首页|整合多源遥感数据的洪涝灾害评估恢复——以河南"7·20"暴雨灾害为例

整合多源遥感数据的洪涝灾害评估恢复——以河南"7·20"暴雨灾害为例

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洪涝灾害发生后通过植被指数和灯光指数定量评估灾后恢复情况,对灾区经济建设和生态恢复的评估具有重要科学意义.该文以河南"7·20"暴雨灾害区为研究区,基于日度和月度NPP-VIIRS数据、Sentinel-NDVI、MO-DIS-EVI数据和统计年鉴数据,构建归一化差异城市指数(normalized difference urban index,NDUI)来表征城市内部空间细节;基于回归模型模拟人口和国内生产总值的空间分布;从研究区的夜间灯光数据和植被覆盖数据 2 个不同的维度来评估洪涝灾害.结果表明:高危区和中危区总面积为 1 429.04 km2,占研究区总面积的 6.06%,高危地区主要分布在郑州西部、新乡东部、安阳东部、鹤壁北部,其中郑州市受灾严重程度最高;从植被覆盖度恢复率(vegetation cover recovery rate,VCRR)来看,卫辉市、淇县、滑县、林州市等地区整体植被恢复情况较差,其VCRR的值大部分在 0 以下,植被覆盖有恶化趋势.NDUI与社会经济统计数据拟合精度高于 0.8,表明NDUI可以在洪涝灾害发生后应用于精确位置救援和灾后针对性重建工作;NPP-VIIRS和MODIS-EVI评估洪涝灾害的结果具有很好的互补性,2 种数据的有机结合进行洪涝灾害研究,对灾后救援和恢复评估均有较高的应用价值.
Post-flood recovery assessment based on multi-source remote sensing data:A case study of the"7·20"rainstorm in Henan
Quantitative post-flood recovery assessment based on vegetation and lighting indices is critical for assessing economic reconstruction and ecological restoration in afflicted areas.This study investigated the"7.20"rainstorm disaster area in Henan.Based on the daily and monthly NPP-VIIRS data,Sentinel-NDVI and MODIS-EVI data,and statistical yearbook data,this study characterized the spatial intricacies within urban areas by constructing a normalized difference urban index(NDUI).Then,it simulated the population and GDP distributions by employing a regression model.Finally,this study assessed the post-flood recovery from two distinct aspects:nighttime light data and vegetation cover data.The results are as follows:①High-and medium-risk zones covered an area of 1 429.04 km2,accounting for 6.06%of the total study area.High-risk zones were primarily distributed in western Zhengzhou,eastern Xinxiang,eastern Anyang,and northern Hebi,with Zhengzhou suffering the most severe impact;② In terms of the vegetation cover recovery rate(VCRR),low overall vegetation recovery was observed in Weihui and Linzhou cities and Qixian and Huaxian counties,with VCRRs mostly below 0.This indicates a deteriorating vegetation cover trend;③ The fitting between NDUI and socio-economic statistical data yielded accuracy exceeding 0.8,suggesting that the NDUI can be applied to precise location-based rescue and targeted post-disaster reconstruction in the aftermath of floods.Additionally,the assessment results based on NPP-VIIRS and MODIS-EVI data were highly complementary,implying that the flood research based on the integration of the two types of data enjoys high application value for post-disaster rescue and recovery assessment.

"7·20"rainstorm in HenanNDUINPP-VIIRSlighting indexfractional vegetation covervege-tation cover recovery rate

黎孟琦、李功权、谢志辉

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长江大学地球科学学院,武汉 430100

河南"7·20"暴雨 NDUI NPP-VIIRS 灯光指数 植被覆盖度 植被覆盖度恢复率

自然资源部城市国土资源监测与仿真重点实验室开放基金课题

KF-2020-05-047

2024

自然资源遥感
中国国土资源航空物探遥感中心

自然资源遥感

CSTPCD北大核心
影响因子:1.275
ISSN:2097-034X
年,卷(期):2024.36(1)
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