Coal and oil shale quality is important to evaluate for mining purposes worldwide. In order to evaluate the quality and analyze the mineralization of coal and oil shale in the Paleogene Lijiaya Formation in Huangxian Coalfield, Eastern China, 27 samples were studied by the methods of geochemistry, sedimentology and coal geology. The results indicated that coal belonged to brown coal with high moisture content, lowmedium ash yield and low sulfur content. It is high-quality coal that is suitable for industrial electricity generation. However, the quality of oil shale varied by layers, while three quality levels could be distinguished: highquality oil shale was located in layers A-1 and B with a thickness of 2.5 m, medium-quality oil shale was deposited in layer A-2 with a thickness of 1.71 m, and poor-quality oil shale was found in layers A-3 and C with a thickness of 1.55 m. So, oil shale layer A can be mined together with coal bed 1, while oil shale layer B can be extracted separately and layer C as a perspective resource would be subject to mining in future.

The NDVI of GreenSeeker has proven to be an effective tool for Management Zoning. An optimal method on the basis of NDVI was proposed to establish Management Zoning accurately in this study. First, the coefficient of variation of time series distance difference of Greenseeker and UAV NDVI was tested, it was significant to evaluate the accuracy of Greenseeker NDVI for large-areas. On this basis, optimal partition numbers and partitioning algorithm were identified according to the Silhouette Coefficient of data structure, the accuracy of estimation of agronomic parameters and the difference of agronomic parameters in each plot under different partition numbers. Results demonstrate that the difference among the points of the distance sequence is not significant (F = 0.641 > 0.05). The NDVI of Greenseeker has high reliability. When the partitioning algorithm and the number of partitions are Kmeans and four, respectively, the Silhouette Coefficient and the accuracy of estimation of agronomic parameters (plant height, nitrogen content) are higher than in other treatments. At the same time, the agronomic parameters in each plot showed the significant differences. The proposed method provides a good prospect to optimize the establishment of management zones.