Prediction of leaf nitrogen in sugarcane ( spp.) by Vis-NIR-SWIR spectroradiometry.

Nitrogen is one of the essential nutrients for the production of agricultural crops, participating in a complex interaction among soil, plant and the atmosphere. Therefore, its monitoring is important both economically and environmentally. The aim of this work was to estimate the leaf nitrogen contents in sugarcane from hyperspectral reflectance data during different vegetative stages of the plant.

A Novel Method for Estimating Chlorophyll and Carotenoid Concentrations in Leaves: A Two Hyperspectral Sensor Approach.

Leaf optical properties can be used to identify environmental conditions, the effect of light intensities, plant hormone levels, pigment concentrations, and cellular structures. However, the reflectance factors can affect the accuracy of predictions for chlorophyll and carotenoid concentrations. In this study, we tested the hypothesis that technology using two hyperspectral sensors for both reflectance and absorbance data would result in more accurate predictions of absorbance spectra.

Genesis and properties of wetland soils by VIS-NIR-SWIR as a technique for environmental monitoring.

Wetlands are important ecosystems characterized by redoximorphic environments producing typical soil forming processes and organic carbon accumulation. Assessments and management of these areas are dependent on knowledge about soil characteristics and variability. By reflectance spectroscopy, information about soils can be obtained since their spectral behaviors are directly related to their chemical, physical, and mineralogical properties reflecting the pedogenetic processes and environment conditions.