Linear spectral unmixing for crop and soil information extraction from a single worldview-2 image

Spatial information related to vegetation status and soil properties is needed in precision farming, especially early in the growing season. At these stages, vegetation has already emerged while soil is also visible in multispectral EO images. In this paper, linear spectral unmixing is applied to an 8 bands WorldView-2 image to extract information on both vegetation and soil acquired at in-season nitrogen sidedress stage in 2010 and 2011 for four corn fields located in the Montérégie region of Quebec, Canada. EO derived soil properties were strongly correlated to EC_a. Correlation between dark soil abundance and EC_a reached R=0.9 and correlation between bright soil abundance and EC_a was about R=-0.7. Vegetation abundance for combined data of several fields was better correlated to measured biomass than NDVI and SAVI. The possibility to get valuable soil and plant information from a single multispectral image offers an interesting cost reduction opportunity for precision farming applications.