Assessment of Workflow Feature Selection on Forest LAI Prediction with Sentinel-2A MSI, Landsat 7 ETM+ and Landsat 8 OLI by Benjamin Brede, Jochem Verrelst, Jean-Philippe Gastellu-Etchegorry, Jan G. P. W. Clevers, Leo Goudzwaard, Jan den Ouden, Jan Verbesselt, Martin Herold

Subjects: Get full text

Estimating soil moisture content under grassland with hyperspectral data using radiative transfer modelling and machine learning by Veronika Döpper, Alby Duarte Rocha, Katja Berger, Tobias Gränzig, Jochem Verrelst, Birgit Kleinschmit, Michael Förster

Get full text

Estimation of leaf area index using PROSAIL based LUT inversion, MLRA-GPR and empirical models: Case study of tropical deciduous forest plantation, North India by Sanjiv K. Sinha, Hitendra Padalia, Anindita Dasgupta, Jochem Verrelst, Juan Pablo Rivera

Subjects: Get full text

Retrieval of Crop Variables from Proximal Multispectral UAV Image Data Using PROSAIL in Maize Canopy by Erekle Chakhvashvili, Bastian Siegmann, Onno Muller, Jochem Verrelst, Juliane Bendig, Thorsten Kraska, Uwe Rascher

Subjects: Get full text

Optimizing the Retrieval of Wheat Crop Traits from UAV-Borne Hyperspectral Image with Radiative Transfer Modelling Using Gaussian Process Regression by Rabi N. Sahoo, Shalini Gakhar, Rajan G. Rejith, Jochem Verrelst, Rajeev Ranjan, Tarun Kondraju, Mahesh C. Meena, Joydeep Mukherjee, Anchal Daas, Sudhir Kumar, Mahesh Kumar, Raju Dhandapani, Viswanathan Chinnusamy

Subjects: Get full text

Retrieval of aboveground crop nitrogen content with a hybrid machine learning method by Katja Berger, Jochem Verrelst, Jean-Baptiste Féret, Tobias Hank, Matthias Wocher, Wolfram Mauser, Gustau Camps-Valls

Subjects: Get full text

Estimating the phenological dynamics of irrigated rice leaf area index using the combination of PROSAIL and Gaussian Process Regression by Oluseun Adeluyi, Angela Harris, Jochem Verrelst, Timothy Foster, Gareth D. Clay

Subjects: Get full text

Multiple Cost Functions and Regularization Options for Improved Retrieval of Leaf Chlorophyll Content and LAI through Inversion of the PROSAIL Model by José Moreno, Ganna Leonenko, Juan Pablo Rivera, Jochem Verrelst

Subjects: Get full text

Gaussian Process Regression Hybrid Models for the Top-of-Atmosphere Retrieval of Vegetation Traits Applied to PRISMA and EnMAP Imagery by Ana B. Pascual-Venteo, Jose L. Garcia, Katja Berger, José Estévez, Jorge Vicent, Adrián Pérez-Suay, Shari Van Wittenberghe, Jochem Verrelst

Subjects: Get full text

Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling by Marina Ranghetti, Mirco Boschetti, Luigi Ranghetti, Giulia Tagliabue, Cinzia Panigada, Marco Gianinetto, Jochem Verrelst, Gabriele Candiani

Subjects: Get full text

Introducing ARTMO’s Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape by Masoumeh Aghababaei, Ataollah Ebrahimi, Ali Asghar Naghipour, Esmaeil Asadi, Adrián Pérez-Suay, Miguel Morata, Jose Luis Garcia, Juan Pablo Rivera Caicedo, Jochem Verrelst

Subjects: “…Automated Radiative Transfer Models Operator…”
Get full text

Deciphering maize vertical leaf area profiles by fusing spectral imagery data and a bell-shaped function by Jinpeng Cheng, Shaoyu Han, Jochem Verrelst, Chunjiang Zhao, Na Zhang, Yu Zhao, Lei Lei, Han Wang, Guijun Yang, Hao Yang

Subjects: Get full text

Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission by Gabriele Candiani, Giulia Tagliabue, Cinzia Panigada, Jochem Verrelst, Valentina Picchi, Juan Pablo Rivera Caicedo, Mirco Boschetti

Subjects: Get full text

A comprehensive survey on quantifying non-photosynthetic vegetation cover and biomass from imaging spectroscopy by Jochem Verrelst, Andrej Halabuk, Clement Atzberger, Tobias Hank, Stefanie Steinhauser, Katja Berger

“…Given three decades of spectroscopy studies on NPV or CR cover detection, we identify the following methodological trends: (1) a shift from unmixing approaches towards regression-based models; (2) a shift from two-band indices towards multi-band equations; and (3) a shift from linear regression towards data-driven machine learning models. (4) In addition, gradual progress in radiative transfer modelling (RTM) in describing the interaction of radiation with non-photosynthetic plant material has been achieved. …”
Get full text

A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data by Katja Berger, Juan Pablo Rivera Caicedo, Luca Martino, Matthias Wocher, Tobias Hank, Jochem Verrelst

“…Intelligent sampling through active learning (AL) heuristics provides a pathway for fast inference of essential vegetation variables by means of hybrid retrieval approaches, i.e., machine learning regression algorithms trained by radiative transfer model (RTM) simulations. In this study we summarize AL theory and perform a brief systematic literature survey about AL heuristics used in the context of Earth observation regression problems over terrestrial targets. …”
Get full text

Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine by Pablo Reyes-Muñoz, Luca Pipia, Matías Salinero-Delgado, Santiago Belda, Katja Berger, José Estévez, Miguel Morata, Juan Pablo Rivera-Caicedo, Jochem Verrelst

“…The workflow involved Gaussian process regression (GPR) algorithms trained on top-of-atmosphere (TOA) radiance simulations generated by the coupled canopy radiative transfer model (RTM) SCOPE and the atmospheric RTM 6SV. …”
Get full text

Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data by Ana B. Pascual-Venteo, Enrique Portalés, Katja Berger, Giulia Tagliabue, Jose L. Garcia, Adrián Pérez-Suay, Juan Pablo Rivera-Caicedo, Jochem Verrelst

“…Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. …”
Get full text