Spectral Data Analysis for Cotton Growth Monitoring
Apr 25, 2019
Since information technology was introduced in agriculture, there has been a great deal of interest in estimating terrestrial biophysical parameters such as vegetation with remotely sensed data. The empirical study presented in this paper focuses on the relationships between vegetation properties and reflectance measured on a cotton canopy throughout its phenological evolution by means of a hand-held spectroradiometer, during a field experiment. The objective was to produce relationships between spectral indices (such as normalized difference vegetation index (NDVI)) and biophysical parameters, such as leaf area index (LAI) and biomass that should be useful for cotton studies from remotely sensed data. The NDVI and the other spectral transformations were found useful to describe some phenological stages for a cotton canopy, because of the statistically significantly correlation with biophysical parameters such as LAI and biomass. Coefficients of determination (r2) for the various relationships ranged in statistically significant levels (0.82-0.96) with leaf area index and better estimation of biomass from vegetation indices by exponential equations. The results show that estimated crop values agree well with field observations and there is a potential in applying this approach on an operational basis in practice with multitemporal remote sensing data.