Google Earth Engine-Based Identification of Flood Extent and Flood-Affected Paddy Rice Fields Using Sentinel-2 MSI and Sentinel-1 SAR Data in Bihar State, India

被引:13
|
作者
Kumar, Himanshu [1 ,4 ]
Karwariya, Sateesh Kumar [2 ,3 ]
Kumar, Rohan [4 ]
机构
[1] ICAR Natl Dairy Res Inst, Karnal 132001, Haryana, India
[2] Govt Gujarat, Commissionerate Rural Dev, Gandhinagar, India
[3] SAC Indian Space Res Org, Ahmadabad, Gujarat, India
[4] Lovely Profess Univ, Phagwara, India
关键词
Flood; Google Earth Engine; Paddy field; Rice; Sentinel-1; SAR; Sentinel-2; MSI; WATER INDEX NDWI;
D O I
10.1007/s12524-021-01487-3
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Flood is the major cause of fatalities associated with natural disasters in the world. In India especially in the state of Bihar, where about half of the area (North Bihar) gets flooded every year due to the overflow of major rivers during the rainy season. Which severely affects human lives, properties, agricultural production, farmers and their livelihood. Usually, the basins of the Kosi and Gandak rivers are known for their worst affects in Bihar. Synthetic aperture radar (SAR) is widely used for robust monitoring of flood events due to its ability to image the surface of the earth in all weather conditions. However, limited studies are available on flood patterns of Bihar and their impact on agriculture. Here, we investigated the flood extents and affected paddy rice fields for Bihar during the months of June-October (2020) using all accessible Sentinel-1 SAR and Sentinel-2 MSI images with additional supporting datasets available on the Google Earth Engine. The study showed that a large portion of Bihar (7019 km(2)) was submerged during monsoon season. The floodwater remains in the agricultural fields for 50 to 65 days causing severe damage to the Kharif crops, mainly rice. The extreme effect of flood was seen in agricultural lands (11.23% of the total area) and populations (15.56% of the total population) in Bihar. Satellite-based identification of flood progression and affected rice fields can be helpful for decision-makers at the time of disaster to prioritize relief and rescue operations.
引用
收藏
页码:791 / 803
页数:13
相关论文
共 50 条
  • [1] Google Earth Engine-Based Identification of Flood Extent and Flood-Affected Paddy Rice Fields Using Sentinel-2 MSI and Sentinel-1 SAR Data in Bihar State, India
    Himanshu Kumar
    Sateesh Kumar Karwariya
    Rohan Kumar
    [J]. Journal of the Indian Society of Remote Sensing, 2022, 50 : 791 - 803
  • [2] Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine
    Singha, Mrinal
    Dong, Jinwei
    Sarmah, Sangeeta
    You, Nanshan
    Zhou, Yan
    Zhang, Geli
    Doughty, Russell
    Xiao, Xiangming
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2020, 166 : 278 - 293
  • [3] Assessment of Sentinel-1 and Sentinel-2 Data for Landslides Identification using Google Earth Engine
    Nugroho, Ferman Setia
    Danoedoro, Projo
    Arjasakusuma, Sanjiwana
    Candra, Danang Surya
    Bayanuddin, Athar Abdurrahman
    Samodra, Guruh
    [J]. 2021 7TH ASIA-PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR (APSAR), 2021,
  • [4] Mapping Paddy Fields in Japan by Using a Sentinel-1 SAR Time Series Supplemented by Sentinel-2 Images on Google Earth Engine
    Inoue, Shimpei
    Ito, Akihiko
    Yonezawa, Chinatsu
    [J]. REMOTE SENSING, 2020, 12 (10)
  • [5] Global Flood Mapper: a novel Google Earth Engine application for rapid flood mapping using Sentinel-1 SAR
    Pratyush Tripathy
    Teja Malladi
    [J]. Natural Hazards, 2022, 114 : 1341 - 1363
  • [6] Global Flood Mapper: a novel Google Earth Engine application for rapid flood mapping using Sentinel-1 SAR
    Tripathy, Pratyush
    Malladi, Teja
    [J]. NATURAL HAZARDS, 2022, 114 (02) : 1341 - 1363
  • [7] Multi-Temporal Sentinel-1 SAR and Sentinel-2 MSI Data for Flood Mapping and Damage Assessment in Mozambique
    Nhangumbe, Manuel
    Nascetti, Andrea
    Ban, Yifang
    [J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2023, 12 (02)
  • [8] Automatic flood detection using sentinel-1 images on the google earth engine
    Moharrami, Meysam
    Javanbakht, Mohammad
    Attarchi, Sara
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2021, 193 (05)
  • [9] Automatic flood detection using sentinel-1 images on the google earth engine
    Meysam Moharrami
    Mohammad Javanbakht
    Sara Attarchi
    [J]. Environmental Monitoring and Assessment, 2021, 193
  • [10] Monitoring the tropical cyclone 'Yass' and 'Amphan' affected flood inundation using Sentinel-1/2 data and Google Earth Engine
    Halder, Bijay
    Bandyopadhyay, Jatisankar
    [J]. MODELING EARTH SYSTEMS AND ENVIRONMENT, 2022, 8 (03) : 4317 - 4332