Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC)

Journal of the Saudi Society of Agricultural Sciences

Volumn 17, Issue 2, 2018, Pages 114-126

  Bhunia, Gouri Sankar ^a   Shit, Pravat Kumar ^b   Maiti, Ramkrishna ^c  

^a Bihar Remote Sensing Applications Centre   (India)

^b Raja Narendra Lal Khan Women's College   (India)

^c VIDYASAGAR UNIVERSITY   (India)

Author keywords

Deterministic interpolation; Geostatistical interpolation; GIS; Soil organic carbon; Spatial variation

Indexed keywords

EID: 85044947685     PISSN: 1658077X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jssas.2016.02.001     Document Type: Article

References (43)

1. Agrawal, O.P., Rao, K.V.G.K., Chauhan, H.S., Khandelwal, M.K., Geostatistical analysis of soil salinity improvement with subsurface drainage system. Trans ASAE 38 (1995), 1427–1433.
2. Bao, S.D., Soil and Agricultural Chemistry Analysis. 2000, China Agriculture Press, Beijing p. 495.
3. Behera, S.K., Shukla, A.K., Spatial distribution of surface soil acidity, electrical Conductivity, soil organic carbon content and exchangeable Potassium, calcium and magnesium in some cropped acid Soils of India. Land Degrad. Dev. 26 (2015), 71–79.
4. Burgess, T.M., Webster, R., Optimal interpolation and isarithmic mapping of soil properties I: the semivariogram and punctual kriging. J. Soil Sci. 31 (1980), 315–331.
5. Burle, M.L., Mielniczuk, J., Focchi, S., Effect of cropping systems on soil chemical characteristics, with emphasis on soil acidification. Plant Soil 190 (2005), 309–316.
6. Cambardella, C.A., Moorman, T.B., Novak, J.M., Parkin, T.B., Karlen, D.L., Turco, R.F., Konopka, A.E., Field-scale variability of soil properties in central Iowa soils. Soil Sci. Soc. Am. J. 58 (1994), 1501–1511.
7. Cheng, X.F., Xie, Y., Spatial distribution of soil organic carbon density in Anhui Province based on GIS. Sientia Geograph. Sin. 29:4 (2009), 540–544 (in Chinese).
8. ESRI, Using ArcGIS Geostatistical Analyst. 2001, ESRI Press, Redlands, CA.
9. Gurumurthy, K.T., Kiran, Kumar M., Prakasha, H.C., Changes in physic–chemical properties of soils under different land use systems. Karnataka J. Agric. Sci. 22:5 (2009), 1107–1109.
10. Hani, A., Abari, S.A.H., Determination of Cd, Zn, K, pH, TNV, organic material and electrical conductivity (EC) distribution in agricultural soils using geostatistics and GIS (case study: South Western of Natanz – Iran). World Acad. Sci., Eng. Technol. 5:12 (2011), 22–25.
11. Hussain, I., Shakeel, M., Faisal, M., Soomro, Z.A., Hussain, T., Distribution of total dissolved solids in drinking water by means of Bayesian kriging and gaussian spatial predictive process water quality. Expos. Health 6:4 (2014), 177–185.
12. Johnston, K., Ver, Hoef J.M., Krivoruchko, K., Lucas, N., Using ArcGIS Geostatistical Analyst. 2001, ESRI Press, Redlands, CA.
13. Knotters, M., Heuvelink, G.B.M., Hoogland, T., Walvoort, D.J.J., 2010. A Disposition of Interpolation Techniques; Wageningen University and Research Centre, Statutory Research Tasks Unit for Nature and the Environment: Wageningen, The Netherlands.
14. Krivoruchko, K., Empirical Bayesian Kriging, 2012, Esri, Redlands, CA, USA Available online: < http://www.esri.com/news/arcuser/1012/empirical-byesian-kriging.html> (accessed 17.10.15).
15. Krivoruchko, K., Butler, K., Unequal Probability-Based Spatial Mapping, 2013, Esri, Redlands, CA, USA Available online: < http://www.esri.com/esrinews/arcuser/spring2013/~/media/Files/Pdfs/news/arcuser/0313/unequal.pdf>.
16. Kumar, S., Lal, R., Liu, D., Rafiq, R., Estimating the spatial distribution of organic carbon density for the soils of Ohio, USA. J. Geogr. Sci. 23:2 (2013), 280–296.
17. Kumar, S., Lal, R., Lloyd, D.C., Assessing spatial variability in soil characteristics with geographically weighted principal components analysis. Comput. Geosci. 16 (2012), 827–835, 10.1007/s10596-012-9290-6.
18. Li, X.F., Chen, Z.B., Chen, H.B., Chen, Z.Q., Spatial distribution of soil nutrients and their response to land use in eroded area of South China. Proc. Environ. Sci. 10 (2011), 14–19.
19. Li, Y., Shi, Z., Wu, C.F., Li, H.X., Li, F., Improved prediction and reduction of sampling density for soil salinity by different geostatistical methods. Agric. Sci. China 6 (2007), 832–841.
20. Liu, D., Wang, Z., Zhang, B., Song, K., Li, X., Li, J., Spatial distribution of soil organic carbon and analysis of related factors in croplands of the black soil region, northeast China. Agric. Ecosyst. Environ. 113 (2006), 73–81.
21. Liu, L., Wang, H., Dai, W., Lei, X., Yang, X., Li, X., Spatial variability of soil organic carbon in the forestlands of northeast China. J. Forest. Res. 25:4 (2014), 867–876.
22. Mirzaei, R., Sakizadeh, M., Comparison of interpolation methods for the estimation of groundwater contamination in Andimeshk–Shush Plain Southwest of Iran. Environ. Sci. Pollut. Res., 2015, 1–12.
23. Mousavifard, S.M., Momtaz, H., Sepehr, E., Davatgar, N., Sadaghiani, M.H.R., Determining and mapping some soil physico–chemical properties using geostatistical and GIS techniques in the Naqade region, Iran. Arch. Agron. Soil. Sci., 2012, 10.1080/03650340.2012.74055.
24. Nayanaka, V.G.D., Vitharana, W.A.U., Mapa, R.B., Geostatistical analysis of soil properties to support spatial sampling in a paddy growing Alfisol. Trop. Agric. Res. 22 (2010), 34–44.
25. Nielsen, D.R., Wendroth, O., Spatial and Temporal Statistics—Sampling Field Soils and Their Vegetation. 2003, Catena Verlag GMBH, Reiskirchen, German.
26. Pang, S., Li, T.X., Zhang, X.F., Wang, Y.D., Yu, H.Y., Spatial variability of cropland lead and its influencing factors: a case study in Shuangliu county, Sichuan province, China. Geoderma 162 (2011), 223–230.
27. Pillon, C.N., Stocks and Quality of soil Organic Matter as Affected by No –Till Cropping System, Doctorate Thesis. 2000, Federal University of Rio Grande do Sul, Porto Alegre pp. 248.
28. Robertson, G.P., GS+: Geostatistics for the Environmental Sciences. 2008, Gamma Design, Plainwell, Mich.
29. Robinson, T.P., Metternicht, G.M., Testing the performance of spatial interpolation techniques for mapping soil properties. Comput. Electeron. Agric. 50 (2006), 97–108.
30. Saha, D., Kukal, S.S., Bawa, S.S., Soil organic carbon stock and fractions in relation to land use and soil depth in the degraded shiwaliks hills of lower Himalayas. Land Degrad. Dev., 2012, 10.1002/ldr.2151.
31. Saito, H., McKenna, A., Zimmerman, D.A., Coburn, T.C., Geostatistical interpolation of object counts collected from multiple strip transects: ordinary kriging versus finite domain kriging. Stoch. Environ. Res. Risk Assess. 19 (2005), 71–85.
32. Sheikh, A.M., Kumar, M., Bussman, R.W., Todari, N.P., Forest carbon stocks and fluxes in physiographic zones of India. Carbon Bal. Manage. 6:15 (2011), 1–10.
33. Shit, P.K., Bhunia, G.S., Maiti, R.K., Assessment of factors affecting ephemeral gully development in badland topography: a case study at Garbheta badland (Pashchim Medinipur). Int. J. Geosci. 4:2 (2013), 461–470, 10.4236/ijg.2013.42043.
34. Soil Survey Manual, All India Soil and Land Use Survey Organization. 1970, I.A.R.I., New Delhi.
35. Tripathi, R., Nayak, A.K., Shahid, M., Raja, R., Panda, B.B., Mohanty, S., Kumar, A., Lal, B., Gautam, P., Sahoo, R.N., Characterizing spatial variability of soil properties in salt affected coastal India using geostatistics and kriging. Arab. J. Geosci., 2015, 10.1007/s12517-015-2003-4.
36. Varouchakis, E.A., Hristopulos, D.T., Comparison of stochastic and deterministic methods for mapping groundwater level spatial variability in sparsely monitored basins. Environ. Monit. Assess. 185 (2013), 1–19.
37. Vauclin, M., Vieira, S.R., Vachaud, G., Nielsen, D.R., The use of cokriging with limited field soil observations. Soil Sci. Soc. Am. J. 47 (1983), 175–184.
38. Venteris, E., Basta, N., Bigham, J., Rea, R., Modeling spatial patterns in soil arsenic to estimate natural baseline concentrations. J. Environ. Qual. 43:3 (2014), 936–946.
39. Wang, Y.Q., Shao, M.A., Spatial variability of soil physical properties in a region of the Loess Plateau of PR China subject to wind and water erosion. Land Degrad. Dev. 24:3 (2013), 296–304.
40. Wei, J.B., Xiao, D.N., Zeng, H., Fu, Y.K., Spatial variability of soil properties in relation to land use and topography in a typical small watershed of the black soil region, northeastern China. Environ. Geol. 53 (2008), 1663–1672.
41. Zare-mehrjardi, M., Taghizadeh-Mehrjardi, R., Akbarzadeh, A., Evaluation of geostatistical techniques for mapping spatial distribution of soil PH, salinity and plant cover affected by environmental factors in Southern Iran. Not. Sci. Biol. 2:4 (2010), 92–103.
42. Zhang, W., Wang, K.L., Chen, H.S., He, X.Y., Zhang, J.G., Ancillary information improves kriging on soil organic carbon data for a typical karst peak cluster depression landscape. J. Sci. Food Agric. 92:5 (2012), 1094–1102.
43. Zhang, Z., Yu, D., Shi, X., Weindorf, D.C., Sun, Y., Wang, H., Zhao, Y., Effects of prediction methods for detecting the temporal evolution of soil organic carbon in the Hilly Red Soil Region, China, Environ. Earth Sci. 64 (2011), 319–328, 10.1007/s12665-010-0849-z.