A sub-pixel method for estimating planting fraction of paddy rice in Northeast China

Timely and accurate data regarding the distribution of paddy rice are valuable for various agricultural studies. In this study, we aimed to develop a sub-pixel method for estimating the planting fraction of paddy rice in Northeast China. This method assumes low seasonal variations in moisture in paddy rice fields compared with other upland crops due to the presence of flooding water throughout the growing season. We used the coefficient of variation (CV) of the land surface water index (LSWI) derived from the moderate resolution imaging spectroradiometer (MODIS) to indicate the water condition. High resolution images obtained by an unmanned aerial vehicle (UAV) were used to test this assumption and to develop the relationship between the CV of LSWI and the planting fraction of paddy rice. The results showed that the CV of LSWI could effectively indicate the planting fraction of paddy rice, where our method explained 84% of the variation in the planting fraction of paddy rice in the UAV survey sites. Validation based on the statistical data showed that this method explained 78% and 85% of the variations in the paddy rice area at the county and prefecture levels, respectively. Moreover, the performance of this method was good independent of the field survey data, and this alternative approach may facilitate mapping of the planting distribution of paddy rice over large areas.