Gabriele Candiani - IEEE Xplore Author Profile
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Gabriele Candiani

Also published under: G. Candiani

Publications
12
Citations
30
Publications by Year
20092024
Co-Authors:
Show All Co-Authors (52)
Image of author Gabriele Candiani

Gabriele Candiani

Also published under: G. Candiani

Affiliation

Institute for Electromagnetic Sensing of the Environment
National Research Council
Milan, Italy

Publication Topics

Biography

Gabriele Candiani received the M.S. degree in environmental engineering from Politecnico di Milano, Milan, Italy, in 2002, and the Ph.D. degree in information engineering from Università degli Studi di Brescia, Brescia, Italy, in 2010.,He is currently a Researcher with the National Research Council of Italy, Milan, Italy, focusing on remote sensing applications in the “Agriculture and Food Security” domain. His primary interest lies in developing machine learning algorithms to estimate crop traits, within a hybrid framework that exploits radiative transfer models. His previous research activities involved the use of remote sensing for water quality monitoring, air quality prediction, hydrocarbon exploration, data fusion of satellite images ...
Publications
12
Citations
30
Publications by Year
20092024
Co-Authors:
Show All Co-Authors (52)
Author's Published Works

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Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations

Lorenzo Parigi;Gabriele Candiani;Ignazio Gallo;Piero Toscano;Mirco Boschetti

2024 19th Conference on Computer Science and Intelligence Systems (FedCSIS)
Year: 2024 | Conference Paper |
Hyperspectral images from newly launched (ASI-PRISMA and DLR-EnMAP) and future satellite (ESA-CHIME) are an opportunity, thanks to the high spectral resolution and full range continuity, to improve the retrieval of information about the crop parameters and status. The high dimensionality of hyperspectral data and the non-linear relationship between the crop biophysical parameters and their spectra...Show More

Towards crop traits estimation from hyperspectral data: evaluation of neural network models trained with real multi-site data or synthetic RTM simulations

Lorenzo Parigi;Gabriele Candiani;Ignazio Gallo;Piero Toscano;Mirco Boschetti

Year: 2024 | Conference Paper |

Vegetation Biomass and Nitrogen Content Estimation Using Ensembles: Regression and Active Learning Strategies for Field Sampling Reduction

Donato Amitrano;Gabriele Candiani;Luca Cicala;Marco De Mizio;Francesco Tufano

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2024 | Volume: 17 | Journal Article |
Cited by: Papers (1)
Optimization of agricultural practices is crucial to ensure high and sustainable food production. In this regard, hyperspectral remote sensing demonstrated its usefulness in the building of models able to predict several vegetation parameters. The effort, in terms of time and costs, of a remote sensing campaign depends on both the instruments to be exploited and the number of samples to be acquire...Show More

Vegetation Biomass and Nitrogen Content Estimation Using Ensembles: Regression and Active Learning Strategies for Field Sampling Reduction

Donato Amitrano;Gabriele Candiani;Luca Cicala;Marco De Mizio;Francesco Tufano

Year: 2024 | Volume: 17 | Journal Article |

The Influence of Plasmodesmata Number and Opening State on Molecular Transports in Plants

Beatrice Ruzzante;Alessandro Piscopo;Svyatoslav Salo;Maurizio Magarini;Gabriele Candiani

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
Year: 2023 | Volume: 9, Issue: 3 | Journal Article |
Cited by: Papers (1)
Molecular Communication (MC) studies the transport of information encoded in signaling molecules. To date, its application field is mainly restrained to health-related uses. However, MC in plants has been gaining increasing interest. The primary transport route in plant cell-to-cell communication are Plasmodesmata (PDs), pore-like structures dotting the plant cell wall. PDs opening state is influe...Show More

The Influence of Plasmodesmata Number and Opening State on Molecular Transports in Plants

Beatrice Ruzzante;Alessandro Piscopo;Svyatoslav Salo;Maurizio Magarini;Gabriele Candiani

Year: 2023 | Volume: 9, Issue: 3 | Journal Article |

Retrieving Biophysical And Biochemical Crop Traits Using Continuum-Removed Absorption Features From Hyperspectral Proximal Sensing

Ramin Heidarian Dehkordi;Francesco Nutini;Simone Mereu;Gabriele Candiani;Margherita De Peppo;Mirco Boschetti

2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Year: 2022 | Conference Paper |
In recent years, hyperspectral sensors, thanks to their very high spectral resolution, has attracted increasing attention for monitoring crop traits across the precision agricultural settings. In this paper, we evaluated the potential of hyperspectral spectroscopic indicators, by analyzing several properties of continuum-removed absorption features retrieved based on segmented upper hull and infle...Show More

Retrieving Biophysical And Biochemical Crop Traits Using Continuum-Removed Absorption Features From Hyperspectral Proximal Sensing

Ramin Heidarian Dehkordi;Francesco Nutini;Simone Mereu;Gabriele Candiani;Margherita De Peppo;Mirco Boschetti

Year: 2022 | Conference Paper |

Prototyping Vegetation Traits Models in the Context of the Hyperspectral Chime Mission Preparation

J. Verrelst;C. De Grave;E. Amin;P. Reyes;M. Morata;E. Portales;S. Belda;G. Tagliabue;C. Panigada;M. Boschetti;G. Candiani;K. Segl;S. Guillasso;K. Berger;M. Wocher;T. Hank;U. Rascher;C. Isola

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Year: 2021 | Conference Paper |
Cited by: Papers (9)
The Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is in preparation to carry a unique visible to shortwave infrared spectrometer. CHIME will globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. The mission shall provide Level 1B, 1C and 2A products, as well a set of d...Show More

Prototyping Vegetation Traits Models in the Context of the Hyperspectral Chime Mission Preparation

J. Verrelst;C. De Grave;E. Amin;P. Reyes;M. Morata;E. Portales;S. Belda;G. Tagliabue;C. Panigada;M. Boschetti;G. Candiani;K. Segl;S. Guillasso;K. Berger;M. Wocher;T. Hank;U. Rascher;C. Isola

Year: 2021 | Conference Paper |

Characterization of fine metal particles using hyperspectral imaging in automatic weee recycling systems

G. Candiani;N. Picone;L. Pompilio;M. Pepe;M. Colledani

2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Year: 2015 | Conference Paper |
Cited by: Papers (2)
Waste from electric and electronic equipment (WEEE) represents the fastest growing waste stream in EU. The large amount and the high variability of electric and electronic products introduced every year in the market make the WEEE recycling process a complex task, especially considering that mechanical processes currently used by recycling companies are not flexible enough. In this context, hypers...Show More

Characterization of fine metal particles using hyperspectral imaging in automatic weee recycling systems

G. Candiani;N. Picone;L. Pompilio;M. Pepe;M. Colledani

Year: 2015 | Conference Paper |

Geolithological mapping of carbonate system deposits for hydrocarbon exploration using hyperspectral imagery

M. Pepe;M. Boschetti;G. Candiani;P. Villa;F. Righetti;V. Clementi

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Year: 2015 | Conference Paper |
Cited by: Papers (1)
Hyperspectral remote sensing can support exploration activities helping in the recognition of lithologycal outcrops over extended areas. This is mainly due to the nature of the mineral reflectance spectra which feature very narrow absorption peaks, therefore requiring hyperspectral sensors to be assessed. In this work, the capabilities for geolithology recognition of aerial hyperspectral data have...Show More

Geolithological mapping of carbonate system deposits for hydrocarbon exploration using hyperspectral imagery

M. Pepe;M. Boschetti;G. Candiani;P. Villa;F. Righetti;V. Clementi

Year: 2015 | Conference Paper |

Hyperdimensional data exploitation through parametric reduction

Loredana Pompilio;Monica Pepe;Gabriele Candiani

2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Year: 2014 | Conference Paper |
Feature reduction of hyperspectral data is a big challenge, particularly because the reduced dimensions must preserve the separability properties and key information content. Nevertheless, various techniques have been developed so far and are well documented in the literature. Here we characterize a novel technique of feature reduction, with main emphasis on the ability of enhancing the informativ...Show More

Hyperdimensional data exploitation through parametric reduction

Loredana Pompilio;Monica Pepe;Gabriele Candiani

Year: 2014 | Conference Paper |

Airborne remote sensing for mapping asbestos roofs in aosta valley

Federico Frassy;Gabriele Candiani;Pieralberto Maianti;Andrea Marchesi;Francesco Rota Nodari;Marco Rusmini;Carlo Albonico;Marco Gianinetto

2012 IEEE International Geoscience and Remote Sensing Symposium
Year: 2012 | Conference Paper |
Cited by: Papers (5)
This paper describes the use of airborne hyperspectral remote sensing for mapping asbestos roofs in an orographic complex area in Northern Italy, the Aosta Valley. Using training samples collected during field surveys, thematic classification was able to detect the majority of asbestos surfaces. Considering the total amount of asbestos areas validation showed a correct detection of about 80%, whil...Show More

Airborne remote sensing for mapping asbestos roofs in aosta valley

Federico Frassy;Gabriele Candiani;Pieralberto Maianti;Andrea Marchesi;Francesco Rota Nodari;Marco Rusmini;Carlo Albonico;Marco Gianinetto

Year: 2012 | Conference Paper |

High-resolution SAR and high-resolution optical data integration for sub-urban land-cover classification

Marco Rusmini;Gabriele Candiani;Federico Frassy;Pieralberto Maianti;Andrea Marchesi;Francesco Rota Nodari;Luigi Dini;Marco Gianinetto

2012 IEEE International Geoscience and Remote Sensing Symposium
Year: 2012 | Conference Paper |
Cited by: Papers (5)
This study shows a comparison between pixel-based and object-based approaches in data fusion of high-resolution multispectral GeoEye-1 imagery and high-resolution COSMO-SkyMed SAR data for land-cover/land-use classification. The per-pixel method consisted of a maximum likelihood classification of fused data based on discrete wavelet transform and a classification from optical images alone. Optical...Show More

High-resolution SAR and high-resolution optical data integration for sub-urban land-cover classification

Marco Rusmini;Gabriele Candiani;Federico Frassy;Pieralberto Maianti;Andrea Marchesi;Francesco Rota Nodari;Luigi Dini;Marco Gianinetto

Year: 2012 | Conference Paper |

Off-line Data Assimilation to provide the best estimate of tropospheric ozone concentrations by means of EnKF

Gabriele Candiani;Claudio Carnevale;Giovanna Finzi;Enrico Pisoni;Marialuisa Volta

49th IEEE Conference on Decision and Control (CDC)
Year: 2010 | Conference Paper |
Cited by: Papers (2)
Different Data Assimilation techniques have been formalized and applied in the context of complex nonlinear models, to describe chemistry and physics of the atmosphere. In the literature the main approaches presented are based on a) statistical interpolation (SI) techniques, including optimal interpolation methods, residual kriging methods, regression, etc... and on b) variational methods, as well...Show More

Off-line Data Assimilation to provide the best estimate of tropospheric ozone concentrations by means of EnKF

Gabriele Candiani;Claudio Carnevale;Giovanna Finzi;Enrico Pisoni;Marialuisa Volta

Year: 2010 | Conference Paper |

Optimal interpolation to re-analyse PM10 concentration modelling simulations

Gabriele Candiani;Claudio Carnevale;Veronica Filisina;Giovanna Finzi;Enrico Pisoni;Marialuisa Volta

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference
Year: 2009 | Conference Paper |
Cited by: Papers (4)
An optimal interpolation technique is formalized and applied to the output of an air quality deterministic model in order to improve the description of the evolution of pollutant (namely particulate matter, PM10) in atmosphere. The paper presents an application of the methodology to the Northern Italy region, often affected by high concentration of PM10. The validation of the methodology performed...Show More

Optimal interpolation to re-analyse PM10 concentration modelling simulations

Gabriele Candiani;Claudio Carnevale;Veronica Filisina;Giovanna Finzi;Enrico Pisoni;Marialuisa Volta

Year: 2009 | Conference Paper |

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