In riverine flood-plain areas, the extraction of the spatial pattern of flood extents and durations during flood instances permit flood planners to anticipate likely threats from floods and to articulate actions to mitigate these events. Rapid flood mapping is a critical aspect for flood estimation and evaluation in the early stage. Accurate early updates of flood inundation have been made possible by remote sensing. The present study applies satellite derived Water indices and Classification

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... thod to analyzes and estimates spatio-temporal flood-2014 extent using landsat-8 flood instance images in Lower Chenab Plain, Pakistan. The lower Chenab plain is particularly prone to frequent riverine flooding but is understudied. It has experienced history worst flooding in 2014. Cloud-free Landsat-8 data was acquired for pre-flood, during-flood, and post-flood periods for detailed analysis. We used Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Water Ratio Index (WRI) for the delineation of inundated areas. we also used supervised classification to detect and compare flooded areas with used indices. The analysis allowed us to compute flooded areas, duration and flood recession.The proposed RS technique provides an empirical basis for rapid identification of inundated areas, which enable emergency response and relief efforts on newly flooded areas. Thus, our study provides another perspective and substantial contributions to flood monitoring using free satellite data in Pakistan.