Close-range hyperspectral spectroscopy reveals leaf water content dynamics

Towards Estimating Leaf Water Content through Hyperspectral Data

Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging

Automated collection of large scale plant phenotype datasets using high throughput imaging systems has the potential to alleviate current bottlenecks in data-driven plant breeding and crop improvement. In this study, we demonstrate the characterization of temporal dynamics of plant growth and water use, and leaf water content of two maize genotypes under two different water treatments. RGB (Red...

A physically-based model for retrieving foliar biochemistry and leaf orientation using close-range imaging spectroscopy

Article history: Received 12 October 2015 Received in revised form 21 January 2016 Accepted 12 February 2016 Available online 1 March 2016 Radiative transfer models have long been used to characterize the foliar content at the leaf and canopy levels. However, they still do not apply well to close-range imaging spectroscopy, especially because directional effects are usually not taken into accou...

Water stress of sugarbeet as related to leaf and canopy temperatures and to leaf Water content

Mapping forest leaf dry matter content from hyperspectral data Abebe

Leaf dry matter content (LDMC) is a central vegetation property that plays an important role in assessments of ecosystem functions. In this study, LDMC was estimated from hyperspectral airborne image by inversion of the INFORM radiative transfer model using Continuous Wavelet Analysis (CWA). Stand parameters were collected for 33 sample plots during a field campaign in July 2013 in the Bavarian...