2012 Volume 28 Issue 3 Pages 89-96
The monitoring of paddy fields in tropical region, where cropping patterns vary according to landforms and water conditions, requires spatio-temporal analysis using multi-temporal/seasonal satellite images. However, the large amount of rainfall in the humid tropics in Asian region increases the difficulty of obtaining cloud free satellite images. This study used images obtained by ALOS PALSAR, which is an all-weather sensor, in combination with optical pan-sharpened image from an ALOS AVNIR-2 and PRISM, which provides excellent spectral and spatial resolution, to evaluate paddy field detection in Cianjur District, an outstanding rice-producing area in Java Island, Indonesia.The land cover of the study area could be classified with an overall accuracy of 72.3% and an overall Kappa coefficient of 0.53. Above all, paddy fields could be well classified with Kappa coefficients between 0.73 and 0.91. The large scale paddy fields could be classified with Kappa coefficients above 0.81, on the other hand, complicated-shaped small scale paddy fields in the Gute volcanic mountain slope could be classified with a Kappa coefficient of lower than 0.76.The rice cropping pattern was investigated by temporally totaling the occupancy of water-covered areas. A semiannual crop pattern was primarily adopted in the basins where large scale and uniform paddy fields had been developed, except during the dry season between June and September. In contrast, terrace paddy fields exhibited unique seasonal patterns according to water conditions. These results essentially agreed with the cropping calendar that had been created based on the interviews survey. Therefore, the use of high-resolution optical sensor images obtained by ALOS AVNIR-2 and PRISM, together with temporal images obtained by PALSAR, could classify land cover and paddy fields with high spatio-temporal resolution in tropical regions.
