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Agricultural Land Conversion Drivers in Northeast Iran: Application of Structural Equation Model

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Abstract

Identifying driving forces behind agricultural land conversion (ALC) remains one of the most difficult challenges that agricultural and environmental scientists must continually deal with. The difficulty emerges from the fact that in ALC, multiple actions and interactions between different factors (i.e., economic, political, environmental, biophysical, institutional, and cultural) exist and make it difficult to understand the function of the processes behind the changes. The phenomenon of ALC in different countries is varied in terms of intensity, trends and drivers. The main goal of this study was to understand these drivers in Northeast Iran through applying structural equation model (SEM). Using multi-stage stratified random sampling, 101 executive officers participated in the study. Data were collected through a structured questionnaire. A multi-stakeholder analysis and a mixed-method (qualitative and quantitative) approach were applied. Results revealed that not only from the policy makers’ perspective but also based on the SEM, “economic”, “political”, “technological”, “social” and “environmental” factors should respectively be the five major drivers of ALC. The results also showed that among other drivers, “more profitability of non-agriculture sectors”, “excessive rising of land prices”, “farmers’ income instability”, “land fragmentation”, “urban sprawl” and “inheritance laws” are the main six causes of ALC. Hence, it can be concluded that policy-makers and planners need to take these drivers and subsidiaries more into consideration in order to properly respond to ALC.

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Azadi, H., Barati, A.A., Rafiaani, P. et al. Agricultural Land Conversion Drivers in Northeast Iran: Application of Structural Equation Model. Appl. Spatial Analysis 9, 591–609 (2016). https://doi.org/10.1007/s12061-015-9160-4

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