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Flood is a major environmental problem in India as it has devastating effects on life and property. The objective of present study is to delineate and identify flood hazard and risk assessment at landscape level using Landsat satellite data from 1974-2013 in Chamoli District, Uttarakhand, India covering total geographical area of 8030 km2. The study area lies between 30-31° N latitude and 79-80° E longitude. The satellite data was ortho-rectified and the study area was extracted using district boundary. The vegetation type/land use map was prepared using on-screen visual interpretation technique. The multi-flood time series dataset was used for preparation of Digital Elevation Model. Geographical Information System was used for identification of flood prone areas which were classified with zone-wise. A flood frequency map was developed using the multi-date Landsat satellite imagery. The classified vegetation type/land use map from 1974-2013 was overlaid to find out the frequency of the flood. Flood affected areas were classified into very low, low, medium, high, very high and extremely high based on vulnerability to the potential of flood hazard. The areas were further categorized, based on the vulnerability of flood viz; extremely high (6) very high (5), high (4), medium (3), low (2) and very low (1) respectively. The study assigned the scores to each class for further determination of risk zone in various thematic layers such as slope, aspect and elevation. The incorporation of all thematic layers and flood frequency map was generated to prepare flood hazard and risk map using GIS platform. Flood frequency and flood prone areas were calculated using DEM. The vegetation type/land use map was integrated for creation of flood hazard and risk assessment. Based on this analysis the flood risk zones at different levels and intensity in the Chamoli district were prepared. This flood hazard and risk assessment maps will be useful to management and mitigate losses of lives and property from recurrent flood disasters in Chamoli District. This model can also be applied to comparable areas in Himalayas.