Rapid Flood Monitoring Using Sentinel-1 and Landsat-8 Images (Case study: Kashkan River, Poldakhter City)

Document Type : Original Article

Authors

1 M.Sc. Student, Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran

2 Department of Remote sensing and GIS, Faculty of Geography, University of Tehran

3 PhD Student, Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran

10.30467/nivar.2023.417413.1265

Abstract

Flood is known as one of the natural disasters that cause financial and human losses not only in developing countries but also in the developed countries. Synthetic Aperture Radar (SAR) sensors are an essential data source for flood crisis planners and experts, because they have the ability to image the earth's surface independently of weather conditions and time of the day. This advantage coupled with cloud computing platforms such as Google Earth Engine (GEE) provide a tremendous opportunity for the crisis response community for effective management plans. It allows them to quickly access ready data for analysis which is of great importance in case of flooding. The purpose of this research is to quickly monitor the flood of Kashkan river. The algorithm presented in this study uses time series images of Sentinel-1 and Landsat 8 along with other auxiliary data for flood monitoring in the GEE system. This algorithm relies on multi-temporal SAR statistics to identify unexpected floods in near real-time. Additionally, historical Landsat-based surface water class probabilities are used to distinguish unexpected floods from permanent or seasonal surface water. Based on the results of this research, Sentinel-1 images have an acceptable performance for flooded areas detection in Sentinel-1 images. Therefore, managers can use this method to obtain flood information and locations in order to reduce flood damages.

Keywords

Main Subjects

References

1.    حمیدی فراهانی، ر.، نیکنام سرابی، ح. و فارسی، ز. (1398). درس آموخته های بحران سیل لرستان: تجربه امدادرسانی در سیل پلدختر. علوم مراقبتی نظامی، 6(3 (مسلسل 21) )، 171-173. 
2.    دودانگه، پ.، عبادی، ح. و کیانی، ع. (1400). شناسایی مناطق سیل‏ زده با محاسبات آماری سری زمانی بر پایۀ تلفیق داده‌های راداری و اپتیکی. اکوهیدرولوژی، 8(3)، 623-639.
3.    رجبی زاده، ی.، ایوب زاده، س.ع.، و ظهیری، ع. (1398). بررسی سیل استان گلستان در سال 1397 و 1398 و ارائه ی راه کارهای کنترل و مدیریت آن در آینده. اکوهیدرولوژی، 6(4 )، 921-942. 
4.    سلیمانی، ک.، درویشی، ش. (1399). پهنه‌‌بندی و پایش خطر سیل بهار 1398 خوزستان با استفاده از داده های لندست-8. اکوهیدرولوژی، 7(3)، 647-662.‎
5.    سلیمانی ساردو، ف.، رفیعی ساردویی، ا.، مصباح زاده، ط. و آذره، ع. (1400). استفاده از تصاویر سنتینل-1 جهت پایش خسارت سیلاب فروردین ، جنوب استان کرمان براساس الگوریتم جنگل تصادفی. مجله علوم و مهندسی آبخیزداری ایران، 15(53 )، 23-32. 
6.    گنجی، ک.، قره‌چلو، س. و احمدی، ا. (1399). استخراج پهنه‌های سیلابی با استفاده از نسبت‌گیری طیفی داده‌های ماهواره‌ای Landsat-8 و Sentinel-2 (مطالعه موردی: سیل آق‌قلا). ترویج و توسعه آبخیزداری، 8(31)، 42-53.
7.    نگارش، ح.، طاووسی، ت. و مهدی نسب، م. (1390). بررسی شدت سیل خیزی حوضه آبریز رودخانه کشکان. جغرافیای طبیعی، 4(13)، 49-58.
8.    Amani, M. et al, 2020. Google earth engine cloud computing platform for remote sensing big data applications: A comprehensive review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
9.    Ban, Y., Jacob, A. and Gamba, P. 2015. Spaceborne SAR data for global urban mapping at 30 m resolution using a robust urban extractor. ISPRS Journal of Photogrammetry and Remote Sensing, 103, pp.28-37.
10.    Borah, S.B., Sivasankar, T., Ramya, M.N.S. & Raju, P.L.N. 2018. Flood inundation mapping and monitoring in Kaziranga National Park, Assam using Sentinel-1 SAR data. Environmental monitoring and assessment, 190(9): 520.
11.    DeVries, B., Huang, C., Armston, J., Huang, W., Jones, J. W., & Lang, M. W. 2020. Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine. Remote Sensing of Environment, 240, 111664.
12.    Inman, V.L. and Lyons, M.B. 2020. Automated inundation mapping over large areas using Landsat data and Google Earth Engine. Remote Sensing, 12(8): pp.1348.
13.    Moharrami, M., Javanbakht, M., & Attarchi, S. 2021. Automatic flood detection using sentinel-1 images on the google earth engine. Environmental monitoring and assessment, 193, pp,1-17.‏
14.    Pour Akrami, S., Tavakoli Saboor, S.M., Mohammadi Islam Javi, Z., Ghasemzadeh, A. 
2017. Rapid Extraction of Flooded Area Using SAR Images. 24th National Geomatics Conference. pp.1-6.
15.    Shen, X., Wang, D., Mao, K., Anagnostou, E. and Hong, Y. 2019. Inundation extent mapping by synthetic aperture radar: a review. Remote Sensing, 11(7): pp.1-17
16.    Wang, Y., Colby, JD. and Mulcahy, KA. 2002. An efficient method for mapping flood extent in a coastal floodplain using Landsat TM and DEM data. International Journal of Remote Sensing 23(18), pp.3681– 3696.
 
 
Nivar
Volume 47, 122-123 - Serial Number 122
September 2023
Pages 82-94

Files

History

  • Receive Date: 21 September 2023
  • Accept Date: 11 October 2023
  • First Publish Date: 11 October 2023

Share

How to cite

Statistics