Dynamics of agricultural land systems in western Mediterranean areas: a clustering approach based on the self-organizing map

Published: 18 October 2023
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In the present study, we implemented an unsupervised learning procedure, a self-organizing map (SOM), for characterizing the main agricultural land systems (ALS) in western Mediterranean areas. Input data derived from national agricultural censuses of two periods (2000 and 2010) at the municipality level. The SOM allowed us to aggregate the items into clusters based on the proximity between the associated input variables. The main clusters were then mapped back to the geographical space and interpreted in terms of ASL typologies. The main ALS from the census 2000 included one permanent grassland system with extensive farming; two arable land systems, corresponding to winter and summer crops; and two permanent cropland systems, relatable to intensively cultivated or marginal areas. The ALS from the census 2010 included only one arable land system with a non-intensive use of irrigation; two permanent cropland systems similar to those found in 2000; one more extensive permanent grassland system; and a mixed system characterized by permanent grassland and arable land. In summary, the main trends emerging from the transitions between the two censuses periods were: i) a reduction in agricultural land use; ii) an increase in utilized agricultural and irrigated area; iii) a contraction in arable land and permanent grassland. Using a data-driven approach such as SOM allowed us to discover hidden patterns in the input census data. Therefore, the prevalent agricultural typologies characterising the ALS in the two analysed periods resulted to be shaped by the reality of the surveyed area solely, with regard to its agronomic assessment.

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A Farm to Fork strategy, 2020. Available from: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52020DC0381 (accessed on 7th April 2023)
Abu Hammad A, Tumeizi A, 2012. Land degradation: Socioeconomic and environmental causes and consequences in the eastern mediterranean. Land Degrad. Dev. 23:216-26. DOI: https://doi.org/10.1002/ldr.1069
van Asselen S, Verburg PH, 2012. A Land System representation for global assessments and land-use modeling. Glob. Change Biol. 18:3125-48. DOI: https://doi.org/10.1111/j.1365-2486.2012.02759.x
Bajocco S, De Angelis A, Perini L, Ferrara A, Salvati L, 2012. The impact of Land Use/Land Cover Changes on land degradation dynamics: A Mediterranean case study. Environ. Manag. 49:980-9. DOI: https://doi.org/10.1007/s00267-012-9831-8
EU biodiversity strategy for 2030, 2021. Available from: https://op.europa.eu/en/publication-detail/-/publication/31e4609f-b91e-11eb-8aca-01aa75ed71a1 (accessed on 7th April 2023)
Bonet A, 2004. Secondary succession of semi-arid Mediterranean old-fields in south-eastern Spain: Insights for conservation and restoration of degraded lands. J. Arid Environ. 56:213-33. DOI: https://doi.org/10.1016/S0140-1963(03)00048-X
Debolini M, Marraccini E, Dubeuf JP, Geijzendorffer IR, Guerra C, Simon M, Targetti S, Napoléone C, 2018. Land and farming system dynamics and their drivers in the Mediterranean Basin. Land Use Policy 75:702-10. DOI: https://doi.org/10.1016/j.landusepol.2017.07.010
Debolini M, Schoorl JM, Temme A, Galli M, Bonari E, 2013. Changes in Agricultural Land Use Affecting Future Soil Redistribution Patterns: A Case Study in Southern Tuscany (Italy). Land Degrad. Dev. 26:574-86. DOI: https://doi.org/10.1002/ldr.2217
DrakeDrake NA VA, 2014. Review of spatial and temporal methods for assessing land degradation in the Mediterranean. Advances In Environmental Monitoring And Modelling 1:1-52.
Erb KH, Haberl H, Jepsen MR, Kuemmerle T, Lindner M, Müller D, Verburg PH, Reenberg A, 2013. A conceptual framework for analysing and measuring land-use intensity. Curr. Opin. Environ. Sustain. 5:464-70. DOI: https://doi.org/10.1016/j.cosust.2013.07.010
Estel S, Kuemmerle T, Alcántara C, Levers C, Prishchepov A, Hostert P, 2015. Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series. Remote Sens. Environ. 163:312-25. DOI: https://doi.org/10.1016/j.rse.2015.03.028
Estel S, Kuemmerle T, Levers C, Baumann M, Hostert P, 2016. Mapping cropland-use intensity across Europe using MODIS NDVI time series. Environ. Res. Lett. 11. DOI: https://doi.org/10.1088/1748-9326/11/2/024015
Eurostat, 2023. Eurostat Agriculture Glossary. Available from: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Category:Agriculture_glossary
Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A, Thau D, Stehman S V., Goetz SJ, Loveland TR, Kommareddy A, Egorov A, Chini L, Justice CO, Townshend JRG, 2013. High-resolution global maps of 21st-century forest cover change. Science 342:850-3. DOI: https://doi.org/10.1126/science.1244693
Hill J, Stellmes M, Udelhoven T, Röder A, Sommer S, 2008. Mediterranean desertification and land degradation. Mapping related land use change syndromes based on satellite observations. Glob. Planet. Change 64:146–57. DOI: https://doi.org/10.1016/j.gloplacha.2008.10.005
Huber R, Bakker M, Balmann A, Berger T, Bithell M, Brown C, Grêt-Regamey A, Xiong H, Le QB, Mack G, Meyfroidt P, Millington J, Müller B, Polhill JG, Sun Z, Seidl R, Troost C, Finger R, 2018. Representation of decision-making in European agricultural agent-based models. Agric. Syst. 167:143-60. DOI: https://doi.org/10.1016/j.agsy.2018.09.007
Jansen LJM, Di Gregorio A, 2002. Parametric land cover and land-use classifications as tools for environmental change detection. Agric. Ecosyst. Environ. 91:89-100. DOI: https://doi.org/10.1016/S0167-8809(01)00243-2
Jepsen MR, Kuemmerle T, Müller D, Erb K, Verburg PH, Haberl H, Vesterager JP, Andrič M, Antrop M, Austrheim G, Björn I, Bondeau A, Bürgi M, Bryson J, Caspar G, Cassar LF, Conrad E, Chromý P, Daugirdas V, Van Eetvelde V, Elena-Rosselló R, Gimmi U, Izakovicova Z, Jančák V, Jansson U, Kladnik D, Kozak J, Konkoly-Gyuró E, Krausmann F, Mander Ü, McDonagh J, Pärn J, Niedertscheider M, Nikodemus O, Ostapowicz K, Pérez-Soba M, Pinto-Correia T, Ribokas G, Rounsevell M, Schistou D, Schmit C, Terkenli TS, Tretvik AM, Trzepacz P, Vadineanu A, Walz A, Zhllima E, Reenberg A, 2015. Transitions in European land-management regimes between 1800 and 2010. Land Use Policy 49:53-64. DOI: https://doi.org/10.1016/j.landusepol.2015.07.003
Kanevski M, Pozdnoukhov A, Timonin V, 2009. Machine Learning for Spatial Environmental data. EPFL Press, Lausanne, Switzerland. DOI: https://doi.org/10.1201/9781439808085
Khan F, 2012. An initial seed selection algorithm for k-means clustering of georeferenced data to improve replicability of cluster assignments for mapping application. Appl. Soft Comput. J. 12:3698-700. DOI: https://doi.org/10.1016/j.asoc.2012.07.021
Kohonen T, 1982. Self-organized formation of topologically correct feature maps. Biol. Cybern. 43:59-69. DOI: https://doi.org/10.1007/BF00337288
Kohonen T, 2001. Self-organizing maps. Springer-Verlag, Berlin, Heidelberg, New York 3rd ed., p. 501. DOI: https://doi.org/10.1007/978-3-642-56927-2
Kuemmerle T, Kaplan JO, Prishchepov AV, Rylsky I, Chaskovskyy O, Tikunov VS, Müller D, 2015. Forest transitions in Eastern Europe and their effects on carbon budgets. Glob. Change Biol. 21:3049-61. DOI: https://doi.org/10.1111/gcb.12897
Lambin EF, Geist H, Rindfuss RR, 2006. Introduction: Local Processes with Global Impacts. Land-Use And Land-Cover Change, pp. 1-8. DOI: https://doi.org/10.1007/3-540-32202-7_1
Lambin EF, Meyfroidt P, 2011. Global land use change, economic globalization, and the looming land scarcity. Proc. Nat. Acad. Sci. (PNAS). 108:3465-72. DOI: https://doi.org/10.1073/pnas.1100480108
Levers C, Müller D, Erb K, Haberl H, Jepsen MR, Metzger MJ, Meyfroidt P, Plieninger T, Plutzar C, Stürck J, Verburg PH, Verkerk PJ, Kuemmerle T, 2018. Archetypical patterns and trajectories of land systems in Europe. Reg. Environ. Change. 18:715-32. DOI: https://doi.org/10.1007/s10113-015-0907-x
Li X, Wu K, Liang Y, 2023. A Review of Agricultural Land Functions: Analysis and Visualization Based on Bibliometrics. Land. 12:561. DOI: https://doi.org/10.3390/land12030561
Lloyd S, 1982. Least squares quantization in PCM. IEEE Trans. Inf. Theory. 28:129-37. DOI: https://doi.org/10.1109/TIT.1982.1056489
MacQueen J, 1967. Some methods for classification and analysis of multivariate observations. Proceedings Of The Fifth Berkeley Symposium On Mathematical Statistics And Probability, Volume 1. Statistics 5.1:281-98.
Malek Ž, Verburg P, 2017. Mediterranean land systems: Representing diversity and intensity of complex land systems in a dynamic region. Landsc. Urban Plan. 165:102-16. DOI: https://doi.org/10.1016/j.landurbplan.2017.05.012
Marraccini E, Debolini M, Moulery M, Abrantes P, Bouchier A, Chéry JP, Sanz Sanz E, Sabbatini T, Napoleone C, 2015. Common features and different trajectories of land cover changes insix Western Mediterranean urban regions. Appl. Geogr. 62:347-56. DOI: https://doi.org/10.1016/j.apgeog.2015.05.004
McCulloch WS, Pitts W, 1943. A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 5:115-33. DOI: https://doi.org/10.1007/BF02478259
Murray-Rust D, Robinson DT, Guillem E, Karali E, Rounsevell M, 2014. An open framework for agent based modelling of agricultural land use change. Environ. Model. Softw. 61:19-38. DOI: https://doi.org/10.1016/j.envsoft.2014.06.027
Rabelo M, Debolini M, Villani R, Sabbatini T, Silvestri N, 2021. Expansion and specialization of agricultural systems in western mediterranean areas: A global analysis based on the two last census data. Agronomy 11. DOI: https://doi.org/10.3390/agronomy11050904
Rega C, Short C, Pérez-Soba M, Luisa Paracchini M, 2020. A classification of European agricultural land using an energy-based intensity indicator and detailed crop description. Landsc. Urban Plan. 198. DOI: https://doi.org/10.1016/j.landurbplan.2020.103793
Schröter D, Cramer W, Leemans R, Prentice IC, Araújo MB, Arnell NW, Bondeau A, Bugmann H, Carter TR, Gracia CA, De La Vega-Leinert AC, Erhard M, Ewert F, Glendining M, House JI, Kankaanpää S, Klein RJT, Lavorel S, Lindner M, Metzger MJ, Meyer J, Mitchell TD, Reginster I, Rounsevell M, Sabaté S, Sitch S, Smith B, Smith J, Smith P, Sykes MT, Thonicke K, Thuiller W, Tuck G, Zaehle S, Zierl B, 2005. Ecology: Ecosystem service supply and vulnerability to global change in Europe. Science 310:1333-7. DOI: https://doi.org/10.1126/science.1115233
Silvestri N, Pistocchi C, Sabbatini T, Rossetto R, Bonari E, 2012. Diachronic analysis of farmers’ strategies within a protected area of central Italy. Ital. J. Agron. 7.2:e20-e20. DOI: https://doi.org/10.4081/ija.2012.e20
Sluiter R, De Jong SM, 2007. Spatial patterns of Mediterranean land abandonment and related land cover transitions. Landsc. Ecol. 22:559-76. DOI: https://doi.org/10.1007/s10980-006-9049-3
Stellmes M, Röder A, Udelhoven T, Hill J, 2013. Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data. Land Use Policy 30:685-702. DOI: https://doi.org/10.1016/j.landusepol.2012.05.007
Symeonakis E, Calvo-Cases A, Arnau-Rosalen E, 2007. Land use change and land degradation in southeastern Mediterranean Spain. Environ. Manag. 40:80-94. DOI: https://doi.org/10.1007/s00267-004-0059-0
Tonini M, Parente J, Pereira MG, 2018. Global assessment of rural-urban interface in Portugal related to land cover changes. Nat. Hazards Earth Syst. Sci. 18:1647-64. DOI: https://doi.org/10.5194/nhess-18-1647-2018
Václavík T, Lautenbach S, Kuemmerle T, Seppelt R, 2013. Mapping global land system archetypes. Glob. Environ. Change 23:1637-47. DOI: https://doi.org/10.1016/j.gloenvcha.2013.09.004
Verburg PH, Crossman N, Ellis EC, Heinimann A, Hostert P, Mertz O, Nagendra H, Sikor T, Erb K-H, Golubiewski N, Grau R, Grove M, Konaté S, Meyfroidt P, Parker DC, Chowdhury RR, Shibata H, Thomson A, Zhen L, 2015. Land system science and sustainable development of the earth system: A global land project perspective. Anthropocene 12:29-41. DOI: https://doi.org/10.1016/j.ancene.2015.09.004
Verburg PH, Erb K-H, Mertz O, Espindola G, 2013. Land System Science: between global challenges and local realities. Curr. Opin. Environ. Sustain. 5:433-7. DOI: https://doi.org/10.1016/j.cosust.2013.08.001
Verburg PH, Overmars KP, 2009. Combining top-down and bottom-up dynamics in land use modeling: Exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model. Landsc. Ecol. 24:1167-81. DOI: https://doi.org/10.1007/s10980-009-9355-7
Vesanto J, 1999. SOM-based data visualization methods. Intell. Data Anal. 3:111-26. DOI: https://doi.org/10.1016/S1088-467X(99)00013-X
Viana CM, Freire D, Abrantes P, Rocha J, Pereira P, 2022a. Agricultural land systems importance for supporting food security and sustainable development goals: A systematic review. Sci. Total Environ. 806.
Viana CM, Freire D, Abrantes P, Rocha J, Pereira P, 2022b. Agricultural land systems importance for supporting food security and sustainable development goals: A systematic review. Sci. Total Environ. 806:150718. DOI: https://doi.org/10.1016/j.scitotenv.2021.150718
Villani R, Sabbatini T, Perez OM, Guiomar N, Debolini M, 2019. An open dataset about georeferenced harmonized national agricultural censuses and surveys of seven mediterranean countries. Data In Brief 27:104774. DOI: https://doi.org/10.1016/j.dib.2019.104774
van Vliet J, de Groot HLF, Rietveld P, Verburg PH, 2015. Manifestations and underlying drivers of agricultural land use change in Europe. Landsc. Urban Plan. 133:24-36. DOI: https://doi.org/10.1016/j.landurbplan.2014.09.001
Wehrens R, Buydens LMC, 2007. Self- and Super-organizing Maps in R: The kohonen Package. J. Stat. Softw. 21:1-19. DOI: https://doi.org/10.18637/jss.v021.i05
Wehrens R, Kruisselbrink J, 2018. Flexible Self-Organizing Maps in kohonen 3.0. J. Stat. Softw. 87:1-18. DOI: https://doi.org/10.18637/jss.v087.i07
Young J, Richards C, Fischer A, Halada L, Kull T, Kuzniar A, Tartes U, Uzunov Y, Watt A, 2007. Conflicts between biodiversity conservation and human activities in the central and eastern European countries. Ambio 36:545-50. DOI: https://doi.org/10.1579/0044-7447(2007)36[545:CBBCAH]2.0.CO;2
van der Zanden EH, Levers C, Verburg PH, Kuemmerle T, 2016. Representing composition, spatial structure and management intensity of European agricultural landscapes: A new typology. Landsc. Urban Plan. 150:36.49. DOI: https://doi.org/10.1016/j.landurbplan.2016.02.005

How to Cite

Rabelo, M. C., Tonini, M., & Silvestri, N. (2023). Dynamics of agricultural land systems in western Mediterranean areas: a clustering approach based on the self-organizing map. Italian Journal of Agronomy, 18(3). https://doi.org/10.4081/ija.2023.2199