A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape

Ecological Indicators

Volumn 52, Issue , 2015, Pages 394-403

  Were, Kennedy ^a,b   Bui, Dieu Tien ^c   Dick, Øystein B ^a   Singh, Bal Ram ^a  

^a NORWEGIAN UNIVERSITY OF LIFE SCIENCES   (Norway)

^b KENYA AGRICULTURAL RESEARCH INSTITUTE   (Kenya)

^c UNIVERSITY OF SOUTH EASTERN NORWAY   (Norway)

Author keywords

Artificial neural networks; Digital soil mapping; Eastern Mau; Kenya; Random forests; Soil organic carbon; Support vector regression

Indexed keywords

CARBON; CLIMATE CHANGE; DECISION TREES; ECOLOGY; ECOSYSTEMS; FORECASTING; MAPPING; MEAN SQUARE ERROR; NEURAL NETWORKS; REGRESSION ANALYSIS; SOILS; VECTORS;

DIGITAL SOIL MAPPINGS; EASTERN MAU; KENYA; RANDOM FORESTS; SOIL ORGANIC CARBON; SUPPORT VECTOR REGRESSION (SVR);

ORGANIC CARBON;

ARTIFICIAL NEURAL NETWORK; CALIBRATION; COMPARATIVE STUDY; DATA SET; DIGITAL MAPPING; ERROR ANALYSIS; MAPPING; ORGANIC CARBON; PREDICTION; REGRESSION ANALYSIS; SOIL ORGANIC MATTER;

KENYA; MAU FOREST;

EID: 84921524606     PISSN: 1470160X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolind.2014.12.028     Document Type: Article

References (74)

1. T. Amare, C. Hergarten, H. Hurni, B. Wolfgramm, B. Yitaferu, and Y.G. Selassie Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy ISRN Soil Sci. 720589 2013 11 10.1155/2013/720589
2. E. Aynekulu, T.-G. Vågen, K. Shepherd, and L. Winowiecki A protocol for measurement and monitoring soil carbon stocks in agricultural landscapes. Version 1. 1 2011 World Agroforestry Centre Nairobi
3. L. Butterbach-Bahl, and M. Dannenmann Soil carbon and nitrogen interactions and biosphere-atmosphere exchange of nitrous oxide and methane R. Lal, K. Lorenz, R.F. Hüttl, B.U. Schneider, J. von Braun, Recarbonization of the Biosphere: Ecosystems and the Global Carbon Cycle 2012 Springer Science+Business Media 429 442
4. A. Bationo, J. Kihara, B. Vanlauwe, B. Waswa, and J. Kimetu Soil organic carbon dynamics, functions and management in West African agro-ecosystems Agric. Syst. 94 2007 13 25
5. J. Batlle-Aguilar, A. Brovelli, A. Porporato, and D.A. Barry Modelling soil carbon and nitrogen cycles during land use change - a review Agron. Sustain Dev. 31 2011 251 274
6. G.R. Blake Bulk density C.A. Black, Methods of Soil Analysis, Part 1. Physical and Mineralogical Properties, including Statistics of Measurement and Sampling 1965 American Society of Agronomy, Inc Madison, Wisconsin, USA
7. J.M. Bremner, and C.S. Mulvaney Nitrogen - total A.L. Page, Methods of soil analysis, Part 2. Chemical and microbiological properties 2nd edition 1982 American Society of Agronomy, Inc Madison, Wisconsin, USA
8. A.H. Cambule, D.G. Rossiter, J.J. Stoorvogel, and E.M.A. Smaling Soil organic carbon stocks in the Limpopo National Park, Mozambique: amount, spatial distribution and uncertainty Geoderma 213 2014 46 56
9. J.B. Campbell Introduction to Remote Sensing 2002 Taylor & Francis London
10. V. Chaplot, B. Bouahom, and C. Valentin Soil organic carbon stocks in Laos: spatial variations and controlling factors Global Change Biol. 16 2010 1380 1393
11. J. Chen, J. Chen, M. Tan, and Z. Gong Soil degradation: a global problem endangering sustainable development J. Geograph. Sci. 12 2 2002 243 252
12. M. Conforti, S. Pascale, G. Robustelli, and F. Sdao Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy) Catena 113 2014 236 250
13. A. Cutler, D.R. Cutler, and J.R. Stevens C. Zhang, Y. Ma, Ensemble Machine Learning: Methods and Applications 2012 Springer Science+Business Media, LLC
14. P.R. Day Particle fractionation and particle size analysis C.A. Black, Methods of Soil Analysis, Part 1. Physical and Mineralogical Properties, including Statistics of Measurement and Sampling 1965 American Society of Agronomy, Inc Madison, Wisconsin, USA
15. S. Doetterl, A. Stevens, K. van Oost, T.A. Quine, and B. van Wesemael Spatially explicit regional scale prediction of soil organic carbon stocks in cropland using environmental variables and mixed model approaches Geoderma 204-205 2013 31 42
16. J.M. Drake, C. Randin, and A. Guisan Modelling ecological niches with support vector machines J. Appl. Ecol. 43 2006 424 432
17. R.P. Eclesia, E.G. Jobbagy, R.B. Jackson, F. Biganzoli, and G. Piñeiro Shifts in soil organic carbon for plantation and pasture establishment in native forests and grasslands of South America Global Change Biol. 18 2012 3237 3251
18. H. Elbasiouny, M. Abowaly, A. Abu-Alkheir, and A. Gad Spatial variation of soil carbon and nitrogen pools by using ordinary kriging method in an area of north Nile delta, Egypt Catena 113 2014 70 78
19. Government of Kenya Report of the prime minister's task force on the conservation of the Mau forest complex. [Online] 2009 Available: http://www.kws.org/export/sites/kws/info/maurestoration/maupublications/Mau-Forest-Complex-Report.pdf [Accessed 19.01.14]
20. R. Grimm, T. Behrens, M. Märker, and H. Elsenbeer Soil organic carbon concentrations and stocks on Barro Colorado Island - Digital soil mapping using Random Forests analysis Geoderma 146 2008 102 113
21. S.R. Gunn Support Vector Machines for Classification and Regression 1998 University of Southampton, Technical report
22. T. Hengl, G.B.M. Heuvelink, and D.G. Rossiter About regression-kriging: from equations to case studies Comput. Geosci. 33 2007 1301 1315
23. T. Hengl, G.B.M. Heuvelink, and A. Stein A generic framework for spatial prediction of soil variables based on regression-kriging Geoderma 120 2004 75 93
24. S.M. Jaber, and M.I. Al-Qinna Soil organic carbon modelling and mapping in a semi-arid environment using thematic mapper data Photogrammetric Eng. Remote Sens. 77 7 2011 709 719
25. nd edition, Part B Central Kenya, Subpart B1a Southern Rift Valley Province. Ministry of Agriculture, Kenya and German Agency for Technical Cooperation (GTZ), Nairobi.
26. H. Jenny Factors of Soil Formation: A System of Quantitative Pedology 1941 McGraw-Hill
27. S.B. Karunaratne, T.F.A. Bishop, J.A. Baldock, and 1.O.A. Odeh Catchment scale mapping of measureable soil organic carbon fractions Geoderma 219-220 2014 14 23
28. T. Kavzoglu, and I. Colkesen A kernel function analysis for support vector machines for land cover classification Int. J. Appl. Earth Observ. Geoinfomat. 11 5 2009 352 359
29. S. Kumar, and R. Lal Mapping the organic carbon stocks of surface soils using local spatial interpolator J. Environ. Monit. 13 2011 3128 3135
30. S. Kumar, R. Lal, and D. Liu A geographically weighted regression kriging approach for mapping soil organic carbon stock Geoderma 189-190 2012 627 634
31. S. Kumar, R. Lal, and D. Liu Estimating the spatial distribution of organic carbon density for the soils of Ohio, USA J. Geograph. Sci. 23 2 2013 280 296
32. R. Lal Soil carbon sequestration to mitigate climate change Geoderma 123 2004 1 22
33. S. Lee, and D.G. Evangelista Earthquake-induced landslide susceptibility mapping using an artificial neural network Nat. Hazards Earth Syst. Sci. 6 2006 687 695
34. Q. Li, T. Yue, C. Wang, W. Zhang, Y. Yu, B. Li, J. Yang, and G. Bai Spatially distributed modeling of soil organic matter across China: an application of artificial neural network approach Catena 104 2013 210 218
35. Z.P. Liu, M.A. Shao, and Y.Q. Wang Large-scale spatial variability and distribution of soil organic carbon across the entire Loess Plateau, China Soil Res. 50 2 2006 114 124
36. K. Lorenz Ecosystem carbon sequestration R. Lal, K. Lorenz, R.F. Hüttl, B.U. Schneider, J. von Braun, Ecosystem Services and Carbon Sequestration in the Biosphere 2013 Springer Science+Business Media Dordrecht 39 62
37. B.P. Malone, A.B. McBratney, B. Minasny, and G.M. Laslett Mapping continuous depth functions of soil carbon storage and available water capacity Geoderma 154 2009 138 152
38. A. Marchetti, C. Piccini, R. Francaviglia, and L. Mabit Spatial distribution of soil organic matter using geostatistics: a key indicator to assess soil degradation status in central Italy Pedosphere 22 2 2012 230 242
39. M.P. Martin, M. Wattenbach, P. Smith, J. Meersmans, C. Jolivet, L. Boulonne, and D. Arrouays Spatial distribution of soil organic carbon stocks in France Biogeosciences 8 2011 1053 1065
40. A.B. McBratney, M.L.M. Santos, and B. Minasny On digital soil mapping Geoderma 117 2003 3 52
41. G.J.H. McCall Geology of the Nakuru-Thomson's falls-Lake Hannington area: degree sheet No. 35, S.W. Quarter and 43 N.W. Quarter. Report No. 78 1967 Government Printer Nairobi
42. J. Meersmans, F. de Ridder, F. Canters, S. de Baets, and M. van Molle A multiple regression approach to assess the spatial distribution of soil organic carbon (SOC) at the regional scale (Flanders, Belgium) Geoderma 143 2008 1 13
43. U. Mishra, R. Lal, D. Liu, and M. van Meirvenne Predicting the spatial variation of the soil organic carbon pool at a regional scale Soil Sci. Soc. Am. J. 74 2010 906 914
44. D. Murty, M.F. Kirschbaum, R.E. McMurtrie, and H. McGilvray Does conversion of forest to agricultural land change soil carbon and nitrogen? A review of the literature Global Change Biol. 8 2002 105 123
45. D.W. Nelson, and L.E. Sommers Total carbon, organic carbon and organic matter A.L. Page, Methods of Soil Analysis, Part 2, Chemical and Microbiological Properties 2nd edition 1982 American Society of Agronomy, Inc Madison, Wisconsin, USA
46. M.Q. Nguyen, P.M. Atkinson, and H.G. Lewis Super-resolution mapping using Hopfield neural network with fused images IEEE Trans. Geosci. Remote Sens. 44 3 2006 736 749
47. J.R. Okalebo, K.W. Gathna, and P.L. Woomer Laboratory Methods for Soil and Plant Analysis: A Working Manual 2nd edition 2002 Tropical Soil Biology and Fertility Programme Nairobi
48. K. Pachomphon, P. Dlamini, and V. Chaplot Estimating carbon stocks at regional level using soil information and easily accessible auxiliary variables Geoderma 155 2010 372 380
49. J. Platt Fast training of support vector machines using sequential minimal optimization B. Schölkopf, C.J.C. Burges, A.J. Smola, Advances in Kernel Methods - Support Vector Learning 1999 MIT Press MA 185 208
50. D.S. Powlson, P.J. Gregory, W.R. Whalley, J.N. Quinton, D.W. Hopkins, A.P. Whitmore, P.R. Hirsch, and K.W.T. Goulding Soil management in relation to sustainable agriculture and ecosystem services Food Policy 36 2011 S72 S87
51. A. Pozdnoukhov Support vector regression for automated robust spatial mapping of natural radioactivity Appl. GIS 1 2 2005 21.1-21.10
52. R Core Team, 2013. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://wwwR-projectorg/.
53. R. Rakkiyappan, and P. Balasubramaniam Delay-dependent asymptotic stability for stochastic delayed recurrent neural networks with time varying delays Appl. Math. Comput. 198 2 2008 526 533
54. R.A.V. Rossel, and T. Behrens Using data mining to model and interpret soil diffuse reflectance spectra Geoderma 158 2010 46 54
55. Ruß, G.; Kruse, R.; 2010. Regression models for spatial data: An example from precision agriculture. In: Perner, P.; ICDM 2010, LNAI 6171, pp. 450-463.
56. H.B. Shelukindo, E. Semu, B.M. Msanya, B.R. Singh, and P.K.T. Munishi Predictor variables for soil organic carbon contents in the Miombo woodlands ecosystem of Kitonga forest Int. J. Agric. Sci. 4 7 2014 222 231
57. P. Smith Soils as carbon sinks: the global context Soil Use Manage 20 2004 212 218
58. P. Smith Land use change and soil organic carbon dynamics Nutr. Cycl. Agroecosyst. 81 2008 169 178
59. A.J. Smola, and B. Schölkopf A tutorial on support vector regression Stat. Comput. 14 2004 199 222
60. G.B. Tesfahunegn, L. Tamene, and P.L.G. Vlek Catchment scale spatial variability of soil properties and implications on site-specific soil management in northern Ethiopia Soil Till. Res. 117 2011 124 139
61. D. Tien Bui, B. Pradhan, O. Lofman, and I. Revhaug Landslide susceptibility assessment in Vietnam using support vector machine, decision tree and Naïve Bayes models Math. Prob. Eng. 2012 1 26
62. UNEP, 2009. Kenya: Atlas of our changing environment. Division of Early Warning and Assessment (DEWA), United Nations Environment Programme (UNEP). [Online]. Available: http://www.unep.org/dewa/africa/kenyaatlas/ [Accessed 28.09.13].
63. K. Vojislav Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models (Complex Adaptive Systems) 2001 The IMT Press
64. T.G. Vågen, and L.A. Winowiecki Mapping of soil organic carbon stocks for spatially explicit assessments of climate change mitigation potential Environ. Res. Lett. 8 2013 10.1088/1748-9326/8/1/015011 015011 (9 pp)
65. T.G. Vågen, L.A. Winowiecki, A. Abegaz, and K.M. Hagdu Landsat-based approaches for mapping of land degradation prevalence and soil functional properties in Ethiopia Remote Sens. Environ. 134 2013 266 275
66. G.M. Vasques, S. Grunwald, N.B. Comerford, and J.O. Sickman Regional modelling of soil carbon at multiple depths within a subtropical watershed Geoderma 156 2010 326 336
67. K.O. Were, Ø.B. Dick, and B.R. Singh Remotely sensing the spatial and temporal land cover changes in Eastern Mau forest reserve and Lake Nakuru drainage basin, Kenya Appl. Geogr. 41 2013 75 86
68. K.O. Were, B.R. Singh, and Ø.B. Dick Effects of land cover changes on soil organic carbon and total nitrogen stocks in the Eastern Mau Forest Reserve, Kenya (Chapter 6) R. Lal, B.R. Singh, D.L. Mwaseba, D. Kraybill, D.O. Hansen, L.O. Eik, Sustainable Intensification to Advance Food Security and Enhance Climate Resilience in Africa 2015 Springer International Publishing Switzerland 113 133 10.1007/978-3-319-09360-4-6
69. M. Wiesmeier, F. Barthold, B. Blank, and I. Kögel-Knabner Digital mapping of soil organic matter stocks using Random Forest modeling in a semi-arid steppe ecosystem Plant Soil 340 2011 7 24
70. M. Wiesmeier, P. Spörlein, U. Geuß, E. Hangen, S. Haug, A. Reischl, B. Schilling, M. von Lützow, and I. Kögel-Knabner Soil organic carbon stocks in southeast Germany (Bavaria) as affected by land use, soil type and sampling depth Global Change Biol. 18 2012 2233 2245
71. G. Williams Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery, use R 2011 Springer Science+Business Media, LLC DOI 10.1007/9781441998-2
72. J.P. Wilson, and J.C. Gallant Terrain Analysis: Principles and Applications 2000 John Wiley & Sons, Inc
73. Y. Yang, J. Fang, Y. Tang, C. Ji, C. Zheng, J. He, and B. Zhu Storage, patterns and controls of soil organic carbon in the Tibetan grasslands Global Change Biol. 14 2008 1592 1599
74. L. Zhuang, and H.H. Dai Parameter optimization of kernel-based classifier on imbalance text learning. Pricai: 2006 Trends in Artificial Intelligence, Proceedings 4099 2006 434 443