Investigation of optimal vegetation indices for retrieval of leaf chlorophyll and leaf area index using enhanced learning algorithms

Optimization of dual-polarized bistatic specular scatterometer for studying microwave scattering response and vegetation growth parameters retrieval of paddy crop using a machine learning algorithm

(2020) Suraj A. Yadav et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems

(2016) Jadunandan Dash et al.   PROGRESS IN PHYSICAL GEOGRAPHY

Random Forests for Global and Regional Crop Yield Predictions

(2016) Jig Han Jeong et al.   PLoS One

A real-time plant discrimination system utilising discrete reflectance spectroscopy

(2015) P. Symonds et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression

(2013) Fei Li et al.   EUROPEAN JOURNAL OF AGRONOMY

Forcing a wheat crop model with LAI data to access agronomic variables: Evaluation of the impact of model and LAI uncertainties and comparison with an empirical approach

(2011) R. Casa et al.   EUROPEAN JOURNAL OF AGRONOMY

An assessment of the effectiveness of a random forest classifier for land-cover classification

(2011) V.F. Rodriguez-Galiano et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands

(2011) I. Herrmann et al.   REMOTE SENSING OF ENVIRONMENT

Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

(2011) Jochem Verrelst et al.   REMOTE SENSING OF ENVIRONMENT

Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at regional scales

(2009) Martha C. Anderson   Journal of Applied Remote Sensing

Estimating chlorophyll content from hyperspectral vegetation indices: Modeling and validation

(2008) Chaoyang Wu et al.   AGRICULTURAL AND FOREST METEOROLOGY