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تحلیل روند موضوعی سرزندگی و پایداری چشم انداز نواحی روستایی رویکردی بر بهبود کیفیت زندگی.

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  • معلومة اضافية
    • Alternate Title:
      Thematic Trend Analysis of Landscape Vitality and Sustainability of Rural Areas: An Approach to Enhancing Quality of Life.
    • نبذة مختصرة :
      The vitality and sustainability of rural landscapes are fundamental to enhancing the quality of life for residents. This study aimed to analyze thematic trends in rural landscape vitality and sustainability, with a particular focus on quality-oflife improvements, and to trace their evolution over four decades (1980–2025) to inform future research directions. Using a descriptive-analytical and quantitative approach, this applied research developed a targeted search strategy to exclude irrelevant literature, ultimately analyzing 674 indexed publications through scientometric methods. SciMAT software was employed to map thematic networks, revealing key research clusters across four distinct time periods. The internal linkages within these networks highlighted dominant discourses, including communication planning for quality-of-life enhancement, ecosystem services, sustainability, and sustainable development as emerging focal areas. Findings from the fourth and fifth periods indicate a growing prominence of keywords such as geographic information systems (GIS), rural-cultural landscape, sustainable livelihoods, quality of life, public spaces, and communication management. These trends suggest that strategies emphasizing local cultural promotion, landscape preservation, and active social participation are critical to sustaining and improving rural quality of life. This study offers a thematic foundation for future research and policy development, particularly in light of the increasing global emphasis on landscape sustainability and rural livelihood enhancement. [ABSTRACT FROM AUTHOR]
    • نبذة مختصرة :
      Copyright of Geography & Environmental Sustainability is the property of Razi University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)