Mapping the Climate Vulnerability of Eco-Villages in the Yangtze River Delta: A Statistical Exploration Using Big Data Trends and Environmental Indicators.

Hancheng Liu1, Yaxin Bao1, Xingyan Chen2, Jialong Zhang3, Yun Tong1*

1School of Fine Arts, Nanjing Normal University, Nanjing Jiangsu, 210023, China
2Jiangsu Communication and Media School, Nanjing Jiangsu, 210012, China
3Nanjing Forestry University College of Art ＆ Design, Nanjing Jiangsu, 210037, China

*Corresponding author: Yun Tong
Email: m18912976899@163.com

Hancheng Liu Email: 19524258206@163.com
Yaxin Bao Email: yaxinbao2002@163.com
Xingyan Chen Email: 13913392565@163.com
Jialong Zhang Email: m15051804075@163.com

ABSTRACT
Background: The Yangtze River Delta (YRD) is one such sensitive economic and ecological zone in China, and its eco-villages that are a balance between the need to preserve the environment, and the need to develop socio economically, are also being subjected to more and more risk owing to climatic issues. Knowledge on the geographical distribution of climate susceptibility is the vitality towards specific policies of adaptation.
Objectives:
The objective of the study is intended to examine the climate vulnerability of eco-villages in the YRD using a comprehensive Climate Vulnerability Index (CVI) that considers both climatic, social, infrastructural and institutional indicators. It also tells spatial clusters and validates the model against the field data.
Methods: The study will utilize both a qualitative and a quantitative data analysis methodology based on a set of Geographic Information System or GIS elements, Principal Component Analysis or PCA, and normalization of big data methods. The CVI has been formulated with the help of IPCC vulnerability spectrum comprising of exposure, sensitivity, as well as, adaptive capacity. They employed the Kernel Density Estimation (KDE) to identify Hotspots of interest. The accuracy of mapping was tested by carrying out ground validation in 15 eco-villages selected randomly.
Results: Among the 112 eco-villages surveyed, 14.3 percent of them were assessed as very vulnerable whereas 38.4 percent were moderately vulnerable. Jiangsu and Zhejiang provinces showed the best average score of the CVI. PCA indicated climate exposure (floods and temperature deviations) as the main factor, social (population age, income inequality), infrastructural (road density, green access), and institutional (disaster policy decision, other disasters) levels. It was identified that there are three key areas of vulnerable spots: Ningbo-Shanghai seaboard, Lower Yangtze Agricultural Basin, and Suzhou-Hangzhou transition zone. The overall mapping accuracy was validated in the ground as 86.7 percent.
Conclusions: The study has concluded that that climate vulnerability in the Yangtze River Delta is driven by a mix of climate, social, infrastructure, and institutional factors. Regions like Jiangsu and Zhejiang face the highest vulnerability, while Shanghai is comparatively less exposed.

Keywords: Climate Vulnerability, Eco-Villages, Yangtze River Delta, GIS Mapping, Big Data Analysis

INTRODUCTION
The rising importance of climate change has made it necessary to assess how prepared local areas are to handle environmental pressures, mainly in areas that are both important for nature and valuable for the economy. Another region is the Yangtze River Delta (YRD), which is a lively economic route and one of China’s busiest and most industrialized areas. Even as the area’s businesses grow, climate change still affects the YRD severely, for example, through rises in sea levels, harsh weather, and damage to the environment [1, 2].

Sustainable development depends on ensuring that the structure and vital functions of an ecosystem remain unchanged. All the same, when humans engage in large activities, it changes the landscape and nature processes a lot, which can lead to risks that jeopardize human well-being. More and more people are interested in using ecological risk assessment (ERA) to control risks and provide support for preserving ecosystems. In the past few years, the YRD region in eastern China has received special attention for both protecting the environment and building eco-friendly development [3, 4]. Natural areas and cities in the region are currently exposed to great threats. Since this environment and agricultural sector are important, their inherent vulnerability is due to the high number of neighboring cities, the economic value along important shipping lanes, numerous factories, and the conflict between building economies and protecting the environment. The region requires prompt attention. As a result of these challenges, it gradually becomes more difficult to manage cities and villages, and this means missed chances for economic development that also protect the environment [5, 6].

Due to its large size and exposure to many different climates, China deals with a wide range of disasters that harm the environment. As shown by data from the Emergency Events Database, the country was ranked among the world’s top ten most affected by disasters linked to natural hazards between 2000 and 2019 in terms of the number of hazards facing the country, the cost of those hazards, and casualties. Floods have happened at a high rate in the Pearl River Delta in southern China, as well as the Yangtze River Delta in eastern China. For this reason, studying the risks of floods in the Yangtze and Pearl River Delta, as well as in China as a whole, has attracted a lot of attention and mainly concerns modelling and predicting floods and assessing their effect and threats. Also, there are studies that assess the vulnerability or risks of cyclone events, storm surges, droughts, and pollution [7, 8].

In China, the Yangtze River Economic Belt (YREB) is a significant area known for its people, its economic activities, and its abundant nature. As a result of intense development and unsustainable use of land for many years, several problems have arisen, for instance, weakened vegetation, fast drying of lakes and wetlands, and serious water and air pollution. Many recent studies on the YREB have investigated different environmental change effects, which include natural disasters, pollution, climate change, and declining people’s health [9, 10]. Both the environment and people’s activities in the YRD make it susceptible to climate change. Sea-level rise, storm surges, flooding, and salinized soil are threats that the region has to deal with as a coastal delta. At the same time, increased industrial activity and changing land use have affected the environment, decreasing the area’s ability to handle natural disasters. They increase the difficulties faced by eco-villages as they support ecological preservation and promote economic and social development at the same time [11, 12]. Figure 2 outlines the urgent need to assess climate vulnerability in the Yangtze River Delta (YRD), a region critical for both China’s economy and ecology. Rising climate threats—like sea-level rise, extreme weather, and pollution—combine with rapid industrial growth and urbanization to degrade ecosystems. As one of the world’s most disaster-prone nations, China faces high environmental risks, making Ecological Risk Assessment (ERA) essential. ERA supports sustainable planning and strengthens eco-village resilience against these complex, overlapping pressures.
Study area: The Yangtze River Economic Belt (YREB) which is the area of focus in the research stretches across nine provinces, i.e., Zhejiang, Jiangsu, Anhui, Hubei, Jiangxi, Hunan, Sichuan, Yunnan, and Guizhou, and two municipalities or Shanghai and Chongqing. Within the past 30 years, the population growth rate and greater strain in the use of land has been so huge as to seriously deteriorate the terrestrial and aquatic ecosystems of the region. The YREB exhibits a wide extent of meteorological conditions and ecosystems with average annual temperatures being 14.2 o C to 17.8 o C while the precipitation levels are between 873.9 mm to 2397.5 mm. There are 165 national nature reserves (NRs) in it, over an area of 73,634.75 km 2, which is or about 3.6 per cent of the area. Such reserves consist of forest ecosystems (90 NRs), wild animal habitats (47 NRs), inland wetlands (14 NRs) and wild plant areas (12 NRs). There were no geological and paleontological reserves that could exclude since they have little relevance to the study on their spatial and biodiversity.

Climate Vulnerability Indicator Framework:
A version of the Climate vulnerability index (CVI) was made using information from the IPCC framework; it contains three important components in all:

Exposure: Because of exposure to climate anomalies (when rainfall or temperature differs greatly), the number of floods is increasing.
Sensitivity: How sensitive this could be: whether the population, its ages, and land use are high or changing.
Adaptive capacity: Green infrastructure, indicators of GDP per capita, and the strength of local governments are aspects of adaptive capacity.

Data processing and normalization:
All the layers of data were given the same spatial resolution in ArcGIS and QGIS. The variables were normalized with statistical methods called Z-scores and min-max scaling before being included in the CVI.

Principal Component Analysis (PCA):
Principal Component Analysis was used to help eliminate the number of dimensions in order to find the most influential variables that provoke vulnerability. The components that have eigenvalues greater than 1 and cumulative variance more than 70 percent have been retained in the analysis.

Making and Analyzing Maps of Spatial Vulnerability:
GIS tools were used to spatially depict CVI scores which were graded into five vulnerability grades; very low, low, moderate, high, and very high eco-villages. Spatial clustering was identified using Kernel Density Estimation (KDE) in order to find out the hotspots of vulnerability.

Validation and ground verification:
To provide a proof of the model correctness, a subset of eco-villages (n = 15) was chosen randomly and was surveyed (field surveys) and the interviewed (interviews by stakeholders). It also compared the observed level of vulnerability to the mappings of the levels of vulnerability to check levels of agreement and finalize on the model.

RESULTS
Table 1 shows demographics of the 112 sampled eco-villages in different provinces, population magnitude and economic foundation. Most of these eco-villages are in Jiangsu (31.30) and Zhejiang (25) while the rest of the provinces have 15.20 and 10.70 in Anhui and Shanghai respectively and 17.80 in other provinces. Village population characteristics include a per-village or village population of 1,000 to 3,000 (45.5 percent), below 1,000 population (40.2 percent) and above 3,000 population (14.3 percent). As far as an economic base is concerned, more than a half of the villages (52.7 percent) are dominated by agricultural production, 33.9 percent are characterized by a mixed economic base, and 13.4 percent are proximate to industrial district.

Discussion
Frequent and severe cases of air pollution have shown up throughout China recently. It is now very important to spot factors and analyze social vulnerability for environmental protection and sustainable growth. Still, there are not many studies that link social vulnerability to air pollution. In relation to research about social vulnerability, this paper made a new trial for evaluating social vulnerability to air pollution. With the PPC model, researchers found out the top three factors that influence the social vulnerability index (SVI) and evaluated SVI as well as the dimensions associated with it. It was found that adaptability has greater values than susceptibility and exposure. The situation is bad since SVI measures are very high in the area as a whole. High SVI is mostly found in the regions around the study area’s northern and southern edges. There is less SVI in Shanghai than in these two provinces. At the level of a prefecture-level city, the low-value SVI centers are always found in the center of the city. This allows those who make decisions to find solutions to air pollution problems, depending on the differences in social vulnerability and where it occurs [13].

Ecological vulnerability of estuarine islands must be understood and checked so that the ecosystem services and sustainable development of those islands are maintained. Nevertheless, because estuarine islands are affected by multiple sources, including climate change and human pressure, it is hard to do a complete evaluation of their ecological vulnerability. As a result, we studied Chongming Island to create an evaluation system for ecological vulnerability of estuarine island ecosystems with the pressure-state-response (PSR) conceptual model, and examined how ecological vulnerability has changed and where it was located in 2005 and 2015. According to the results, the major issues from saltwater intrusion and land use were found in the north and east of the wetland; the eco-vulnerability index (EV) for Chongming Island slightly dropped between 2005 and 2015; and through the assessment, three types of towns for eco-island planning were identified [14].

Risk assessments are important for handling and avoiding risks, which makes a positive contribution to sustainable development. In spite of using a social-ecological and multi-hazard approach, earlier risk assessments did not give equal attention to the social and ecological elements involved. To fill this gap, we relied on a framework that includes ES within the process of risk assessment. ES indicators that have been grouped into a module were applied to study the nature of risks in the Pearl and Yangtze River deltas. It is evident that there is a higher chance of flooding in the Pearl River Delta, and different factors cause the most risk at different scales. By identifying vulnerable regions, authorities can create specific plans that will help reduce risks of disasters triggered by nature. It has been realized that ecosystem services matter for assessing risk and including them in risk strategies means policies are created to help ecosystems serve the community’s needs in a sustainable way [3].

A study analyzed how the value of ecosystem services (ESV) has changed in the important economic and ecological YRMRM area in China’s central region. They collected experts’ opinions from a wide survey and included them in the process of making ESV suitable for the region. They investigated how the areas of extreme heat and cold in ESV changed, and we examined if the place’s ESV could be linked to where it was and how far away it was. According to their findings, ESV fell between 2000 and 2015 since a decline in land used for agriculture reduced the value of the food supply. The number of cold spots went up while the number of hot spots went down during the YRMRM. The value of ESVs for each place went down as those places were further away from their nearest provincial centre, lake, and the Yangtze River. The biggest ESV was found about 42 km away from the nearest provincial city, 10 km from the Yangtze River, and was near a lake. It provides valuable field information to the study of evaluating ESV according to what stakeholders believe. With the help of the detailed assessment of ESV throughout the region, there is improved collaboration on both sustainable growth and ecological preservation in the YRMRM [15].

CONCLUSION
The study has concluded that that climate vulnerability in the Yangtze River Delta is driven by a mix of climate, social, infrastructure, and institutional factors. Regions like Jiangsu and Zhejiang face the highest vulnerability, while Shanghai is comparatively less exposed. Around half of the surveyed eco-villages fall into moderate to very high vulnerability categories, with only a small share showing low or very low risk. Hotspot areas such as the Ningbo–Shanghai seaboard and Suzhou–Hangzhou belt are under severe pressure from urban expansion, flooding, and land degradation. Lastly, the model used for mapping vulnerability shows strong reliability, with an accuracy rate of 86.7% confirmed through ground validation. An optimized Climate Vulnerability Index (CVI) based on IPCC frames and supported by field measurements shows crucial variations of regions. The Jiangsu and Zhejiang provinces are the ones that show the maximum mean of CVI which is an indication of increased exposure to climate risks like floods and abnormal temperatures. Most eco-villages are categorized as moderate to high vulnerability, where the hotspot clusters can be traced to the Ningbo-Shanghai seaboard, the Lower Yangtze Agricultural Basin and Suzhou-Hangzhou transition zone (where there is a lot of urban increase and land-use change, and environmental deterioration). In Principal Component Analysis, the exposure climate was found to have the most significant power with social vulnerability, infrastructure quality, and institutional capacity, to some extent. It is remarkable that the mapping model had good accuracy whose match rate in ground validations was 86.7 percent. Such concepts stress the need to create resilience plans specific to geography and harmonize it with planning the ecological protection with social and economic growth, especially in fast-growing or ecologically sensitive regions. Policy makers as well as planners and stake holders can use the findings to design specific interventions that would increase adaptation capacity whilst also protecting the ecological integrity of the YRD.

Ran, P., Hu, S., Frazier, A. E., Qu, S., Yu, D., & Tong, L. (2022). Exploring changes in landscape ecological risk in the Yangtze River Economic Belt from a spatiotemporal perspective. Ecological Indicators, 137, 108744. https://doi.org/10.1016/j.ecolind.2022.108744
Yi, R., Chen, Y., & Chen, A. (2025). Evaluating urban climate resilience in the Yangtze River Delta urban agglomeration: A novel method integrating the DPSIR model and Sustainable Development Goals. Journal of Environmental Management, 376, 124517. https://doi.org/10.1016/j.jenvman.2025.124517
Peng, Y., Welden, N., & Renaud, F. G. (2024). Incorporating ecosystem services into comparative vulnerability and risk assessments in the Pearl River and Yangtze River Deltas, China. Ocean & Coastal Management, 249, 106980. https://doi.org/10.1016/j.ocecoaman.2023.106980
Li, J., Liu, X., Wang, Y., Peng, X., Tang, H., & Li, M. (2025). Ecological tourism suitability evaluation and landscape ecological risk analysis of the Yangtze River Delta Region from 2000 to 2020 based on the MaxEnt model. Journal of Asian Architecture and Building Engineering, 1–18. https://doi.org/10.1080/13467581.2025.2510617
Guo, Y., Wang, W., Zhang, X., Liu, C., Wang, Y., Chen, W., Wan, X., Zhang, X., Lin, Y., Zhang, X., & Liu, Y. (2025). Revealing the impact of urbanization on landscape ecological risk: A case study of the lower reaches of the Yangtze River, China. Frontiers in Environmental Science, 13, 1589832. https://doi.org/10.3389/fenvs.2025.1589832
Pan, Y., Wang, J., An, Z., Li, J., & Weng, G. (2025). Comprehensive Evaluation and Dynamic Evolution Characteristics of Tourism Ecological Security Using the DPSIR-DS Model in the Yangtze River Economic Belt, China. SAGE Open, 15(1). https://doi.org/10.1177/21582440241309881.
Xie, Q., Dong, Y., Yu, K., Zhang, Y., & Xu, H. (2020). Comprehensive Evaluation of Urban Economic Development in Yangtze River Delta Based on Cluster-Principal Component Analysis. Complexity, 2021(1), 3328761. https://doi.org/10.1155/2021/3328761
Li, Y., & Wang, S. (2023). Exploration of Eco-Environment and Urbanization Changes Based on Multi-Source Remote Sensing Data—A Case Study of Yangtze River Delta Urban Agglomeration. Sustainability, 16(14), 5903. https://doi.org/10.3390/su16145903
Wang, M., Ji, M., Wu, X., Deng, K., & Jing, X. (2022). Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China. Sustainability, 15(10), 8268. https://doi.org/10.3390/su15108268
Shi, Z., Wang, Y., Zhao, Q., & Zhu, C. (2022). Assessment of spatiotemporal changes of ecological environment quality of the Yangtze River Delta urban agglomeration in China based on MRSEI. Frontiers in Ecology and Evolution, 10, 1013859. https://doi.org/10.3389/fevo.2022.1013859
Zhao, J., Pan, J., & Tan, L. (2024). Sustainable evaluation of ecotourism in the Yangtze River delta urban agglomeration: A system coordination perspective. Sustainable Operations and Computers, 6, 57-70. https://doi.org/10.1016/j.susoc.2025.01.002
Yuan, Y., Wei, S., Wan, D., & Liu, D. (2024). A study of land-economy-society-ecology coordination in the Yangtze River Delta based on coupled coordination degree model. International Review of Economics & Finance, 95, 103474. https://doi.org/10.1016/j.iref.2024.103474
Ge, Y., Zhang, H., Dou, W., Chen, W., Liu, N., Wang, Y., Shi, Y., & Rao, W. (2016). Mapping Social Vulnerability to Air Pollution: A Case Study of the Yangtze River Delta Region, China. Sustainability, 9(1), 109. https://doi.org/10.3390/su9010109
Peng, W., Wang, D., & Cai, Y. (2020). Assessing Ecological Vulnerability under Climate Change and Anthropogenic Influence in the Yangtze River Estuarine Island-Chongming Island, China. International Journal of Environmental Research and Public Health, 18(21), 11642. https://doi.org/10.3390/ijerph182111642
Zhang, G., Zheng, D., Xie, L., Zhang, X., Wu, H., & Li, S. (2021). Mapping changes in the value of ecosystem services in the Yangtze River Middle Reaches Megalopolis, China. Ecosystem Services, 48, 101252. https://doi.org/10.1016/j.ecoser.2021.101252