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Abstract
A rapid increase in the concentration of greenhouse gases (GHGs) aggravates global warming of the Earth's atmosphere. It is necessary to monitor the emission rate as well as emission quantity of methane as a major component of GHGs. The objective of this study is to develop mathematical models for the estimation of methane emission from a deep-water rice field, using information extracted from satellite images. The methodology proposal in the study consists of two models: firstly, the true ground data of the monthly biomass of rice and average methane emission rate were analysed to set up the methane emission rate model; secondly, the biomass of rice and various reflectances of the wavelength obtained from satellite images were investigated. It has been found that Landsat TM band 3, band 4, band 5, band 7 and the normal differential vegetation index as well as the National Oceanic and Atmospheric Administration AVHRR band 1, band 2 and NDVI are well related to the biomass of rice, which can be used to estimate the biomass of rice, the so-called remote sensing (RS) biomass model Finally the estimation of methane emission can be manipulated by using the methane emission rate model coupled with the RS biomass model based on data from satellite imageries. Comparison between estimated methane emission from satellite images and experimental methane emission data measured at the Prachinburi Rice Research Center reveals that the methodology proposed can be used to estimate methane emission from a deep-water rice field with satisfactory accuracy, particularly during the reproductive stage of rice and maturation.