Rice straw open-field burning is practiced in many countries and has been proven to be a significant source of emissions during the harvest season. Current approaches to obtain the fraction of rice straw subject to open burning vary significantly, and can lead to incorrectly estimating air pollutant emissions. This study proposes a remote sensing approach by classifying high-resolution imagery taken by Formosat-2 (FS-2) to map burned areas of rice paddy fields during harvest season to provide visualized and accurate estimations. We requested FS-2 image acquisition over the Chianan Plain, which is the greatest rice-producing area of Taiwan, during 3 weeks following the harvesting of the fall crops in 2009. Simultaneously, a mobile team on the ground examined the state of the rice paddies when FS-2 was scheduled to take the images. Based on these data, a procedure that integrated a ground truth-based classification scheme, land use data, spectral signatures, and supervised decision rules was applied to identify burned sites. The results were verified using the field data, with an overall accuracy of 87% for distinguishing among the 6 cover types of rice paddies, showing that 27.3% of the paddies within the study area were openly burned. Based on the mapping results, a comprehensive inventory of the air pollutant emissions from straw open burning in Taiwan is presented. To facilitate the management of emission sources and to improve local air quality, we encourage the use of FS-2 imaging to monitor the open burning of rice straw.

Rice is produced in more than 95 countries worldwide and is a staple food for over half of the world's population. Rice is also a major food crop of Taiwan. There are numerous rice crops planted on the western plains of Taiwan, and, after the harvest season, the left-over straw is often burned on-site. The air pollutants from the burning emissions include CO₂, CO, CH₄ and other suspended particles, most of these being the greenhouse gases which cause global climate change. In this study FORMOSAT-2 satellite images and ground-truth data from 2008 and 2009 are used to conduct supervised classification and calculate the extent of the straw burning areas. It was found that 10% of the paddies in the study area were burned after harvest during this 2-yr period. On this pro rata basis, we calculated the overall carbon emissions from the burning of the straw. The findings showed that these few farmers produced up to 34 000 tons of carbon emissions in 2008, and 40 000 tons in 2009. The study results indicate that remotely sensed images can be used to efficiently evaluate the important characteristics for carbon emission detection. It also provides quantitative results that are relevant to tracking sources of transport pollution, postharvest burning, and Asian dust in Taiwan