Skip to main content
Log in

Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review

  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

The conventional means to record hydrological parameters of aflood often fail to record an extreme event. Remote sensingtechnology along with geographic information system (GIS)has become the key tool for flood monitoring in recent years.Development in this field has evolved from optical to radarremote sensing, which has provided all weather capabilitycompared to the optical sensors for the purpose of flood mapping.The central focus in this field revolves around delineation of floodzones and preparation of flood hazard maps for the vulnerable areas.In this exercise flood depth is considered crucial for flood hazardmapping and a digital elevation model (DEM) is considered to bethe most effective means to estimate flood depth from remotelysensed or hydrological data. In a flat terrain accuracy of floodestimation depends primarily on the resolution of the DEM. Riverflooding in the developing countries of monsoon Asia is very acutebecause of their heavy dependence on agriculture but any floodestimation or hazard mapping attempt in this region is handicappedby poor availability of high resolution DEMs. This paper presents areview of application of remote sensing and GIS in flood managementwith particular focus on the developing countries of Asia.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Ali, A. and Quadir, D. A.: 1987, Agricultural hydrologic and oceanographic studies in Bangladesh with NOAA AVHRR data, International Journal of Remote Sensing 8(6), 917–925.

    Google Scholar 

  • Ali, S., Hassan, A., Martin, T. C., and Hassan Q. K.: 2001, Geospatial tools for monitoring flood plain water dynamics, In: M. Owe, K. Brubaker, J. Ritchie, and A. Rango, A. (eds), Remote Sensing and Hydrology 2000, IAHS Publication, Oxford, pp. 465–471.

    Google Scholar 

  • Andre, G., Guillande, R., and Bahoken, F.: 2002, Flood mapping using spatial radar and optical imagery and digital elevation model: Limits and capacities, Houille Blanche-Revue Int. De LEAU 1, 49–54.

    Google Scholar 

  • Barton, I. and Bathols, J.: 1989, Monitoring floods with AVHRR, International Journal of Remote Sensing 10(12), 1873–1892.

    Google Scholar 

  • Berg, A. and Gregiore, J. M.: 1983, Use of remote sensing techniques for rice production forecasting in West Africa, (Mali and Guinea: Niger-Bani project), ESA Satellite Remote Sensing for Developing Countries, Ispra, Italy, pp. 161–168

    Google Scholar 

  • Beven, K. J. and Kirkby, M. J.: 1979, A physically based, variable contributing area model of basin hydrology, Hydrol. Sci. Bull. 24, 43–69.

    Google Scholar 

  • Bhavsar, P. D.: 1984, Review of remote sensing applications in hydrology and water resource management in India, Advances in Space Research 4(11), 193–200.

    Google Scholar 

  • Blyth, K.: 1995, A telenetwork for acquisition, processing and dissemination of Earth Observation data for monitoring and emergency management of floods, In: Proc. First ERS Thematic Working Group Meeting on Flood Monitoring. European Space Agency/ESRIN, Frascati, Italy, 26-27 June.

    Google Scholar 

  • Boyle, S. J., Tsams, I. K., Manber, A. S. C. E., and Kanaroglu, P. S.: 1998, Developing geographical information system for land use impact assessment in flooding conditions, Journal of Water Resource Planning and Management 124(2), 89–98.

    Google Scholar 

  • Brakenridge, G. R., Tracy, R. T., and Know, J. C.: 1998, Orbital SAR remote sensing of the river flood waves, International Journal of Remote Sensing 19(7), 1439–1445

    Google Scholar 

  • Brimicombe, J., and Bratlet, J. M.: 1996, Linking geographical information system with hydraulic simulation modeling for flood risk assessment: The Honk Kong Approach, In: M. F. Goodchild (eds), GIS and Environmental Modeling, Oxford University Press, New York, pp. 165–168.

    Google Scholar 

  • Brivio, P. A., Colombo, R., Maggi, M., and Tomasoni, R.: 2002, Integration of remote sensing data and GIS for accurate mapping of flooded areas, International Journal of Remote Sensing 23(3), 429–441.

    Google Scholar 

  • Brouder, J. A. M.: 1994, Flood study in the Meghna-Dhonagoda Polder, Bangladesh, In: Proc. Asian Institute of Remote Sensing, Bangalore, India, 17-23 November.

    Google Scholar 

  • Brunsden, D. and Thorns, J. B.: 1979, Landscape sensitivity and change, Trans. Inst. Br. Geogr., New Series 4, 463–484.

    Google Scholar 

  • Chen, P., Liew, S. C., and Lim, H.: 1999, Flood detection using multitemporal Radarsat and ERS SAR data, In: Proc. 20th Asian Conference of Remote Sensing, Hong Kong, 22-25 November.

  • Choen, K. and Kwang-Hoon, C.: 1998, Flood damage mapping in North Korea using multi-sensor data, In: Proc. 19th Asian Conference of Remote Sensing, Manila, Philippines, 16-20 November.

  • Clark, M. J.: 1998, Putting water in its place: A perspective on GIS in hydrology and water management, Hydrological Processes 12, 823–834.

    Google Scholar 

  • Collins, S. H. and Moon, G. C.: 1981, Algorithms for dense digital terrain models, Photogrammetric Engineering and Remote Sensing 47, 71–76.

    Google Scholar 

  • Coppock, J. T.: 1995, GIS and natural hazard: an overview from a GIS perspective, In: A. Carrara and F. Guzzetti (eds), Geographical Information System in Assessing Natural Hazard, Kluwer Academic, Netherlands, pp. 21–34.

    Google Scholar 

  • Deutsch, M.: 1976, Optical processing of ERTS data for determining extent of 1973 Mississippi River flood, USGS Professional Paper 929, ERTS-1, A New Window on Our Planet, pp. 209–222.

  • Deutsch, M. and Ruggles, F.: 1974, Optical data processing and projected application of the ERTS1 imagery covering the 1973 Mississippi River Valley floods, Water Resource Bulletin 10(5), 1023–1039.

    Google Scholar 

  • Deutsch, M., Ruggles, F., Guss, P., and Yost, E.: 1973, Mapping the 1973 Mississippi floods from the Earth Resource Technology satellites, In: Proc. International Symposium on Remote Rensing and Water Resource Management, American Water Resource Association, No. 17, Burlington, Ontario, pp. 39–55.

    Google Scholar 

  • Dhakal, A. S., Amda, T., Aniya, M., and Sharma, R. R.: 2002, Detection of areas associated with flood and erosion caused by a heavy rainfall using multi temporal Landsat TM data, Photogrammetric Engineering and Remote Sensing 68(3), 233–239.

    Google Scholar 

  • Fowler, R. A.: 2002, LIDAR for flood mapping, Earth Observation Magazine 9(7) (http://www.eomonline.com/Common/Archives/July00/robert.htm, true as par 30th May, 2003)

  • Gamon, J. A., Field, C. B., Goulden, M. L., Griffin, K. L., Hartley, A. E., Joel, G., Penuela, J., and Valentini, R.: 1995, Relationship between NDVI, canopy structure and photosynthesis in their Californian vegetation types, Ecological Applications 5, 28–41.

    Google Scholar 

  • Godschalk, D. R.: 1991, Disaster mitigation and hazard management, In: T. E. Drabek and G. J. Hoetmer (eds), Emergency Management: Principles and Practice for Local Government, International City Management Association, Washington, D.C. pp. 131–160.

    Google Scholar 

  • Gumley, L. and King, M. D.: 1995, Remote sensing of flooding in the US Upper Midwest during the summer of 1993, Bulletin of American Meteorological Society 76(6), 933–943.

    Google Scholar 

  • Gupta, A.: 1983, High magnitude floods and stream channel response, Special Publication of International Association of Sedimentology 6, 219–227.

    Google Scholar 

  • Gupta, A.: 1988, Large floods as geomorphic events in the humid tropics, In: Victor R. Barker, Craig R. Kochel, and Peter C. Paton (eds), Flood Geomorphology, John Wiley and Sons, pp. 301–321.

  • Hallberg, G. R., Hoyer, B. E., and Rango, A.: 1973, Application of ERTS1 imagery to flood inundation mapping, NASA Special Publication No. 327, Symposium on Significant Results Obtained from the Earth Resources Satellite 1, Vol. 1, Technical presentations, section A, pp. 745–753.

    Google Scholar 

  • Hausmann, P. and Weber, M.: 1988, Possible contributions of hydroinformatics to risk analysis in insurance, In: Proc. 2nd International Conference on Hydroinformatics, Zurich, Switzerland, 9-13 September, Balkema, Rotterdam.

    Google Scholar 

  • Hess, L. L., Melack, J. M., and Simonett, D. S.: 1990, Radar detection of flooding beneath the forest canopy-a review, International Journal of Remote Sensing 11(7), 1313–1325.

    Google Scholar 

  • Hodgson, M. E., Jensen, J. R., Schmidt, L., Schill, S., and Davis, B.: 2003, An evaluation of LIDAR and IFSAR derived digital elevation models in leaf-on conditions with USGS level-1 and level-2 DEMs, Remote Sensing of Environment 84, 295–308.

    Google Scholar 

  • Honda, K. C., Francis, X.J., and Sah V. P.: 1997, Flood monitoring in central plain of Thailand using JERS-1 SAR data, In: Proc. 18th Asian Conference of Remote Sensing,Malaysia, 20-24 October.

  • Horritt, M. S. and Bates, P. D.: 2001, Predicting flood plain inundation: Raster based modeling versus the finite element approach, Hydrological Processes 15(5), 825–842.

    Google Scholar 

  • Huguenin, R. L., Karaska, M. A., Blaricom, D. V., and Jensen, J. R.: 1997, Subpixel classification of bald cypress and tupelo gum trees in Thematic Mapper imagery, Photogrammetric Engineering & Remote Sensing 63, 717–725.

    Google Scholar 

  • Huh, O. K., Ali, A., and Quadir, D. A.: 1985a, Mapping of green leaf biomass over Bangladesh with NOAA satellite AVHRR data, Manuscript Report prepared for UN Flood and Agriculture Organization, Coastal Studies Institute, Louisiana State University., Baton Rouge, LA.

    Google Scholar 

  • Huh, O. K., Ali, A., and Quadir, D. A.: 1985b, Observations on the surface waters of the Bay of Bengal with NOAA satellite AVHRR data, Manuscript Report prepared for UN Flood and Agriculture Organization, Coastal Studies Institute, Louisiana State University, Baton Rouge, LA.

    Google Scholar 

  • Huh, O. K., Ali, A., and Quadir, D. A.: 1985c, Use of NOAA satellite AVHRR data to monitor river flood hydrology in Bangladesh, Manuscript Report prepared for UN Flood and Agriculture Organization, Coastal Studies Institute, Louisiana State University, Baton Rouge, LA.

    Google Scholar 

  • Hunter, G. J. and Goodchild, M. F: 1995, Dealing with error in spatial databases-a simple casestudy, Photogrammetric Engineering & Remote Sensing 61(5), 529–537.

    Google Scholar 

  • Imhoff, M. L., Vermillion, C., Story, M. H., Choudhury, A. M., Gafoor, A., and Polcyn, P.: 1987, Monsoon flood boundary delineation and damage assessment using space borne imaging radar and Landsat data, Photogrammetric Engineering and Remote Sensing 53(4), 405–413.

    Google Scholar 

  • Islam, M. M. and Sadu, K.: 2000a, Development of flood hazard maps of Bangladesh using NOAAAVHRR images with GIS, Hydrological Science Journal 45(3), 337–355.

    Google Scholar 

  • Islam, M. M., and Sadu, K.: 2000b, Flood hazard assessment in Bangladesh using NOAA-AVHRR data with geographical information system, Hydrological Processes 14(3), 605–620.

    Google Scholar 

  • Islam, M. M. and Sadu, K.: 2000c, Satellite remote sensing data analysis for flood damaged zoning with GIS for flood management, Journal of Hydraulic Engineering 44, 301–306.

    Google Scholar 

  • Islam, M. M. and Sadu, K.: 2001, Flood damage and modelling using satellite remote sensing data with GIS: Case study of Bangladesh; In: Jerry Ritchie et al. (eds), Remote Sensing and Hydrology 2000, IAHS Publication, Oxford, pp. 455–458.

    Google Scholar 

  • Islam, M. M. and Sadu, K.: 2002, Development of priority map remote sensing data for flood counter measures by geographical information system, Journal of Hydrological Engineering 7(5), 346–355.

    Google Scholar 

  • Jensen, J. R., Rutchey, K., Koch, M., and S. Narumalani: 1995, Inland Wetland Change Detection in the Everglades Water Conservation Area 2A Using A Time Series of Normalized Remotely Sensed Data, Photogrammetric Engineering & Remote Sensing 61(2), 199–209.

    Google Scholar 

  • Jin, Y. Q.: 1999, A flooding index and its regional threshold values for monitoring in china from SSM/I data, International Journal of Remote Sensing 20(5), 1025–1030.

    Google Scholar 

  • Jones, K. H.: 1998, A comparison of algorithms used to compute hill slope as a property of the DEM, Comput. Geosci. 24(4), 315–323.

    Google Scholar 

  • Kundus, P., Karszenbaum, H., Pultz, T., Paramuchi, G., and Bava, J.: 2001, Influence of flood conditions and vegetation status on the radar back scatter of wetland ecosystem, Canadian Journal of Remote Sensing 27(6), 651–662.

    Google Scholar 

  • Lee, J., Snyder, P. K., and Fisher, P. F.: 1992, Modeling the effect of data errors on feature extraction from digital elevation models, Photogrammetric Engineering & Remote Sensing 58(10), 1461–1467.

    Google Scholar 

  • Liu, R. and Liu, N.: 2002, Flood area and damage estimation in Zhejiang, China, Journal of Environmental Management 66, 1–8.

    Google Scholar 

  • Liu, Z. L., Huang, F., Li, L.Y., and Wan, E. P.: 1999, Dynamic monitoring and damage evaluation of flood in northwest Jilin with remote sensing, In: Proc. 20th Asian Conference of Remote Sensing, Hong Kong, 22-25 November.

  • Long, N. T. and Trong, B. D.: 2001, Flood monitoring of Mekong River Delta, Vietnam using ERS SAR Data, In: Proc. 22nd Asian Conference of Remote Sensing, Singapore, 5-9 November.

  • Lowry, R. T., Langham, E. J., and Murdy, N.: 1981, A preliminary analysis of SAR mapping of Manitoba flood, May 1979, In: Proc. Satellite Hydrology, Fifth Anniversary. William T. Pecora Memorial Symposium on Remote Sensing 1979, AmericanWater Resource Association Technical Publication No. TPS81-1, pp. 316–323.

  • Lyon, J. D., Yuan, G., Lunetta, R. S., and Elvidge, C. D.: 1998, A change detection experiment using vegetation indices, Photogrammetric Engineering and Remote Sensing, 64, 143–150.

    Google Scholar 

  • McGinnis, D. F. and Rango, A.: 1975, Earth Resource Satellite System for flood monitoring, Geophys. Res. Lett. 2(4), 132–135.

    Google Scholar 

  • Melack, J. M., Hess, L. L., and Sippel, S.: 1994, Remote sensing of lakes and floodplains in the Amazon Basin, Remote Sensing Review 10, 127–142.

    Google Scholar 

  • Michener, W. K. and Houhoulis, P. F.: 1997, Detection of vegetation changes associated with extensive flooding in a forested ecosystem, Photogrammetric Engineering & Remote Sensing 63(12), 1363–1374.

    Google Scholar 

  • Miller, L. D., Yang, Y., Matthews, M., and Irons, R. T.: 1983, Correlations of rice yields to radiometric estimates of canopy biomass as a junction of growth stage, In: Proc. 4th Asian Conference of Remote Sensing, 10-15 November, Colombo, Srilanka, A.6.1–A 6.21.

  • Moore, I. D., Grayson, R. B., and Ladson, A. R.: 1991, Digital terrain modelling: A review of hydrological, geomorphological, and biological applications, Hydrological Processes 5, 3–30.

    Google Scholar 

  • Morrison, R. B. and Cooley, M. E.: 1973, Assessment of flood damage in Arizona by means of ERTS-1 imagery, In: Proc. Symposium on Significant Result Obtained from the Earth Resource Satellite 1, Vol. 1, New Carrollton, Maryland, pp. 755–760.

    Google Scholar 

  • Morrison, R. B. and White, P. G.: 1976, Monitoring flood inundation, USGS Professional Papers No. 929, ERTS-1, A New Window on Our Planet, pp. 196–208.

  • Nico, G., Pappalepore, M., Pasquariello, G., Refice, A., and Samarelli, S.: 2000, Comparison of SAR amplitude vs. coherence flood detection methods-a GIS application, International Journal of Remote Sensing 21(8), 1619–1631.

    Google Scholar 

  • Oberstadler, R., Honsch, H., and Huth, D.: 1997, Assessment of the mapping capabilities of ERS-1 SAR data for flood mapping: A case study of Germany, Hydrological Processes 10(10), 1415–1425.

    Google Scholar 

  • Okamoto, K. and Fukuhara,M.: 1996, Estimation of paddy field area using the area ratio of categories in each pixel of Landsat TM, International Journal of Remote Sensing 17, 1735–1749.

    Google Scholar 

  • Okamoto, K., Yamakawa, S., and Kawashima, H.: 1998, Estimation of flood damage of North Korea in 1995, International Journal of Remote Sensing 19(2), 365–371.

    Google Scholar 

  • Patel, N. K., Singh, T. P., Sahai, B., and Patel, M.: 1985, Spectral response of rice crops and its relation to yield and yield attributes, International Journal of Remote Sensing 6, 657–664.

    Google Scholar 

  • Pope, K. O., Rejmankova, E., Paris, J.F. et al.: 1997,Detecting seasonal flooding cycles in marshes of the Yucatan Peninsula with SIR-C polarimetric radar imagery, Remote Sensing of Environment 59(2), 157–166.

    Google Scholar 

  • Profeiti, G. and MacIntosh, H.: 1997, Flood management through Landsat TM and ERS SAR data: a case study, Hydrological Processes 11(10), 1397–1408.

    Google Scholar 

  • Quan,W., Watanabe, M., Hayashi, S., and Murakami, S.: 2003, Using NOAA AVHRR data to assess flood damage in China, Environmental Monotoring and Assessment 82, 119–148.

    Google Scholar 

  • Rango, A. and Anderson, A. T.: 1974, Flood hazard studies in the Mississippi River Basin using remote sensing, Water Resource Bulletin 10(5), 1060–1081.

    Google Scholar 

  • Rango, A. and Solomonson, V. V.: 1974, Regional flood mapping from space, Water Resource Research 10(3),473–484.

    Google Scholar 

  • Rango, A. and Solomonson, V. V.: 1977, The utility of short wavelength (<1 mm) remote sensing techniques for the monitoring and assessment of hydrological parameters, In: Proc. 11th Int. Symp. on Remote Sensing of Environ., Ann Arbor, MI, 25-29 April 1977, pp. 55–64.

  • Rashid, H. and Pramanik, M. A. H.: 1993, Areal extent of the 1988 flood in Bangladesh: How much did the satellite imagery show? Natural Hazards 8, 189–200.

    Google Scholar 

  • Reed, S., Johnson, D., and Sweeney, T.: 2002, Application of national geographic information system data base to support two-year flood and the threshold run-off estimate, Journal of Hydrological Engineering 7(3), 209–219.

    Google Scholar 

  • Rejesk, D.: 1993, GIS and risk: A three cultural problem, In: M. F. Goodchild, B. O. Parks, and L. T. Steyaerts (eds), Environmental Modeling With GIS, Oxford University Press, New York, pp. 49–267.

    Google Scholar 

  • Rocha, J. S., Marques, Z., Ramos, I., and Ameida, R.: 1994, Simulation of risk flood areas on GIS, In: Tsakiris, G. and Santos, M. A. (eds), Advances in Water Resource Technology and Management, Balkema, Rotterdam, pp. 375–383.

    Google Scholar 

  • Rosenqvist, A., Shimada, M., Chapman, B., Freeman, A., Grande, G. De, and Saatchi, S.: 2000, The global rainforest mapping-a review, International journal of Remote Sensing 21(6 & 7), 1375–1387.

    Google Scholar 

  • Rosenqvist, A., Forsberg, B. R., Pimentel, T., Rauste, Y. A., and Riche, J. E.: 2002, The use of space borne radar data to model inundation patterns and trace gas emission in the central Amazon flood plain, International Journal of Remote Sensing 23(7), 1303–1328.

    Google Scholar 

  • Ruangsiri, P., Sripumin, R., Polongam, S., Kanjanasuntorn, P., and Wongparn, S.: 1984, State of flooding in the Mun-Chi River Basin area, N. E. Thailand by digital Landsat data analysis, Report: Remote Sensing Division, National Resource Council of Thailand, Bangkok, Thailand.

    Google Scholar 

  • Sado, K., and Islam, M. M.: 1997, Satellite remote sensing data analysis for flooded area and weather study: Case study of Dhaka city, Bangladesh, Journal of Hydraulic Engineering 41, 945–950.

    Google Scholar 

  • Saikh, M., Green, D., and Cross, H.: 2001, A remote sensing approach to determine environmental flows for wet lands of the Lower Darling River, New South Wales, Australia, International Journal of Remote Sensing 22(9), 1737–1751.

    Google Scholar 

  • Sharma, P.: 1999, Flood risk mapping of Dikrong subbasin of Assam, Proc. Map Asia 1999.Source: http://www.gisdevelopment.net/proceedings/mapindia/1999/index.htm

  • Shibayama, M. and Akiyama, T.: 1989, Seasonal visible, near-infrared and multi infrared spectra of rice canopies in relation to LAI and above-ground dry phytomass, Remote Sensing of the Environment 27, 119–127.

    Google Scholar 

  • Singh, A.: 1989, Digital change detection techniques using remotely-sensed data, International Journal of Remote Sensing 10, 989–1003.

    Google Scholar 

  • Smith, L. C.: 1997, Satellite remote sensing of river inundation area, stage and discharge: A review, Hydrological Processes 11, 1427–1439.

    Google Scholar 

  • Smith, C. and Price, J.: 2002, A new generation of flood management, Arc User 5(4), 20–22.

    Google Scholar 

  • Tappen, G. D., Tyler, D., Wehde, M., and Moor, D.: 1992, Monitoring rangeland dynamics in Senegal with AVHRR data, Geocarto International 1,87–98.

    Google Scholar 

  • Tholey, N., Clandillon, S., and De Fraipont, P.: 1997, The contribution of space borne SAR and optical data in monitoring flood events; examples in Northern and Southern France, Hydrological Processes 11(10), 1427–1439.

    Google Scholar 

  • Toutin, T.: 2002, DEMfrom stereo Landsat 7 ETM+ data over high relief areas, International Journal of Remote Sensing 23(10), 2133–2139.

    Google Scholar 

  • Townsend, P. A. and Walsh, S. J.: 1998, Modelling flood plain inundation using integrated GIS with radar and optical remote sensing, Geomorphology 21(98), 295–312.

    Google Scholar 

  • Wadge, G., Wislocki, A. P., Pearson, J., and Whittow, J. B.: 1993, Mapping natural hazards with spatial modeling System, In: P. M. Mather (eds), Geographic Information Handling Research and Applications, John Wiley and Sons Inc., New York.

    Google Scholar 

  • Wang, W., Hess, L. L., Filoso, S., and Melack, T. M.: 1995, Understanding the radar back scattering from flooded and non-flooded Amazonian Forests: result from canopy back scatter modelling, Remote Sensing of Environment 54(3), 324–332.

    Google Scholar 

  • Wang, Y., Colby, J. D., and Mulcahy, K. A.: 2002, An efficient method for mapping flood extent in a coastal flood plain using Landsat TM and DEM data, International Journal of Remote Sensing 23(18), 3681–3696.

    Google Scholar 

  • Wiesnet, D. R., McGinnis, D. F., and Pritchard, J. A.: 1994, Mapping of the 1973 Mississippi River floods by the NOAA-2 satellite, Water Resource Bulletin 10(5), 1040–1049.

    Google Scholar 

  • Wolock, D. M.: 1995, Effects of subbasin size on topographic characteristics and simulated flow paths in sleepers river watershed, Vermont, Water Resour. Res. 31(8), 1989–1997.

    Google Scholar 

  • Yamagata, Y. and Akiyama, T.: 1988, Flood damage analysis using multi temporal Landsat TM data, International Journal of Remote Sensing 9(3), 503–514.

    Google Scholar 

  • Yang, C., Zhou, C., and Wan, Q.: 1999, Deciding the flood extent with Radarsat SAR data and Image Fusion, In: Proc. 20th Asian Conference of Remote Sensing, Hong Kong, 22-25 November.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joy Sanyal.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sanyal, J., Lu, X.X. Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review. Natural Hazards 33, 283–301 (2004). https://doi.org/10.1023/B:NHAZ.0000037035.65105.95

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:NHAZ.0000037035.65105.95

Navigation