Accuracy evaluation of flood monitoring based on multiscale remote sensing for different landscapes

References

• Amiri BJ, Gao JF, Fohrer N, Mueller F, Adamowski J. 2018. Regionalizing flood magnitudes using landscape structural patterns of catchments. Water Resour Manage. 32(7):2385–2403.
   Google Scholar
• Aplin P. 2004. Spatial variation in land cover and choice of spatial resolution for remote sensing. Int J Remote Sens. 25:3687–3702.
   Google Scholar
• Bartlett M. 1936. The square root transformation in analysis of variance. Suppl J Roy Stat Soci. 3(1):68–78
   Google Scholar
• Benson BJ, Mackenzie MD. 1995. Effects of sensor spatial resolution on landscape structure parameters. Landscape Ecol. 10(2):113–120.
   Google Scholar
• Bian L, Butler R. 1999. Comparing effects of aggregation methods on statistical and spatial properties of simulated spatial data. Photogrammet Eng Remote Sens. 65:73–84.
   Google Scholar
• Biggin DS. 2010. A comparison of ERS-1 satellite radar and aerial photography for river flood mapping. Water Environ J. 10:59–64.
   Google Scholar
• Bilskie MV, Hagen SC, Medeiros SC, Passeri DL. 2014. Dynamics of sea level rise and coastal flooding on a changing landscape. Geophys Res Lett. 41(3):927–934.
   Google Scholar
• Chen ZG. 2017. Flooded area classification by high resolution SAR images. Wuhan University.
   Google Scholar
• Cracknell AP. 1998. Review article Synergy in remote sensing – what's in a pixel? Int J Remote Sens. 19(11):2025–2047.
   Google Scholar
• Data Center for Resources and Environmental Sciences, C.R. The China's 1:1 million landform type data set. http://www.resdc.cn.
   Google Scholar
• de Andrade MMN, Szlafsztein CF. 2018. Vulnerability assessment including tangible and intangible components in the index composition: an Amazon case study of flooding and flash flooding. Sci Total Environ. 630:903–912.
   Google Scholar
• Du H, Voss KJ. 2004. Effects of point-spread function on calibration and radiometric accuracy of CCD camera. Appl Opt . 43(3):665–670.[InsertedFromOnline.
   Google Scholar
• Feyisa GL, Meilby H, Fensholt R, Proud SR. 2014. Automated water extraction index: a new technique for surface water mapping using Landsat imagery. Remote Sens Environ. 140:23–35.
   Google Scholar
• Forster BC, Best P. 1994. Estimation of SPOT P-mode point spread function and derivation of a deconvolution filter. Isprs J Photogrammet Remote Sens. 49:32–42.
   Google Scholar
• Fu BJ, Xu YD, Lv YH. 2010. Scale characteristics and coupled research of landscape pattern and soil and water loss. Adv Earth Sci. 25:673–681.
   Google Scholar
• Gianinetto M, Villa P, Lechi G. 2005. Postflood damage evaluation using Landsat TM and ETM + data integrated with DEM. IEEE Trans Geosci Remote Sens. 44:236–243.
   Google Scholar
• Golub GH, Van Loan CF. 2012. Matrix computations. JHU Press.
   Google Scholar
• Goodchild MF, Quattrochi DA. 1997. Scale, multiscaling, remote sensing, and GIS.
   Google Scholar
• Gustafson EJ. 1998. Quantifying landscape spatial pattern: what is the state of the art? Ecosystems. 1(2):143–156.
   Google Scholar
• Haibo Y, Zongmin W, Hongling Z, Yu G. 2011. Water body extraction methods study based on RS and GIS. Procedia Environ Sci. 10:2619–2624.
   Google Scholar
• Haines-Young R, Chopping M. 1996. Quantifying landscape structure: a review of landscape indices and their application to forested landscapes. Prog Phys Geogr. 20(4):418–445.
   Google Scholar
• Hatfield J. 2001. Upscaling and downscaling methods for environmental research. J Environ Qual. 30(3):1100.
   Google Scholar
• He HS, Ventura SJ, Mladenoff DJ. 2002. Effects of spatial aggregation approaches on classified satellite imagery. Int J Geogr Inform Sci. 16(1):93–109.
   Google Scholar
• Hinton PR, McMurray I, Brownlow C. 2004. SPSS explained. Routledge.
   Google Scholar
• Hlavka C, Dungan J. 2002. Areal estimates of fragmented land cover: effects of pixel size and model-based corrections. Int J Remote Sens. 23(4):711–724.
   Google Scholar
• Hocking RR. 1976. A biometrics invited paper. The analysis and selection of variables in linear regression. Biometrics. 32(1):1–49.
   Google Scholar
• Horritt MS, Mason DC, Luckman AJ. 2001. Flood boundary delineation from synthetic aperture radar imagery using a statistical active contour model. Int J Remote Sens. 22(13):2489–2507.
   Google Scholar
• Huang CQ, Townshend JRG, Liang SL, Kalluri SNV, DeFries RS. 2002. Impact of sensor's point spread function on land cover characterization: assessment and deconvolution. Remote Sens Environ. 80(2):203–212.
   Google Scholar
• Ji L, Zhang L, Wylie B. 2009. Analysis of dynamic thresholds for the normalized difference water index. Photogramm Eng Remote Sens. 75:1307–1317.
   Google Scholar
• Kim K-H, Pauleit S. 2007. Landscape character, biodiversity and land use planning: the case of Kwangju City Region, South Korea. Land Use Policy. 24(1):264–274.
   Google Scholar
• Lee S-H, Lim S-Y, Kim N, Park N-C, Yang H, Park K-S, Park Y-P. 2011. Increasing the storage density of a page-based holographic data storage system by image upscaling using the PSF of the Nyquist aperture. Opt Express. 19(13):12053. 12065
   Google Scholar
• Leng Y, Li N. 2017. Improved change detection method for flood monitoring. J Radars. 6:204–212.
   Google Scholar
• Li J, Zhou Q, Chen X, Ling Tian QL, Li TY. 2018. Spatial sale study on quantitative remote sensing of highly dynamic coastal/inland waters. Geomat Inform Sci Wuhan Univ. 43:937–942.
   Google Scholar
• Li JG, Huang SF, Li JR. 2010. Research on extraction of water body from ENVISAT ASAR images: a modified Otsu threshold method. J Nat Disasters. 19:139–145.
   Google Scholar
• Li X, Lu L, Cheng G, Xiao H. 2001. Quantifying landscape structure of the Heihe River Basin, north-west China using FRAGSTATS. J Arid Environ. 48(4):521–535.
   Google Scholar
• Lv YH, Chen LD, Fu BJ. 2007. Analysis of the integrating approach on landscape pattern and ecological processes. Prog Geogr. 26:1–10.
   Google Scholar
• Marceau DJ, Hay GJ. 1999. Remote sensing contributions to the scale issue. Can J Remote Sens. 25(4):357–366.
   Google Scholar
• Mason A. 2001. Unresolved issues. J Econ Perspect. 2:41–58.
   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.
   Google Scholar
• McGarigal K. 2014. Landscape pattern metrics. Wiley StatsRef: Statistics Reference Online.
   Google Scholar
• McGarigal K, Cushman SA, Ene E. 2012. FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. http://www.umass.edu/landeco/research/fragstats/fragstats.html.
   Google Scholar
• McGarigal K, Marks BJ. 1995. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen. Tech. Rep. PNW-GTR-351. Portland, OR: US Department of Agriculture, Forest Service, Pacific Northwest Research Station. 122 p, 351
   Google Scholar
• Moody A, Woodcock CE. 1994. Scale-dependent errors in the estimation of land-cover proportions: implications for global land-cover datasets. Photogramm Eng Remote Sens. 60:585–596.
   Google Scholar
• Moody A, Woodcock CE. 1995. The influence of scale and the spatial characteristics of landscapes on land-cover mapping using remote sensing. Landscape Ecol. 10(6):363–379.
   Google Scholar
• NCDR. 2016. The action of China's Disaster Reduction during “12th Five-Year Plan” period. NCDR
   Google Scholar
• O'Neil R. 1998. Homage to St. Michael: or, why are there so many books on scale? Ecol Scale.
   Google Scholar
• O'Neil R, Krummel J. 1988. Indices of landscape pattern. Landscape Ecol. 1.
   Google Scholar
• O'Neill R, Hunsaker C, Timmins SP, Jackson B, Jones K, Riitters KH, Wickham JD. 1996. Scale problems in reporting landscape pattern at the regional scale. Landscape Ecol. 11:169–180.
   Google Scholar
• Orman US. 2001. Determination of flood inundated areas using RS techniques in the western Black Sea Region of Turkey. Turk J Eng Environ Sci. 25:379–389.
   Google Scholar
• Otsu N. 1979. A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern. 9:62–66.
   Google Scholar
• Otsu N. 2007. A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern. 9:62–66.
   Google Scholar
• Ponzoni J, Galvão F, Epiphanio LS, José CN. 2002. Spatial resolution influence on the identification of land cover classes in the Amazon environment. An Acad Bras Cienc. 74:196–198.
   Google Scholar
• Quattrochi CA. 1997. Scale in remote sensing and GIS. Lewis Publishers.
   Google Scholar
• Quattrochi DA, Lam NSN. 2010. On the issues of scale, resolution, and fractal analysis in the mapping sciences. Prof Geogr. 44:88–98.
   Google Scholar
• Rahman MS, Di LP. 2017. The state of the art of spaceborne remote sensing in flood management. Nat Hazards. 85(2):1223–1248.
   Google Scholar
• Rango A, Anderson AT. 1974. Flood hazard studies in the Mississippi river basin using remote sensing. J Am Water Resources Assoc. 10(5):1060–1081.
   Google Scholar
• Raptis V, Vaughan R, Wright G. 2003. The effect of scaling on land cover classification from satellite data. Comput Geosci. 29:705–714.
   Google Scholar
• Read JM, Lam SN. 2002. Spatial methods for characterising land cover and detecting land-cover changes for the tropics. Int J Remote Sens. 23(12):2457–2474.
   Google Scholar
• Smith JH, Stehman SV, Wickham JD, Yang L. 2003. Effects of landscape characteristics on land-cover class accuracy. Remote Sens Environ. 84(3):342–349.
   Google Scholar
• Stewart JB, Engman ET, Feddes RA, Kerr YH. 1998. Scaling up in hydrology using remote sensing: summary of a Workshop. Int J Remote Sens. 19(1):181–194.
   Google Scholar
• Takeuchi S, Konishi T, Suga Y, Kishi S. 1999. Comparative study for flood detection using JERS-1 SAR and Landsat TM data. Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International. Vol. 872. p. 873–875.
   Google Scholar
• Tockner K, Lorang MS, Stanford JA. 2010. River flood plains are model ecosystems to test general hydrogeomorphic and ecological concepts. River Res App. 26(1):76–86.
   Google Scholar
• Townshend JRG. 1981. Spatial resolution of satellite images. Prog Phys Geogr. 5.
   Google Scholar
• Townshend JRG, Justice CO. 1988. Selecting the spatial resolution of satellite sensors required for global monitoring of land transformations. Int J Remote Sens. 9(2):187–236.
   Google Scholar
• Turner MG, O'Neill RV, Gardner RH, Milne BT. 1989. Effects of changing spatial scale on the analysis of landscape pattern. Landscape Ecol. 3(3–4):153–162.
   Google Scholar
• Wang FT, Wang SX, Zhou Y. 2011. Application and prospect of multi-spectral remote sensing in major natural disaster assessment. Spectrosc Spect Anal. 31:577–582.
   Google Scholar
• Wei CJ, Wang SX. 1998. The role of remote sensing technology in monitoring and evaluation of flood disaster in China. Bull Chinese Acad Sci. 13:443–447.
   Google Scholar
• Weng Q. 2014. Scale issues in remote sensing. John Wiley & Sons.
   Google Scholar
• Wiens JA. 2002. Riverine landscapes: taking landscape ecology into the water. Freshwater Biol. 47(4):501–515.
   Google Scholar
• Woodcock CE, Strahler AH. 1987. The factor of scale in remote sensing. Remote Sens Environ. 21(3):311–332.
   Google Scholar
• Wu H, Li Z-L. 2009. Scale issues in remote sensing: a review on analysis, processing and modeling. Sensors. 9(3):1768–1793.
   Google Scholar
• Wu J, Shen W, Sun W, Tueller PT. 2002. Empirical patterns of the effects of changing scale on landscape metrics. Landscape Ecol. 17(8):761–782.
   Google Scholar
• Xiong JG, Wang SX, Zhou Y. 2010. A sensitivity analysis and accuracy assessment of different water extraction index models based on ALOS AVNIR-2 data. Remote Sens Land Resour. 22:46–50.
   Google Scholar
• Xu H. 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens. 27(14):3025–3033.
   Google Scholar
• Yamagata Y, Akiyama T. 1988. Flood damage analysis using multitemporal Landsat Thematic Mapper data. Int J Remote Sens. 9(3):503–514.
   Google Scholar
• Zhang G, Zheng G, Gao Y, Xiang Y, Lei Y, Li J. 2017. Automated water classification in the Tibetan plateau using Chinese GF-1 WFV data. Photogramm Eng Remote Sens. 83(7):509–519.
   Google Scholar
• Zhang H, Xu XY, Zhang L, Wang HR. 2011. Comprehensive assessment of loss of flood and water logging disasters from 2000 to 2010 and analysis of their causes. J Econom Water Resour. 29:5–9.
   Google Scholar
• Zhang M, Li Z, Tian B, Zhou J, Tang P. 2016. The backscattering characteristics of wetland vegetation and water-level changes detection using multi-mode SAR: a case study. Int J Appl Earth Obs Geoinform. 45:1–13.
   Google Scholar
• Zhang SJ. 2005. Research on remote sensing monitoring and disaster evaluation of flood disaster. Nanjing University of Information Science and Technology.
   Google Scholar