Skip to main content
SpringerLink
Log in

Estimating floodwater from MODIS time series and SRTM DEM data

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

Real-time flood mapping with an automatic flood-detection technique is important in emergency response efforts. However, current mapping technology still has limitations in accurately expressing information on flood areas such as inundation depth and extent. For this reason, the authors attempt to improve a floodwater detection method with a simple algorithm for a better discrimination capacity to discern flood areas from turbid floodwater, mixed vegetation areas, snow, and clouds. The purpose of this study was to estimate a flood area based on the spatial distribution of a nationwide flood from the Moderate Resolution Imaging Spectroradiometer (MODIS) time series images (8-day composites, MOD09A1, 500-m resolution) and a digital elevation model (DEM). The results showed the superiority of the developed method in providing instant, accurate flood mapping by using two algorithms, which modified land surface water index from MODIS image and eight-direction tracking algorithm based on DEM data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Farr T, Rosen P, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, Seal D, Shaffer S, Shimada J, Umland J, Werner M, Oskin M, Burbank D, Alsdorf D (2007) The shuttle radar topography mission. Rev Geophys 45:RG2004. doi:10.1029/2005RG000183

  2. Gao BC (1996) NDWI a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens Environ 58:257–266. doi:10.1016/S0034-4257(96)00067-3

    Article  Google Scholar 

  3. Islam AS, Bala SK, Haque MA (2010) Flood inundation map of Bangladesh using MODIS time-series image. J Flood Risk Manag 99(4):333–339. doi:10.1111/j.1753-318X.2010.01074.x

    Google Scholar 

  4. Kwak Y, Park J, Yorozuya A, Fukami K (2012) Estimation of flood volume in Chao Phraya river basin: Thailand from MODIS images coupled with flood Inundation level, IEEE-IGARSS2012, pp 887–890. doi:10.1109/IGARSS.2012.6351416

  5. Lehner B, Verdin K, Jarvis A (2006) HydroSHEDS Technical Documentation, Version 1.0, World Wildlife Fund US, Washington, pp 1–27

  6. NASA (2003) SRTM Water Body Data (SWBD). http://dds.cr.usgs.gov/srtm/version2_1/SWBD. Accessed 15 January 2011

  7. NDMA (2011) National Disaster Management Authority Government of Pakistan, annual report 2011, Prime Minister’s secretariat, Islamabad in Pakistan. http://www.ndma.gov.pk. Accessed 7 January 2012

  8. Pinheiro ACT, Descloitres J, Privette JL, Susskind J, Iredell L, Schmaltz J (2007) Near-real time retrievals of land surface temperature within the MODIS Rapid Response System. Remote Sens Environ 106:326–336. doi:10.1016/j.rse.2006.09.006

    Article  Google Scholar 

  9. Rosenqvist A, Shimada M, Ito N, Watanabe M (2007) ALOS PALSAR: a pathfinder mission for global-scale monitoring of the environment. IEEE Trans Geosci Remote Sens 45(11):3307–3316. doi:10.1109/TGRS.2007.901027

    Article  Google Scholar 

  10. Sakamoto T, Nguyen V, Kotera A, Ohno H, Ishitsuka N, Yokozawa M (2007) Detecting temporal changes in the extent of annual flooding within the Cambodia and the Vietnamese Mekong Delta from MODIS time-series imagery. Remote Sens Environ 109(3):295–313. doi:10.1016/j.rse.2007.01.011

    Article  Google Scholar 

  11. USGS (2011) The United States Geological Survey. http://lpdaac.usgs.gov/lpdaac/products/modis_products_table/surface_reflectance/8_day_l3_global_500m/myd09a1. Accessed 10 January 2011

  12. USGS (2006) HydroSHEDS, Technical Documentation Version 1.0. pp 1–27. http://hydrosheds.cr.usgs.gov/. Accessed 20 January 2011

  13. Wang M, Shi W, Tang J (2011) Water property monitoring and assessment for China’s inland Lake Taihu from MODIS-Aqua measurements. Remote Sens Environ 115:841–854. doi:10.1016/j.rse.2010.11.012

    Article  Google Scholar 

  14. Xiao X, Boles S, Frolking S, Li C, Bau JY, Salas W (2006) Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images. Remote Sens Environ 100:95–113. doi:10.1016/j.rse.2005.10.004

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant-in-Aid for Young Scientists (B: 24710211).

Author information

Authors and Affiliations

  1. International Centre for Water Hazard and Risk Management (ICHARM) Under the Auspices of UNESCO, Public Works Research Institute (PWRI), 1-6 Minamihara, Tsukuba, Ibaraki, 305-8516, Japan

    Youngjoo Kwak

  2. Tokyo University of Information Sciences, Chiba, 265-8501, Japan

    Jonggeol Park

  3. National Institute for Land and Infrastructure Management (NILIM), Ministry of Land, Infrastructure, Transport and Tourism (MLIT), 1 Asahi, Tsukuba, Ibaraki, 305-0804, Japan

    Kazuhiko Fukami

Authors
  1. Youngjoo Kwak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jonggeol Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kazuhiko Fukami
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Youngjoo Kwak.

About this article

Cite this article

Kwak, Y., Park, J. & Fukami, K. Estimating floodwater from MODIS time series and SRTM DEM data. Artif Life Robotics 19, 95–102 (2014). https://doi.org/10.1007/s10015-013-0140-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-013-0140-y

Keywords

Search

Navigation