Papers

ARTMO:

• Verrelst, J., Romijn, E., Kooistra, L. (2012). Mapping vegetation structure in a heterogeneous river floodplain ecosystem using pointable CHRIS/PROBA data. Remote Sensing, 4(9), p. 2866-2889. 
• Verrelst, J., Rivera, J.P. Veroustraete, F., Muñoz-Marí, J., Clevers, J.G.P.W., Camps-Valls, G., Moreno, J. (2015). Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods – A comparison. ISPRS Journal of Photogrammetry and Remote Sensing, 108, p. 260-272. 
• Verrelst, J., Camps-Valls, G., Muñoz-Marí, J., Rivera, J.P. Veroustraete, F., Clevers, J.G.P.W., Moreno, J. (2015). Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties – A review. ISPRS Journal of Photogrammetry and Remote Sensing, 108, p. 273-290. 
• Verrelst, J., Malenovský, Z., Van der Tol, C., Camps-Valls, G., Gastellu-Etchegory, J.P., Lewis, P., Moreno, J. (2019). Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods. Surveys in Geophysics, 40(3), pp. 589-629  

Spectral Indices toolbox:

• Rivera, J.P., Verrelst, J., Delegido, J., Veroustraete, F., Moreno, J. (2014). On the Semi-automatic Retrieval of Biophysical Parameters based on Spectral Index Optimization. Remote Sensing, 6(6), p. 4924-4951.
• Delegido, J., Verrelst, J., Rivera, J.P.,  Ruiz-Verdú, A., Moreno, J. (2015). Brown and green LAI mapping through spectral indices. International Journal of Applied Earth Observation and Geoinformation, 35, p. 350-358.

Machine learning regression algorithms (MLRA) toolbox:

• Rivera, J.P., Verrelst, J., Muñoz-Marí J., Moreno, J. and Camps-Valls, G. (2014). Toward a semiautomatic machine learning retrieval of biophysical parameters. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing,7 (4), p. 1249-1259.
•  Van Wittenberghe, S., Verrelst, J., Rivera, J.P., Alonso, L., Moreno, J., Samson, R. (2014).  Gaussian processes retrieval of leaf parameters from a multi-species reflectance, absorbance and fluorescence dataset. Journal of Photochemistry and Photobiology B: Biolgoy, 134, p. 37-48.
• Okujeni, A., van der Linden, S., Jakimow, B., Rabe., A., Verrelst, J., Hostert, P., (2014). A comparison of advanced regression algorithms for quantifying urban land cover. Remote Sensing, 6(7). p. 6324-6346. 
• Lázaro-Gredilla, M., Titsias, M.K., Verrelst, J., Camps-Valls, G. (2014). Retrieval of Biophysical Parameters with Heteroscedastic Gaussian Processes. IEEE Geoscience and Remote Sensing Letters, 11(4). p. 838-842. 
• Verrelst, J., Rivera, J.P. Moreno, J., Camps-Valls, G., (2013). Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval. ISPRS Journal of Photogrammetry and Remote Sensing, 86, p. 157-167. 
• Verrelst J., Rivera, J.P., Gitelson, A., Delegido, J., Moreno, J., Camps-Valls, G., (2016). Spectral band selection for vegetation properties retrieval using Gaussian processes regression. International Journal of Applied Earth Observation and Geoinformation, 52, p. 554-567. 
• Rivera, J.P., Verrelst, J., Muñoz-Marí J., Camps-Valls, G., Moreno, J.  (2017). Hypersectral dimenstionality reduction for biophysical variable statistical retrieval. ISPRS Journal of Photogrammetry and Remote Sensing, 132, p. 88-101. 
• Verrelst, J., Rivera-Caicedo, J.P., Reyes-Muñoz, P., Morata, M., Amin, E., Tagliabue, G., Panigada, C., Hank, T., Berger, K.  (2021).  Mapping landscape canopy nitrogen content from space using PRISMA data. ISPRS Journal of Photogrammetry and Remote Sensing, 178, p. 382-395. 
• Salinero-Delgado, M.; Estévez, J.; Pipia, L.; Belda, S.; Berger, K.; Paredes Gómez, V.; Verrelst, J. Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression. Remote Sens. 2022, 14, 146.
• Ayala Izurieta, J.E., Jara Santillán, C.A., Márquez, C.O. et al. Improving the remote estimation of soil organic carbon in complex ecosystems with Sentinel-2 and GIS using Gaussian processes regression. Plant Soil (2022).
• Caballero, G.; Pezzola, A.; Winschel, C.; Casella, A.; Sanchez Angonova, P.; Rivera-Caicedo, J.P.; Berger, K.; Verrelst, J.; Delegido, J. Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery. Remote Sens. 2022, 14, 4531. 
• Reyes-Muñoz, P., Kovács, D. D., Berger, K., Pipia, L., Belda, S., Rivera-Caicedo, J. P., & Verrelst, J. (2024). Inferring global terrestrial carbon fluxes from the synergy of Sentinel 3 & 5P with Gaussian process hybrid models. Remote Sensing of Environment, 305, 114072. 
• García-Soria, J. L., Morata, M., Berger, K., Pascual-Venteo, A. B., Rivera-Caicedo, J. P., & Verrelst, J. (2024). Evaluating epistemic uncertainty estimation strategies in vegetation trait retrieval using hybrid models and imaging spectroscopy data. Remote Sensing of Environment, 310, 114228. 

Active learning:

• Verrelst J., Dethier, S., Rivera, J.P., Munoz-Mari, J., Camps-Valls, G., Moreno, J.  (2016). Active learning methods for efficient hybrid biophysical variable retrieval. IEEE Geoscience and Remote Sensing Letters, 13, p. 1012-1016. 
• Verrelst, J., Berger, K., Rivera-Caicedo, J.P., (2020). Intelligent Sampling for Vegetation Nitrogen Mapping Based on Hybrid Machine Learning Algorithms . IEEE Geoscience and Remote Sensing Letters,. 
• Berger, K., Rivera Caicedo, J.P., Martino, L., Wocher, M., Hank, T., Verrelst, J. (2021). A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data. Remote Sensing.  13(2):287. 
• Berger, K.; Hank, T.; Halabuk, A.; Rivera-Caicedo, J.P.; Wocher, M.; Mojses, M.; Gerhátová, K.; Tagliabue, G.; Dolz, M.M.; Venteo, A.B.P.; Verrelst, J. (2021). Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery. Remote Sensing. 13(22):4711. 
• Binh, N.; Hauser,L.; Hoa, P.; Thao,G.; An, N.; hut, H.; Phuong, T.; Verrelst, J. (2022). Quantifying mangrove leaf area index from Sentinel-2 imagery using hybrid models and active learning. International Journal of Remote Sensing. 
• Candiani, G.; Tagliabue, G.; Panigada, C.; Verrelst, J.; Picchi, V.; Rivera Caicedo, J.P.; Boschetti, M. (2022). Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission. Remote Sensing. 14:1792. 
• Pascual-Venteo, A. B., Portalés, E., Berger, K., Tagliabue, G., Garcia, J. L., Pérez-Suay, A., ... & Verrelst, J. (2022). Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data. Remote Sensing, 14(10), 2448.
• Wocher, M., Berger, K., Verrelst, J., & Hank, T. (2022). Retrieval of carbon content and biomass from hyperspectral imagery over cultivated areas. ISPRS Journal of Photogrammetry and Remote Sensing, 193, 104-114.
• Sahoo, R.N.; Gakhar, S.; Rejith, R.G.; Verrelst, J.; Ranjan, R.; Kondraju, T.; Meena, M.C.; Mukherjee, J.; Daas, A.; Kumar, S.; et al. Optimizing the Retrieval of Wheat Crop Traits from UAV-Borne Hyperspectral Image with Radiative Transfer Modelling Using Gaussian Process Regression. Remote Sens. 2023, 15, 5496.
• Jia, M., Guo, X., Zhang, L., Wang, M., Wang, W., Lu, C., ... & Verrelst, J. Mapping Mangrove Functional Traits From Sentinel-2 Imagery Based on Hybrid Models Coupling with Active Learning Strategies. International Journal of Applied Earth Observation and Geoinformation, 2024, 130, 103905.

LUT-based inversion toolbox:

• Rivera, J.P., Verrelst, J., Leoneko, G., Moreno, J. (2013). Multiple cost functions and regularization options for improved retrieval of leaf chlorophyll content and LAI through inversion of the PROSAIL model. Remote Sensing, 5(7), p. 3280-3304. 
• Verrelst, J., Rivera, J.P., Leoneko, G., Alonso, L., Moreno, J. (2014). Optimizing LUT-based RTM Inversion for Semiautomatic Mapping of Crop Biophysical Parameters from Sentinel-2 and -3 data: Role of Cost Functions. IEEE Transactions on Geoscience and Remote Sensing, 52(1), p. 257-269. 
• Chakhvashvili, E.; Siegmann, B.; Muller, O.; Verrelst, J.; Bendig, J.; Kraska, T.; Rascher, U. (2022). Retrieval of Crop Variables from Proximal Multispectral UAV Image Data Using PROSAIL in Maize Canopy. Remote Sensing, 514, 1247. 

Machine learning classification algorithms (MLCA) toolbox:

• ghababaei, M.; Ebrahimi, A.; Naghipour, A.A.; Asadi, E.; Pérez-Suay, A.; Morata, M.; Garcia, J.L.; Rivera Caicedo, J.P.; Verrelst, J. (2022) Introducing ARTMO’s Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape. Remote Sensing, 14, 4452
• Reis Pereira, M.; Verrelst, J.; Tosin, R.; Rivera Caicedo, J.P.; Tavares, F.; Neves dos Santos, F.; Cunha, M. Plant Disease Diagnosis Based on Hyperspectral Sensing: Comparative Analysis of Parametric Spectral Vegetation Indices and Nonparametric Gaussian Process Classification Approaches. Agronomy 2024, 14, 493. 

Global Sensitivity Analysis (GSA) toolbox: 

• Verrelst, J., Rivera, J.P., Moreno, J. (2015). ARTMO's global sensitivity analysis (GSA) toolbox to quantify driving variables of leaf and canopy radiative transfer models. EARSeL eProceedings, Special Issue 2: 9^th EARSeL Imaging Spectroscopy Workshop, 2015. 1-11. 

• Verrelst, J., Rivera, J.P., van der Tol, C., Magnani, F., Mohammed, G., Moreno, J. (2015).  Global sensitivity analysis of the SCOPE model: What drives simulated canopy-leaving sun-induced fluorescence? Remote Sensing of Environment, 166, 8-21.

• Morcillo-Pallarés, P., Rivera-Caicedo, J.P., Belda, S., De Grave, C., Burriel, H., Moreno, J., Verrelst, J. (2019).  Quantifying the Robustness of Vegetation Indices through Global Sensitivity Analysis of Homogeneous and Forest Leaf-Canopy Radiative Transfer Models. Remote Sensing, 11(20). 

Emulator toolbox:

• Rivera, J.P., Verrelst, J., Gómez-Dans, J., Muñoz-Marí, J., Moreno, J., Camps-Valls, G. (2015). An Emulator Toolbox to Approximate Radiative Transfer Models with Statistical Learning. Remote Sensing. p. 7, 9347-9370. 
• Verrelst, J., Sabater, N., Rivera, J.P., Muñoz-Marí, J., Vicent, J., Camps-Valls, G., Moreno, J. (2016). Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis. Remote Sensing. 8(8), 673. 
• Verrelst, J., Rivera Caicedo, J.P., Muñoz-Marí, J., Camps-Valls, G., Moreno, J. (2017). SCOPE-Based Emulators for Fast Generation of Synthetic Canopy Reflectance and Sun-Induced Fluorescence Spectra. Remote Sensing. 9(9), 927. 
• Vicent, J., Verrelst, J., Rivera Caicedo, J.P., Sabater, N., Muñoz-Marí, J., Camps-Valls, G., Moreno, J. (2018). Emulation as an Accurate Alternative to Interpolation in Sampling Radiative Transfer Codes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.  
• Verrelst, J., Rivera Caicedo, J.P., Vicent, J., Morcillo-Pallarés, P., Moreno, J. (2019). Approximating Empirical Reflectance Data through Emulation: Opportunities for Synethetic Scene Generation. Remote Sensing. 11(2): 157.  
• Vicent, J., Rivera-Caicedo, J.P., Verrelst, J., Muñoz-Marí, J., Sabater, N. , Berthelot, B., Camps-Valls, G., Moreno, J. (2021). Systematic Assessment of MODTRAN Emulators for Atmospheric Correction. IEEE Transactions on Geoscience and Remote Sensing.  
• Morata, M.; Siegmann, B.; Morcillo-Pallarés, P.; Rivera-Caicedo, J.P.; Verrelst, J. (2021). Emulation of Sun-Induced Fluorescence from Radiance Data Recorded by the HyPlant Airborne Imaging Spectrometer. Remote Sensing. 13 (21), 4368.
• Morata, M.; Siegmann, B.; Pérez-Suay A.; García-Soria, J. L.; Rivera-Caicedo, J. P. ; Verrelst, J. Neural Network Emulation of Synthetic Hyperspectral Sentinel-2-like Imagery with Uncertainty. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi: 10.1109/JSTARS.2022.3231380. 

Atmospheric LUT Generator (ALG) toolbox:

• Vicent, J., Sabater, N., Verrelst, J., Alonso, L., & Moreno, J. (2017). Assessment of approximations in aerosol optical properties and vertical distribution into FLEX atmospherically-corrected surface reflectance and retrieved sun-induced fluorescence. Remote Sensing. 9(7), 675. 
• Vicent, J., Verrelst, J., Sabater, N., Alonso, L., Rivera Caicedo, J.P., Martino, L., Muñoz-Mari, J. & Moreno, J. (2020). Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0). Geoscientific Model Development. 13, 1945–1957
• Vicent, J., Martino, L., Verrelst, J., & Camps-Valls, G. (2023). Multi-fidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models. IEEE Transactions on Geoscience and Remote Sensing.

TOC2TOA:

•  Verrelst, J., Vicent, J., Rivera Caicedo, J.P., Lumbierres, M., Morcillo Pallarés, P., & Moreno, J. (2019). Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data. Remote Sensing. 11(6), 1923. 
•  Estévez, J., Vicent, J., Rivera Caicedo, J.P., Morcillo Pallarés, P., Vuolo, F., Sabater, N., Camps-Valls, G., Moreno, J. Verrelst, J. (2020). Gaussian processes retrieval of LAI from Sentinel-2 top-of-atmosphere data. ISPRS Journal of Photogrammetry and Remote Sensing. 167, 289-304. 
•  Estévez, J., Berger, K., Vicent, J., Rivera-Caicedo. J.P., Wocher, M., Verrelst, J. (2021). Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow. Remote Sensing. 13(8), 1589. 
•  Estévez, J.; Salinero-Delgado, M.; Berger, K.; Pipia, L.; Rivera-Caicedo, J.P.; Wocher, M.; Reyes-Muñoz, P.; Tagliabue, G.; Boschetti, M.; Verrelst, J. (2022). Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data. Remote Sensing of Environment. 273, 112958. 
• Reyes-Muñoz, P.; Pipia, L.; Salinero-Delgado, M.; Belda, S.; Berger, K.; Estévez, J.; Morata, M.; Rivera-Caicedo, J.P.; Verrelst, J. (2022). Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine. Remote Sensing. 14, 1347. 
• Pascual-Venteo, A.B.; Garcia, J.L.; Berger, K.; Estévez, J.; Vicent, J.; Pérez-Suay, A.; Van Wittenberghe, S.; Verrelst, J. (2024) Gaussian Process Regression Hybrid Models for the Top-of-Atmosphere Retrieval of Vegetation Traits Applied to PRISMA and EnMAP Imagery.  Remote Sensing, 16, 1211.

SCOPE:

• Verrelst, J., Rivera, J.P., van der Tol, C., Magnani, F., Mohammed, G., Moreno, J. (2016).  Evaluating the predictive power of sun-induced chlorophyll fluorescence to estimate net photosynthesis of vegetation canopies: A SCOPE modeling study. Remote Sensing of Environment, 176, 139-151. 

DATimeS:

• Belda, S., Pipia, L., Morcillo-Pallarés, P., Rivera-Caicedo, J. P., Amin, E., de Grave, C., Verrelst, J. (2020).  DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection. Environmental Modelling & Software, 127. 
• Belda, S., Pipia, L., Morcillo-Pallarés, P., Verrelst, J. (2020).  Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring. Agronomy, 10(5), 618. 
• Amin, E.; Belda, S.; Pipia, L.; Szantoi, Z.; El Baroudy, A.; Moreno, J.; Verrelst, J. (2022).  Multi-Season Phenology Mapping of Nile Delta Croplands Using Time Series of Sentinel-2 and Landsat 8 Green LAI. Remote Sensing, 14(8), 1812. 

Other ARTMO contributions:

1. Verrelst J. and co-authors, (2021). Progress in hybrid models for applications in remote sensing of vegetation, 40th EARSeL Symposium, 7-10 June, Warsaw, Poland, webinar. (presentation)
2. Verrelst J. and co-authors, (2020). Development of vegetation traits models using hybrid retrieval workflows in the context of the CHIME mission preparation, SBG (Surface Biology and Geology) Algorithms working group, 21 December, webinar. (presentation)
3. De Grave C., Verrelst, J., Pipia, L., Siegman, B., Reyes, P., Morcillo, P., Rivera, J.P., Rascher, U, Moreno, J. (2020). Use of the SYN product for estimating key vegetation variables within the context of FLEX, 6th S3VT, 15-17 December, virtual meeting. (presentation)
4. Vicent, J., Sabater, N., Alonso, L., Verrelst, J., Martino, L., Berthelot, B., Moreno, J. (2020). Comparative analysis of atmospheric RTMs using the Atmospheric Look-up table Generator (ALG) toolbox. In: Atelier TRATTORIA 2020, Toulouse, France. (poster)
5. Verrelst, J., Johnson, E.,  Morcillo Pallarés, P., Vicent, J., Rivera-Caicedo, J.P., Camps-Valls, G. (2019). Emulation for Approximating Radiative Transfer Modeling: Computational Efficiency and Sensitivity Analysis. In: ESA's Phi-week, 9-13 September, 2019, Frascati, Italy. (poster)
6. Verrelst, J., de Grave, C., Amin, E.,  Rivera-Caicedo, J.P.,  Morcillo Pallarés, P., Pipia, L., Belda, S., Moreno, J. (2019). Prototyping FLEX FLORIS and Sentinel-3 OLCI Vegetation Products in Support of Forthcoming FLEX Photosynthesis Estimates. In: ESA's Living Planet Symposium 2019, 13-17 May, Milan, Italy. (presentation)
7. Verrelst, J., Alonso, L., Urego, P., Belda, S., Morcillo Pallarés, P., Rivera-Caicedo, J.P.,  Moreno, J. (2019). WorldView Biophysical Variables Retrieval over Antwerp and Valencia. In: HTYPERCITY final meeting, 25 March, Antwerp, Belgium (presentation)
8. Verrelst, J., Rivera-Caicedo, J.P., Vicent, J., Morcillo Pallarés, P., Esévez, J., Moreno, J. (2019). TOC2TOA: An ARTMO toolbox to simulate top-of-atmosphere radiance data for imaging spectroscopy applications. In: 11th EARSeL Imaing Spectroscopy Workshop, 06-8 February, Brno, Czech Republic. (presentation)
9. Verrelst, J., Rivera, J.P.,  Moreno, J. (2018). Progress in emulation for radiative transfer modeling and mapping. In: IGARSS2018 , 22-27 July, Valencia, Spain. (presentation)
10. Verrelst, J., Rivera, J.P.,  Vicent, J.,  Moreno, J. (2018). Approximating experimental vegetation spectrscopy data through emulation. In: IGARSS2018 , 22-27 July, Valencia, Spain. (presentation)
11. Verrelst, J., Rivera, J.P.,  Gitelson, A., Delegido, J., Van Wittenberghe, S.,  Moreno, J. , Camps-Valls, J., (2017). Automated spectral band selection for optimized vegetation properties retrieval using Gaussian processes regression. In: 10th EARSeL Imaging Spectroscopy Workshop , 19-21 April, Zurich, Switzerland. (presentation)
12. Verrelst, J., Sabater, N., Rivera, J.P.,  Muñoz, J., Vicent, J., Moreno, J. , Camps-Valls, J., (2017). Emulation of radiative transfer models: new opportunities for spectroscopy data processing. In: 10th EARSeL Imaging Spectroscopy Workshop, 19-21 April, Zurich, Switzerland. (presentation)
13. Verrelst, J., Rivera, J.P., Moreno, J.  (2017). Emulation of radiative transfer models. In: Annual OPTIMIZE Workshop and MC Meeting, 22-23 February, Limassol, Cyprus. (presentation)
14. Verrelst, J., Rivera, J.P., Moreno, J.  (2017). Speeding up the simulation of vegetation fluorescence through emulation: Practical applications for FLEX data processing. In: Remote Sensing of Fluoresence, Photosynthesis and Vegetation Status, 17-19 January, ESA-ESRIN, Frascati, Italy. (presentation)
15. Verrelst, J., Rivera, J.P.,  Sanchis-Muñoz, J., Pereira-Sendoval, M. , Delegido, J., Moreno, J.  (2017). ARTMO retrieval toolboxes for optimized and automated vegetation properties mapping from Senintel-2 data. In: Remote Sensing of Fluoresence, Photosynthesis and Vegetation Status, 17-19 January, ESA-ESRIN, Frascati, Italy. (poster)
16. Verrelst, J., Rivera, J.P.,  Moreno, J.  (2016). From model simulations towards vegetation properties mapping: automating, optimizing & simplifying. In: ISSI Workshop on Exploring the Earth's Ecostystems on a Global Scale: Requirements, Capabilities and Directions in Spaceborne Imaging Spectroscopy, 21-25 November, Bern, Switzerland. (presentation)
17. Verrelst, J., Rivera, J.P.,  Moreno, J.  (2016). From SAIL simulations towards automated remote sensing applications: an overview of 6 years of ARTMO developments. In: SAIL35 Symposium, 27-28 September 2016, Enschede, The Netherlands. (abstract & presentation)
18. Verrelst, J., Van der Tol, C., Magnani, F., Rivera, J.P., Mohammed, G., Moreno, J. (2015). Estimating net photosynthesis of vegetation from solar-induced chlorophyll fluorescence - A modelling study. In: IGARSS 2015, 26-31 July, Milan, Italy. (poster & proceedings)
19. Verrelst, J., Rivera, J.P., Gómez-Dans, J., Camps-Valls, G., Moreno, J. (2015). Replacing radiative transfer models by surrogate approximations through machine learning. In: IGARSS 2015, 26-31 July, Milan, Italy. (poster & proceedings)
20. Verrelst, J., Rivera, J.P., Moreno, J. (2015). ARTMO's global sensitivity analysis (GSA) toolbox to quantify driving variables of leaf and canopy radiative transfer models. In: 9th EARSEL SIG Imaging Spectroscopy Workshop, 14-16 April, Luxembourg. (presentation)
21. Verrelst, J., Rivera, J.P.,Van Der Tol, C., Magnani F., Mohammed, G., Moreno, J. (2015). On the relationships between solar-induced fluorescence and net photosynthesis of the canopy: a SCOPE modeling study. In: 9th EARSEL SIG Imaging Spectroscopy Workshop, 14-16 April, Luxembourg. (presentation)
22. Verrelst, J., Rivera, J.P., Camps-Valls, G., Moreno, J.  (2014). ARTMO's retrieval toolboxes for optimizing parametric, non-parametric and physically-based biophysical variable mapping. In: Recent Advances of Quantitative Remote Sensing (RAQRS)-IV, 22-26 September 2014, Valencia, Spain. (abstract & poster)
23.  Verrelst, J., Rivera, J.P., Camps-Valls, G., Moreno, J.  (2013). Recent advances in Biophysical Parameter Retrieval Methods - Opportunities for Sentinel-2 . In: ESA Living Planet Symposium 2013, 09-13 September, Edinburgh, UK. (abstract & poster)

24. Rivera, J.P., Verrelst, J.,  Leonenko, G., Moreno, J. (2013). Evaluación de múltiples funciones de mérito en la inversión de parámetros biofísicos a través del modelo PROSAIL usando tablas de búsqueda. In: XV Congreso de la Asociación Española de Teledetección (AET) 2013, 22-24 October, Madrid, Spain. (paper & poster)

25. Rivera, J.P., Verrelst, J.,  Delegido, J., Moreno, J. (2013). Herramienta informática para el diseño y evaluación de índices espectrales genéricos para la inversión de parámetros biofísicos. In: XV Congreso de la Asociación Española de Teledetección (AET) 2013, 22-24 October, Madrid, Spain. (paper & presentation)

26. Verrelst, J., Rivera, J.P., Muñoz, J., Moreno, J. Camps-Valls, G. (2013). ARTMO’s new Machine Learning Regression Algorithm (MLRA) module for semiautomatic mapping of biophysical parameters. In: EARSeL 8th SIG-Imaging Spectroscopy Workshop 2013, 08-10 April, Nantes, France. (paper & presentation)

27. Verrelst, J., Rivera, J.P., Guadalarjara, A., Delegido, J., Moreno, J. (2013). ARTMO’s new Spectral Indices (SI) module to rapidly evaluate a multitude of SIs for mapping of biophysical parameters. In: EARSeL 8th SIG-Imaging Spectroscopy Workshop 2013, 08-10 April, Nantes, France. (paper & presentation)

28. Verrelst, J., Rivera, J.P., Leonenko, G., Alonso, L., Moreno, J. (2012). Optimizing LUT-based radiative transfer model inversion for retrieval of biophyiscal parameters using hyperspectral data. In: IGARSS 2012, 22-27 July, Munich Germany (paper & presentation).

29. Verrelst, J., Rivera, J.P., Leonenko, G., Alonso, L., Moreno, J. (2012). Using the ARTMO toolbox for automated retrieval of biophysical parameters through radiative transfer model inversion: Optimizing LUT-based inversion. In: EGU General Assembly 2012, 22-27 April, Vienna, Austria. (poster)

30. Verrelst, J., Rivera, J.P., Leonenko, G., Alonso, L., Moreno, J. (2012). ARTMO: a toolbox for automated retrieval of biophysical parameters through inversion of plant radiative transfer models. In: 2nd Terrabites Symposium 2012, 6-8 February, Frascati, Italy. (poster)

31. Verrelst, J., Rivera J.P., Alonso, L., Moreno, J. (2011). An Automated Radiative Transfer Models Operator (ARTMO) toolbox for automated retrieval of biophysical parameters through model inversion. In: European Geosciences Union (EGU) General Assembly 2011, 03-08 April, Vienna, Austria. (poster)

32. Verrelst, J., Rivera J.P., Alonso, L., Moreno, J. (2011). ARTMO: an Automated Radiative Transfer Models Operator toolbox for automated retrieval of biophysical parameters through model inversion. In: EARSeL 7th SIG-Imaging Spectroscopy Workshop 2011, 11-13 April, Edinburgh, UK. (paper & presentation)