America Journal, 70(2): 327-336. doi: 10.2136/sssaj2005.0128
[88]	Odeh I O A, McBratney A B, Chittleborough D J.1994. Spatial prediction of soil properties from landform attributes derived from a digital elevation model[J]. Geoderma, 63(3-4): 197-214. doi: 10.1016/0016-7061(94)90063-9
[89]	Odeh I O A, McBratney A B, Chittleborough D J.1995. Further results on prediction of soil properties from terrain attributes-heterotopic cokriging and regression-kriging[J]. Geoderma, 67(3-4): 215-226. doi: 10.1016/0016-7061(95)00007-B
[90]	Park S J, Vlek P L G.2002. Environmental correlation of three-dimensional soil spatial variability: A comparison of three adaptive techniques[J]. Geoderma, 109(1-2): 117-140. doi: 10.1016/S0016-7061(02)00146-5
[91]	Qi F, Zhu A X.2003. Knowledge discovery from soil maps using inductive learning[J]. International Journal of Geographical Information Science, 17(8): 771-795. doi: 10.1080/13658810310001596049

The review and outlook of digital soil mapping

RichHTML

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

References 91

Related Articles 1

Metrics

Comments

Recommended 0