Armed conflicts and resulting displacement disrupt people’s sense of place, leading to an imbalance in the people–place relationship, exaggerated by rehabilitation efforts that overlook the sense of place among conflict- and displacement-impacted communities. A continuous landscape narrative that extends from pre- to post-conflict times contributes to recreating the essence of lost landscapes and therefore reconnecting their sense of place. Focusing on a Syrian city that hosted internally displaced persons (IDPs) in the aftermath of the Syrian conflict, this study aims to structure a virtual landscape and narrative depiction of conflict-impacted landscapes. This study proposes a storytelling approach for narrative construction and an AI-powered visualisation approach to revive the image of the elusive landscapes. This study utilised qualitative research methods through in-depth, semi-structured interviews for data collection and an online survey for exploring the perception of virtual landscape images generated with AI text-to-image models (DALL.E 2 and Bing Image Creator). This study indicates that narratives, supported by AI visualisation, are reliable for comprehending landscape transformation and changes in the sense of place. The two approaches can serve as rehabilitation initiatives in post-crisis settings to recall images of elusive landscapes to save them from being lost forever.

中文翻译：

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冲突后城市景观叙事：当代口头叙事虚拟可视化的两种方法

武装冲突和由此产生的流离失所扰乱了人们的地方感，导致人与地方关系失衡，而忽视受冲突和流离失所影响的社区的地方感的重建工作则加剧了这种不平衡。从冲突前到冲突后的连续景观叙事有助于重建失落景观的本质，从而重新连接它们的地方感。本研究以叙利亚冲突后收容境内流离失所者 (IDP) 的叙利亚城市为重点，旨在构建受冲突影响景观的虚拟景观和叙事描述。这项研究提出了一种用于叙事构建的讲故事方法和一种人工智能驱动的可视化方法来恢复难以捉摸的景观的图像。本研究采用定性研究方法，通过深入的半结构化访谈进行数据收集，并进行在线调查，以探索人工智能文本到图像模型（DALL.E 2 和 Bing Image Creator）生成的虚拟景观图像的感知。这项研究表明，人工智能可视化支持的叙事对于理解景观转变和地方感的变化是可靠的。这两种方法可以作为危机后环境中的恢复举措，以回忆难以捉摸的景观图像，以免它们永远消失。