Monitoring of floods using multi-source remote sensing images on the GEE platform

被引：0
|
作者：
Liu X. [1 ,2 ,3 ]
Cui Y. [1 ,2 ,3 ]
Shi Z. [1 ,3 ]
Fu Y. [4 ]
Run Y. [1 ,3 ]
Li M. [1 ,3 ]
Li N. [1 ,3 ]
Liu S. [5 ]
机构：
[1] Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Kaifeng
[2] Key Laboratory of Integrative Prevention of Air Pollution and Ecological Security of Henan province, Kaifeng
[3] School of Geography and Environmental Science, Henan University, Kaifeng
[4] Institute of Geology and Exploration, Henan Geology and Exploration Bureau, Zhengzhou
[5] Henan Institute of Geophysics and Spatial Information, Zhengzhou
来源：
National Remote Sensing Bulletin | 2023年 / 27卷 / 09期
基金：
中国国家自然科学基金;
关键词：
flood disaster; Google Earth Engine (GEE); Landsat; multi-source remote sensing; night lights; NPP-VIIRS DNB; Sentinel;
D O I：
10.11834/jrs.20221063
中图分类号：
学科分类号：
摘要：
Limited by the weather during floods, the remote sensing data used for flood assessments are mostly radar images or aerial data, and the role of numerous night lights and optical image data in flood assessments needs to be further explored. This paper took Fuyang from July to August as the research area, based on the monitoring data of Sentinel-1, Sentinel-2, and Landsat 8 and extracted water body information with the help of Google Earth Engine. This paper used night light data (NPP-VIIRS DNB) to establish the total night-time light (TNL) and compounded night light (CNLI) to explore the relationship between water changes and night lights to monitor and evaluate the effect of floods. Results showed the following: (1) The distribution of water bodies in the southern part of Fuyang changed remarkably from July to August, especially the water bodies in the Mengwa Flood Diversion Project increased substantially. On July 31, the water body area reached the maximum of 323 km2, which was six times larger than the water body area before the flood, and then the coverage of water bodies was declining. This trend corresponded to the time of flood storage and discharge of Wangjiaba gate. (2) The combined analysis of Fuyang night light index TNL index and CNLI index found the change trend of the light index was opposite to that of the water body, indicating the night light index can effectively reflect the changing of flood disasters. (3) Analyzing the water body and night light index of eastern Fuyang with relatively complete data further showed night light and water body data can be used to monitor floods. This paper expanded the application range of night light data and optical images and confirmed that after rigorous data processing, multisource remote sensing data such as radar image based on Sentinel-1, optical image based on Sentinel-2, and Landsat 8 can effectively monitor the change of flood disaster and play an important role in flood monitoring in the future. © 2023 Science Press. All rights reserved.
引用
收藏
页码：2179 / 2190
页数：11
相关论文
共 40 条
  • [1] Boccardo P, Tonolo F G., Remote sensing role in emergency mapping for disaster response, Engineering Geology for Society and Territory, 5, pp. 17-24, (2015)
  • [2] Cao C Y, Shao X, Uprety S., Detecting light outages after severe storms using the S-NPP/VIIRS day/night band radiances, IEEE Geoscience and Remote Sensing Letters, 10, 6, pp. 1582-1586, (2013)
  • [3] Feeny S, Trinh T A, De Silva A., Detecting disasters and disaster recovery in Southeast Asia: findings from space, Natural Hazards Review, 23, 2, (2022)
  • [4] Feyisa G L, Meilby H, Fensholt R, Proud S R., Automated Water Extraction Index: a new technique for surface water mapping using Landsat imagery, Remote Sensing of Environment, 140, pp. 23-35, (2014)
  • [5] Gao Y, Wang H, Wang P T, Sun X Y, Lu T T., Population spatial processing for Chinese coastal zones based on census and multiple night light data, Resources Science, 35, 12, pp. 2517-2523, (2013)
  • [6] Guo L, Shu Q Y, Li J., Flood disaster loss assessment based on NPP-VIIRS night lights, Water Resources Development Research, 20, 2, pp. 62-68, (2020)
  • [7] Huang P, Xu X H, Li D L., Rapid extraction of water area in Poyang Lake based on Sentinel-1 satellite images, Journal of Water Resources Research, 7, 5, pp. 483-491, (2018)
  • [8] Huang S E, Zhang Y Z, Gu X Q., Poyanghu flood disaster system study basing on remote sensing and geographical information system, Jiangxi Meteorological Science & Technology, 26, 4, pp. 44-46, (2003)
  • [9] Kato S, Rose F G, Sun-Mack S, Miller W F, Chen Y, Rutan D A, Stephens G L, Loeb N G, Minnis P, Wielicki B A, Winker D M, Char-lock T P, Stackhouse P W, Xu K M, Collins W D., Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties, Journal of Geophysical Research: Atmospheres, 116, D19, (2011)
  • [10] Li F, Mi X N, Liu J, Liu X Y., Spatialization of GDP in Beijing using NPP-VIIRS data, Remote Sensing for Land and Resources, 28, 3, pp. 19-24, (2016)
1234