352
Views
6
CrossRef citations to date
0
Altmetric
Articles

Geospatial modeling of surface soil texture of agricultural land using fuzzy logic, geostatistics and GIS techniques

, &
Pages 1452-1464 | Received 06 Sep 2018, Accepted 20 May 2019, Published online: 11 Jun 2019

References

  • Adhikari, K., R. B. Kheir, M. B. Greve, P. K. Bocher, B. P. Malone, B. Minasny, A. B. McBratney, and M. H. Greve. 2013. High-resolution 3-D mapping of soil texture in Denmark. Soil Science Society of America Journal 77 (3):860–76. doi:10.2136/sssaj201.
  • Akpa, S. I. C., I. O. A. Odeh, T. F. A. Bishop, and A. E. Hartemink. 2014. Digital mapping of soil particle-size fractions for Nigeria. Soil Science Society of America Journal 78 (6):1953–66. doi:10.2136/sssaj2014.05.0202.
  • Arrouays, D., M. G. Grundy, A. E. Hartemink, J. W. Hempel, G. B. M. Heuvelink, S. Y. Hong, P. Lagacherie, G. Lelyk, A. B. McBratney, N. J. McKenzie, et al. 2014. GlobalSoilMap: Towards a fine-resolution global grid of soil properties. Advances in Agronomy 125:93–134. doi:10.1016/B978-0-12-800137-0.00003-0.
  • Asadzadeh, F., A. Akbarzadeh, A. A. Zolfaghari, R. Taghizadeh Mehrjardi, M. Mehrabanian, H. Rahimi Lake, and M. A. Sabeti. 2012. Study and comparison of some geostatistical methods for mapping cation exchange capacity in soils of northern Iran. Annals of Faculty Engineering Hunedoara 1:59–66.
  • Bodrud-Doza, M., A. T. Islam, F. Ahmed, S. Das, N. Saha, and M. Safiur Rahman. 2016. Characterization of groundwater quality using water evaluation indices, multivariate statistics and geostatistics in central Bangladesh. Water Science 30 (1):19–40. doi:10.1016/j.wsj.2016.05.001.
  • Camarinha, P. I. M., I. C. B. Trannin, S. J. C. Simoes, and G. P. Bernardes. 2011. Fuzzy logic and geostatistical techniques for spatialization of soil texture in region with rough terrains. Procedia Environmental Sciences 7:347–52. doi:10.1016/j.proenv.2011.07.060.
  • Castro-Franco, M., M. B. Domenech, M. R. Borda, and J. L. Costa. 2018. A spatial dataset of topsoil texture for the southern Argentine Pampas. Geoderma Regional 12:18–27. doi:10.1016/j.geodrs.2017.11.003.
  • Cole, S., E. Mikhailova, C. Post, C. Privette, M. A. Schlautman, and M. Cope. 2017. Comparing SSURGO data with geospatial field measurements to estimate soil texture and infiltration rate classes in glaciated soils. Communications in Soil Science and Plant Analysis 48 (11):1309–18. doi:10.1080/00103624.2017.1341916.
  • Cotching, W. E., G. Oliver, M. Downie, R. Corkrey, and R. B. Doyle. 2013. Land use and management influences on surface soil organic carbon in Tasmania. Soil Research 51 (8):615–30. doi:10.1071/SR12251.
  • Curcio, D., G. Ciraolo, F. D’Asaro, and M. Minacapilli. 2013. Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy. Procedia Environmental Sciences 19:494–503. doi:10.1016/j.proenv.2013.06.056.
  • Dobarco, M. R., D. Arrouays, P. Lagacherie, R. Ciampalini, and N. P. A. Saby. 2017. Prediction of topsoil texture for Region Centre (France) applying model ensemble methods. Geoderma 298:67–77. doi:10.1016/j.geoderma.2017.03.015.
  • Dobarco, M. R., T. G. Orton, D. Arrouays, B. Lemercier, J. B. Paroissien, C. Walter, and N. P. A. Saby. 2016. Prediction of soil texture using descriptive statistics and area-to-point kriging in Region Centre (France). Geoderma Regional 7 (3):279–92. doi:10.1016/j.geodrs.2016.03.006.
  • Dubey, S., R. K. Pandey, and S. S. Gautam. 2013. Literature review on fuzzy expert system in agriculture. International Journal of Soft Computing Engineer 2 (6):289–91.
  • Greve, M. H., R. B. Kheir, M. B. Greve, and P. K. Bocher. 2012. Quantifying the ability of environmental parameters to predict soil texture fractions using regression-tree model with GIS and LIDAR data: The case study of Denmark. Ecological Indicators 18:1–10. doi:10.1016/j.ecolind.2011.10.006.
  • Grunwald, S. 2009. Multi-criteria characterization of recent digital soil mapping and modeling approaches. Geoderma 152 (3–4):195–207. doi:10.1016/j.geoderma.2009.06.003.
  • Khan, S. R., M. K. Abbas, and A. Ul Hussan. 2012. Effect of induced soil compaction on changes in soil properties and wheat productivity under sandy loam and sandy clay loam soils: A greenhouse experiment. Communications in Soil Science and Plant Analysis 43 (19):2550–63. doi:10.1080/00103624.2012.711877.
  • Kremenov, O. 2004. Fuzzy modeling of soil maps. Master Thesis, Helsinki University of Technology, Department of Surveying.
  • Lewis, S. M., G. Fitts, M. Kelly, and L. Dale. 2014. A fuzzy logic based spatial suitability model for drought-tolerant switchgrass in the United States. Computers and Electronics in Agriculture 103:39–47. doi:10.1016/j.compag.2014.02.006.
  • Liao, K., S. Xu, J. Wu, and Q. Zhu. 2013. Spatial estimation of surface soil texture using remote sensing data. Soil Science and Plant Nutrition 59 (4):488–500. doi:10.1080/00380768.2013.802643.
  • Mikhailova, E. A., C. J. Post, M. A. Schlautman, J. M. Galbraith, and H. A. Zurqani. 2018. Usability of soil survey soil texture data for soil health indicator scoring. Communications in Soil Science and Plant Analysis 49 (15):1826–34. doi:10.1080/00103624.2018.1474918.
  • Mirzaee, S., S. Ghorbani-Dashtaki, J. Mohammadi, H. Asadi, and F. Asadzadeh. 2016. Spatial variability of soil organic matter using remote sensing data. Catena 145:118–27. doi:10.1016/j.catena.2016.05.023.
  • Oliver, M. A., and R. Webster. 2014. A tutorial guide to geostatistics: Computing and modelling variograms and kriging. Catena 113:56–69. doi:10.1016/j.catena.2013.09.006.
  • Prein, A. F., R. M. Rasmussen, K. Ikeda, C. Liu, M. P. Clark, and G. J. Holland. 2017. The future intensification of hourly precipitation extremes. Nature Climate Change 7:48–52. doi:10.1038/NCLIMATE3168.
  • Ranjbar, F., and M. Jalali. 2016. The combination of geostatistics and geochemical simulation for the site-specific management of soil salinity and sodicity. Computers and Electronics in Agriculture 121:301–12. doi:10.1016/j.compag.2015.12.010.
  • Robinson, T. P., and G. M. Metternicht. 2006. Testing the performance of spatial interpolation techniques for mapping soil properties. Computers and Electronics in Agriculture 50:97–108. doi:10.1016/j.compag.2005.07.003.
  • Salvacion, A. R. 2017. Mapping spatio-temporal changes in climatic suitability of corn in the Philippines under future climate condition. Quaestiones Geographicae 36 (1):105–20. doi:10.1515/quageo-2017-0008.
  • Salvacion, A. R., I. B. Pangga, and C. J. R. Cumagun. 2015. Assessment of mycotoxin risk on corn in the Philippines under current and future climate change conditions. Reviews of Environmental Health 30 (3):135–42. doi:10.1515/reveh-2015-0019.
  • Sanchez, P. A., S. Ahamed, F. Carre, A. E. Hartemink, J. Hempel, J. Huising, P. Lagacherie, A. B. McBratney, N. J. McKenzie, M. D. Mendonca-Santos, et al. 2009. Digital soil map of the world. Science 325 (5941):680–81. doi:10.1126/science.1175084.
  • Santra, P., M. Kumar, and N. Panwar. 2017. Digital soil mapping of sand content in arid western India through geostatistical approaches. Geoderma Regional 9:56–72. doi:10.1016/j.geodrs.2017.03.003.
  • Shi, J., H. Wang, J. Xu, J. Wu, X. Liu, H. Zhu, and C. Yu. 2007. Spatial distribution of heavy metals in soils: A case study of Changxing, China. Environmental Geology 52 (1):1–10. doi:10.1007/s00254-006-0443-6.
  • Shifteh Some’e, B., F. Hassanpour, A. Ezani, S. R. Miremadi, and H. Tabari. 2011. Investigation of spatial variability and pattern analysis of soil properties in the northwest of Iran. Environmental Earth Science 64:1849–64. doi:10.1007/s12665-011-0993-0.
  • Soil Survey Staff. 2014a. Kellogg soil survey laboratory methods manual. Soil Survey Investigations Report No. 42, Version 5. R. Burt and Soil Survey Staff (ed.). United States Department of Agriculture, Natural Resources Conservation Service.
  • Soil Survey Staff. 2014b. Keys to soil taxonomy, 12th ed., United States Department of Agriculture, National Soil Survey Center, Natural Resources Conservation Service, Washington, DC.
  • Thompson, J. A., E. M. Pena-Yewtukhiw, and J. H. Grove. 2006. Soil-landscape modeling across a physiographic region: Topographic patterns and model transportability. Geoderma 133:57–70. doi:10.1016/j.geoderma.2006.03.037.
  • Van Capelle, C., S. Schrader, and J. Brunotte. 2012. Tillage-induced changes in the functional diversity of soil biota - A review with a focus on German data. European Journal of Soil Biology 50:165–81. doi:10.1016/j.ejsobi.2012.02.005.
  • Wang, D. C., G. L. Zhang, M. S. Zhao, X. Z. Pan, Y. G. Zhao, D. C. Li, and B. Macmillan. 2015. Retrieval and mapping of soil texture based on land surface diurnal temperature range data from MODIS. PLoS ONE 10 (6):e0129977. doi:10.1371/journal.pone.0129977.
  • Wang, Z., W. Shi, and Z. Xu. 2017. Mapping soil particle-size fractions: A comparison of compositional kriging and log-ratio kriging. Journal of Hydrology 564:526–41. doi:10.1016/j.jhydrol.2017.01.029.
  • Webster, R., and M. A. Oliver. 2007. Geostatistics for environmental scientists. 2nd ed. Brisbane: Wiley. doi: 10.1002/9780470517277.
  • Xing-Yi, Z., S. Yue-Yu, Z. Xu-Dong, M. Kai, and S. J. Herbert. 2007. Spatial variability of nutrient properties in black soil of northeast China. Pedosphere 17 (1):19–29. doi:10.1016/S1002-0160(07)60003-4.
  • Zhao, Z., T. L. Chow, H. W. Rees, Z. Xing, F. Meng, and Q. Yang. 2009. Predict soil texture distributions using an artificial neural network model. Computers and Electronics in Agriculture 65:36–48. doi:10.1016/j.compag.2008.07.008.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.