Predicting soil organic carbon density using auxiliary environmental variables in northern Iran

References

• Alvarez R, Steinbach HS, Bono A. 2011. An artificial neural network approach for predicting soil carbon budget in agroecosystems. Soil Sci Soc Am J. 75:965–975.
   Web of Science ®Google Scholar
• Angers DA, Eriksen-Hamel NS. 2008. Full-inversion tillage and organic carbon distribution in soil profiles: a meta-analysis. Soil Sci Soc Am J. 72:1370–1374.
   Web of Science ®Google Scholar
• Ayoubi S, Khoramli F, Sahrawat KL, Rodrigues De Lima AC. 2011. Assessing impacts of land use change on soil quality indicators in a loessial soil in Golestan Province, Iran, northern Iran. J Agr Sci Tech. 13:727–742.
   Web of Science ®Google Scholar
• Ayoubi S, Mokhtari Karchegani P, Mosaddeghi MR, Honarjoo N. 2012. Soil aggregation and organic carbon as affected by topography and land use change in western Iran. Soil Till Res. 121:18–26.
   Web of Science ®Google Scholar
• Ayoubi S, Pilehvar Shahri A, Mokhtari Karchegani P, Sahrawat KL. 2011. Biomass and remote sensing biomass. Croatia: InTech Publication. Chapter 10, Application of artificial neural network (ANN) to predict soil organic matter using remote sensing data in two ecosystems; p. 181–196.
   Google Scholar
• Batjes NH, Sombroek WG. 1997. Possibilities for carbon sequestration in tropical and subtropical soils. Global Change Biol. 3:161–173.
   Web of Science ®Google Scholar
• Berhongaray G, Alvarez R, De Paepe J, Caride C, Cantet R. 2013. Land use effects on soil carbon in the Argentine Pampas. Geoderma. 192:97–110.
   Web of Science ®Google Scholar
• Bronick CJ, Lal R. 2005. Manuring and rotation effects on soil organic carbon concentration for different aggregate size fractions on two soils in northeastern Ohio, USA. Soil Till Res. 81:239–252.
   Web of Science ®Google Scholar
• Burke IC, Yonker CM, Parton WJ, Cv C, Flach K, Schimel DS. 1989. Texture, climate, and cultivation effects on soil organic matter content in U.S. grasslands soils. Soil Sci Soc Am J. 53:800–805.
   Web of Science ®Google Scholar
• Christensen BT. 1992. Physical fractionation of soil and organic matter in primary particle size and density separates. Adv Agron. 20:1–90.
   Google Scholar
• Cotler H, Ortega-Larrocea MP. 2006. Effects of land use on soil erosion in a tropical dry forest ecosystem, Chamela watershed, Mexico. Catena. 65:107–117.
   Web of Science ®Google Scholar
• Day PR. 1965. Methods of soil analysis. Madison (WI): ASA. Part 1, Particle fractionation and particle-size analysis; p. 545–567.
   Google Scholar
• Eastman JR, Fulk M. 1993. Long sequence time series evaluation using standardized principal components. Photogramm Eng Rem S. 59:991–996.
   Web of Science ®Google Scholar
• Fang X, Xue ZJ, Li BC, An SS. 2012. Soil organic carbon distribution in relation to land use and its storage in a small watershed of the Loess Plateau, China. Catena. 88:6–13.
   Web of Science ®Google Scholar
• Fu BJ, Liu SL, Ma KM, Zhu YG. 2004. Relationships between soil characteristics, topography and plant diversity in a heterogeneous deciduous broad-leaved forest near Beijing, China. Plant Soil. 261:47–54.
   Web of Science ®Google Scholar
• Fuchs H, Magdon P, Klein C, Flessa F. 2009. Estimating aboveground carbon in a catchment of the Siberian forest tundra: combining satellite imagery and field inventory. Remot Sens Environ. 113:518–531.
   Web of Science ®Google Scholar
• Gao B-C. 1996. NDWI – a normalized difference water index for remote sensing of vegetation liquid water from space. Remot Sens Environ. 58:257–266.
   Web of Science ®Google Scholar
• Garten CT, Post WM, Hanson PJ, Cooper LW. 1999. Forest soil carbon inventories and dynamics along an elevation gradient in the southern Appalachian Mountains. Biogeochemistry. 45:115–145.
   Web of Science ®Google Scholar
• Gomez C, Viscarra Rossel RA, McBratney AB. 2008. Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: an Australian case study. Geoderma. 146:403–411.
   Web of Science ®Google Scholar
• Gray JM, Humphreys GS, Deckers JA. 2009. Relationships in soil distribution as revealed by a global soil database. Geoderma. 150:309–323.
   Web of Science ®Google Scholar
• Ichii K, Matsui Y, Yamaguchi Y, Ogawa K. 2001. Comparison of global net primary production trends obtained from satellite based normalized difference vegetation index and carbon cycle model. Global Biogeochem Cy. 15:351–363.
   Web of Science ®Google Scholar
• Ingleby HR, Crowe TG. 2001. Neural network models for predicting organic matter content in Saskatchewan soils. Canadian Biosys Eng. 43:71–75.
   Google Scholar
• Jackson TJ, Schmugge TJ. 1991. Vegetation effects on the microwave emission of soils. Remot Sens Environ. 36:203–212.
   Web of Science ®Google Scholar
• Jorgensen SE, Bendoricchio G. 2001. Fundamentals of ecological modelling. 3rd ed. Oxford: Elsevier.
   Google Scholar
• Karchegani PM, Ayoubi S, Mosaddeghi MR, Honarjoo N. 2012. Soil organic carbon pools in particle-size fractions as affected by slope gradient and land use change in hilly regions, western Iran. J Mat Sci. 9:87–95.
   Google Scholar
• Kaul M, Hill RL, Walthall C. 2005. Artificial neural networks for corn and soybean yield prediction. Agric Syst. 85:1–18.
   Web of Science ®Google Scholar
• Kheir RB, Greve MH, Bøcher PK, Greve MB, Larsen R, McCloy K. 2010. Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark. Environ Manag. 91:1150–1160.
   Web of Science ®Google Scholar
• Khormali F, Ajami M, Ayoubi S, Srinivasarao C, Wani SP. 2009. Role of deforestation and hillslope position on soil quality attributes of loess-derived soils in Golestan province, Iran. Agr Ecosyst Environ. 134:178–189.
   Web of Science ®Google Scholar
• Lamsal S. 2009. Visible near-infrared reflectance spectroscopy for geospatial mapping of soil organic matter. Soil Science. 174:35–44.
   Web of Science ®Google Scholar
• Li Y. 2010. Can the spatial prediction of soil organic matter contents at various sampling scales be improved by using regression kriging with auxiliary information? Geoderma. 159:63–75.
   Web of Science ®Google Scholar
• Liu DW, Wang ZM, Zhang B, Song K, Li X, Li J, Li F, Duan H. 2006. Spatial distribution of soil organic carbon and analysis of related factors in croplands of the black soil region, Northeast China. Agr Ecosyst Environ. 113:73–81.
   Web of Science ®Google Scholar
• Liu Z, Shao M, Wang Y. 2011. Effect of environmental factors on regional soil organic carbon stocks across the Loess Plateau region, China. Agr Ecosyst Environ. 142:184–194.
   Web of Science ®Google Scholar
• Maia SMF, Ogle SM, Cerri CC, Cerri CEP. 2010. Changes in soil organic carbon storage under different agricultural management systems in the Southwest Amazon Region of Brazil. Soil Till Res. 106:177–184.
   Web of Science ®Google Scholar
• McDaniel PA, Munn LC. 1985. Effect of temperature on organic carbon-texture relationships in mollisols and aridisols. Soil Sci Soc Am J. 49:1486–1489.
   Web of Science ®Google Scholar
• McKenzie NJ, Cresswell HP, Ryan PJ, Grundy M. 2000. Contemporary land resource survey requires improvements in direct soil measurement. Commun Soil Sci Plant Anal. 31:1553–1569.
   Web of Science ®Google Scholar
• Mendoza-Vega J. 2002. The influence of land use/land cover and soil types on amounts of soil organic carbon and soil characteristics [dissertation]. Uppsala: Swedish University of Agricultural Sciences.
   Google Scholar
• Mishra U, Lal R, Slater B, Calhoun F, Liu D, Van Meirvenne M. 2009. Predicting soil organic carbon stock using profile depth distribution functions and ordinary kriging. Soil Sci Soc Am J. 73:614–621.
   Web of Science ®Google Scholar
• Mohammadi J, Shataee S. 2010. Possibility investigation of tree diversity mapping using landsat ETM+ data in the Hyrcanian forests of Iran. Remot Sens Environ. 114:1504–1512.
   Web of Science ®Google Scholar
• Mouazen AM, Kuang B, De Baerdemaeker J, Ramon H. 2010. Comparison among principal component, partial least squares and back propagation neural network analyses for accuracy of measurement of selected soil properties with visible and near infrared spectroscopy. Geoderma. 158:23–31.
   Web of Science ®Google Scholar
• Nelson DW, Sommers LE. 1982. Method of soil analysis, chemical and microbiological properties. Madison (WI): ASA. Part 2, Total carbon, organic carbon, and organic matter; p. 539–579.
   Google Scholar
• Percival HJ, Parfitt RL, Scott NA. 2009. Factors controlling soil carbon levels in New Zealand Grasslands: is clay content important? Soil Sci Soc Am J. 64:1623–1630.
   Web of Science ®Google Scholar
• Pilehvar Shahri AR. 2011. Incorporation of remotely sensed data and terrain attributes to predict soil organic carbon in Zargham Abad. Semirom. Isfahan [master of science]. Isfahan: Isfahan University of Technology.
   Google Scholar
• Post WM, Izaurralde RC, Mann LK, Bliss N. 2001. Monitoring and verifying changes of organic carbon in soil. Clim Change. 51:73–99.
   Web of Science ®Google Scholar
• Pradhan R, Ghose MK, Jeyaram A. 2010. Land cover classification of remotely sensed satellite data using bayesian and hybrid classifier. Int J Comput Appl. 7:1–4.
   Google Scholar
• Schwanghart W, Jarmer T. 2011. Linking spatial patterns of soil organic carbon to topography. A case study from south-eastern Spain. Geomorphology. 126:252–263.
   Web of Science ®Google Scholar
• Shariari A, Khormali F, Kehl M, Ayoubi S, Welp G. 2011. Effect of long term cultivation and crop rotations on organic carbon in loess derived soils of Golestan Province, northern Iran. Int J Plant Prod. 5:147–152.
   Web of Science ®Google Scholar
• Somaratne S, Seneviratne G, Coomaraswamy U. 2005. Prediction of soil organic carbon across different land use patterns: a neural network approach. Soil Sci Soc Am J. 69:1580–1589.
   Web of Science ®Google Scholar
• Tan ZX, Lal R, Smeck NE, Calhoun FG. 2004. Relationships between surface soil organic carbon pool and site variables. Geoderma. 121:187–195.
   Web of Science ®Google Scholar
• Thompson JA, Kolka RK. 2005. Soil carbon storage estimation in a forested watershed using quantitative soil-landscape modeling. Soil Sci Soc Am J. 69:1086–1093.
   Web of Science ®Google Scholar
• Van Der Werf GR, Morton DC, Defries RS, Olivier JGJ, Kasibhatla PS, Jackson RB, Collatz GJ, Randerson, JT. 2009. CO2 emissions from forest loss. Nat Geosci. 2:737–738.
   Web of Science ®Google Scholar
• Wang S, Wang X, Ouyang Z. 2012. Effects of land use, climate, topography and soil properties on regional soil organic carbon and total nitrogen in the Upstream Watershed of Miyun reservoir, North China. Environ Sci. 24:387–395.
   Web of Science ®Google Scholar
• Wang Y-Q, Zhang X-C, Zhang J-L, Li S-J. 2009. Spatial variability of soil organic carbon in a watershed on the Loess Plateau. Pedosphere. 19:486–495.
   Web of Science ®Google Scholar
• Wetterlind J, Stenberg B, Soderstrom M. 2008. The use of near infrared (NIR) spectroscopy to improve soil mapping at the farm scale. Preci Agric. 9:57–69.
   Web of Science ®Google Scholar
• Wierenga PJ. 1985. Spatial variability of soil water properties in irrigated soils. Paper presented at: Proceedings of a Workshop of the ISSS and the SSSA; Las Vegas, NV.
   Google Scholar
• Wilson JP, Gallant JC. 2000. Terrain analysis: principles and applications. New York (NY): John Wiley & Sons.
   Google Scholar
• Yimer F, Ledin S, Abdelkadir A. 2006. Soil property variations in relation to topographic aspect and vegetation community in the south-eastern highlands of Ethiopia. Forest Ecol Manag. 232:90–99.
   Web of Science ®Google Scholar
• Zhao Z, Yang Q, Benoy G, Chow TL, Xing Z, Rees HW, Meng FR. 2010. Using artificial neural network models to produce soil organic carbon content distribution maps across landscapes. Can J Soil Sci. 90:75–87.
   Web of Science ®Google Scholar
• Zinn YL, Lal TR, Resck DVS. 2005. Texture and organic carbon relations described by a profile pedotransfer function for Brazilian Cerrado soils. Geoderma. 127:168–173.
   Web of Science ®Google Scholar
• Zurada JM, Malinowski A, Cloete I. 1994. Sensitivity analysis for minimization of input data dimension for feed forward neural network. Paper presented at: Proceedings IEEE International Symposium May 30; London (UK).
   Google Scholar