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Surveillance des inondations par imagerie multisource sur la plateforme GEE

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Kaifeng 475004, China

    Key Laboratory of Integrative Prevention of Air Pollution and Ecological Security of Henan province, Kaifeng 475004, China

    School of Geography and Environmental Science, Henan University, Kaifeng 475004, China

  • Email：lxy@henu.edu.cn
  • Introduction：刘小燕， 研究方向为遥感信息提取与城乡生态效应。E-mail： lxy@henu.edu.cn
LIU Xiaoyan123,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Kaifeng 475004, China

    Key Laboratory of Integrative Prevention of Air Pollution and Ecological Security of Henan province, Kaifeng 475004, China

    School of Geography and Environmental Science, Henan University, Kaifeng 475004, China

  • Email：cuiyp@lreis.ac.cn
  • Introduction：崔耀平，研究方向为遥感大数据和空间优化。E-mail： cuiyp@lreis.ac.cn
CUI Yaoping123*,  
  • Affiliation：

    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Kaifeng 475004, China

    School of Geography and Environmental Science, Henan University, Kaifeng 475004, China

SHI Zhifang13,  
  • Affiliation：

    Institute of Geology and Exploration, Henan Geology and Exploration Bureau, Zhengzhou 450001, China

FU Yiming4,  
  • Affiliation：

    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Kaifeng 475004, China

    School of Geography and Environmental Science, Henan University, Kaifeng 475004, China

RUN Yadi13,  
  • Affiliation：

    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Kaifeng 475004, China

    School of Geography and Environmental Science, Henan University, Kaifeng 475004, China

LI Mengdi13,  
  • Affiliation：

    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Kaifeng 475004, China

    School of Geography and Environmental Science, Henan University, Kaifeng 475004, China

LI Nan13,  
  • Affiliation：

    Henan Institute of Geophysics and Spatial Information, Zhengzhou 450009, China

LIU Sujie5

résumé

En raison des conditions météorologiques pendant la période des inondations, les données de télédétection utilisées pour l’évaluation des inondations sont principalement des images radar ou des données aériennes, tandis que le rôle de nombreuses données d’éclairage nocturne et d’images optiques dans l’évaluation des inondations reste à approfondir. Cette étude porte sur la ville de Fuyang en juillet-août, basée sur les données satellites Sentinel-1, Sentinel-2 et Landsat 8. À l’aide de la plateforme de mégadonnées de télédétection GEE (Google Earth Engine), les informations sur les plans d’eau ont été extraites, et les indices d’éclairage nocturne Total Night-time Light (TNL) et Compounded Night Light Index (CNLI) construits à partir des données d’éclairage nocturne ont été utilisés pour étudier la relation entre les changements des plans d’eau et l’éclairage nocturne afin de surveiller et d’évaluer la dynamique des inondations. Les résultats montrent : (1) Des changements significatifs dans la répartition des plans d’eau dans le sud de Fuyang en juillet-août, en particulier une augmentation notable de la surface d’eau dans la zone de stockage d’eau de Mengwa, la surface d’eau atteignant son maximum de 323 km2 le 31 juillet, soit six fois plus que la surface avant les inondations, suivie d’une diminution de la couverture en eau, correspondant aux heures d’ouverture et de vidange du barrage de Wangjiaba. (2) Une analyse combinée des indices d’éclairage nocturne TNL et CNLI pour les variations de l’éclairage nocturne à Fuyang montre que la tendance des indices d’éclairage est inverse à celle des changements des plans d’eau, indiquant que ces indices peuvent refléter efficacement le processus de changement des inondations. (3) Une analyse combinée des données de plans d’eau et des indices d’éclairage nocturne pour la partie est de Fuyang, où les données sont plus complètes, confirme que les données d’éclairage nocturne et d’eau peuvent être utilisées pour surveiller les inondations. Cette étude prenant l’inondation de cette année à Fuyang en exemple étend l’application des données d’éclairage nocturne et des images optiques, et confirme qu’après un traitement strict des données, les données multisources de télédétection telles que les images radar Sentinel-1 et les images optiques Sentinel-2 et Landsat 8 peuvent efficacement surveiller les changements liés aux inondations, jouant un rôle important dans la surveillance future des inondations.

mots-clés

Google Earth Engine (GEE); éclairage nocturne; télédétection multisource; inondations; Sentinel; NPP-VIIRS DNB; Landsat

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