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Determination of land productivity index based on parametric approach using GIS technique

Year 2012, Volume: 1 Issue: 1, 51 - 57, 01.03.2012

Abstract

The land productive capacity can be evaluated directly or indirectly. Direct evaluations are carried out in the field, greenhouses or laboratory by means of some experiments under given climatic and management conditions. Indirect evaluations consist basically in developing and applying models of varying complexity, thereby attempting to estimate land productivity. The main objective of this research was to determine land productivity index based on parametric approach using GIS. This study was carried out in Çetinkaya district located on Bafra Delta Plain. The study area covers about 1762.4 ha. After analysing and evaluating topographic, soil physical and chemical properties, result map was generated for land productivity index (LPI) by means of GIS. After LPI taking into rating of soil and topographic parameters was calculated using square root formula, productivity classification was determined for each land mapping unit. According to results, while most of the study area’s land productivity (45.4%-800.0 ha) consist of excellent and good classes (I and II) in terms of agricultural uses, it was found that 19.7% (346.6 ha) of study area has average (III), 25.1% (441.6) of it has poor (IV) and rest of it (9.8%) has extremely poor or nil (V).

References

  • Ardahanloğlu, I., Öztas, T., Evren, S., Yılmaz, T., Yıldırım, Z.N., 2003. Spatial variability of exchangeable sodium, electrical conductivity, Dengiz, O. 2007. Assessment of Soil Productivity and Erosion Status for the Ankara-Sogulca Catchment Using GIS. International Journal of Soil Science 2 (1), 15-28.
  • Dengiz, O., Ozcan, H., Köksal, E.S., Baskan, O., Kosker, Y., 2010. Sustainable Natural Resource Management and Environmental Assessment in The Salt Lake (Tuz Golu) Specially Protected Area. Journal of Environmental Monitoring and Assessment 161: 327-342.
  • Delgado, F., Lopez, R., 1998. Evaluation of soil Development Impact on the Productivity of Venezuelan Soils. Adv. Geo. Ecol. 31: 133-142
  • Devi, G.M.G., Kumar, K.S.A., 2008. Remote Sensing and GIS Application for Land Quality Assessment for Coffee Growing Areas of Karnataka. Journal of the Indian Society of Remote Sensing 36, 89-97.
  • Eswaran, H., Bienforth, F.H., Reich, P., 2003. A global Assessment of Land Quality. In: Wiebe (ed.) Land Quality, Agricultural Productivity and Food Security: Biophysical Processes and Economic Choices at Local, Regional and Global Levels. Publ. Edward Elgar Northampton, MA. USA, pp 112-132.
  • Fresco, L. O., Huizing, H., Keulen, H. v., Luning, H. A., Schipper, R. A., 1994. Land Evaluation and Farming Systems Analysis for Land Use Planning. FAO Working Document.
  • Pieri, C., Dumanski, J., Hamblin, A., Young, A., 1995. Land quality indicators. World Bank Discussion Papers 315. Washington: World Bank.
  • Southorn, N., Cattle, S., 2000. Monitoring soil quality for central tablelands grazing systems. Communications in Soil Science and Plant Analysis, 31, 2211–2229.
  • Soil Survey Staff, 1999. Soil Taxonomy. A Basic of soil classification for making and interpreting soil survey. USDA Handbook No: 436, Washington D.C. USA.
  • Wander, M.M., Bollero, G.A., 1999. Soil quality assessment of tillage impacts in Illinois. Soil Science Society of America Journal, 63, 961–971.
Year 2012, Volume: 1 Issue: 1, 51 - 57, 01.03.2012

Abstract

References

  • Ardahanloğlu, I., Öztas, T., Evren, S., Yılmaz, T., Yıldırım, Z.N., 2003. Spatial variability of exchangeable sodium, electrical conductivity, Dengiz, O. 2007. Assessment of Soil Productivity and Erosion Status for the Ankara-Sogulca Catchment Using GIS. International Journal of Soil Science 2 (1), 15-28.
  • Dengiz, O., Ozcan, H., Köksal, E.S., Baskan, O., Kosker, Y., 2010. Sustainable Natural Resource Management and Environmental Assessment in The Salt Lake (Tuz Golu) Specially Protected Area. Journal of Environmental Monitoring and Assessment 161: 327-342.
  • Delgado, F., Lopez, R., 1998. Evaluation of soil Development Impact on the Productivity of Venezuelan Soils. Adv. Geo. Ecol. 31: 133-142
  • Devi, G.M.G., Kumar, K.S.A., 2008. Remote Sensing and GIS Application for Land Quality Assessment for Coffee Growing Areas of Karnataka. Journal of the Indian Society of Remote Sensing 36, 89-97.
  • Eswaran, H., Bienforth, F.H., Reich, P., 2003. A global Assessment of Land Quality. In: Wiebe (ed.) Land Quality, Agricultural Productivity and Food Security: Biophysical Processes and Economic Choices at Local, Regional and Global Levels. Publ. Edward Elgar Northampton, MA. USA, pp 112-132.
  • Fresco, L. O., Huizing, H., Keulen, H. v., Luning, H. A., Schipper, R. A., 1994. Land Evaluation and Farming Systems Analysis for Land Use Planning. FAO Working Document.
  • Pieri, C., Dumanski, J., Hamblin, A., Young, A., 1995. Land quality indicators. World Bank Discussion Papers 315. Washington: World Bank.
  • Southorn, N., Cattle, S., 2000. Monitoring soil quality for central tablelands grazing systems. Communications in Soil Science and Plant Analysis, 31, 2211–2229.
  • Soil Survey Staff, 1999. Soil Taxonomy. A Basic of soil classification for making and interpreting soil survey. USDA Handbook No: 436, Washington D.C. USA.
  • Wander, M.M., Bollero, G.A., 1999. Soil quality assessment of tillage impacts in Illinois. Soil Science Society of America Journal, 63, 961–971.
There are 10 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Orhan Dengiz

Mustafa Sağlam This is me

Publication Date March 1, 2012
Published in Issue Year 2012 Volume: 1 Issue: 1

Cite

APA Dengiz, O., & Sağlam, M. (2012). Determination of land productivity index based on parametric approach using GIS technique. Eurasian Journal of Soil Science, 1(1), 51-57.