Assessment of the vulnerability of farmers toward climate change: a case from Chitre-Parbat of Nepal

As the threat of global risks has increased, the study of village heritage has begun to move away from the interpretation of traditional values or the presentation of historical wisdom to focus on the vulnerability of villages. Taking Chinese traditional villages (a type of vernacular heritage) as the target, this study clarifies the connotation of village vulnerability and its generation pattern. Drawing on the framework of “exposure-sensitivity-adaptive capacity”, a set of vulnerability evaluation index systems integrating the characteristics of village heritage is proposed. By utilizing vulnerability index and obstacle degree models, we analyze the spatial differentiation and evolutionary characteristics of vulnerability in 123 traditional villages within Aba Prefecture, Sichuan Province, southwestern China, while also exploring the main factors influencing vulnerability evolution at different spatial scales. The results reveal an “east high, west low” spatial pattern and a clustered distribution of vulnerability in traditional villages across the region. From 2012 to 2019, the vulnerability levels fluctuated and intensified, with decreasing individual differences. The evolutionary characteristics of exposure, sensitivity, and adaptive capacity also displayed significant variations. Persistent and stable influences on village vulnerability were identified from factors such as land use scale, population density, gross domestic product, and land fragmentation. Based on these findings, strategic recommendations for village classification, protection, and development are proposed.

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Assessment of the vulnerability of farmers toward climate change: a case from Chitre-Parbat of Nepal

Cited by 2 publications

References 39 publications

Predicting rainfall in Nineveh Governorate in northern Iraq using machine learning time-series forecasting algorithm

Predicting rainfall in Nineveh Governorate in northern Iraq using machine learning time-series forecasting algorithm

Increasing Vulnerability of Village Heritage: Evidence from 123 Villages in Aba Prefecture, Sichuan, China

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