Paddy field mapping in South-East Asia with NOAA AVHRR based on time-series of spectral mixture analysis

In Asian countries, paddy field is indispensable for our lives not only as a source of food but also ecosystem, hydrology, landscape and culture. It is presumed to be one of the most likely source of atmospheric methane and affects atmospheric phenomena in the local scale. In this sense it is necessary to get the detailed spatial distribution of paddy field in Asian region. The improved understanding of paddy field distribution at large spatial scales has increased the interest in deriving crop yield and methane emission estimations. Nevertheless, the collection of such data through field surveys is time-consuming and expensive in South-East Asia regions. Remotely sensing data from satellite images provide an alternative means of obtaining paddy field distribution. In this study, land cover characterization technique for paddy fields is investigated using time series of NOAA/AVHRR data. The method proposed in this study includes six processing steps: 1) precise geometric and radiometric correction, 2) automatic cloud screening, 3) atmospheric correction by 6S code, 4) BRDF correction by kernel model, 5) automatic endmember selection for spectral mixture analysis, 6) generation of vegetation, soil and water map and their time series analysis.