Skip to main content

Advertisement

SpringerLink
Log in

Agricultural land suitability assessment for agricultural productivity based on GIS modeling and multi-criteria decision analysis: the case of Tekirdağ province

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Grains play a significant role in meeting the nutritional needs of the increasing world population. Consequently, the need for new studies on agricultural production and land suitability assessments has increased. The present paper aims to perform agricultural land suitability assessment to evaluate agricultural productivity in Tekirdağ province to determine precise productive agricultural areas. This study combines a variety of datasets to develop a dynamic model using GIS-based multi-criteria decision analysis for land suitability assessment and agricultural productivity. The datasets used in this study are supported by terrestrial samples and processed with spatial technologies. The results of the study indicate that the agricultural potential of the provincial lands is quite high. It reveals that 65.7% of province lands are suitable for agricultural production. Of the remaining lands, 20.3% is marginally suitable while only 8% of the land is unsuitable for agricultural production. In the northwestern part, suitable land for agricultural productivity is higher compared to other parts of the study area. This part also corresponds to the areas where industrial activities are marginal. The results also imply that agricultural activities in grain production areas must be reconsidered and replanned according to the new classification of land suitability assessment. In this respect, our study suggests that the policymakers and the government should take necessary steps to ensure the protection and sustainability of agricultural lands while planning for the industrial and settlement development in grain production areas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

On demand.

Code availability

Not applicable.

References

  • Abeysingha, N. S., Singh, M., Sehgal, V. K., Khanna, M., Pathak, H., Jayakody, P., & Srinivasan, R. (2015). Assessment of water yield and evapotranspiration over 1985 to 2010 in the Gomti River basin in India using the SWAT model. Current Science, 108 (12), 2202–2212. http://www.jstor.org/stable/24905656

  • Agriculture Report. (2019). Agriculture Report of Tekirdağ Agriculture and Forest Province Directorate. Tekirdağ.

  • Akgul, M., & Basayigit, L. (2005). Detailed soil survey and mapping of Suleyman Demirel Universitiy farming land. Suleyman Demirel University Journal of Institute of Natural and Applied Sciences, 9(3), 1–10.

    Google Scholar 

  • Akıncı, H., Özalp, A. Y., & Turgut, B. (2013). Agricultural land use suitability analysis using GIS and AHP technique. Computers and Electronics in Agriculture, 97, 71–82. https://doi.org/10.1016/j.compag.2013.07.006

    Article  Google Scholar 

  • Aldababseh, A., Temimi, M., Maghelal, P., Branch, O., & Wulfmeyer, V. (2018). Multi-criteria evaluation of irrigated agriculture suitability to achieve food security in an arid environment. Sustainability, 10(3), 803. https://doi.org/10.3390/su10030803

    Article  Google Scholar 

  • Arabameri, A., Pradhan, B., Rezaei, K., & Conoscenti, C. (2019). Gully erosion susceptibility mapping using GIS-based multi-criteria decision analysis techniques. CATENA, 180, 282–297. https://doi.org/10.1016/j.catena.2019.04.032

    Article  Google Scholar 

  • Arsanjani, J. J., Helbich, M., Kainz, W., & Boloorani, A. D. (2013). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21, 265–275. https://doi.org/10.1016/j.jag.2011.12.014

    Article  Google Scholar 

  • Arslan, M. (2016). The effect of organic fertilizer use on yield and some yield properties in silage maize cultivation. Research Journal of Agricultural Sciences, 9(2), 37–41.

    Google Scholar 

  • Ates, K., & Turan, V. (2015). Some soil characteristics and the fertility status of agricultural soils in Bingöl central district. Turkish Journal of Agricultural Research, 2(2), 108–113.

    Google Scholar 

  • Balezentis, T., Chen, X., Galnaityte, A., & Namiotko, V. (2020). Optimizing crop mix with respect to economic and environmental constraints: An integrated MCDM approach. Science of the Total Environment, 705, 135896. https://doi.org/10.1016/j.scitotenv.2019.135896

    Article  CAS  Google Scholar 

  • Basa, S., Kurt, S., Yasavul, E., & Ucar, A. (2017). Management of wastewater of settlement areas in potable water basins within Tekirdağ province. The Turkish Journal of Occupational/environmental Medicine and Safety (TURJOEM), 21(3), 365–376.

    Google Scholar 

  • Boroushaki, S., & Malczewski, J. (2010). Using the fuzzy majority approach for GIS-based multicriteria group decision-making. Computers & Geosciences, 36, 302–312. https://doi.org/10.1016/j.cageo.2009.05.011

    Article  Google Scholar 

  • Caglayan, I., Yesil, A., Cieszewski, C., Gul, F. K., & Kabak, O. (2020). Mapping of recreation suitability in the Belgrad Forest Stands. Applied Geography, 116, 102153. https://doi.org/10.1016/j.apgeog.2020.102153

    Article  Google Scholar 

  • Chen, Y., Yu, J., & Khan, S. (2010). Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation. Environmental Modelling & Software, 25, 1582–1591.

    Article  Google Scholar 

  • Chief Inspectorate of Environmental Protection. (2020). CORINE Land Cover (CLC) Programme. Chief Inspectorate of Environmental Protection.

  • Cimrin, K. M., & Boysan, S. (2006). Nutrient status of Van agricultural soils and their relationships with some soil properties. Yuzuncu Yil University Journal of Agricultural Sciences, 16(2), 105–111.

    Google Scholar 

  • Darwish, K. M., Wahba, M., & Awad, F. (2006). Agricultural soil suitability of haplo-soils for some crops in newly reclaimed areas of Egypt. Journal of Applied Sciences Research, 2(12), 1235–1243.

    Google Scholar 

  • Dengiz, O., Ozdemir, N., Ozturk, E., & Yakupoglu, T. (2009). Classification of hazelnut cultivation areas for agricultural suitability in the easter Black Sea region, case study; Unye-Tekkiraz district. Anadolu Journaş of Agricultural Sciences, 24(3), 174–183.

    Google Scholar 

  • Dengiz, O., & Özcan, H. (2006). Determination of productivity index (PI) of soils of Samsun-Bafra Plain using GIS technique. Selcuk University Journal of Faculty of Agriculture, 20(38), 136–142.

    Google Scholar 

  • Dengiz, O., & Sarıoglu, F. E. (2011). General distribution of potential agricultural areas of Samsun Province and importance of soil survey and mapping. Anadolu Journal of Agricultural Sciences, 26(3), 241–250.

    Google Scholar 

  • Dengiz, O., & Sarıoglu, F. E. (2013). Parametric approach with linear combination technique in land evaluation studies. Journal of Agricultural Sciences, 19, 101–112.

    Google Scholar 

  • Dindaroglu, T., & Canbolat, M. Y. (2011). Evaluation of soil quality in Kuzgun Dam Lake water production basin. Journal of Agricultural Faculty of Atatürk University, 42(2), 145–151.

    Google Scholar 

  • DSI. (2018). DSI (The General Directorate of State Hydraulic Works) 2018 Activity Report. Tekirdağ State Hydraulic Works 113th Branch Directorate. Tekirdağ.

  • El Baroudy, A. A. (2011). Land evaluation by integrating remote sensing and GIS for cropping system analysis in Siwa Oasis, Western Desert of Egypt. Egypt. Journal of Soil Sciences, 51, 211–222.

    Google Scholar 

  • El Baroudy, A. A. (2016). Mapping and evaluating land suitability using a GIS-based model. CATENA, 140, 96–104. https://doi.org/10.1016/j.catena.2015.12.010

    Article  CAS  Google Scholar 

  • Elsheikh, R., Sharif, A. R. B. M., Amiri, F., Ahmad, N. B., Balasundram, S. K., & Soom, M. A. M. (2013). Agriculture land suitability evaluator (ALSE): A decision and planning support tool for tropical and subtropical crops. Computers and Electronics in Agriculture, 93, 98–110. https://doi.org/10.1016/j.compag.2013.02.003

    Article  Google Scholar 

  • FAO. (1983). Guidelines. Land evaluation for rainfed agriculture. Rome: FAO Soils Bulletin No. 52.

  • FAO. (1985). Guidelines. Land evaluation for irrigated agriculture. Rome: FAO Soils Bulletin No. 55.

  • Farmer Registration System Report. (2019). Crop production statistics of Tekirdağ province. Farmer Registration System. Tekirdağ.

  • Fourcaud, T., Zhang, X., Stokes, A., Lambers, H., & Korner, C. (2008). Plant growth modelling and applications: The increasing importance of plant architecture in growth models. Annals Botany, 101, 1053–1063.

    Article  Google Scholar 

  • Gao, L. Z. (2001). Digital agriculture and agricultural development in China. Computer and Agriculture, 9, 1–3.

    Google Scholar 

  • Gbanie, S. P., Tengbe, P. B., Momoh, J. S., Medo, J., & Kabba, V. T. S. (2013). Modelling landfill location using geographic information systems (GIS) and multi-criteria decision analysis (MCDA): Case study Bo. Southern Sierra Leone. Applied Geography, 36, 3–12. https://doi.org/10.1016/j.apgeog.2012.06.013

    Article  Google Scholar 

  • GDM-ATLAS. (2020). Topographical and digital maps of Tekirdağ province (scale: 1:100.000). General Directorate of Mapping, Ankara.

  • Hamzeh, S., Mokarram, M., & Alavipanah, S. K. (2014). Combination of fuzzy and AHP methods to assess land suitability for barley: Case study of semi arid lands in the southwest of Iran. Desert, 19, 173–181. https://doi.org/10.22059/JDESERT.2014.52346

  • Hanan, J. S., & Hearn, A. B. (2003). Linking physiological and architectural models of cotton. Agricultural Systems, 75(1), 47–77.

    Article  Google Scholar 

  • Horuz, A., & Dengiz, O. (2018). The relationships between some physico-chemical properties and nutrient element content of paddy raised on alluvial land in Terme region. Journal of Agricultural Sciences, 33, 58–67. https://doi.org/10.7161/omuanajas.310249

    Article  Google Scholar 

  • İkincikarakaya, S. Ü., Beyaz, K. B., & Rezaei, F. (2013). Natural resources and agriculture. Turkish Journal of Scientific Reviews, 6(1), 104–109.

    Google Scholar 

  • Jahan, A., Edwards, K. L., & Bahraminasab, M. (2016). Multi-criteria decision analysis for supporting the selection of engineering materials in product design. Butterworth-Heinemann.

    Google Scholar 

  • Jaklič, T., Debeljak, M., Zgajnar, J., & Juvančič, L. (2018). Incorporation of emergy into multiple-criteria decision analysis for sustainable and resilient structure of dairy farms in Slovenia. Agricultural Systems, 164. https://doi.org/10.1016/j.agsy.2018.03.005

  • Jin, Z. Q. (1996). Studies of simulation on effects of globe climate changes on food production in China. PhD thesis, Nanjing University, Jiangsu, China.

  • Joerin, F., Thériault, M., & Musy, A. (2001). Using GIS and outranking multicriteria analysis for land-use suitability assessment. International Journal of Geographical Information Science, 15, 153–174.

    Article  Google Scholar 

  • Jones, J. W., Keating, B. A., & Porter, C. H. (2001). Approaches to modular model development. Agricultural Systems, 70, 421–443.

    Article  Google Scholar 

  • Kamali, F. P., Borges, J. A., Meuwissen, M. P., de Boer, I. J., & Lansink, A. G. O. (2017). Sustainability assessment of agricultural systems: The validity of expert opinion and robustness of a multi-criteria analysis. Agricultural Systems, 157, 118–128. https://doi.org/10.1016/j.agsy.2017.07.013

    Article  Google Scholar 

  • Kayacetin, F. (2006). Seed production of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.). Biotech Studies, 15, 1–2.

    Google Scholar 

  • Kong, C., Lan, H., Yang, G., & Xu, K. (2016). Geo-environmental suitability assessment for agricultural land in the rural–urban fringe using BPNN and GIS: A case study of Hangzhou. Environmental Earth Sciences, 75, 1136. https://doi.org/10.1007/s12665-016-5956-z

    Article  CAS  Google Scholar 

  • Kontgis, C., Schneider, A., Ozdogan, M., Kucharik, C., Duc, N. H., & Schatz, J. (2019). Climate change impacts on rice productivity in the Mekong River Delta. Applied Geography, 102, 71–83. https://doi.org/10.1016/j.apgeog.2018.12.004

    Article  Google Scholar 

  • Korkmaz, K. (2007). Global warming and effect on agricultural applications. Alatarım, 6(2), 43–49.

    Google Scholar 

  • Kourtit, K., Macharis, C., & Nijkamp, P. (2014). A multi-actor multi-criteria analysis of the performance of global cities. Applied Geography, 49, 24–36. https://doi.org/10.1016/j.apgeog.2013.09.006

    Article  Google Scholar 

  • Kremer, P., & DeLiberty, T. L. (2011). Local food practices and growing potential: Mapping the case of Philadelphia. Applied Geography, 31(4), 1252–1261. https://doi.org/10.1016/j.apgeog.2011.01.007

    Article  Google Scholar 

  • Krois, J., & Schulte, A. (2014). GIS-based multi-criteria evaluation to identify potential sites for soil and water conservation techniques in the Ronquillo watershed, northern Peru. Applied Geography, 51, 131–142. https://doi.org/10.1016/j.apgeog.2014.04.006

    Article  Google Scholar 

  • Kumar, S., & Hassan, M. I. (2013). Selection of a landfill site for solid waste management: An application of AHP and spatial analyst tool. Journal of the Indian Society of Remote Sensing, 41, 45–56. https://doi.org/10.1007/s12524-011-0161-8

    Article  Google Scholar 

  • Liliane, T. N., & Charles, M. S. (2020). Factors affecting yield of crops, agronomy-climate change & food security. Edited by Amanullah, IntechOpen,. https://doi.org/10.5772/intechopen.90672

    Article  Google Scholar 

  • Liu, D., Tang, W., Liu, Y., Zhao, X., & He, J. (2017). Optimal rural land use allocation in central China: Linking the effect of spatiotemporal patterns and policy interventions. Applied Geography, 86, 165–182. https://doi.org/10.1016/j.apgeog.2017.05.012

    Article  Google Scholar 

  • Malczewski, J. (2004). GIS-based land-use suitability analysis: A critical overview. Progress in Planning, 62, 3–65.

    Article  Google Scholar 

  • Malczewski, J. (2006). GIS-based multi-criteria decision analysis: A survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.

    Article  Google Scholar 

  • Malczewski, J., & Rinner, C. (2015). Multicriteria decision analysis in geographic information science. Advances in Geographic Information Science. New York, pp. 220–228.

  • Mighty, M. A. (2015). Site suitability and the analytic hierarchy process: How GIS analysis can improve the competitive advantage of the Jamaican coffee industry. Applied Geography, 58, 84–93. https://doi.org/10.1016/j.apgeog.2015.01.010

    Article  Google Scholar 

  • Mishelia, A., & Zirra, E. M. (2015). Application of geographic information system (G.I.S) in evaluating suitable areas for wheat cultivation in Adamawa State Nigeria. International Journal of Scientific Knowledge, 6, 14–22.

    Google Scholar 

  • Mokarram, M., Rangzan, K., Moezzi, A., & Baninemehc, J. (2010). Land suitability evaluation for wheat cultivation by fuzzy theory approach as compared with parametric method. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 140–145.

    Google Scholar 

  • Montgomery, B., Dragicevic, S., Dujmovic, J., & Schmidt, M. (2016). A GIS-based logic scoring of preference method for evaluation of land capability and suitability for agriculture. Computer Electronics in Agriculture, 124, 340–353.

    Article  Google Scholar 

  • Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885–900.

    Article  Google Scholar 

  • Moriasi, D. N., Gitau, M. W., Pai, N., & Daggupati, P. (2015). Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of the ASABE, 58(6), 1763–1785. https://doi.org/10.13031/trans.58.10715

  • Nouri, H., Mason, R. J., & Moradi, N. (2017). Land suitability evaluation for changing spatial organization in Urmia County towards conservation of Urmia Lake. Applied Geography, 81, 1–12. https://doi.org/10.1016/j.apgeog.2017.02.006

    Article  Google Scholar 

  • Ozsahin, E., Ozdes, M., & Eroglu, I. (2019). Possible effects on economic sectors of climate change in TR21 Trakya region. In Eds: Konukçu F, Albut S, Alturk B. p. 169–177, Süleymanpaşa, Tekirdağ: Tekirdağ Namık Kemal University.

  • Ozsahin, E., & Eroglu, I. (2017). Spatiotemporal change of anthropogenic biomes (anthromes) of Tekirdağ province. lnternational Journal of Geography and Geography Education, 35, 218–227.

  • Ozsahin, E., & Eroglu, I. (2018). Land capability classification of Tekirdağ province according to ecological conditions. Istanbul, Turkiye, Kriter Yayınevi.

  • Ozyazıcı, M. A., Dengiz, O., & Imamoglu, A. (2014). Determination of some land and soil characteristics of Siirt province with geographic information system analysis. Turk J Agric Res, 1(2), 128–137.

    Google Scholar 

  • Pan, G., & Pan, J. (2012). Research in crop land suitability analysis based on GIS. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. pp.314–325.

  • Patel, N. N., Angiuli, E., Gamba, P., Gaughan, A., Lisini, G., Stevens, F. R., & Trianni, G. (2015). Multitemporal settlement and population mapping from Landsat using Google Earth Engine. International Journal of Applied Earth Observation and Geoinformation, 35, 199–208.

    Article  Google Scholar 

  • Pramanik, M. K. (2016). Site suitability analysis for agricultural land use of Darjeeling district using AHP and GIS techniques. Model. Earth Systems and Environment, 2, 56. https://doi.org/10.1007/s40808-016-0116-8

    Article  Google Scholar 

  • Riquier, J., Bramao, D. L., & Cornet, J. P. (1970). A new system of soil appraisal in terms of actual and potential productivity. FAO Soil Resources, Development and Conservation Service, Land and Water Development Division, FAO, Rome.

  • Rodriguez-Gallego, L., Achkar, M., & Conde, D. (2012). Land suitability assessment in the catchment area of four southwestern Atlantic coastal lagoons: Multicriteria and optimization modeling. Environmental Management, 50, 140–152. https://doi.org/10.1007/s00267-012-9843-4

    Article  Google Scholar 

  • Sadras, V., & Calderini, D. (2009). Crop physiology: Applications for genetic improvement and agronomy. Academic Press.

    Google Scholar 

  • Saglam, M., & Dengiz, O. (2013). The evaluating with factor and geostatistics analyses methods of soil chemical quality indices. Journal of Agriculture Faculty of Ege University, 50(2), 181–190.

    CAS  Google Scholar 

  • Sahin, S., & Cigizoglu, K. H. (2012). The sub-climate regions and the sub-precipitation regime regions in Turkey. Journal of Hydrology, 451, 180–189. https://doi.org/10.1016/j.jhydrol.2012.04.062

    Article  Google Scholar 

  • Sarı, H. & Özşahin, E. (2016). CORINE Sistemine Göre Tekirdağ İlinin AKAÖ (Arazi Kullanımı/Arazi Örtüsü) Özelliklerinin Analizi/Analysis of LULC (landuse/landcover) characteristics of Tekirdag province based on the CORINE system. Alinteri Journal of Agriculture Science, 30 (1), 13–26 . Retrieved from https://dergipark.org.tr/tr/pub/alinterizbd/issue/24325/257756

  • Schmitter, P., Kibret, K. S., Lefore, N., & Barron, J. (2018). Suitability mapping framework for solar photovoltaic pumps for smallholder farmers in sub-Saharan Africa. Applied Geography, 94, 41–57. https://doi.org/10.1016/j.apgeog.2018.02.008

    Article  Google Scholar 

  • Sys, C., Van Ranst, E., Debaveye, J., & Beernaert, F. L. (1991). Methods in land evaluation part III. International Training Center for Post Graduate Soil Scientists State University.

    Google Scholar 

  • Sys, C., Van Ranst, E., Debaveye, J., & Beernaert, F. L. (1993). Land evaluation part III, crop requirements. Agricultural Publications No. 7, ITC, Ghent.

  • Taghizadeh-Mehrjardi, R., Nabiollahi, K., Rasoli, L., Kerry, R., & Scholten, T. (2020). Land suitability assessment and agricultural production sustainability using machine learning models. Agronomy, 10, 573. https://doi.org/10.3390/agronomy10040573

    Article  Google Scholar 

  • Tasan, M., & Demir, Y. (2017). Determination of spatial distribution of iron and manganese contents with different interpolation methods at rice cultivated areas. Anadolu Journal of Agricultural Sciences, 32, 64–73. https://doi.org/10.7161/omuanajas.287480

    Article  Google Scholar 

  • Terh, S. H., & Cao, K. (2018). GIS-MCDA based cycling paths planning: A case study in Singapore. Applied Geography, 94, 107–118. https://doi.org/10.1016/j.apgeog.2018.03.007

    Article  Google Scholar 

  • TSMS. (2020). Climate measurement records (1970–2019). TSMS (Turkish State Meteorological Service), Ankara.

  • Tugay, M. E. (2012). The way of increasing of agricultural production in Turkey. Research Journal of Agricultural Sciences, 5(1), 1–8.

    Google Scholar 

  • TUIK. (2020). Crop production statistics. Turkish Statistical Institute (TUIK). Ankara.

  • Vanolya, N. M., Jelokhani-Niaraki, M., & Toomanian, A. (2019). Validation of spatial multicriteria decision analysis results using public participation GIS. Applied Geography, 112, 102061. https://doi.org/10.1016/j.apgeog.2019.102061

    Article  Google Scholar 

  • Vurarak, Y., & Bilgili, M. E. (2015). Agricultural mechanization, erosion, and carbon emission: A review. Anadolu Journal of Agricultraul Sciences, 30, 307–316. https://doi.org/10.7161/anajas2015.30.3.307-316

    Article  Google Scholar 

  • West, J. (2019). Multi-criteria evolutionary algorithm optimization for horticulture crop management. Agricultural Systems, 173, 469–481. https://doi.org/10.1016/j.agsy.2019.03.016

    Article  Google Scholar 

  • Yalew, S. G., van Griensven, A., & van der Zaag, P. (2016). AgriSuit: A web-based GIS-MCDA framework for agricultural land suitability assessment. Computers and Electronics in Agriculture, 97, 71–82. https://doi.org/10.1016/j.compag.2016.08.008

    Article  Google Scholar 

  • Yılmaz, G., & Kınay, A. (2015). Determination of yield and yield components some sunflower (Helianthus annuus L.) varieties in Tokat-Kazova conditions. Anadolu Journal of Agricultral Sciences, 30, 281–286. https://doi.org/10.7161/anajas.2015.30.3.281-286

    Article  Google Scholar 

  • Zabihi, H., Alizadeh, M., Kibet Langat, P., Karami, M., Shahabi, H., Ahmad, A., Nor Said, M., & Lee, S. (2019). GIS multi-criteria analysis by ordered weighted averaging (OWA): Toward an integrated citrus management strategy. Sustainability, 11(4), 1009. https://doi.org/10.3390/su11041009

    Article  Google Scholar 

  • Zengin, M., Cetin, U., Ersoy, I., & Ozaytekin, H. H. (2003). Determination of the fertility status of Beyşehir district soils. Selcuk University Journal of Faculty of Agriculture, 17(31), 24–30.

    Google Scholar 

  • Zhang, J., Su, Y., Wu, J., & Liang, H. (2015). GIS based land suitability assessment for tobacco production using AHP and fuzzy set in Shandong province of China. Computers and Electronics in Agriculture, 114, 202–211. https://doi.org/10.1016/j.compag.2015.04.004

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Arts and Sciences, Department of Geography, Tekirdağ Namık Kemal University, Tekirdağ, Turkey

    Emre Ozsahin

  2. Faculty of Engineering, Environmental Engineering, Tekirdağ Namık Kemal University, Tekirdağ, Turkey

    Mehmet Ozdes

Authors
  1. Emre Ozsahin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mehmet Ozdes
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

EO conceived and designed the analysis, collected the data, and performed the analysis. MO contributed to data and analysis, wrote the paper, and other contributions.

Corresponding author

Correspondence to Emre Ozsahin.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Table 8 Ratio of factors and variables affecting agricultural productivity
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ozsahin, E., Ozdes, M. Agricultural land suitability assessment for agricultural productivity based on GIS modeling and multi-criteria decision analysis: the case of Tekirdağ province. Environ Monit Assess 194, 41 (2022). https://doi.org/10.1007/s10661-021-09663-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-021-09663-1

Keywords

Search

Navigation