Abstract:
The proposed approach aims to estimate the flood extent and soil wetness using AMSR-E passive microwave data. The approach is applied over the Mackenzie River Basin, whic...Show MoreMetadata
Abstract:
The proposed approach aims to estimate the flood extent and soil wetness using AMSR-E passive microwave data. The approach is applied over the Mackenzie River Basin, which is situated in northwestern Canada. The methodology is based on the polarization ratio index (PR), which is computed using AMSR-E 37 GHz, vertically and horizontally polarized brightness temperature values. The water surface fraction (WSF), which represents the fraction of flooded soil, was derived on a pixel-per-pixel basis. The fractional vegetation cover was added to the WSF calculation in order to take into account the temporal variation of the vegetation shading effect. The WSF derived from AMSR-E data, WSF(AMSR-E), was compared to those derived from the Moderate-resolution Imaging Spectroradiometer Terra instrument (MODIS-Terra) images (250 m), WSF(MODIS). A rating curve relationship was developed between the observed discharge and WSF(MODIS). It was noted that the WSF obtained from AMSR-E images systematically exceed those from MODIS, as they are formed from a combination of different contributions, including open water surface, flooded area and wetlands, which are abundant in the northern climates. Therefore, a wetness index was defined based on the difference between passive microwave and visible image responses. This index was able to qualitatively describe the temporal evolution of the wetness over the Mackenzie River Basin. The availability of discharge observations and passive microwave data leads to the definition of a consistent wetness index and soil moisture monitoring over the Mackenzie River Basin. A satisfactory agreement was noted between the wetness index, the precipitation, and the temperature values. The wetness index agrees well with the measured soil moisture.
Published in: Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05.
Date of Conference: 29-29 July 2005
Date Added to IEEE Xplore: 14 November 2005
Print ISBN:0-7803-9050-4