Analyzing the inundation patterns in Asia floodplains by passive microwave data

Haolu Shang; Li Jia; Massimo Menenti

doi:10.1117/12.977238

21 November 2012 Analyzing the inundation patterns in Asia floodplains by passive microwave data

Haolu Shang, Li Jia, Massimo Menenti

Proceedings Volume 8524, Land Surface Remote Sensing; 85240E (2012) https://doi.org/10.1117/12.977238
Event: SPIE Asia-Pacific Remote Sensing, 2012, Kyoto, Japan

Abstract

Soil water saturation condition is an essential factor that indicates the possible temporal and spatial hazard of inundations in floodplains. To monitor wetness conditions over a long period of time and large areas, passive microwave data is used to study the inundation pattern of large floodplains in Asia, such as the Poyang Lake floodplain. The polarization difference brightness temperature at 37GHz is sensitive to the water extension even under dense forest. However, the mixing of signals from open water, bare soil and vegetation makes it difficult to obtain the soil-water saturation conditions from 37GHz data. That is because 37GHz microwave emission is attenuated by the vegetation canopy, which shows seasonal changes in Asia floodplains. We developed a linear mixing model to eliminate the signal from vegetation and derive the soil- water saturation condition from 37GHz data. Vegetation attenuation factors, in terms of vegetation fractional area and LAI, have been estimated by correlation with the NDVI. Thus the vegetation attenuation function is built according to the relationship between 37GHz and NDVI data of agricultural areas, with the help of Harmonic analysis of time series to obtain continuous NDVI time series. Comparing the soil-water saturated area from 37GHz and water extension area of Poyang Lake from SAR image data at higher spatial resolution, our result shows a good fit with SAR data but relatively higher values.

Citation Download Citation

Haolu Shang, Li Jia, and Massimo Menenti "Analyzing the inundation patterns in Asia floodplains by passive microwave data", Proc. SPIE 8524, Land Surface Remote Sensing, 85240E (21 November 2012); https://doi.org/10.1117/12.977238

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