The use of satellite remote sensing for flood risk management
Presentata da: Francesca Franci
Coordinatore Dottorato
Prof. Alberto Lamberti
Relatore
Prof. Gabriele Bitelli
Alma Mater Studiorum – Università di Bologna
DOTTORATO DI RICERCA IN
Ingegneria Civile, Ambientale e dei Materiali
Ciclo XXVII
Esame finale anno 2015
Abstract
Over the last decades the impact of natural disasters to the global environment is becoming more and more severe. The number of disasters has dramatically increased, as well as the cost to the global economy and the number of people affected. Among the natural disaster, flood catastrophes are considered to be the most costly, devastating, broad extent and frequent, because of the tremendous fatalities, injuries, property damage, economic and social disruption they cause to the humankind. In the last thirty years, the World has suffered from severe flooding and the huge impact of floods has caused hundreds of thousands of deaths, destruction of infrastructures, disruption of economic activity and the loss of property for worth billions of dollars.
In this context, satellite remote sensing, along with Geographic Information Systems (GIS), has become a key tool in flood risk management analysis.
Remote sensing for supporting various aspects of flood risk management was investigated in the present thesis. In particular, the research focused on the use of satellite images for flood mapping and monitoring, damage assessment and risk assessment. The contribution of satellite remote sensing for the delineation of flood prone zones, the identification of damaged areas and the development of hazard maps was explored referring to selected cases of study.
KEYWORDS: Satellite remote sensing Flood risk management Geographic Information System Change detection analysis Object-based classification
CONCLUSIONS
The use of remote sensing for supporting various aspects of flood risk management was investigated in the present thesis. The research focused on the contribution of satellite images for three main applications: flood mapping and monitoring, flood damage assessment and flood risk assessment. Different geospatial approaches were developed regarding each phase examined.
In order to evaluate the potential of satellite remote sensing concerning flood prone areas mapping and monitoring, a Landsat time series, comprising five free cloud-cover satellite images, was collected and processed for Dhaka district territory (Bangladesh).
The image processing was performed by means of supervised classification technique, to generate multitemporal land-use/cover maps, and change detection procedure to compare them. The map of routinely flooded areas due to the heavy monsoon rains, which typically occur from May to October, was generated. Moreover, it was possible to map and quantify the recession of the water. From the comparison of three multitemporal maps (covering thirteen-year period) the impact of the urban growth and land use/cover changes on the water drainage system was analysed. Despite the lack of ground reference data, the validation procedure performed collecting ground truth points by photointerpretation, confirmed the effectiveness of Landsat images for land use/cover mapping. Moreover, they were found to be a relevant source for supporting flood detection and the monitoring of flood prone areas. The proposed methodology may be applied in other region affected by similar risk and characterized by marked seasonality, if a cloud-free multispectral time series is available.
The contribution of satellite remote sensing for the damage assessment purpose was investigated for the analysis of extreme floods occurred in Bangladesh in 2004. In this case, the research was performed by processing a Landsat image and an ASTER image in order to provide the pre-event and post-event setting of water bodies respectively. Using overlay operations in GIS environment, the flooded areas were identified and thereafter associated with the administrative divisions and land use data of Bangladesh. The results demonstrated that satellite images, acquired before and after flooding occurrence, could allow to delineate inundated area which can be used along with other geospatial data, to support damage assessment and vulnerability analyses, which are essential for developing protective actions and mitigation plans against the flood risk.
Finally, the research focused on the use of remote sensing data for producing flood hazard maps. In this case, the study was conducted on a portion of Yialias river basin (Cyprus), often affected by flash flood. A Multi-Criteria Analysis (MCA), assisted by GIS, was performed to produce the hazard zoning map of the study area. Five flood-causing factors depending on the available data were considered: slope, distance to main channels, drainage texture land use and geology. The Analytic Hierarchy Process (AHP) technique was used for deriving the weight of each criterion in the computation of the Flood Hazard Index (FHI); then, FHI values were associated to seven hazard categories to generate easily-readable flood hazard map. Except for the geological map, the factors layers were obtained by processing a GeoEye-1 image and the Digital Elevation Model (DEM). In particular, the GeoEye- 1 was classified using an object-based technique to extract land use/cover data, while geoprocessing tools in GIS environment were used to obtain the other factors from the DEM. This case study demonstrated the effectiveness and the benefit of using remote sensing data to provide valuable information concerning the hazard assessment when several data are not available. Furthermore, the MCA/AHP approach was found to be a fast and cost effective way to use remote sensing techniques, coupled with GIS, for constructing flood hazard map. It offers a flexible, step-by-step and transparent way for analysing and understanding spatial phenomena.
Natural flood disaster is common and cannot be stop. The research results highlighted the high potential of remote sensing techniques in providing valuable and objective data for flood risk management activities, relating to the identification of inundated areas, the monitoring of flood prone territory and the damage assessment after an event.
REFERENCES :
[1] Münchener Rückversicherungs-Gesellschaft (Munich Re), “NatCatSERVICE Loss events worldwide 1980 – 2013,” München, Germany, 2014.
[2] Münchener Rückversicherungs-Gesellschaft (Munich Re), “NATHAN World Map of Natural Hazards,” München, Germany, 2011.
[3] C. Van Westen, “Remote sensing for natural disaster management,” Int. Arch. Photogramm. Remote Sens., vol. XXXIII, pp. 1609–1617, 2000.
[4] D. M. Tralli, R. G. Blom, V. Zlotnicki, A. Donnellan, and D. L. Evans, “Satellite remote sensing of earthquake, volcano, flood, landslide and coastal inundation hazards,” ISPRS J. Photogramm. Remote Sens., vol. 59, no. 4, pp. 185–198, Jun. 2005.
[5] J. Sanyal and X. X. Lu, “Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review,” Nat. Hazards, vol. 33, no. 2, pp. 283–301, Oct. 2004.
[6] United Nations Department of Economic and Social Affairs (UN/DESA) Population Division, World Urbanization Prospects: The 2014 Revision, Highlights. New York: United Nations, 2014.
[7] M. Garschagen, P. Mucke, A. Schauber, T. Seibert, T. Welle, J. Birkmann, J. Rhyner, S. Kohler, T. Loster, D. Reinhard, and I. Matuschke, WorldRiskReport 2014. Bündnis Entwicklung Hilft (Alliance Development Works) and United Nations University – Institute for Environment and Human Security (UNU-EHS), 2014.
[8] J. Yoshitani, N. Takemoto, and T. Merabtene, “Factor Analysis of Water-related Disasters in Bangladesh,” 2007.
[9] C. Price, A. Mugnai, K. Lagouvardos, and V. Kotroni, “High-impact floods and flash floods in Mediterranean countries: the FLASH preliminary database,” Adv. Geosci., vol. 23, pp. 1–9, 2010.
[10] B. Li and J. Liu, “Application of Remote Sensing Technique for Disaster Management,” in 2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006, pp. 283–286.
[11] United Nations Department of Economic and Social Affairs (UN/DESA) Population Division, “World Population Prospects: The 2012 Revision. Volume I : Comprehensive Tables,” New York, 2013.
[12] United Nations Inter-Agency Secretariat of the International Strategy for Disaster Reduction (UN/ISDR), Living with Risk: A global review of disaster reduction initiatives, vol. I. New York and Geneva: United Nations, 2004, pp. 16–30.
[13] A. Lavell, M. Oppenheimer, C. Diop, J. Hess, R. Lempert, J. Li, R. Muir-Wood, and S. Myeong, “Climate Change: New Dimensions in Disaster Risk, Exposure, Vulnerability, and Resilience,” in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, C. B. Field, V. Barros, T. F. Stocker, D. Qi, D. J. Dokken, K. L. Ebi, M. D. Mastrandrea, K. J. Mach, G.-K. Plattner, S. K. Allen, M. Tigno, and P. M. Midgley, Eds. Cambridge, UK, and New York, NY, USA: Cambridge University Press, 2012, pp. 25–64.
[14] C. J. Van Westen, “Remote sensing and GIS for natural hazards assessment and disaster risk management,” in Treatise on Geomorphology, vol. 3, J. Shroder and M. P. Bishop, Eds. Elsevier, 2013, pp. 259–298.
[15] J. C. Villagrán de León, Vulnerability. A Conceptual and Methodological Review, vol. 4. Paffenholz, Bornheim, Germany, 2006.
[16] D. Crichton, “UK and Global Insurance Responses to Flood Hazard,” in Non-structural measures for water management problems, 2002, no. 56, pp. 239–251.
[17] M. Dilley, R. S. Chen, U. Deichmann, A. L. Lerner-Lam, M. Arnold, J. Agwe, P. Buys, O. Kjekstad, B. Lyon, and Y. Gregory, Natural Disaster Hotspots. A Global Risk Analysis. Washington, D.C. U.S.A., 2005.
[18] T. J. Cova, “GIS in emergency management,” in Geographical Information Systems: Principles, Techniques, Applications, and Management, P. A. Longley, M. F. Goodchild, D. J. Maguire, and D. V. Rhind, Eds. New York: John Wiley & Sons, 1999, pp. 845–858.
[19] D. E. Alexander, Confronting Catastrophe: New perspectives on natural disasters. Oxford New York: Oxford University Press, 2000.
[20] H. Taubenböck, J. Post, A. Roth, K. Zosseder, G. Strunz, and S. Dech, “A conceptual vulnerability and risk framework as outline to identify capabilities of remote sensing,” Nat. Hazards Earth Syst. Sci., vol. 8, no. 3, pp. 409–420, May 2008.
[21] O. M. Bello and Y. A. Aina, “Satellite remote sensing as a tool in disaster management and sustainable development: towards a synergistic approach,” Procedia - Soc. Behav. Sci., vol. 120, pp. 365–373, Mar. 2014.
[22] P. Boccardo, “New perspectives in emergency mapping,” Eur. J. Remote Sens., vol. 46, pp. 571–582, Jul. 2013.
[23] K. E. Joyce, S. E. Belliss, S. V. Samsonov, S. J. McNeill, and P. J. Glassey, “A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters,” Prog. Phys. Geogr., vol. 33, no. 2, pp. 183–207, Jun. 2009.
[24] F. Dell’Acqua, C. Bignami, M. Chini, G. Lisini, D. A. Polli, and S. Stramondo, “Earthquake Damages Rapid Mapping by Satellite Remote Sensing Data: L’Aquila April 6th, 2009 Event,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 4, no. 4, pp. 935–943, Dec. 2011.
[25] R. Casciere, F. Franci, and G. Bitelli, “Use of Landsat imagery to detect land cover changes for monitoring soil sealing; case study: Bologna province (Italy),” in Proc. 2nd International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 2014, p. 92290V.
[26] H. Guo, Y. Chen, Q. Feng, Q. Lin, and F. Wang, “Assessment of damage to buildings and farms during the 2011 M 9.0 earthquake and tsunami in Japan from remote sensing data,” Chinese Sci. Bull., vol. 56, no. 20, pp. 2138–2144, Jul. 2011.
[27] B. A. Margono, S. Turubanova, I. Zhuravleva, P. Potapov, A. Tyukavina, A. Baccini, S. Goetz, and M. C. Hansen, “Mapping and monitoring deforestation and forest degradation in Sumatra (Indonesia) using Landsat time series data sets from 1990 to 2010,” Environ. Res. Lett., vol. 7, no. 3, Sep. 2012.
[28] P. Chen, S. C. Liew, and L. K. Kwoh, “Tsunami damage assessment using high resolution satellite imagery: a case study of Aceh, Indonesia,” in IEEE International Geoscience and Remote Sensing Symposium, 2005, 2005, vol. 2, pp. 1405–1408.
[29] D. Ehrlich, H. D. Guo, K. Molch, J. W. Ma, and M. Pesaresi, “Identifying damage caused by the 2008 Wenchuan earthquake from VHR remote sensing data,” Int. J. Digit. Earth, vol. 2, no. 4, pp. 309–326, Dec. 2009.
[30] A. M. F. Lagmay and Project NOAH Storm Surge Component Team, “Devastating storm surges of Typhoon Haiyan,” Project NOAH Open-File Reports, vol. 3, no. 6. pp. 45–56, Mar- 2015.
[31] G. Bitelli, R. Camassi, L. Gusella, and A. Mognol, “IMAGE CHANGE DETECTION ON URBAN AREA : THE EARTHQUAKE CASE,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., vol. XXXV, no. Part B, pp. 692–697, 2004.
[32] K. E. Joyce, K. C. Wright, S. V. Samsonov, and V. G. Ambrosia, “Remote sensing and the disaster management cycle,” in Advances in Geoscience and Remote Sensing, G. Jedlovec, Ed. InTech, 2009, pp. 317–346.
[33] A. Stumpf and N. Kerle, “Object-oriented mapping of landslides using Random Forests,” Remote Sens. Environ., vol. 115, no. 10, pp. 2564–2577, Oct. 2011.
[34] S. Lewis, “Remote sensing for natural disasters: Facts and figures.” [Online]. Available: http://www.scidev.net/global/earth-science/feature/remote-sensing-for-natural-disastersfacts-and-figures.html?from=related articles.
[35] D. Pieri and M. Abrams, “ASTER watches the world’s volcanoes: a new paradigm for volcanological observations from orbit,” J. Volcanol. Geotherm. Res., vol. 135, no. 1–2, pp. 13–28, Jul. 2004.
[36] G. P. Petropoulos, W. Knorr, M. Scholze, L. Boschetti, and G. Karantounias, “Combining ASTER multispectral imagery analysis and support vector machines for rapid and costeffective post-fire assessment: a case study from the Greek wildland fires of 2007,” Nat. Hazards Earth Syst. Sci., vol. 10, no. 2, pp. 305–317, Feb. 2010.
[37] Natural Resources Canada, “Thermal Imaging,” 2014. [Online]. Available: http://www.nrcan.gc.ca/earth-sciences/geomatics/satellite-imagery-air-photos/satelliteimagery-products/educational-resources/9319.
[38] T. Strozzi, U. Wegmiiller, L. Tosl, G. Bitelli, and V. Spreckels, “Land Subsidence Monitoring with Differential SAR Interferometry,” Photogramm. Eng. Remote Sens., vol. 67, no. 11, pp. 1261–1270, 2001.
[39] G. Bitelli, F. Bonsignore, S. Del Conte, F. Novali, I. Pellegrino, and L. Vittuari, “Integrated Use of Advanced InSAR and GPS Data for Subsidence Monitoring,” in Engineering Geology for Society and Territory - Volume 5, G. Lollino, A. Manconi, F. Guzzetti, M. Culshaw, P. Bobrowsky, and F. Luino, Eds. Springer International Publishing, 2015, pp. 147–150.
[40] M. C. Spreafico, F. Franci, G. Bitelli, A. L. Valentina Alena Girelli, C. C. Lucente, E. Mandanici, M. A. Tini, and L. Borgatti, “Remote Sensing Techniques in a Multidisciplinary Approach for the Preservation of Cultural Heritage Sites from Natural Hazard: The Case of Valmarecchia Rock Slabs (RN, Italy),” in Engineering Geology for Society and Territory - Volume 8, G. Lollino, D. Giordan, C. Marunteanu, B. Christaras, I. Yoshinori, and C. Margottini, Eds. Springer International Publishing, 2015, pp. 317–321.
[41] C. Bignami, P. Burrato, V. Cannelli, M. Chini, E. Falcucci, A. Ferretti, S. Gori, C. Kyriakopoulos, D. Melini, M. Moro, F. Novali, M. Saroli, S. Stramondo, G. Valensise, and P. Vannoli, “2012 EMILIA EARTHQUAKES Coseismic deformation pattern of the Emilia 2012 seismic sequence imaged by Radarsat-1 interferometry,” Ann. Geophys., vol. 55, no. 4, pp. 789–795, 2012.
[42] S. Dellepiane, E. Angiati, and G. Vernazza, “Processing and segmentation of COSMO-SkyMed images for flood monitoring,” in 2010 IEEE International Geoscience and Remote Sensing Symposium, 2010, no. I, pp. 4807–4810.
[43] S. B. Serpico, S. Dellepiane, G. Boni, G. Moser, E. Angiati, and R. Rudari, “Information Extraction From Remote Sensing Images for Flood Monitoring and Damage Evaluation,” Proc. IEEE, vol. 100, no. 10, pp. 2946–2970, Oct. 2012.
[44] “The International Charter.” [Online]. Available: www.disasterscharter.org. [45] “UNITAR’s Operational Satellite Applications Programme - UNOSAT.” [Online]. Available: www.unitar.org/unosat. [46] “UN-SPIDER.” [Online]. Available: www.un-spider.org.
[47] “Copernicus - The European Earth Observation Programme.” [Online]. Available: www.copernicus.eu.
[48] “JAXA - Japan Aerospace Exploration Agency.” [Online]. Available: http://global.jaxa.jp/article/special/sentinel_asia/index_e.html.
[49] “ITHACA - Information Technology for Humanitarian Assistance, Cooperation and Action.” [Online]. Available: http://www.ithaca.polito.it/.
[50] “Center for Satellite Based Crisis Information.” [Online]. Available: www.zki.dlr.de.
[51] “SERTIT.” [Online]. Available: sertit.u-strasbg.fr.
[52] “Global Disaster Alert and Coordination System.” [Online]. Available: www.gdacs.org.
[53] “Dartmouth Flood Observatory.” [Online]. Available: floodobservatory.colorado.edu.
[54] O. Altan, R. Backhaus, P. Boccardo, F. G. Tonolo, J. Trinder, N. van Manen, S. Zlatanova, and Book, Eds., The Value of Geoinformation for Disaster and Risk Management (VALID) Benefit Analysis and Stakeholder Assessment. Copenhagen, Denmark: Joint Board of Geospatial Information Societies, 2013.
[55] J. Sanyal and X. X. Lu, “Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review,” Nat. Hazards, vol. 33, no. 2, pp. 283–301, Oct. 2004.
[56] H. Taubenböck, M. Wurm, M. Netzband, H. Zwenzner, a. Roth, a. Rahman, and S. Dech, “Flood risks in urbanized areas – multi-sensoral approaches using remotely sensed data for risk assessment,” Nat. Hazards Earth Syst. Sci., vol. 11, no. 2, pp. 431–444, Feb. 2011.
[57] S. K. Jain, A. K. Saraf, A. Goswami, and T. Ahmad, “Flood inundation mapping using NOAA AVHRR data,” Water Resour. Manag., vol. 20, no. 6, pp. 949–959, Sep. 2006.
[58] A. Dewan, “Hazards, Risk, and Vulnerability,” in Floods in a Megacity: Geospatial Techniques in Assessing Hazards, Risk and Vulnerability, Dordrecht: Springer Netherlands, 2013, pp. 35– 74.
[59] B. Büchele, H. Kreibich, a. Kron, a. Thieken, J. Ihringer, P. Oberle, B. Merz, and F. Nestmann, “Flood-risk mapping: contributions towards an enhanced assessment of extreme events and associated risks,” Nat. Hazards Earth Syst. Sci., vol. 6, no. 4, pp. 485–503, Jun. 2006.
[60] V. Bhanumurthy, P. Manjusree, and G. Srinivasa Rao, “Flood Disaster Management,” in Remote Sensing Applications, P. S. Roy, R. S. Dwivedi, and D.Vijayan, Eds. Hyderabad, India: National Remote Sensing Center, 2010, pp. 283–296.
[61] “Landsat mission.” [Online]. Available: http://landsat.usgs.gov/index.php.
[62] L. Smith, “Satellite remote sensing of river inundation area, stage, and discharge: A review,” Hydrol. Process., vol. 11, pp. 1427–1439, 1997.
[63] P. S. Frazier and K. J. Page, “Water Body Detection and Delineation with Landsat TM Data,” Photogramm. Eng. Remote Sens., vol. 66, no. 12, pp. 1461–1467, 2000.
[64] Y. Wang, J. D. Colby, and K. A. Mulcahy, “An efficient method for mapping flood extent in a coastal floodplain using Landsat TM and DEM data,” Int. J. Remote Sens., vol. 23, no. 18, pp. 3681–3696, 2002.
[65] S. N. Goward, J. G. Masek, D. L. Williams, J. R. Irons, and R. J. Thompson, “The Landsat 7 mission. Terrestrial research and applications for the 21st century,” Remote Sens. Environ., vol. 78, no. 1–2, pp. 3–12, Oct. 2001.
[66] M. Gianinetto, P. Villa, and G. Lechi, “Postflood damage evaluation using Landsat TM and ETM+ data integrated with DEM,” IEEE Trans. Geosci. Remote Sens., vol. 44, no. 1, pp. 236– 243, Jan. 2006.
[67] Y. Wang, “Using Landsat 7 TM data acquired days after a flood event to delineate the maximum flood extent on a coastal floodplain,” Int. J. Remote Sens., vol. 25, no. 5, pp. 959– 974, Mar. 2004.
[68] R. F. Thomas, R. T. Kingsford, Y. Lu, and S. J. Hunter, “Landsat mapping of annual inundation (1979–2006) of the Macquarie Marshes in semi-arid Australia,” Int. J. Remote Sens., vol. 32, no. 16, pp. 4545–4569, Aug. 2011.
[69] G. Mallinis, I. Z. Gitas, V. Giannakopoulos, F. Maris, and M. Tsakiri-Strati, “An object-based approach for flood area delineation in a transboundary area using ENVISAT ASAR and LANDSAT TM data,” Int. J. Digit. Earth, vol. 6, no. 2, pp. 1–13, Dec. 2011.
[70] S. K. Jain, R. D. Singh, M. K. Jain, and a. K. Lohani, “Delineation of Flood-Prone Areas Using Remote Sensing Techniques,” Water Resour. Manag., vol. 19, no. 4, pp. 333–347, Aug. 2005.
[71] H. A. Ganaie, H. Hashia, and D. Kalota, “Delineation of Flood Prone Area using Normalized Difference Water Index (NDWI) and Transect Method : A Case Study of Kashmir Valley,” Int. J. Remote Sens. Appl., vol. 3, no. 2, pp. 53–58, 2013.
[72] L. T. K. Ho, M. Umitsu, and Y. Yamaguchi, “Flood hazard mapping by satellite images and SRTM DEM in the Vu Gia–Thu Bon alluvial plain, Central Vietnam,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., vol. XXXVIII, no. Part 8, pp. 275–280, 2010.
[73] J. A. M. De Brouder, “Flood study in the Meghna-Dhonagoda polder, Bangladesh,” in 15th Asian conference on remote sensing, 1994, pp. 1–9.
[74] W. K. Michener and P. F. Houhoulis, “Detection of Vegetation Changes Associated with Extensive Flooding in a Forested Ecosystem,” Photogramm. Eng. Remote Sens., vol. 63, no. 12, pp. 1363–1374, 1997.
[75] A. Dia, J. L. Kouame, J.-P. Rudant, and S. Wade, “Use of Satellite Images to map Flood Extension around the city of Saint Louis in the Senegal River Estuary,” Jàmbá J. Disaster Risk Stud., vol. 1, no. 1, pp. 24–33, Apr. 2006.
[76] P. Worsley and J. Bowler, “Assessing flood damage using SPOT and NOAA AVHRR data,” in Geospatial Information in Agriculture 2001, 2001, pp. 2–7.
[77] C. J. Ticehurst, Y. Chen, F. Karim, D. Dutta, and B. Gouweleeuw, “Using MODIS for mapping flood events for use in hydrological and hydrodynamic models : Experiences so far,” in 20th International Congress on Modelling and Simulation, 2013, pp. 1–9.
[78] X. Zhan, R. A. Sohlberg, J. R. G. Townshend, C. DiMiceli, M. L. Carroll, J. C. Eastman, M. C. Hansen, and R. S. DeFries, “Detection of land cover changes using MODIS 250 m data,” Remote Sens. Environ., vol. 83, pp. 336–350, Nov. 2002.
[79] R. Brakenridge and E. Anderson, “MODIS-BASED FLOOD DETECTION, MAPPING AND MEASUREMENT: THE POTENTIAL FOR OPERATIONAL HYDROLOGICAL APPLICATIONS,” in Transboundary Floods: Reducing Risks Through Flood Management, J. Marsalek, G. Stancalie, and G. Balint, Eds. Dordrecht: Kluwer Academic Publishers, 2006, pp. 1–12.
[80] T. Sakamoto, N. Van Nguyen, A. Kotera, H. Ohno, N. Ishitsuka, and M. Yokozawa, “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., vol. 109, no. 3, pp. 295–313, Aug. 2007.
[81] C. Ticehurst, J. Guerschman, and C. Yun, “The Strengths and Limitations in Using the Daily MODIS Open Water Likelihood Algorithm for Identifying Flood Events,” Remote Sens., vol. 6, no. 12, pp. 11791–11809, Nov. 2014.
[82] J. Shimakage and F. Yamazaki, “Detection of flooded areas following the 2011 Thailand floods using ASTER images,” in Proc. 33rd Asian Conference on Remote Sensing, 2012, pp. 2462– 2479.
[83] K. Kouchi and F. Yamazaki, “Characteristics of Tsunami-Affected Areas in ModerateResolution Satellite Images,” IEEE Trans. Geosci. Remote Sens., vol. 45, no. 6, pp. 1650–1657, Jun. 2007.
[84] D. Hanada and F. Yamazaki, “DETECTION OF FLOODED AREAS BY THE TOHOKU EARTHQUAKE/TSUNAMI USING ASTER THERMAL INFRARED IMAGES,” in 9th International Conference on Urban Earthquake Engineering/ 4th Asia Conference on Earthquake Engineering, 2012, pp. 235–239.
[85] C. Domenikiotis, A. Loukas, N. R. Dalezios, N. R. D. The, and N. Avhrr, “The use of NOAA/AVHRR satellite data for monitoring and assessment of forest fires and floods,” Nat. Hazards Earth Syst. Sci., vol. 3, pp. 115–128, 2003.
[86] “NOAA SATELLITE INFORMATION SYSTEM.” [Online]. Available: http://noaasis.noaa.gov/NOAASIS/ml/avhrr.html.
[87] D. R. Wiesnet, D. F. McGinnis, and J. A. Pritchard, “MAPPING OF THE 1973 MISSISSIPPI RIVER FLOODS BY THE NOAA-2 SATELLITE,” J. Am. Water Resour. Assoc., vol. 10, no. 5, pp. 1040– 1049, Oct. 1974.
[88] R. Bryant and M. Rainey, “Investigation of flood inundation on playas within the Zone of Chotts, using a time-series of AVHRR,” Remote Sens. Environ., vol. 82, pp. 360–375, 2002.
[89] G. Mahé and D. Orange, “Estimation of the flooded area of the Inner Delta of the River Niger in Mali by hydrological balance and satellite data,” Hydro-climatology Var. Chang., no. July, pp. 138–143, 2011.
[90] Q. Wang, M. Watanabe, S. Hayashi, and S. Murakami, “Using NOAA AVHRR Data to Assess Flood Damage in China,” Environ. Monit. Assess., vol. 82, no. 2, pp. 119–148, 2003.
[91] C. J. van der Sande, S. M. de Jong, and A. P. J. de Roo, “A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment,” Int. J. Appl. Earth Obs. Geoinf., vol. 4, no. 3, pp. 217–229, Jun. 2003.
[92] A. Shaker, W. Y. Yan, and N. El-ashmawy, “Panchromatic Assessment Satellite Image Classification for Flood,” J. Appl. Res. Technol., vol. 10, pp. 902–911, 2012.
[93] D. McLaren, J. Doubleday, and S. Chien, “Using WorldView-2 imagery to track flooding in Thailand in a multi-asset sensorweb,” in Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 2012, vol. 8390, pp. 1–8.
[94] M. Pesaresi, A. Gerhardinger, and F. Haag, “Rapid damage assessment of built‐up structures using VHR satellite data in tsunami‐affected areas,” Int. J. Remote Sens., vol. 28, no. 13–14, pp. 3013–3036, Jul. 2007.
[95] N. Kussul, A. Shelestov, and S. Skakun, “Flood Monitoring from SAR Data,” in Use of Satellite and In-Situ Data to Improve Sustainability, F. Kogan, A. Powell, and O. Fedorov, Eds. Dordrecht: Springer Netherlands, 2011, pp. 19–29.
[96] “esa Earth Online.” [Online]. Available: https://earth.esa.int/web/guest/missions. [97] “RADARSAT Constellation.” [Online]. Available: http://www.asccsa.gc.ca/eng/satellites/radarsat/.
[98] “COSMO-SkyMed Sistema duale per l’osservazione della Terra.” [Online]. Available: http://www.asi.it/it/attivita/osservazione_terra/cosmoskymed.
[99] “About ALOS - PALSAR.” [Online]. Available: http://www.eorc.jaxa.jp/ALOS/en/about/palsar.htm.
[100] “TerraSAR-X Image Product Guide.” [Online]. Available: http://www.geoairbusds.com/en/903-technical-information.
[101] D. U. Lawal, A.-N. Matori, A. M. Hashim, I. A. Chandio, S. Sabri, A.-L. Balogun, and H. A. Abba, “Geographic Information System and Remote Sensing Applications in Flood Hazards Management: A Review,” Res. J. Appl. Sci. Eng. Technol., vol. 3, no. 9, pp. 933–947, 2011.
[102] T. Y. Gan, F. Zunic, C.-C. Kuo, and T. Strobl, “Flood mapping of Danube River at Romania using single and multi-date ERS2-SAR images,” Int. J. Appl. Earth Obs. Geoinf., vol. 18, pp. 69–81, Aug. 2012.
[103] P. A. Brivio, R. Colombo, M. Maggi, and R. Tomasoni, “Integration of remote sensing data and GIS for accurate mapping of flooded areas,” Int. J. Remote Sens., vol. 23, no. 3, pp. 429–441, Nov. 2002.
[104] K. Komwong and R. Simking, “ALOS PALSAR AND RADARSAT APPLICATIONS ON FLASH FLOOD DETECTION IN THE LOWER NORTH OF THAILAND,” in Asian Conference on Remote Sensing, 2006.
[105] S. Martinis, a. Twele, and S. Voigt, “Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data,” Nat. Hazards Earth Syst. Sci., vol. 9, no. 2, pp. 303–314, Mar. 2009.
[106] J. B. Henry, P. Chastanet, K. Fellah, and Y. L. Desnos, “ENVISAT multipolarised ASAR data for flood mapping,” in IEEE International Geoscience and Remote Sensing Symposium, 2003, vol. 2, pp. 1136–1138.
[107] S. Plank, “Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to Sentinel-1,” Remote Sens., vol. 6, no. 6, pp. 4870–4906, May 2014.
[108] L. Giustarini, R. Hostache, P. Matgen, G. J.-P. Schumann, P. D. Bates, and D. C. Mason, “A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X,” IEEE Trans. Geosci. Remote Sens., vol. 51, no. 4, pp. 2417–2430, Apr. 2013.
[109] G. Nico, M. Pappalepore, G. Pasquariello, A. Refice, and S. Samarelli, “Comparison of SAR amplitude vs. coherence flood detection methods - a GIS application,” Int. J. Remote Sens., vol. 21, no. 8, pp. 1619–1631, Nov. 2000.
[110] L. Pulvirenti, M. Chini, N. Pierdicca, L. Guerriero, and P. Ferrazzoli, “Flood monitoring using multi-temporal COSMO-SkyMed data: Image segmentation and signature interpretation,” Remote Sens. Environ., vol. 115, no. 4, pp. 990–1002, Apr. 2011.
[111] R. Heremans, A. Willekens, D. Borghys, B. Verbeeck, J. Valckenborgh, M. Acheroy, and C. Perneel, “Automatic detection of flooded areas on ENVISAT/ASAR images using an objectoriented classification technique and an active contour algorithm,” in International Conference on Recent Advances in Space Technologies, 2003, 2003, pp. 311–316.
[112] N. Pierdicca, L. Pulvirenti, M. Chini, G. Boni, G. Squicciarino, and L. Candela, “Flood mapping by SAR: Possible approaches to mitigate errors due to ambiguous radar signatures,” in IEEE Geoscience and Remote Sensing Symposium, 2014, pp. 3850–3853.
[113] Y. Cunjian, W. Siyuan, Z. Zengxiang, and H. Shifeng, “Extracting the flood extent from satellite SAR image with the support of topographic data,” in International Conferences on Info-Tech and Info-Net, 2001, pp. 87–92.
[114] T. Alipour Fard, M. Hasanlou, and H. Arefi, “Classifier Fusion of High-Resolution Optical and Synthetic Aperture Radar (Sar) Satellite Imagery for Classification in Urban Area,” ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., vol. XL–2/W3, no. November, pp. 25–29, Oct. 2014.
[115] N. Chaouch, M. Temimi, S. Hagen, J. Weishampel, S. Medeiros, and R. Khanbilvardi, “A synergetic use of satellite imagery from SAR and optical sensors to improve coastal flood mapping in the Gulf of Mexico,” Hydrol. Process., vol. 26, no. 11, pp. 1617–1628, May 2012.
[116] J. Töyrä, A. Pietroniro, and L. W. Martz, “Multisensor Hydrologic Assessment of a Freshwater Wetland,” Remote Sens. Environ., vol. 75, no. 2, pp. 162–173, Feb. 2001.
[117] J. Senthilnath, S. N. Omkar, V. Mani, and P. G. Diwakar, “Multi-Temporal Satellite Imagery for Flood Damage Assessment,” J. Indian Inst. Sci., vol. 93, no. 1, pp. 105–116, 2013.
[118] C. Pohl and J. L. Van Genderen, “Review article Multisensor image fusion in remote sensing: Concepts, methods and applications,” Int. J. Remote Sens., vol. 19, no. 5, pp. 823–854, Jan. 1998.
[119] S. Yonghua, L. Xiaojuan, G. Huili, Z. Wenji, and G. Zhaoning, “A study on optical and SAR data fusion for extracting flooded area,” in IEEE International Geoscience and Remote Sensing Symposium, 2007, pp. 3086–3089.
[120] C. Dey, X. Jia, and D. Fraser, “Decision Fusion for Reliable Flood Mapping Using Remote Sensing Images,” in Digital Image Computing: Techniques and Applications, 2008, pp. 184– 190.
[121] S. Kuehn, U. Benz, and J. Hurley, “Efficient flood monitoring based on RADARSAT-1 images data and information fusion with object-oriented technology,” in IEEE International Geoscience and Remote Sensing Symposium, 2002, vol. 5, pp. 2862–2864.
[122] United Nations Human Settlements Programme (UN-HABITAT), THE STATE OF THE WORLD’S CITIES REPORT 2006/2007. EARTHSCAN, 2006. [123] N. Islam Khan, “Temporal mapping and spatial analysis of land transformation due to urbanization and its impact on surface water system: a case from Dhaka metropolitan area, Bangladesh,” Int. Arch. Photogramm. Remote Sens., vol. XXXIII, pp. 598–605, 2000.
[124] M. S. Islam, T. Hossain, S. F. Ameen, E. Hoque, and S. Ahamed, “Earthquake induced liquefaction vulnerability of reclaimed areas of Dhaka,” J. Civ. Eng., vol. 38, no. 1, pp. 65–80, 2010.
[125] M. S. Islam, M. Nasrin, and A. J. Khan, “FOUNDATION ALTERNATIVES IN DREDGE FILL SOILS OVERLAYING ORGANIC CLAY,” Lowl. Technol. Int., vol. 15, no. 2, pp. 1–14, 2014.
[126] H. Rashid, L. M. Hunt, and W. Haider, “Urban flood problems in Dhaka, Bangladesh: slum residents’ choices for relocation to flood-free areas,” Environ. Manage., vol. 40, no. 1, pp. 95–104, Jul. 2007.
[127] A. Taleb, “Comparative Study of Urban Area Extension and flood Risk in Dhaka City of Bangladesh,” Glob. J. Hum. Soc. Sci. Geogr. Environ. Geosci., vol. 12, no. 11, 2012.
[128] M. Alam and M. D. G. Rabbani, “Vulnerabilities and responses to climate change for Dhaka,” Environ. Urban., vol. 19, no. 1, pp. 81–97, Apr. 2007.
[129] “USGS-EarthExplorer.” [Online]. Available: http://earthexplorer.usgs.gov/.
[130] C. Song, C. E. Woodcock, K. C. Seto, M. P. Lenney, and S. A. Macomber, “Classification and Change Detection Using Landsat TM Data,” Remote Sens. Environ., vol. 75, no. 2, pp. 230– 244, Feb. 2001.
[131] G. Jianyaa, S. Haiganga, M. Guoruia, and Z. Qimingb, “A review of multi-temporal remote sensing data change detection algorithms,” in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008, vol. XXXVII, no. Part B7, pp. 757–762.
[132] M. Akbari, A. R. Mamanpoush, A. Gieske, M. Miranzadeh, M. Torabi, and H. R. Salemi, “Crop and land cover classification in Iran using Landsat 7 imagery,” Int. J. Remote Sens., vol. 27, no. 19, pp. 4117–4135, Oct. 2006.
[133] “ENVI Reference Guide.” © ITT Visual Information Solutions.
[134] H. Rahman, “Agricultural Land Use and Land susceptibility in Bangladesh : An overview,” 2008. [Online]. Available: http://fpd-bd.com/wpcontent/uploads/2013/05/agriculturallanduse.pdf.
[135] A. T. Jeyaseelan, “DROUGHTS & FLOODS ASSESSMENT AND MONITORING USING REMOTE SENSING AND GIS,” Satell. Remote Sens. GIS Appl. Agric. Meteorol., pp. 291–313, 2004.
[136] B. Merz, H. Kreibich, R. Schwarze, and a. Thieken, “Review article ‘Assessment of economic flood damage,’” Nat. Hazards Earth Syst. Sci., vol. 10, no. 8, pp. 1697–1724, Aug. 2010.
[137] F. Messner, E. Penning-rowsell, C. Green, S. Tunstall, A. Van Der Veen, S. Tapsell, T. Wilson, J. Krywkow, C. Logtmeijer, A. Fernández-bilbao, P. Geurts, and D. Haase, “Evaluating flood damages: guidance and recommendations on principles and methods principles and methods,” 2007.
[138] E. Pantaleoni, B. a. Engel, and C. J. Johannsen, “Identifying agricultural flood damage using Landsat imagery,” Precis. Agric., vol. 8, no. 1–2, pp. 27–36, Feb. 2007.
[139] M. Haq, M. Akhtar, S. Muhammad, S. Paras, and J. Rahmatullah, “Techniques of Remote Sensing and GIS for flood monitoring and damage assessment: A case study of Sindh province, Pakistan,” Egypt. J. Remote Sens. Sp. Sci., vol. 15, no. 2, pp. 135–141, Dec. 2012.
[140] A. Scarsi, W. J. Emery, G. Moser, F. Pacifici, and S. B. Serpico, “An automated flood detection framework for very high spatial resolution imagery,” in IEEE Geoscience and Remote Sensing Symposium, 2014, pp. 4954–4957.
[141] S. Gupta and M. Muralikrishna, “South Asia Disaster Risk Management Programme: Synthesis Report on SAR Countries Disaster Risks,” 2010.
[142] T. H. Dewan, “Societal impacts and vulnerability to floods in Bangladesh and Nepal,” Weather Clim. Extrem., vol. IN PRESS, pp. 1–7, Dec. 2015.
[143] World Bank Group, Economics of Adaptation to Climate Change - Bangladesh. 2010. [144] M. Monirul Qader Mirza, “Global warming and changes in the probability of occurrence of floods in Bangladesh and implications,” Glob. Environ. Chang., vol. 12, no. 2, pp. 127–138, Jul. 2002.
[145] C. Ninno, P. A. Dorosh, L. C. Smith, and D. K. Roy, “The 1998 Floods in Bangladesh Disaster Impacts, Household Coping Strategies, and Response,” WASHINGTON, D.C., 1998.
[146] A. N. H. A. Hossain, “INTEGRATED FLOOD MANAGEMENT CASE STUDY BANGLADESH: FLOOD MANAGEMENT,” 2003.
[147] World Bank, “2004 Floods in Bangladesh Damage and Needs Assessment and Proposed Recovery Program: Main Report,” Washington, DC, 2005.
[148] Bangladesh and Disaster & Emergency Response DER Sub-Group, “Monsoon floods 2004 - Post-flood needs assessment summary report,” Dhaka, Bangladesh, 2004.
[149] “Government of the People’s Republic of Bangladesh - Ministry of Education.” [Online]. Available: http://www.moedu.gov.bd/old/bangladesh.htm.
[150] Y. Wang, Z. Li, Z. Tang, and G. Zeng, “A GIS-Based Spatial Multi-Criteria Approach for Flood Risk Assessment in the Dongting Lake Region, Hunan, Central China,” Water Resour. Manag., vol. 25, no. 13, pp. 3465–3484, Jun. 2011.
[151] M. D. Su, J. L. Kang, L. F. Chang, and A. S. Chen, “A grid-based GIS approach to regional flood damage assessment,” J. Mar. Sci. Technol., vol. 13, no. 3, pp. 184–192, 2005.
[152] J. Yin, D. Yu, Z. Yin, J. Wang, and S. Xu, “Multiple scenario analyses of Huangpu River flooding using a 1D/2D coupled flood inundation model,” Nat. Hazards, vol. 66, no. 2, pp. 577–589, Nov. 2012.
[153] A. Zerger and S. Wealands, “Beyond Modelling: Linking Models with GIS for Flood Risk Management,” Nat. Hazards, vol. 33, no. 2, pp. 191–208, Oct. 2004.
[154] S. S. Saini and S. P. Kaushik, “Risk and vulnerability assessment of flood hazard in part of Ghaggar Basin: A case study of Guhla block, Kaithal, Haryana, India,” Int. J. Geomatics Geosci., vol. 3, no. 1, pp. 42–54, 2012.
[155] Y. Ouma and R. Tateishi, “Urban Flood Vulnerability and Risk Mapping Using Integrated Multi-Parametric AHP and GIS: Methodological Overview and Case Study Assessment,” Water, vol. 6, no. 6, pp. 1515–1545, May 2014.
[156] G. P. Siddayao, S. E. Valdez, and P. L. Fernandez, “Analytic Hierarchy Process (AHP) in Spatial Modeling for Floodplain Risk Assessment,” Int. J. Mach. Learn. Comput., vol. 4, no. 5, pp. 450–457, 2014.
[157] R. Sinha, G. V. Bapalu, L. K. Singh, and B. Rath, “Flood Risk Analysis in the Kosi River Basin , North Bihar Using Multi-Parametric Approach of Analytical Hierarchy Process (AHP),” J. Indian Soc. Remote Sens., vol. 36, no. December, pp. 293–307, 2008.
[158] R. Krishnamurthy and M. Jayaprakash, “Flood hazard assessment of Vamanapuram River Basin, Kerala, India: An approach using Remote Sensing & GIS techniques,” Adv. Appl. Sci. Res., vol. 4, no. 3, pp. 263–274, 2013.
[159] B. Pradhan, “Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing,” J. Spat. Hydrol., vol. 9, no. 2, 2009.
[160] S. J. Carver, “Integrating multi-criteria evaluation with geographical information systems,” Int. J. Geogr. Inf. Syst., vol. 5, no. 3, pp. 321–339, Jan. 1991.
[161] H. Jiang and J. R. Eastman, “Application of fuzzy measures in multi-criteria evaluation in GIS,” Int. J. Geogr. Inf. Sci., vol. 14, no. 2, pp. 173–184, Mar. 2000.
[162] J. Malczewski, “GIS-based multicriteria decision analysis: a survey of the literature,” Int. J. Geogr. Inf. Sci., vol. 20, no. 7, pp. 703–726, Aug. 2006.
[163] G. Kandilioti and C. Makropoulos, “Preliminary flood risk assessment: the case of Athens,” Nat. Hazards, vol. 61, no. 2, pp. 441–468, Aug. 2011.
[164] K. Musungu, S. Motala, and J. Smit, “Using Multi-criteria Evaluation and GIS for Flood Risk Analysis in Informal Settlements of Cape Town : The Case of Graveyard Pond,” South African J. Geomatics, vol. 1, no. 1, pp. 77–91, 2012.
[165] G. Yalcin and Z. Akyurek, “Analysing flood vulnerable areas with multicriteria evaluation,” in 20th ISPRS Congress, 2004, pp. 1–6.
[166] S. Yahaya, N. Ahmad, and R. F. Abdalla, “Multicriteria Analysis for Flood Vulnerable Areas in Hadejia-Jama’are River Basin , Nigeria,” Eur. J. Sci. Res., vol. 42, no. 1, pp. 71–83, 2010.
[167] Y. Chen, D. Barrett, R. Liu, L. Gao, M. Zhou, L. Renzullo, S. Cuddy, and I. Emelyanova, “A spatial framework for regional-scale flooding risk assessment,” in 7th International Congress on Environmental Modelling and Software Modelling, 2014.
[168] T. L. Saaty, The analytic hierarchy process: planning, priority setting, resources allocation. New York: McGraw, 1980, pp. 20–25.
[169] D. Lawal and A. Matori, “Detecting Flood Susceptible Areas Using GIS-based Analytic Hierarchy Process,” 2012 Int. Conf. Futur. Environ. Energy IPCBEE, vol. 28, pp. 4–8, 2012.
[170] S. C. Michaelides, F. S. Tymvios, and T. Michaelidou, “Spatial and temporal characteristics of the annual rainfall frequency distribution in Cyprus,” Atmos. Res., vol. 94, no. 4, pp. 606–615, 2009.
[171] CYPADAPT project (LIFE10 ENV/CY/000723) - Development of a national strategy for adaptation to climate change adverse impacts in Cyprus., “Report on the future climate change impact, vulnerability and adaptation assessment for the case of Cyprus. Deliverable 3.4,” 2012.
[172] World Health Organization, “The WHO e-Atlas of disaster risk for the European Region - Volume 1. Exposure to natural hazards (version 2.0),” 2011. [Online]. Available: http://data.euro.who.int/e-atlas/europe/.
[173] Water Development Department (WDD), “Report on the identification of areas for which potential significant flood risks exist or might be considered likely to occur,” 2011.
[174] D. D. Alexakis, D. G. Hadjimitsis, A. Agapiou, K. Themistocleous, and A. Retalis, “Monitoring urban land cover using satellite remote sensing techniques and field spectroradiometric measurements: case study of ‘Yialias’ catchment area in Cyprus,” J. Appl. Remote Sens., vol. 6, no. 1, pp. 063603–11, Nov. 2012.
[175] D. D. Alexakis, D. G. Hadjimitsis, and A. Agapiou, “Estimating Flash Flood Discharge in a Catchment Area with the Use of Hydraulic Model and Terrestrial Laser Scanner,” in Advances in Meteorology, Climatology and Atmospheric Physics, C. G. Helmis and P. T. Nastos, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013, pp. 9–15.
[176] D. S. Fernández and M. a. Lutz, “Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis,” Eng. Geol., vol. 111, no. 1–4, pp. 90–98, Feb. 2010.
[177] T. Blaschke, “Object based image analysis for remote sensing,” ISPRS J. Photogramm. Remote Sens., vol. 65, no. 1, pp. 2–16, Jan. 2010.
[178] F. Franci, A. Lambertini, and G. Bitelli, “Integration of different geospatial data in urban areas: a case of study,” in Second International Conference on Remote Sensing and Geoinformation of the Environment, 2014, p. 92290P.
[179] S. Bhaskaran, S. Paramananda, and M. Ramnarayan, “Per-pixel and object-oriented classification methods for mapping urban features using Ikonos satellite data,” Appl. Geogr., vol. 30, no. 4, pp. 650–665, Dec. 2010.
[180] J. Schiewe, “SEGMENTATION OF HIGH-RESOLUTION REMOTELY SENSED DATA - CONCEPTS , APPLICATIONS AND PROBLEMS,” in Symposium on Geospatial Theory, Processing and Applications, 2002.
[181] H. Taubenböck, T. Esch, M. Wurm, a. Roth, and S. Dech, “Object-based feature extraction using high spatial resolution satellite data of urban areas,” J. Spat. Sci., vol. 55, no. 1, pp. 117–132, Jun. 2010.
[182] M. Baatz and A. Schäpe, “Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation,” in Angewandte Geographische Informationsverarbeitung XII AGIT symposium, 2000, vol. 58, pp. 12–23.
[183] U. C. Benz, P. Hofmann, G. Willhauck, I. Lingenfelder, and M. Heynen, “Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information,” ISPRS J. Photogramm. Remote Sens., vol. 58, no. 3–4, pp. 239–258, Jan. 2004.
[184] L. Bruzzone and L. Carlin, “A Multilevel Context-Based System for Classification of Very High Spatial Resolution Images,” IEEE Trans. Geosci. Remote Sens., vol. 44, no. 9, pp. 2587–2600, Sep. 2006.
[185] T. Esch, M. Thiel, M. Bock, a. Roth, and S. Dech, “Improvement of Image Segmentation Accuracy Based on Multiscale Optimization Procedure,” IEEE Geosci. Remote Sens. Lett., vol. 5, no. 3, pp. 463–467, Jul. 2008.
[186] N. S. Magesh, K. V. Jitheshlal, N. Chandrasekar, and K. V. Jini, “Geographical information system-based morphometric analysis of Bharathapuzha river basin, Kerala, India,” Appl. Water Sci., vol. 3, no. 2, pp. 467–477, Mar. 2013.
[187] A. N. Strahler, “Quantitative Geomorphology of Drainage Basins and Channel Networks,” in Handbook of Applied Hydrology, New York: McGraw Hill Book Company, 1964.
[188] R. E. Horton, “Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology.,” Geol. Soc. Am. Bull., vol. 56, no. 3, pp. 275–370, 1945.
[189] S. A. Schumm, “Evolution of drainage system and slopes in badlands of Perth Amboy, New Jersey.,” Geol. Soc. Am. Bull., vol. 67, 1956.
[190] S. Shankar and K. Dharanirajan, “Drainage Morphometry of Flood Prone Rangat Watershed , Middle Andaman , India- A Geospatial Approach,” Int. J. Innov. Technol. Explor. Eng., vol. 3, no. 11, pp. 15–22, 2014.
[191] M. Rudraiah, S. Govindaiah, and S. Vittala, “Morphometry using remote sensing and GIS techniques in the sub-basins of Kagna river basin, Gulburga district, Karnataka, India,” J. Indian Soc. Remote Sens., vol. 36, no. December, pp. 351–360, 2008. [192] R. Parveen, U. Kumar, and V. K. Singh, “Geomorphometric Characterization of Upper South Koel Basin, Jharkhand: A Remote Sensing & GIS Approach,” J. Water Resour. Prot., vol. 4, pp. 1042–1050, 2012.
[193] M. O. Nyadawa and J. K. Mwangi, “GEOMORPHOLOGIC CHARACTERITICS OF NZOIA RIVER BASIN,” J. Agric. Sci. Technol., vol. 12, no. 2, pp. 145–161, 2011.
[194] a. C. Dinesh, V. Joseph Markose, and K. S. Jayappa, “Bearing, azimuth and drainage (bAd) calculator: A new GIS supported tool for quantitative analyses of drainage networks and watershed parameters,” Comput. Geosci., vol. 48, pp. 67–72, Nov. 2012.
[195] K. G. Smith, “Standards for grading texture of erosional topography,” Am. J. Sci., vol. 248, no. 9, pp. 655–668, Sep. 1950.
[196] P. D. Sreedevi, K. Subrahmanyam, and S. Ahmed, “The significance of morphometric analysis for obtaining groundwater potential zones in a structurally controlled terrain,” Environ. Geol., vol. 47, no. 3, pp. 412–420, Oct. 2004.
[197] R. A. Hajam, H. Aadil, and B. SamiUllah, “Application of Morphometric Analysis for GeoHydrological Studies Using Geo-Spatial Technology –A Case Study of Vishav Drainage Basin,” J. Waste Water Treat. Anal., vol. 4, no. 3, pp. 1–12, 2013.
[198] M. Civita, Idrogeologia applicata e ambientale. 2005, pp. 36–37.
[199] Q. Weng, “Modeling Urban Growth Effects on Surface Runoff with the Integration of Remote Sensing and GIS,” Environ. Manage., vol. 28, no. 6, pp. 737–748, Feb.
[200] S. Drobne and A. Lisec, “Multi-attribute Decision Analysis in GIS : Weighted Linear Combination and Ordered Weighted Averaging,” Informatica, vol. 33, pp. 459–474, 2009.
Full Text
ليست هناك تعليقات:
إرسال تعليق