Maximum discrimination index: a tool for land cover identification

Abstract

This work presents an adaptable index that is applied to a pair of covers to be discriminated. Its adaptability relies on the procedure to determine the numerical value of the wavelengths or bands involved: the maximization of an operator based on the geometric mean of squared differences. This index is applied to the particular case of discrimination of wheat from ryegrass in different phenological stages. The maximum discrimination index outperforms other indices such as the normalized difference vegetation index, advanced normalized vegetation index and normalized difference greenness index. Its efficacy of discrimination is characterized and compared with the normalized difference greenness index (the second with better performance). It is observed that the proposed index has a more predictable behavior and reaches a discrimination accuracy as high as 95.5%. The maximum discrimination index could be adjusted to different covers and employed as a tool for discrimination. Spectral signatures coming from any platform: field, aerial or satellite, can be handled.

Optimization of Topdressing for Winter Wheat by Accurate Growth Monitoring and Improved Production Estimation

“…Crop NDVI of the plots was extracted from the multispectral orthographic map [25], while crop coverages of the plots were calculated from the RGB orthographic map by a method using threshold of vegetation index decided by human interpreting to divide crop and soil [26][27][28]. The vegetation index used for crop coverage extraction was the normalized difference greenness index (NDGI), as NDGI is sensitive to the canopy biomass and vegetation fraction or leaf area [29]: NDGI = DN green − DN red DN green + DN red (17) where DN green is the digital number of the green band and DN red is the digital number of the red band.…”