Application of spatial statistic in assessing canopy cover variation of rangeland plant species of sheep fescue
Subject Areas : forestamir hoseim kavian por 1 , ardavan ghorbani 2 , gholam ali heshmati 3
1 - Ph.D Student of Range Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
2 - Assistant Professor, Dept. of Range and watershed Management, Faculty of Agricultural Technology and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
3 - Profesor, Dept. of Range and watershed Management; Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
Keywords: Festuca ovina, IDW, Canopy cover changes, spatial statistic, Kriging,
Abstract :
According to the continuous changes in natural ecosystems, particularly rangelands, and variety of affecting factors and the cost of direct measurement, the application of new techniques in different studies is necessary. In this study the capability of spatial statistical techniques in the assessment of canopy cover variation of Festuca ovina L. species was investigated. Canopy cover was recorded using plots at 45 sites. Then Inverse Distance Weighted (IDW) and Kriging were used for interpolating and estimating of F. ovina canopy cover using GS+5 and ArcGIS10. Results showed that the best variogram was exponential, and simple and ordinary Kriging were the best interpolation methods in comparison with the other methods according to the results maps accuracy assessments. Effective range of F.ovina canopy cover (48300 meter) is close to some chemical and physical soil properties including, acidity in the second depth (51500m), and organic matter in the second depth (47710m), clay in the first depth and sand in the first and second depths (49400m). Spatial variability of mentioned soil characteristics have affected the percentage of F. ovina canopy cover and at the distance greater than effective range, samples have no spatial dependence. To investigate the relationships between mentioned soil characteristics and canopy cover of F. ovina, and the optimal sampling interval can be considered between 47710 to 49400 meters. Results of this study show that spatial statistic can be used for evaluating canopy cover of rangeland species variability.
1-Arzani, H., S.H. Kaboli, H. Mirdavoudi, M. Farahpour, M.S. Azimi, 2008. Reliability of ETM+ and TM data for estimating vegetation cover of arid areas rangelands (case study Markazi province of Iran). Iranian Journal of Range and Desert Research 15 (3): 320-347.
2-Cambardella, C.A., T.B. Moorman, T.B. Parkin, D.L. Karlen, R.F. Turco, A.E. Konopka, 1994. Field scale variability of soil properties in Central Iowa soils. Soil Science Society of America Journal. 58: 1501-1511.
3-Dowling A.J., A.A. Webb, J.C. Scanlon, 1986. Surface soil chemical and physical patterns in a brig low-Dawson gum forest, central Queensland. Journal. of Ecology 11(2):155-162.
4-Einax, J.W., U. Soldt, 1999. Geostatistic and multivariate statistical methods for the assessment of polluted soil-merits and limitations. Chemometrica and Intelligent Laboratory System 49:79-91.
5-Fan, F., Q. Wang., Y. Wang, 2007. Land use and land cover change in Guangzhou, China, from 1998 to 2003, based on Landsat TM/ETM+ imagery. Sensors 7: 1323-1342.
6-Ghanbari, F, 2008. Predicting the spatial distribution of forest allometric characteristics using geostatistics and GIS. MSc Thesis. Gorgan University of agricultural sciences and natural resources, 160 pp.
7-Ghorbani, A., J. Sharifi, A.H. Kavianpoor, B. Malekpour, F. Aghche Gheshlagh, 2013. Iranian Journal of Range and Desert Research 20 (2): 379-396.
8-Goovaerts, P., 1997. Geostatistics for natural resources evaluation. Oxford University Press, New York. 483 pp.
9-Jacob, H., G. Clarke, 2002. " Methods of Soil Analysis, Part 4, Physical Method", Soil Science Society of America, Inc, Madison, Wisconsin, USA, 1692 pp.
10-Jurado-Exposito, M., F. Lopez-Granados, J.L. Gonzalez-Andujar, L. Garcia-Torres, 2005. Spatial and temporal analysis of Convolvulus arvensis L. populations over four growing seasons. European Journal Agronomy 21 (4): 287–296.
11-Hasani pak, A., 2007. Geostatistics, Tehran University Press, 314 pp. (In Persian)
12-Kavianpoor, A.H., A. Esmali Ouri, Z. Jafarian Jeloudar, A. Kavian, 2012. Spatial Variability of Some Chemical and Physical Soil Properties in Nesho Mountainous Rangelands, American Journal of Environmental Engineering 2(1): 34-44.
13-Kavianpoor, A.H., A. Esmali Ouri, Z. Jafarian Jeloudar, A. Kavian, 2013. Investigation on variability of runoff and soil loss in summer rangeland of Nesho in Mazandaran province, Iran-Watershed Management Science & Engineering 21: 59-66.
14-Kumke, T., A. Schoonderwaldt, U. Kienel, 2005. Spatial variability of sedimentological properties in a large Siberian lake, Aquatic Sciences 67: 86–96.
15-Knudsen, D., G.A. Peterson, P.F. Pratt, 1982. Lithium, sodium, potassium. In Methods of soil analysis, part 2, ed. A. L. Page. Madison, Wisc.: ASA-SSSA.
16-Lefsky, M.A., W.B. Cohen, 2003. Selection of remotely sensed data. In M.A. Wulder and S.E. Franklin (editors), Remote Sensing of Forest Environments: Concepts and case studies, Kluwer Academic Publishers, Boston, USA. 13–46p.
17-Li, H.B. & J.F. Reynolds, 1995. ‘On definition and quantification of heterogeneity’, Oikos73, 280–284.
18-Lu, D., P. Mausel, E. Brondi'Zio, E. Moran, 2004. Change detection techniques. International Journal of Remote Sensing 25: 2365–2407.
19-McLean, E.O., 1982. Soil pH and lime requirement. In Methods of soil analysis, part 2, ed. A. L. Page. Madison, Wisc.: ASA-SSSA.
20-Mohammadi, J., 2006. pedometery (spatial statistics), Pelk Press, 453 pp. (In Persian)
21-Nelson, D.W., L.E. Sommers, 1982. Total carbon and organic matter. In Methods of soil analysis, part 2, ed. A. L. Page. Madison, Wisc.: ASA-SSSA.
22-Olsen, S.R., L.E. Sommers, 1982. Phosphorus. P. 403- 430. In A. L. Page (ed), Methods of soil analysis, Agron. No. 9, Part 2: Chemical and microbiological properties, 2nd ed., Am. Soc. Agron., Madison, WI, USA.
23-Polhaman, H., 1993. Geostatistical modeling of environment data. Catena 20:191-198.
24-Tahmasebi, A., 2003. Study of Vegetation Cover and Soil in Relation to Geomorphology Units Watershed using GIS. Thesis submitted for MSc. Tarbiat modarres University. 67 Pp.
25-Webster, R. & M.A. Oliver, 2000. Geostatistics for Environmental Scientists. John Wiley and sons, Brisbane, Australia. 271pp.