首页|基于多源数据的南昌市洪涝灾害韧性及驱动因素研究

基于多源数据的南昌市洪涝灾害韧性及驱动因素研究

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洪涝灾害事件对城市的经济发展和居民的人身安全造成了巨大的威胁。定量测度城市洪涝灾害韧性指数,可加快韧性城市建设,为城市高质量发展提供有力的保障。将研究区划分为100 mx100m的栅格单元,以多源数据为支撑,基于PSR模型从自然、经济、社会、基础设施4个维度构建城市洪涝灾害韧性评价指标体系,采用AHP-熵权法探究南昌市洪涝灾害韧性的空间分布,并通过地理探测器探究其主要驱动因子。结果表明:南昌市洪涝灾害韧性极低等级和低等级分别占总面积的5。9%和5。7%,主要分布在南昌市西湖区、青云谱区和青山湖区,其主要原因是不透水面占比较大,植被覆盖度偏低。地理探测器结果表明,南昌市洪涝灾害韧性的主要驱动因素是不透水面占比、地形湿度指数和建筑物密度。研究结果可为相关部门对洪涝灾害的应对与预防提供依据。
Research on Resilience and Driving Factors of Flood Disasters in Nanchang City Based on Multi-source Data
Flood disasters pose a significant threat to urban economic development and the safety of residents'life and properties.Quantifying the resilience index of urban flood disasters can accelerate the construction of resilient cities and provide strong support for the high-quality development of cities.This study took Nanchang city in Jiangxi province as an example.The study area was discretized into 100m x 100m grid units.Multi-source data were used to construct an urban flood disaster resilience evaluation index system,based on PSR model,from four dimensions:nature,economy,society,and infrastructure.The AHP-entropy weight method was employed to explore the spatial distribution of flood disaster resilience at the pixel scale.Additionally,the main driving factors were identified using the geographical detector.The results revealed that the areas of extremely low and low levels of flood disaster resilience accounted for 5.9%and 5.7%of the total area,respectively.These areas were primarily located in Xihu District,Qingyunpu District,and Qingshan Lake District of Nanchang city.The primary contributing factors were identified as the large proportion of impervious surfaces and low vegetation coverage.The geographical detector analysis indicated that the main driving factors of flood disaster resilience in Nanchang City were the proportion of impervious surfaces,terrain humidity index,and the density of buildings.These findings provided a valuable basis for decision making regarding effective responses to prevent and reduce urban flood disasters.

flood disasters resiliencequantitative measurementmulti-source dataNanchang City

李聪毅、程朋根、付家能、周曙磊、齐广玉

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东华理工大学测绘与空间信息工程学院,江西南昌 330013

东华理工大学江西省流域生态过程与信息重点实验室,江西南昌 330013

洪涝灾害韧性 定量测度 多源数据 南昌市

2024

长江流域资源与环境
中国科学院资源环境科学与技术局 中国科学院武汉文献情报中心

长江流域资源与环境

CSTPCDCSSCICHSSCD北大核心
影响因子:1.35
ISSN:1004-8227
年,卷(期):2024.33(12)