 The researchers developed a novel method to estimate above-ground biomass, AGB, using a snapshot hyperspectral sensor mounted on an unmanned aerial vehicle, UAV. They compared the performance of different models, including those which use spectral data alone or in combination with crop height. The results showed that the best model was one which combines both spectral data and crop height. This model had the highest correlation coefficient, are 2 equals 0.78 and lowest root mean square error, RMSE equals 1.08T slash HA among all tested models. Furthermore, this model also had the smallest mean absolute error, MAE equals 0.83T slash HA. Therefore, this model could provide more accurate estimates of AGB than other models. This article was authored by Ji Boyu, Gui Junyang, Chong Chunli, and others.