Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine

被引:119
作者
Singha, Mrinal [1 ]
Dong, Jinwei [1 ]
Sarmah, Sangeeta [2 ]
You, Nanshan [1 ]
Zhou, Yan [1 ]
Zhang, Geli [3 ]
Doughty, Russell [4 ]
Xiao, Xiangming [4 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
[3] China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China
[4] Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA
基金
中国国家自然科学基金;
关键词
Flood; Sentinel-1; SAR; Google Earth Engine; Bangladesh; Sentinel-2; SURFACE-WATER; EXTENT; RESOLUTION; DYNAMICS;
D O I
10.1016/j.isprsjprs.2020.06.011
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Globally, flooding is the leading cause of natural disaster related deaths, especially in Bangladesh where approximately one third of national area gets flooded annually by overflowing rivers during the monsoon season, which drastically affects paddy rice agriculture and food security. However, existing studies on the pattern of floods and their impact on agriculture in Bangladesh are limited. Here we examined the spatiotemporal pattern of floods for the country during 2014-2018 using all the available Sentinel-1 Synthetic Aperture Radar (SAR) images and the Google Earth Engine (GEE) platform. We also identified the flood-affected paddy rice fields by integrating the flooding areas and remote sensing-based paddy rice planting areas. Our results indicate that flooding is frequent in northeastern Bangladesh and along the three major rivers, the Ganges, Brahmaputra, and Meghna. Between 2014 and 2018, the flood-affected paddy rice areas accounted for 1.61-18.17% of the total paddy rice area. The satellite-based detection of floods and flood-affected paddy rice fields advance our understanding of the annual dynamics of flooding in Bangladesh, which is essential for adaptation and mitigation strategies where severe annual floods threaten human lives, properties, and agricultural production.
引用
收藏
页码:278 / 293
页数:16
相关论文
共 56 条
[1]  
Adikari Y., 2009, GLOBAL TRENDS WATER
[2]   Remote Sensing-Based Quantification of the Impact of Flash Flooding on the Rice Production: A Case Study over Northeastern Bangladesh [J].
Ahmed, M. Razu ;
Rahaman, Khan Rubayet ;
Kok, Aaron ;
Hassan, Quazi K. .
SENSORS, 2017, 17 (10)
[3]   Challenges for flood risk management in flood-prone Sirajganj region of Bangladesh [J].
Ali, Md. H. ;
Bhattacharya, B. ;
Islam, A. K. M. S. ;
Islam, G. M. T. ;
Hossain, Md. S. ;
Khan, A. S. .
JOURNAL OF FLOOD RISK MANAGEMENT, 2019, 12 (01)
[4]   Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images [J].
Amitrano, Donato ;
Di Martino, Gerardo ;
Iodice, Antonio ;
Riccio, Daniele ;
Ruello, Giuseppe .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 56 (06) :3290-3299
[5]  
[Anonymous], 2015, The Human Cost of Weather Related Disasters 1995-2015
[6]   The impacts of climate change on river flood risk at the global scale [J].
Arnell, Nigel W. ;
Gosling, Simon N. .
CLIMATIC CHANGE, 2016, 134 (03) :387-401
[7]   A semi-automated tool for surface water mapping with RADARSAT-1 [J].
Brisco, B. ;
Short, N. ;
van der Sanden, J. ;
Landry, R. ;
Raymond, D. .
CANADIAN JOURNAL OF REMOTE SENSING, 2009, 35 (04) :336-344
[8]   Normalized Difference Flood Index for rapid flood mapping: Taking advantage of EO big data [J].
Cian, Fabio ;
Marconcini, Mattia ;
Ceccato, Pietro .
REMOTE SENSING OF ENVIRONMENT, 2018, 209 :712-730
[9]   Multi-temporal synthetic aperture radar flood mapping using change detection [J].
Clement, M. A. ;
Kilsby, C. G. ;
Moore, P. .
JOURNAL OF FLOOD RISK MANAGEMENT, 2018, 11 (02) :152-168
[10]  
Congalton RG, 2008, ASSESSING ACCURACY R