Leaf area index (LAI) is a critical vegetation structural variable and is essential in the
feedback of vegetation to the climate system. The advancement of the global Earth …

An unprecedented spectroscopic data stream will soon become available with forthcoming
Earth-observing satellite missions equipped with imaging spectroradiometers. This data …

Empirical vegetation indices derived from spectral reflectance data are widely used in
remote sensing of the biosphere, as they represent robust proxies for canopy structure, leaf …

Vegetation indices computed from spectral signatures are vastly used for monitoring the
terrestrial biosphere. Indices are convenient proxies for canopy structure, and leaf pigment …

This paper reviews advanced Neural Network (NN) techniques available to process
hyperspectral data, with a special emphasis on plant disease detection. Firstly, we provide a …

Forthcoming superspectral satellite missions dedicated to land monitoring, as well as
planned imaging spectrometers, will unleash an unprecedented data stream. The …

Upcoming satellite hyperspectral sensors require powerful and robust methodologies for
making optimum use of the rich spectral data. This paper reviews the widely applied coupled …

Leaf area index (LAI) is an important indicator of crop growth. In this paper, a hybrid
inversion method was developed to estimate the LAI values of crops. Based on PROSAIL …

Hyperspectral data (Table 1) is acquired as continuous narrowbands (eg, each band with 1
to 10 nanometer or nm bandwidths) over a range of electromagnetic spectrum (eg, 400 …

High-throughput, noninvasive field phenoty** has revealed genetic variation in crop
morphological, developmental, and agronomic traits, but rapid measurements of the …