DETERMINATION OF AGRICULTURAL LAND SUITABILITY CLASSES FOR SAMSUN PROVINCE BASED ON PARAMETRIC AND HIERARCHY APPROACHES

Year 2019, Issue: 40, 490 - 506, 30.07.2019

İnci Demirağ Turan Orhan Dengiz

https://doi.org/10.32003/iggei.531850

Cited By: 1

Abstract

Land quality index is an important tool for
evaluating agro-ecosystem. The aim of this study is to determine and
agricultural land suitability classes for Samsun province based on two
different land quality indexes model (parametric-AKIg and hierarchy-AKIa)
approaches and to create maps of them. Total 995 soil samples were taken from
soil surface (0-20cm) in Samsun province covers about 9579 km². Total
data set (TDS) consists of nine land and physic-chemical soil properties (soil
depth, slope, texture, pH, EC, lime content, nitrogen, phosphorus, and
potassium. In order to generate MDS, principal component analysis was done.
Exponential and Gaussian of simple kriging models were used to generate
distribution map of the AKIa and AKIg suitability classes in TDS. According to
results, about 15% total study area is not suitable for agricultural activities
whereas, about 30% of it is suitable and highly suitable for agricultural
usage. In addition, Exponential simple of kriging models were used to generate
distribution map of the AKIa and AKIg suitability classes in MDS. According to
results, about 29.5% total study area was found as suitableand highly suitable for
agricultural activities in AKIa model while, about 22.1% of it is suitable and
highly suitable for agricultural usages in AKIg model. Moreover, the results of
linear correlation and kappa statistical analysis showed that land quality was
better estimated using AKIa, compared to the AKIg in TDS and MDS.

Keywords

Land Quality, Minimum Data Set, Principal Components Analysis, Samsun

PARAMETRİK VE HİYERARŞİK MODELSEL YAKLAŞIMLA SAMSUN İLİ ARAZİLERİNİN TARIMSAL ARAZİ UYGUNLUK SINIFLARIN BELİRLENMESİ

Abstract

Arazi kalite indeksi
agro-ekosistemlerinin değerlendirilmesinde önemli bir araçtır. Bu çalışmanın
amacı, parametrik (AKIg) ve hiyerarşik (AKIa) yaklaşımlı iki farklı arazi
kalite indeks modeli kullanılarak Samsun iline ait arazilerin tarımsal amaçlı
arazi uygunluk sınıflamasının belirlenmesi ve haritalanmasıdır. 9579
km² alana sahip olan Samsun ilinden 995 adet yüzey toprak
örneklemesi yapılmıştır. Arazi özelliklerinden derinlik
ve eğim, fizikokimyasal toprak özelliklerinden ise bünye, pH, EC, kireç,
verimlilik özelliklerinden ise fosfor, potasyum ve azot olmak üzere toplam 9
faktör ile toplam veri seti (TVS) oluşturulmuştur. Minimum
veri setin (MVS) oluşturulmasında ise temel bileşenler analizi uygulanmıştır.
TVS’ne göre AKIa ve AKIg modellerine ait dağılım haritalarının oluşturulmasında
Kriging’in basit üssel ve Gaussian
modelleri kullanılmıştır. Her iki modele göre çalışma alanının yaklaşık %15’i
işlemeli tarıma arazi kalitesi bakımından hiçbir zaman uygun değilken, yaklaşık
% 30’u ise çok uygun ve uygun olduğu belirlenmiştir. MVS’ne
göre AKIa ve AKIg modellerine ait dağılım haritalarının oluşturulmasında ise Kriging’in basit üssel ve doğal küresel modelleri
kullanılmıştır.  Buna göre, AKİa için
toplam alanın %29,5’si çok uygun ve uygun iken, AKİg yaklaşımı için % 22.1’i
uygun ve çok uygun sınıf olarak belirlenmiştir. Ayrıca, TVS ve MVS’ne göre AKIa
ve AKIg lineer korelasyon ve kappa istatistik analizleri ile
karşılaştırıldığında ise TVS-AKIa modelinin en yüksek değere sahip olduğu
belirlenmiştir. 

Keywords

Minimum Veri Seti, Arazi Kalitesi, Temel Bileşenler Analizi, Samsun

References

• Ahmed, G.B., Shariff, A.R.M., Balasundram, S.K. & bin Abdullah, A.F. (2016). Agriculture land suitability analysis evaluation based multi criteria and gıs approach. In IOP Conference Series: Earth and Environmental Science, 37(1), 1-8.
• Albaji, M. &Hemadi, J. (2011). Investigation of Different Irrigation Systems Based on the Parametric Evaluation Approach on the Dasht Bozorg Plain. Transactions of the Royal Society of South Africa, 66 (3), 163-169.
• Andrews, S.S., Karlen, D.L.& Mitchell, J.P. (2002b). A comparison of soil quality indices methods for vegetable production system in northern California. Agricultural Ecosystems Environmental, 90, 25-45.
• Andrews, S.S., Mitchell, J.P., Mancinelli, R., Karlen, K.L., Hartz, T.K., Horwath, W.R., Pettygrove, G.S., Scow, K.M.&Munk, D.S.(2002a). On-farm assessment of soil quality in California's central valley. Agronomy Journal,94,12-23.
• Biswas, S., Hazra, G.C., Purakayastha, T.J., Saha, N., Mitran, T., Roy, S.S., Basak, N.& Mandal, B. (2017). Establishment of critical limits of indicators and indices of soil quality in rice–rice cropping systems under different soil orders. Geoderma, 292, 34-48.
• Blecker, S.W., Stillings, L.L., Amacher, M.C., Ippolito, J.A.& DeCrappeo, N.M.(2012). Development of vegetation based soil quality indices for mineralized terrane in arid and semi-arid regions. Ecological Indicators, 20, 65-74.
• Bouyoucos, G.J. (1951). A Recalibration of the hydrometer method for making mechanical analysis of soil. Agronomy Journal, 43, 434-438.
• Bray, R.H.& Kurtz, L.T. (1945). Determination of total, organic, and available forms of phosphorus in soils. Journal of Soil Science, 59: 39-45.
• Briza, Y., Dileonardo, F.& Spisni, A. (2001). Land evaluation in the province of Ben Slimane, Morocco. 21st Course Professional Master. Remote Sensing and Natural Resource Evaluation. Florence, Italy.
• Cheng, J., Ding, C., Li, X., Zhang, T.& Wang, X. (2016). Soil quality evaluation for navel orange production systems in central subtropical China. Soil& Tillage Research, 155, 225-232.
• Cohen, J. (1960) A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46.
• Da Silva, A.F., Barbosa, A.P., Zimback, C.R.L., Landim, P.M.B.& Soares, A. (2015). Stimation of croplands using indicator kriging and fuzzy classification. Computers and Electronics in Agriculture, 111, 1-11.
• Dedeoğlu, M. &Dengiz, O. (2018). Coğrafi bilgi sistemleri ile entegre edilen çok kriterli karar destek analiz yaklaşımı kullanılarak arazi uygunluk sınıflarının belirlenmesi. Süleyman Demirel Üniversitesi Ziraat Fakültesi Dergisi, 13 (2), 60-72.
• Dengiz, O.& Sarıoglu, F.E. (2011). Samsun İlinin potansiyel tarım alanlarının genel dağılımları ve toprak etüd ve haritalama çalışmalarının önemi. Anadolu Tarım Bilimleri Dergisi, 26 (3), 241-253.
• Dengiz, O., Usul, M.& Keçeci, M. (2006). Atatürk Orman Çiftliği arazilerinin tarımsal kullanım durumlarının değerlendirilmesi. OMÜ Ziraat Fakültesi Dergisi, 21 (1), 55-64.
• Doran, J.W.& Parkin, B.T.(1994). Defining and assessing soil quality. In Doran, JW, Coleman, DC, Bezdicek, DF and Stewart, BA (Eds) ‘Defining Soil Quality for a Sustainable Environment’. Soil Science Society of America Special Publication No 35, Madison, WI., pp. 3-21.
• Fang, L.N.& Song, J.P. (2008).Cultivated land quality assessment based on SPOT multispectral remote sensing image: A case study in Jimo City of Shandong Province. Progress In Geography, 27 (5), 71-78.
• Food and Agricultural Organization (FAO). (1976). A Framevork for land evaluation: Soils Bulletin 32, Food and Agriculture Organization of the United Nations. Rome.
• Food and Agricultural Organization (FAO).(1993). FESLM:an international framework for evaluating sustainable landmanagement. World Resources Report 73. Rome: FAO
• Govaerts, B., Sayre, K.D.& Deckers, J. (2006). A minimum data set for soil quality assessment of wheat and maize cropping in the highlands of Mexico. Soil &Tillage Research, 87, 163-174.
• INPE (Instituto Nacional de Pesquisas Espaciais).(2001). Sistema de Processamento de Informaces Georeferencias −SPRING 3.5.1–Tutoriais. Sao Jose dos Campos: INPE.
• Jackson, M.L.(1958). Soil Chemical Analysis. NJ: Prentice- Hall. Inc.
• Karaatlı, M. (2010). Verilerin düzenlenmesi ve gösterimi.Ş.Kalaycı (Ed.),SPSS uygulamalı çok değişkenli istatistik teknikleriiçinde (s.2-47). Ankara:Asil Yayın Dağıtımı Ltd. Şti.
• Karlen, D.L., Mausbach, M.J., Doran, J.W., Cline, R.G., Harris, R.F.& Schuman, G.E.(1997). Soil quality: a concept, definition and framework for evaluation. Soil Science. Society of America Journal,61, 4-10.
• Larson, W.E.& Pierce, F.J.(1994). The Dynamics of Soil Quality as a Measure of Sustainable Management. Defining Soil Quality for a Sustainable Environment. Soil Science Society of America,37-52. Wisconsin.
• Nabiollahi, K., Taghizadeh-Mehrjardi R., Kerry, R.&Moradian, S. (2017). Assessment of soil quality indices for salt-affected agricultural land in Kurdistan Province, Iran. Ecological Indicators, 83, 482-494.
• Nakajima, T., Lal, R.& Jiang, S. (2015). Soil quality index of a crosby silt loam in central Ohio. Soil Tillage &Research, 146, 323–328.
• Olsen, S.R., Cole, C.V., Watanabe, F.S.& Dean, L.A. (1954). Estimation of available phosphorus in soils by extraction with sodium bicarbonate. USDA Circular Nr 939. Washington, D.C:US Gov. Print. Office.
• Patrono, A. (1998). Multi-criteria analysis and geographic ınformation systems: analysis of natural areas and ecological distributions.Environment and Management, 9, 271-292.
• Qi, Y., Darilek, J.L., Huang, B., Zhao, Y., Sun, W.& Gu, Z. (2009). Evaluating soil quality indices in an agricultural region of Jiangsu Province, China. Geoderma, 149, 325-334.
• Raiesi, F.& Kabiri, V. (2016). Identification of soil quality indicators for assessing the effect of different tillage practices through a soil quality index in a semi-arid environment. Ecological Indicators,71, 198–207.
• Saaty, T.L.(1980). The Analytic Hierarchy Process. (pp.37-85). New York:McGraw-Hill.
• Sanchez-Navarro, A., Gil-Vazquez, J.M., Delgado-Iniesta, M.J., Marin-Sanleandro, P., Blanco-Bernardeau, A.& Ortiz-Silla, R. (2015). Establishing an index and identification of limiting parameters for characterizing soil quality in Mediterranean ecosystems. Catena, 131, 35-45.
• Sarıoğlu, F.E. & Dengiz, O. (2012). Arazi değerlendirme çalışmalarında farklı parametrik yaklaşımların değerlendirilmesi. Toprak Su Dergisi, 1 (2): 75-79.
• Sharma, K.L., Mandal, U.K., Srnivas, K., Vittal, K.P.R., Mandal, B., Grace, J.K.& Ramesh, V. (2005). Long-term soil management effects on crop yields and soil quality in a dryland Alfisol. Soil & Tillage Research,83, 246–259.
• Shukla, M.K., Lal, R.& Ebinger, M. (2006). Determining soil quality indicators by factor analysis. Soil & Tillage Research,87, 194–204.
• Soil Survey Staff. (1992). Procedures for collecting soil samples and methods of analysis for soil survey. Soil Survey Invest. Rep. I. U.S. Gov. Print. Office, Washington D.C.
• Turan, M., Dengiz, O.& Turan Demirağ, İ. (2018). Samsun İlinin Newhall Modeline göre toprak sıcaklık ve nem rejimlerinin belirlenmesi. Türkiye Tarımsal Araştırmalar Dergisi, 5 (2), 131-142.
• Wander, M.M.& Bollero, G.A. (1999). Soil quality assessment of tillage impacts in Illi-nois Soil Science Society of America Journal, 63, 961-971.
• World Bank. (1997). Rural Development: From Vision to Action. Environmentally and Socially Sustainable development Studies and Monographs, Series no. 12, Washington, DC: World Bank.
• Wu, C., Liu, G., Huang, C.& Liu, Q. (2019). Soil quality assessment in Yellow River Delta: Establishing a minimum data set and fuzzy logic model. Geoderma, 334, 82-89.
• Yanbing Q, Jeremy L. D., Biao H., Yongcun Z., Weixia S.& Zhiquan G.(2009). Evaluating soil quality indices in an agricultural region of Jiangsu Province, China.Geoderma,149, 325-334.