Quantifying vegetation biophysical variables from imaging spectroscopy data: A review on retrieval methods

J Verrelst, Z Malenovský, C Van der Tol… - Surveys in …, 2019 - Springer
An unprecedented spectroscopic data stream will soon become available with forthcoming
Earth-observing satellite missions equipped with imaging spectroradiometers. This data …

Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties–A review

J Verrelst, G Camps-Valls, J Muñoz-Marí… - ISPRS Journal of …, 2015 - Elsevier
Forthcoming superspectral satellite missions dedicated to land monitoring, as well as
planned imaging spectrometers, will unleash an unprecedented data stream. The …

Transfer-learning-based approach for leaf chlorophyll content estimation of winter wheat from hyperspectral data

Y Zhang, J Hui, Q Qin, Y Sun, T Zhang, H Sun… - Remote Sensing of …, 2021 - Elsevier
Leaf chlorophyll, as a key factor for carbon circulation in the ecosystem, is significant for the
photosynthetic productivity estimation and crop growth monitoring in agricultural …

Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images

E Raczko, B Zagajewski - European Journal of Remote Sensing, 2017 - Taylor & Francis
Knowledge of tree species composition in a forest is an important topic in forest
management. Accurate tree species maps allow for much more detailed and in-depth …

PROSPECT-PRO for estimating content of nitrogen-containing leaf proteins and other carbon-based constituents

JB Féret, K Berger, F De Boissieu… - Remote Sensing of …, 2021 - Elsevier
Abstract Models of radiative transfer (RT) are important tools for remote sensing of
vegetation, allowing for forward simulations of remotely sensed data as well as inverse …

An overview of crop nitrogen status assessment using hyperspectral remote sensing: Current status and perspectives

Y Fu, G Yang, R Pu, Z Li, H Li, X Xu, X Song… - European Journal of …, 2021 - Elsevier
Nitrogen (N) is significantly related to crop photosynthetic capacity. Over-and-under-
application of N fertilizers not only limits crop productivity but also leads to negative …

Understanding forest health with remote sensing-part I—a review of spectral traits, processes and remote-sensing characteristics

A Lausch, S Erasmi, DJ King, P Magdon, M Heurich - Remote Sensing, 2016 - mdpi.com
Anthropogenic stress and disturbance of forest ecosystems (FES) has been increasing at all
scales from local to global. In rapidly changing environments, in-situ terrestrial FES …

Combining transfer learning and hyperspectral reflectance analysis to assess leaf nitrogen concentration across different plant species datasets

L Wan, W Zhou, Y He, TC Wanger, H Cen - Remote Sensing of …, 2022 - Elsevier
Accurate estimation of leaf nitrogen concentration (LNC) is critical to characterize ecosystem
and plant physiological processes for example in carbon fixation. Remote sensing can …

Exploiting the centimeter resolution of UAV multispectral imagery to improve remote-sensing estimates of canopy structure and biochemistry in sugar beet crops

S Jay, F Baret, D Dutartre, G Malatesta, S Héno… - Remote Sensing of …, 2019 - Elsevier
The recent emergence of unmanned aerial vehicles (UAV) has opened a new horizon in
vegetation remote sensing, especially for agricultural applications. However, the benefits of …

Ensemble machine-learning-based framework for estimating total nitrogen concentration in water using drone-borne hyperspectral imagery of emergent plants: A case …

J Wang, T Shi, D Yu, D Teng, X Ge, Z Zhang… - Environmental …, 2020 - Elsevier
In arid and semi-arid regions, water-quality problems are crucial to local social demand and
human well-being. However, the conventional remote sensing-based direct detection of …