Flood inundation map of Bangladesh using MODIS time‐series images

Abstract

The detection of the spatio-temporal extent of inundation resulting from the floods in 2004 and 2007 in Bangladesh has been studied using time-series MODIS surface reflectance data. Flood inundation maps were developed from vegetation and land water surface indices derived using surface reflectance. The inundation map developed using MODIS data was compared with a corresponding RADAR-SAT image, where both images refer to the satellite-based remote-sensing data. The estimates show a strong correlation with the inundation area derived from the RADARSAT products (coefficient of determination of R 2 : 0.96). The paper shows that it is possible to study flood dynamics by assessing inundation and recession patterns and to perform flood assessments similar to the high-resolution (50 m) microwave satellite, RADARSAT-based flood assessments using products derived from MODIS 500 m imagery. MODIS has advantages over microwave satellite because it has a high observational frequency and these data are available free of cost. We have concluded that this is a useful method to assess the extent of the temporal floods in the People's Republic of Bangladesh. Figure 8 Temporal changes of flood and mixture pixels for four types of paddy fields (single-cropped irrigated rice, single-cropped rain fed rice, doublecropped irrigated rice and triple-cropped irrigated rice), forest and settlement areas.

Coupled Ground- and Space-Based Assessment of Regional Inundation Dynamics to Assess Impact of Local and Upstream Changes on Evaporation in Tropical Wetlands

“…Especially images from seasonal transition times are susceptible to misclassification, since water bodies in the study area dry out heterogeneously inside of a pixel. The determination of pixels, which are covered by vegetation mixed with or completely flooded by water, is usually difficult [30,33]. Pixels can be covered by a mixture of different land types, which are all combined in one index pixel value leading to an over-or underestimation of MODIS-derived inundation [30].…”

“…However, interpretations with MODIS imagery are limited by cloud cover, which often does not allow for daily use [25], and the passive remote sensing approach, where flood detection is reduced under dense vegetation cover [26]. Spatial and temporal extents of the inundation process are often investigated by multi-band classification [11,17,20,21,23,24,[27][28][29][30] using vegetation and humidity indices [17,[20][21][22]29,31,32]. MODIS-derived inundated areas can then be validated by Landsat [22,31,33,34], ASTER [27], and SAR [25], or with national land cover datasets [35].…”

Characterizing floods in the poorly gauged wetlands of the Tana River Delta, Kenya, using a water balance model and satellite data

“…They have been used to characterize water levels (Ordoyne and Friedl, 2008), the seasonality of lake systems (Feng et al, 2012), the extent of annual flooding (Sakamoto et al, 2007) and to map wetlands and flooding patterns (Ticehurst et al, 2009;Islam et al, 2010). MYD09A1 is a level-3 high-quality composite product, with a 500 m resolution.…”

Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas

“…This technique has also been applied to characterize a range of continental water bodies such as large lakes (Birkett, 1995;Ponchaut and Cazenave, 1998;Mercier et al, 2002), paddy rice fields (Islam et al, 2010), or tidal floods (Yan et al, 2010). The general procedure to monitor storage consists in associating water surface elevation and area after evaluating them independently (e.g.…”