Evaluation of the Physical and Environmental Factors Affecting Land Use Changes in Rural Areas of Rasht

Document Type : Original Article

Authors

1 Ph.D. Candidate in Geography and Rural Planning, Rasht Branch, Islamic Azad University, Rasht, Iran

2 Professor Department of Geography, Rasht Branch, Islamic Azad University, Rasht, Iran

3 Associate Professor Department of Geography, Rasht Branch, Islamic Azad University, Rasht, Iran

10.22034/jget.2024.135127

Abstract

The present research is applied in terms of purpose, in terms of nature and method is of descriptive-analytical research. The statistical population of this study includes 37 rural settlements around the city of Rasht. In the field of sample population, according to the objectives of the study, 37 inhabited villages that share a same border with the city of Rasht were selected as sample villages. In this study, all 37 villages have been studied (total number). In this study, a researcher-made questionnaire was used to collect information.

Finally, 516 people participated in completing the questionnaires. Data analysis was performed using one-sample t-test, Pearson correlation coefficient and multivariate linear regression.

. The results of multivariate linear regression analysis showed that among physical factors, the factor of proximity to the city predicts up to 67% of the changes in the dependent variable. Indeed, two factors of proximity to work centers and communication routes access with coefficients of 0.548 and 0.511, respectively, were effective on land use changes. The results of studies for environmental factors showed that four indicators are effective on land use change. The tourism capacities of the village with the standard coefficient of 0.821 had the most impact. The unfavorable rural land for agricultural activities with a standard coefficient of 0.785 had an effect on changes in rural land use. Distance from irrigation sources and lack of access to water with coefficients of 0.613 and 0.568, respectively, were effective in changes in the dependent variable.

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