Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data

Aerial multispectral images are a good source of crop, soil, and ground coverage information. Spectral reflectance indices provide a useful tool for monitoring crop growing status. A series of aerial images were obtained by an airborne MS4100 multispectral imaging system on the cotton and soybean field. Ground hyperspectral data were acquired with a ground-based integration system at the same time. The Normalized Difference Vegetative Index (NDVI), Simple Ratio (SR), and Soil Adjusted Vegetation Index (SAVI) calculated from both systems were analyzed and compared. The information derived from aerial multispectral images has shown the potential to monitor the general growth status of crop field. The vegetation indices derived from both systems were significantly different (p-value was 0.073 at = 0.1 level) at the early growing stage of crops. The correlation coefficients of the image NDVI and ground NDVI were 0.3029 for soybean field and 0.338 for cotton field. SAVI and SR were not correlated.

Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data Academic Article