Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data

References

• Ahlmer AK, Cavalli M, Hansson K, Koutsouris AJ, Crema S, Kalantari Z. 2018. Soil moisture remote-sensing applications for identification of flood-prone areas along transport infrastructure. Environ Earth Sci. 77(14):533.
   Web of Science ®Google Scholar
• Amarnath G, Matheswaran K, Pandey P, Alahacoon N, Yoshimoto S. 2017. Flood mapping tools for disaster preparedness and emergency response using satellite data and hydrodynamic models: a case study of Bagmathi Basin, India. Proc Natl Acad Sci India, Sect A Phys Sci. 87(4):941–950.
   Web of Science ®Google Scholar
• Berezowski T, Bielinski T, Osowicki J. 2020. Flooding extent mapping for synthetic aperture radar time series using river gauge observations. IEEE J Sel Top Appl Earth Obs Remote Sens. 13:2626–2638.
   Web of Science ®Google Scholar
• Bhatt CM, Rao GS. 2016. Ganga floods of 2010 in Uttar Pradesh, north India: a perspective analysis using satellite remote sensing data. Geomatics Nat Hazards Risk. 7(2):747–763.
   Web of Science ®Google Scholar
• Bhatt CM, Rao GS, Farooq M, Manjusree P, Shukla A, Sharma SVSP, Kulkarni SS, Begum A, Bhanumurthy V, Diwakar PG, et al. 2017. Satellite-based assessment of the catastrophic Jhelum floods of September 2014, Jammu & Kashmir, India. Geomatics Nat Hazards Risk. 8 (2):309–327..
   Web of Science ®Google Scholar
• Bhatt CM, Rao GS, Manjushree P, Bhanumurthy V. 2010. Space based disaster management of 2008 Kosi floods, North Bihar, India. J Indian Soc Remote Sens. 38(1):99–108.
   Web of Science ®Google Scholar
• Borah SB, Sivasankar T, Ramya MNS, Raju PLN. 2018. Flood inundation mapping and monitoring in Kaziranga National Park, Assam using Sentinel-1 SAR data. Environ Monit Assess. 190(9):520.
   PubMed Web of Science ®Google Scholar
• Canty MJ, Nielsen AA, Conradsen K, Skriver H. 2020. Statistical analysis of changes in Sentinel-1 time series on the google earth engine. Remote Sens. 12(1):46.
   Google Scholar
• Clement MA, Kilsby CG, Moore P. 2018. Multi‐temporal synthetic aperture radar flood mapping using change detection. J Flood Risk Manage. 11(2):152–168.
   Web of Science ®Google Scholar
• Dhar ON, Nandargi S. 2000. A study of floods in the Brahmaputra Basin in India. Int J Climatol. 20(7):771–781. AID-JOC518 > 3.0.CO;2-Z
   Web of Science ®Google Scholar
• Dhar ON, Nandargi S. 2002. Flood study of the Himalayan tributaries of the Ganga River. Meteorol Appl. 9(1):63–68. https://doi.org/doi/pdf/10.1017/S135048270200107X
   Web of Science ®Google Scholar
• Džubáková K, Molnar P, Schindler K, Trizna M. 2015. Monitoring of riparian vegetation response to flood disturbances using terrestrial photography. Hydrol Earth Syst Sci. 19(1):195–208.
   Web of Science ®Google Scholar
• ESA Sentinel Online. User guides and technical guides of Sentinel-1 SAR. [accessed 2020 Jun 8]. Available from: https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar
   Google Scholar
• Ezzine A, Darragi F, Rajhi H, Ghatassi A. 2018. Evaluation of Sentinel-1 data for flood mapping in the upstream of Sidi Salem dam (Northern Tunisia). Arab J Geosci. 11(8):170.
   Web of Science ®Google Scholar
• Flood Management Information System. (n.d.). History of flood. [accessed 26 June 2019]. Available from: http://fmis.bih.nic.in/history.html.
   Google Scholar
• Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R. 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens Environ. 202:18–27..
   Web of Science ®Google Scholar
• Guha-Sapir D, Rodriguez-Llanes JM, Jakubicka T. 2011. Using disaster footprints, population databases and GIS to overcome persistent problems for human impact assessment in flood events. Nat Hazards. 58(3):845–852.
   Web of Science ®Google Scholar
• Guhathakurta P, Sreejith OP, Menon PA. 2011. Impact of climate change on extreme rainfall events and flood risk in India. J Earth Syst Sci. 120(3):359–373.
   Web of Science ®Google Scholar
• Henry JB, Chastanet P, Fellah K, Desnos YL. 2006. Envisat multi‐polarized ASAR data for flood mapping. Int J Remote Sens. 27(10):1921–1929.
   Web of Science ®Google Scholar
• Herrera-Cruz V, Koudogbo F, Herrera V. 2009. TerraSAR-X rapid mapping for flood events. Proceedings of the International Society for Photogrammetry and Remote Sensing (Earth Imaging for Geospatial Information), Hannover, Germany, p. 170–175.
   Google Scholar
• Ho-Hagemann HTM, Hagemann S, Rockel B. 2015. On the role of soil moisture in the generation of heavy rainfall during the Oder flood event in July 1997. Tellus A: Dyn Meteorol Oceanogr. 67(1):28661.
   Web of Science ®Google Scholar
• Huffman GJ, Bolvin DT, Braithwaite D, Hsu K, Joyce R, Xie P, Yoo SH. 2015. NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG). Algorithm Theor Basis Doc (ATBD) Version. 4:26.
   Google Scholar
• Huffman GJ, Bolvin DT, Nelkin EJ. 2015. Integrated multi-satellite retrievals for GPM (IMERG) technical documentation. NASA/GSFC Code. 612(2015):47.
   Google Scholar
• Jena PP, Chatterjee C, Pradhan G, Mishra A. 2014. Are recent frequent high floods in Mahanadi basin in eastern India due to increase in extreme rainfalls? J Hydrol. 517:847–862..
   Web of Science ®Google Scholar
• Jha RK, Gundimeda H. 2019. An integrated assessment of vulnerability to floods using composite index–A district level analysis for Bihar, India. Int J Disaster Risk Reduct. 35:101074..
   Web of Science ®Google Scholar
• Kwak Y, Arifuzzanman B, Iwami Y. 2015. Prompt proxy mapping of flood damaged rice fields using MODIS-derived indices. Remote Sens. 7(12):15969–15988..
   Google Scholar
• Lal P, Prakash A, Kumar A. 2020. Google Earth Engine for concurrent flood monitoring in the lower basin of Indo-Gangetic-Brahmaputra plains. Nat Hazards. :. 104(2): 1947–1952.
   PubMed Web of Science ®Google Scholar
• Manjusree P, Bhatt CM, Begum A, Rao GS, Bhanumurthy V. 2015. A decadal historical satellite data analysis for flood hazard evaluation: a case study of Bihar (North India). Singap J Trop Geogr. 36(3):308–323.
   Web of Science ®Google Scholar
• Manjusree P, Kumar LP, Bhatt CM, Rao GS, Bhanumurthy V. 2012. Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence angle SAR images. Int J Disaster Risk Sci. 3(2):113–122.
   Web of Science ®Google Scholar
• Martinez JM, Le Toan T. 2007. Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data. Remote Sens Environ. 108(3):209–223.
   Web of Science ®Google Scholar
• Matheswaran K, Alahacoon N, Pandey R, Amarnath G. 2019. Flood risk assessment in South Asia to prioritize flood index insurance applications in Bihar, India. Geomatics Nat Hazards Risk. 10(1):26–48.
   Web of Science ®Google Scholar
• McFeeters SK. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int J Remote Sens. 17(7):1425–1432.
   Web of Science ®Google Scholar
• Mishra V, Aaadhar S, Shah H, Kumar R, Pattanaik DR, Tiwari AD. 2018. The Kerala flood of 2018: combined impact of extreme rainfall and reservoir storage. Hydrol Earth Syst Sci Discuss. 1–13. doi: https://doi.org/10.5194/hess-2018-480
   Google Scholar
• Mishra AK, Meer MS, Nagaraju V. 2019. Satellite-based monitoring of recent heavy flooding over north-eastern states of India in July 2019. Nat Hazards. 97(3):1407–1412..
   Web of Science ®Google Scholar
• Mishra K, Sinha R. 2020. Flood risk assessment in the Kosi megafan using multi-criteria decision analysis: A hydro-geomorphic approach. Geomorphology. 350:106861.
   Web of Science ®Google Scholar
• Nelson RF. 1982. Detecting forest canopy change using Landsat. NASA technical memorandum 83918. Greenbelt, MD: Goddard Space Flight Centre.
   Google Scholar
• Pai DS, Bandgar A, Devi S, Musale M, Badwaik MR, Kundale AP, Gadgil S, Mohapatra M, Rajeevan M. 2020. New normal dates of onset/progress and withdrawal of southwest monsoon over India. [accessed 2020 Jun 15]. https://internal.imd.gov.in/press_release/20200515_pr_804.pdf.
   Google Scholar
• Pandey RK, Crétaux JF, Bergé-Nguyen M, Tiwari VM, Drolon V, Papa F, Calmant S. 2014. Water level estimation by remote sensing for the 2008 flooding of the Kosi River. Int J Remote Sens. 35(2):424–440.
   Web of Science ®Google Scholar
• Prasad AK, Kumar VK, Singh S, Singh RP. 2006. Potentiality of multi-sensor satellite data in mapping flood hazard. J Indian Soc Remote Sens. 34(3):219–231..
   Web of Science ®Google Scholar
• Prasad AK, Singh S, Singh RP. 2005. Extreme rainfall event of July 25–27, 2005 over Mumbai, West Coast, India. J Indian Soc Remote Sens. 33(3):365–370..
   Web of Science ®Google Scholar
• Ray K, Pandey P, Pandey C, Dimri AP, Kishore K. 2019. On the recent floods in India. Current Science. 117(2):204.
   Web of Science ®Google Scholar
• Schlaffer S, Matgen P, Hollaus M, Wagner W. 2015. Flood detection from multi-temporal SAR data using harmonic analysis and change detection. Int J Appl Earth Obs Geoinf. 38:15–24.
   Web of Science ®Google Scholar
• Shrestha R, Di L, Yu G, Shao Y, Kang L, Zhang B. 2013 Aug. Detection of flood and its impact on crops using NDVI-Corn case. In 2013 Second International Conference on Agro-Geoinformatics (Agro-Geoinformatics). IEEE; p. 200–204.
   Google Scholar
• Singh RP, Kumar R, Tare V. 2009. Variability of soil wetness and its relation with floods over the Indian subcontinent. Can J Remote Sens. 35(1):85–97.
   Web of Science ®Google Scholar
• Singh A. 1989. Review article digital change detection techniques using remotely-sensed data. Int J Remote Sens. 10(6):989–1003..
   Web of Science ®Google Scholar
• Singha M, Dong J, Sarmah S, You N, Zhou Y, Zhang G, Doughty R, Xiao X. 2020. Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine. ISPRS J Photogramm Remote Sens. 166:278–293.
   Web of Science ®Google Scholar
• Singh SK, Pandey AC, Nathawat MS. 2011. Rainfall variability and spatio temporal dynamics of flood inundation during the 2008 Kosi flood in Bihar State. Asian J Earth Sci. 4(1):9–19.
   Google Scholar
• Sinha R, Bapalu GV, Singh LK, Rath B. 2008. Flood risk analysis in the Kosi river basin, north Bihar using multi-parametric approach of analytical hierarchy process (AHP). J Indian Soc Remote Sens. 36(4):335–349.
   Web of Science ®Google Scholar
• Sunitha Devi S, Krishna Mishra SP, Singh NK, Kashyapi A, Sathi Devi K. 2019. Regional characteristics of the south-west monsoon. [accessed 2020 Sep 20]. http://www.imdpune.gov.in/Clim_Pred_LRF_New/Reports/Monsoon_Report_2019/Chapter_1.pdf.
   Google Scholar
• Tiwari V, Kumar V, Matin MA, Thapa A, Ellenburg WL, Gupta N, Thapa S. 2020. Flood inundation mapping- Kerala 2018; harnessing the power of SAR, automatic threshold detection method and Google Earth Engine. Plos One. 15(8):e0237324.
   PubMed Web of Science ®Google Scholar
• Tripathi G, Pandey AC, Parida BR, Shakya A. 2020. Comparative flood inundation mapping utilizing multi-temporal optical and SAR satellite data over North Bihar region: a case study of 2019 flooding event over North Bihar. In: Spatial information science for natural resource management. IGI Global Publisher of Timely Knowledge; p. 149–168. doi: https://doi.org/10.4018/978-1-7998-5027-4.ch008. https://www.igi-global.com/chapter/comparative-flood-inundation-mapping-utilizing-multi-temporal-optical-and-sar-satellite-data-over-north-bihar-region/257701
   Google Scholar
• Tripathi G, Parida BR, Pandey AC. 2019. Spatio-temporal rainfall variability and flood prognosis analysis using satellite data over North Bihar during the August 2017 flood event. Hydrology. 6(2):38..
   Web of Science ®Google Scholar
• Twele A, Cao W, Plank S, Martinis S. 2016. Sentinel-1-based flood mapping: a fully automated processing chain. Int J Remote Sens. 37(13):2990–3004.
   Web of Science ®Google Scholar
• Uddin K, Matin MA, Meyer FJ. 2019. Operational flood mapping using multi-temporal sentinel-1 SAR images: a case study from Bangladesh. Remote Sens. 11(13):1581.
   Google Scholar
• Ulaby FT, MC. Dobson. 1989. Handbook of radar scattering statistics for terrain. Norwood, MA: Artech House.
   Google Scholar
• Vanama VSK, Mandal D, Rao YS. 2020. GEE4FLOOD: rapid mapping of flood areas using temporal Sentinel-1 SAR images with Google Earth Engine cloud platform. J Appl Rem Sens. 14(03):1.
   Google Scholar
• Vishnu CL, Sajinkumar KS, Oommen T, Coffman RA, Thrivikramji KP, Rani VR, Keerthy S. 2019. Satellite-based assessment of the August 2018 flood in parts of Kerala, India. Geomatics Nat Hazards Risk. 10(1):758–767..
   Web of Science ®Google Scholar
• Wang L, Diao C, Xian G, Yin D, Lu Y, Zou S, Erickson TA. 2020. A summary of the special issue on remote sensing of land change science with Google earth engine. Remote Sens Environ. 248:112002..
   Web of Science ®Google Scholar
• Yuan F, Zhang L, Soe KMW, Ren L, Zhao C, Zhu Y, Jiang S, Liu Y. 2019. Applications of TRMM-and GPM-Era multiple-satellite precipitation products for flood simulations at sub-daily scales in a sparsely gauged watershed in Myanmar. Remote Sens. 11(2):140.
   Google Scholar