Estimation of leaf traits from reflectance measurements: comparison between methods based on vegetation indices and several versions of the PROSPECT model

Estimating leaf chlorophyll content in sugar beet canopies using millimeter- to centimeter-scale reflectance imagery

(2017) Sylvain Jay et al.   REMOTE SENSING OF ENVIRONMENT

Estimation of photosynthesis traits from leaf reflectance spectra: Correlation to nitrogen content as the dominant mechanism

(2017) Benjamin Dechant et al.   REMOTE SENSING OF ENVIRONMENT

PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle

(2017) J.-B. Féret et al.   REMOTE SENSING OF ENVIRONMENT

Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest

(2016) Abebe Mohammed Ali et al.   International Journal of Applied Earth Observation and Geoinformation

Quantifying the influences of spectral resolution on uncertainty in leaf trait estimates through a Bayesian approach to RTM inversion

(2016) Alexey N. Shiklomanov et al.   REMOTE SENSING OF ENVIRONMENT

ACT: A leaf BRDF model taking into account the azimuthal anisotropy of monocotyledonous leaf surface

(2014) Alexis Comar et al.   REMOTE SENSING OF ENVIRONMENT

Evaluation of three proposed indices for the retrieval of leaf water content from the mid-wave infrared (2–6μm) spectra

(2013) Saleem Ullah et al.   AGRICULTURAL AND FOREST METEOROLOGY

A Review of Methods for Sensing the Nitrogen Status in Plants: Advantages, Disadvantages and Recent Advances

(2013) Rafael Muñoz-Huerta et al.   SENSORS

Advanced phenotyping offers opportunities for improved breeding of forage and turf species

(2012) Achim Walter et al.   ANNALS OF BOTANY

A semi-automatic system for high throughput phenotyping wheat cultivars in-field conditions: description and first results

(2012) Alexis Comar et al.   FUNCTIONAL PLANT BIOLOGY

A new optical leaf-clip meter for simultaneous non-destructive assessment of leaf chlorophyll and epidermal flavonoids

(2012) Zoran G. Cerovic et al.   PHYSIOLOGIA PLANTARUM

Wheat leaf bidirectional reflectance measurements: Description and quantification of the volume, specular and hot-spot scattering features

(2012) A. Comar et al.   REMOTE SENSING OF ENVIRONMENT

Retrieval of Leaf Biochemical Parameters Using PROSPECT Inversion: A New Approach for Alleviating Ill-Posed Problems

(2011) Pingheng Li et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Estimating dry matter content from spectral reflectance for green leaves of different species

(2011) Lingli Wang et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling

(2011) Jean-Baptiste Féret et al.   REMOTE SENSING OF ENVIRONMENT

Phenomics – technologies to relieve the phenotyping bottleneck

(2011) Robert T. Furbank et al.   TRENDS IN PLANT SCIENCE

Three-dimensional appearance characterization of diffuse standard reflection materials

(2010) Andreas Höpe et al.   METROLOGIA

Leaf chemical and spectral diversity in Australian tropical forests

(2009) Gregory P. Asner et al.   ECOLOGICAL APPLICATIONS

A dorsiventral leaf radiative transfer model: Development, validation and improved model inversion techniques

(2009) Jan Stuckens et al.   REMOTE SENSING OF ENVIRONMENT

PROSPECT+SAIL models: A review of use for vegetation characterization

(2009) Stéphane Jacquemoud et al.   REMOTE SENSING OF ENVIRONMENT

Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass

(2008) G LEMAIRE et al.   REMOTE SENSING OF ENVIRONMENT

PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments

(2008) Jean-Baptiste Feret et al.   REMOTE SENSING OF ENVIRONMENT

Relations of remote sensing leaf water indices to leaf water thickness in cowpea, bean, and sugarbeet plants

(2007) H.-D. Seelig et al.   REMOTE SENSING OF ENVIRONMENT