A novel change detection and threshold-based ensemble of scenarios pyramid for flood extent mapping using Sentinel-1 data

被引:5
|
作者
Pedzisai, Ezra [1 ]
Mutanga, Onisimo [1 ]
Odindi, John [1 ]
Bangira, Tsitsi [1 ]
机构
[1] Sch Agr Earth & Environm Sci, Discipline Geog, Private Bag X01, ZA-3201 Pietermaritzburg, South Africa
基金
新加坡国家研究基金会;
关键词
Change detection and thresholding; Flood extent map; SAR; Scenarios ensemble; Sentinel-1; RIVER; INUNDATION;
D O I
10.1016/j.heliyon.2023.e13332
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Flood disasters destroy infrastructure, disrupt ecosystem processes, adversely affect social and economic activities and cause human fatalities. As such, flood extent mapping (FEM) is critical to mitigate these impacts. Specifically, FEM is essential to mitigate adverse impacts through early warning, efficient response during evacuation, search, rescue and recovery. Furthermore, accurate FEM is crucial for policy formulation, planning and management, rehabilitation, and promoting community resilience for sustainable occupation and use of floodplains. Recently, remote sensing has become valuable in flood studies. However, whereas free passive remote sensing images have been common input into predictive models, damage assessment and FEM, their utility is constrained by clouds during flooding events. Conversely, microwave-based data is unconstrained by clouds, hence is important for FEM. Hence, to increase the reliability and accuracy of FEM using Sentinel-1 radar data, we propose a three-step process that builds an ensemble of scenarios pyramid (ESP) based on change detection and thresholding technique. We deployed the ESP technique and tested it on a use-case based on two, five and 10 images. The usecase calculated three co-polarized Vertical-Vertical (VV) and three cross-polarized Vertical-Horizontal (VH) normalized difference flood index scenarios to form six binary classified FEMs at the base. We ensembled the base scenarios to three dual-polarized centre FEMs, and likewise the centre scenarios to a final pinnacle flood extent map. The base, centre and pinnacle scenarios were validated using six binary classification performance metrics. The results show that the ESP increased the base-to-pinnacle minimum classification performance metrics with overall accuracy, Cohen's Kappa, intersect over union, recall, F1-score, and Matthews Correlation coefficient of 93.204%, 0.864, 0.865, 0.870, 0.927, and 0.871 respectively. The study also established that the VV channels were superior in FEM than VH at the ESP base. Overall, this study demonstrates the efficacy of the ESP for operational flood disaster management.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images
    Amitrano, Donato
    Di Martino, Gerardo
    Iodice, Antonio
    Riccio, Daniele
    Ruello, Giuseppe
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 56 (06): : 3290 - 3299
  • [32] SHIP DETECTION USING SENTINEL-1 SAR DATA
    Grover, Aayush
    Kumar, Shashi
    Kumar, Anil
    [J]. ISPRS TC V MID-TERM SYMPOSIUM GEOSPATIAL TECHNOLOGY - PIXEL TO PEOPLE, 2018, 4-5 : 317 - 324
  • [33] A Sentinel-1 Based Processing Chain for Detection of Cyclonic Flood Impacts
    Alexandre, Cyprien
    Johary, Rosa
    Catry, Thibault
    Mouquet, Pascal
    Revillion, Christophe
    Rakotondraompiana, Solofo
    Pennober, Gwenaelle
    [J]. REMOTE SENSING, 2020, 12 (02)
  • [34] Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold
    Tran, Khuong H.
    Menenti, Massimo
    Jia, Li
    [J]. REMOTE SENSING, 2022, 14 (22)
  • [35] LAND COVER MAPPING USING SENTINEL-1 SAR DATA
    Abdikan, S.
    Sanli, F. B.
    Ustuner, M.
    Calo, F.
    [J]. XXIII ISPRS CONGRESS, COMMISSION VII, 2016, 41 (B7): : 757 - 761
  • [36] Flood extent mapping for Namibia using change detection and thresholding with SAR
    Long, Stephanie
    Fatoyinbo, Temilola E.
    Policelli, Frederick
    [J]. ENVIRONMENTAL RESEARCH LETTERS, 2014, 9 (03):
  • [37] Comparative Analysis of Flood Extent Mapping Using Sentinel-1A and Landsat-8 Data
    Orangzeb, Muhammad
    [J]. 2017 FIFTH INTERNATIONAL CONFERENCE ON AEROSPACE SCIENCE & ENGINEERING (ICASE), 2017,
  • [38] Random forest classifications for landuse mapping to assess rapid flood damage using Sentinel-1 and Sentinel-2 data
    Billah, Maruf
    Islam, A. K. M. Saiful
    Bin Mamoon, Wasif
    Rahman, Mohammad Rezaur
    [J]. REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2023, 30
  • [39] DETECTION OF LAND USE CHANGE IN URBAN AGGLOMERATION USING SENTINEL-1 SAR DATA
    Zhang, Hong
    Cao, Han
    Wang, Chao
    Dong, Yinbo
    Zhang, Bo
    Li, Lu
    [J]. 2019 10TH INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTITEMPORAL REMOTE SENSING IMAGES (MULTITEMP), 2019,
  • [40] Multitemporal Change Detection Analysis in an Urbanized Environment Based upon Sentinel-1 Data
    Gruenhagen, Lars
    Juergens, Carsten
    [J]. REMOTE SENSING, 2022, 14 (04)