Variabilità spaziale e temporale di parametri applicati alla Precision Farming in risicoltura

Measuring plant biophysical parameters at the field scale can be expensive and time consuming as large amount of sample points and measurements to estimate spatial and temporal variability are necessary. Vegetation indices from remote and proximal sensing could be used to estimate variables linked to canopy properties. Particularly, vegetation indices (VI) from remote sensing provide spatio-temporal information on the entire field canopy variability, overcoming the limitations of sampling field investigation. The development of dedicated algorithms makes the spectral indices computation analysis rather quick. Nowadays, the development of vegetation indices and their application is one of the most important topics in precision agriculture.The objective of this research was to assess the spatial variability of Leaf Area Index (LAI) and plant nitrogen content in paddy rice through remote and proximal sensing imagery analysis in Sardinia. In 2010 and 2011 field measurements of LAI, chlorophyll content and Nitrogen canopy content were taken at 36 sample point locations. At the same points spectral canopy signature was measured with a portable hyperspectral radiometer (ASD, FieldSpec) and a time series of satellite images from RapidEye. Various vegetation indices were adopted to estimate LAI and N plant content.