Author : Bountheo Hemmany

Summary : Early prediction of paddy field area under cultivation is very important thing for predicting rice production, rice consumption, rice shortage and taking various policy decisions in budget planning of a government, especially in countries consuming rice as staple food, shows as Asian countries. MAny countries use the conventional technique of data collection for crop monitoring and yield estimation based on ground-based visits and reports from the farmers to the head of village, eyes estimation was one by field officer of the sub-district level, number of seed per hectare. These methods are subjective very costly and time consuming. However, the result would be dreadful of accuracy of the collected data, especially concerning planted and harvested area. The aim of this study is to extract the paddy field during rice season, use the supervised classification, the classifying NDVI, RVI and three tasselled cap (brightness, greeness, wetness). This research used single satellite imagery, Lansat TM7 to predict paddy field based on combining methods in rice irrigation area: supervised classification of original image, supervised classification of tasselled cap transformation, rule base based on NDVI value, rule base based on RVI value, rule base based on brightness, greenness, wetness of Tassled cap.