Dr. Fabio Maselli Profile

Dr. Fabio Maselli

at Istituto di Biometeorologia

SPIE Involvement:

Author

Publications (16)

SPIE Journal Paper | 27 July 2023

Use of satellite application facility on land surface analysis products to improve an operational method for monitoring forest evapotranspiration

Luca Fibbi, Maurizio Pieri, Marta Chiesi, Fabio Maselli

JARS, Vol. 17, Issue 03, 034503, (July 2023) https://doi.org/10.1117/12.10.1117/1.JRS.17.034503

KEYWORDS: Calibration, Satellites, Ecosystems, Data modeling, Vegetation, Rain, Meteorology, Spatial resolution, Covariance, MODIS

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Proceedings Article | 21 October 2019 Paper

Combining remote sensing data and ecosystem modeling to map rooting depth

S. Sánchez-Ruiz, M. Chiesi, B. Martínez, M. Campos-Taberner, F. García-Haro, F. Maselli, M. Gilabert

Proceedings Volume 11149, 1114923 (2019) https://doi.org/10.1117/12.2532536

KEYWORDS: Ecosystems, Data modeling, Remote sensing, Calibration, Vegetation, Spatial resolution, Systems modeling, Databases, Climatology, Soil science

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Proceedings Article | 18 October 2016 Paper

Mapping growing stock at 1-km spatial resolution for Spanish forest areas from ground forest inventory data and GLAS canopy height

S. Sánchez-Ruiz, M. Chiesi, F. Maselli, M. A. Gilabert

Proceedings Volume 10005, 100051I (2016) https://doi.org/10.1117/12.2241166

KEYWORDS: Spatial resolution, MODIS, Ecosystems, Carbon, Associative arrays, Data modeling, Remote sensing, Scattering, Climatology, Near infrared

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SPIE Journal Paper | 3 November 2014

Use of geographically weighted regression to enhance the spatial features of forest attribute maps

Fabio Maselli, Marta Chiesi, Piermaria Corona

JARS, Vol. 8, Issue 01, 083533, (November 2014) https://doi.org/10.1117/12.10.1117/1.JRS.8.083533

KEYWORDS: Spatial resolution, Data modeling, Image resolution, Ecosystems, Satellites, Landsat, Image enhancement, Carbon, Satellite imaging, Earth observing sensors

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SPIE Journal Paper | 24 September 2013

Application of a single-tree identification algorithm to LiDAR data for the simulation of stem volume current annual increment

Lorenzo Bottai, Lorenzo Arcidiaco, Marta Chiesi, Fabio Maselli

JARS, Vol. 7, Issue 01, 073699, (September 2013) https://doi.org/10.1117/12.10.1117/1.JRS.7.073699

KEYWORDS: LIDAR, Data modeling, Computer simulations, Data acquisition, Biological research, Ecosystems, Error analysis, Algorithm development, Carbon, Accuracy assessment

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SPIE Journal Paper | 21 September 2012

Evaluation of empirical and semi-analytical chlorophyll algorithms in the Ligurian and North Tyrrhenian Seas

Chiara Lapucci, Marina Rella, Carlo Brandini, Nicolas Ganzin, Bernardo Gozzini, Fabio Maselli, Luca Massi, Caterina Nuccio, Alberto Ortolani, Charles Trees

JARS, Vol. 6, Issue 01, 063565, (September 2012) https://doi.org/10.1117/12.10.1117/1.JRS.6.063565

KEYWORDS: MODIS, Water, Ocean optics, Magnesium, Statistical analysis, Algorithm development, Absorption, Active optics, Satellites, Error analysis

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Proceedings Article | 9 October 2007 Paper

Integration of ground and satellite data to simulate forest carbon budget on regional scale

Fabio Maselli, Marta Chiesi, Marco Moriondo, Luca Fibbi, Marco Bindi, Steven Running

Proceedings Volume 6742, 674203 (2007) https://doi.org/10.1117/12.737907

KEYWORDS: Ecosystems, Calibration, Biological research, Data modeling, Carbon, Photosynthesis, Satellites, Atmospheric modeling, Meteorology, Remote sensing

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Proceedings Article | 5 October 2007 Paper

Use of MODIS images to monitor water constituent concentrations in the Tuscany Sea

Carolina Santini, Fabio Maselli, Luca Massi, Maurizio Pieri

Proceedings Volume 6743, 67430M (2007) https://doi.org/10.1117/12.737772

KEYWORDS: MODIS, Absorption, Backscatter, Water, Satellites, Reflectivity, Remote sensing, Ocean optics, Particles, Error analysis

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Proceedings Article | 19 October 2005 Paper

Retrieval of aerosol optical thickness from PROBA-CHRIS images acquired over a coniferous forest

Carmine Maffei, Antonio Leone, Massimo Menenti, Ivan Pippi, Fabio Maselli, Paolo Antonelli

Proceedings Volume 5976, 59760J (2005) https://doi.org/10.1117/12.627661

KEYWORDS: Aerosols, Reflectivity, Atmospheric modeling, Atmospheric particles, Vegetation, Ozone, Scattering, Remote sensing, Optical properties, Sensors

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Proceedings Article | 15 October 2004 Paper

Multi-angular hyperspectral observations of Mediterranean forest with PROBA–CHRIS

Massimo Menenti, Fabio Maselli, Marta Chiesi, Riccardo Benedetti, Simone Cristofori, Donatella Guzzi, Federico Magnani, Sabrina Raddi, Carmine Maffei

Proceedings Volume 5546, (2004) https://doi.org/10.1117/12.559348

KEYWORDS: Reflectivity, 3D modeling, Vegetation, Ecosystems, Data modeling, Sensors, Bidirectional reflectance transmission function, Earth observing sensors, Process modeling, Carbon

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Measurements of spectro-directional radiances done with the imaging spectrometer CHRIS on-board the agile platform PROBA are being used to determine key properties of terrestrial vegetation at the appropriate spatial resolution. These data on vegetation properties can then be used to improve the accuracy and the parameterizations of models describing biosphere processes, i.e. photosynthesis and water use by irrigated crops and trees. The vegetation properties considered are: albedo, Leaf Area Index (LAI), fractional cover, fraction of absorbed photosynthetically active radiation (fAPAR) and canopy chlorophyll content. The Natural Park of San Rossore (Pisa, Central Italy) is a primary test site for several national and international research projects dealing with forest ecosystem monitoring. In particular, since 1999 measurements of transpiration and ecosystem gas-exchange have been regularly taken in the park pine forest to characterize its main water and carbon fluxes. In the same period, several aerial flights have been carried out with onboard hyper-spectral sensors (MIVIS, VIRS, AISA), while a series of satellite images have been acquired using both conventional (NOAAAVHRR, Landsat-TM/ETM+) and advanced sensors (CHRIS-PROBA). The final objective of these activities is to calibrate and validate methodologies which integrate remotely sensed and ancillary data for monitoring forest ecosystem. More specifically, a major research effort has been focused on evaluating the additional information content provided by advanced hyper-spectral multi-angular sensors about the main parameters needed for forest characterization (species, LAI, pigment content, etc.). These activities are part of projects which are financed by the Italian and European Space Agencies (ASI and ESA, respectively) within the framework of the CHRIS-PROBA and SPECTRA missions. During 2002 and 2003 nine complete multi-angular acquisitions were successfully performed over the San Rossore site. This paper summarizes first results of the evaluation of data acquired so far, particularly forward modeling of Top Of Canopy (TOC) reflectances. The models KUUSK, SAIL and GeoSAIL were used to simulate spectro-directional reflectance of different stands in the forest and compared with PROBA - CHRIS and airborne hyperspectral observations. Deviations of simulated from observed reflectances were significant.

Proceedings Article | 12 December 2001 Paper

Application test of the OG-HYC hyperspectral camera

Peter Coppo, Leandro Chiarantini, Fabio Maselli, Stefano Migliorini, Ivan Pippi, Paolo Marcoionni

Proceedings Volume 4540, (2001) https://doi.org/10.1117/12.450656

KEYWORDS: Sensors, Reflectivity, Cameras, Atmospheric corrections, Device simulation, Atmospheric modeling, Vegetation, Data acquisition, Calibration, Atmospheric particles

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Proceedings Article | 17 December 1999 Paper

Use of GAC NDVI data for crop monitoring in North African countries

Felix Rembold, Fabio Maselli

Proceedings Volume 3868, (1999) https://doi.org/10.1117/12.373084

KEYWORDS: Vegetation, Agriculture, Data centers, Calibration, Floods, Data archive systems, Image processing, Environmental monitoring, Pollution control, Sensors

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Proceedings Article | 17 December 1999 Paper

Estimation of forest damage in Mediterranean areas by fuzzy classification of Landsat TM images

Fabio Maselli, Lorenzo Bottai, Arturo Oradini

Proceedings Volume 3868, (1999) https://doi.org/10.1117/12.373086

KEYWORDS: Fuzzy logic, Error analysis, Landsat, Satellites, Satellite imaging, Image classification, Climatology, Remote sensing, Vegetation, Earth observing sensors

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Proceedings Article | 31 December 1996 Paper

Automatic identification of end-members for the spectral decomposition of remotely sensed scenes

Fabio Maselli, Maurizio Pieri, Claudio Conese

Proceedings Volume 2960, (1996) https://doi.org/10.1117/12.262456

KEYWORDS: Vegetation, Landsat, Soil science, Statistical methods, Image analysis, Principal component analysis, Statistical analysis, Computing systems, Fuzzy logic, Earth observing sensors

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Proceedings Article | 30 December 1994 Paper

Definition of multisource prior probabilities for maximum likelihood classification of remotely sensed data

Fabio Maselli, Claudio Conese, A. Rodolfi, Tiziana De Filippis, L. Petkov

Proceedings Volume 2315, (1994) https://doi.org/10.1117/12.196748

KEYWORDS: Data modeling, Information fusion, Lithium, Landsat, Systems modeling, Process modeling, Agriculture, Earth observing sensors, Raster graphics, Error analysis

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Proceedings Article | 17 August 1994 Paper

Statistical integration of ancillary data into an advanced maximum likelihood classifier

Claudio Conese, Fabio Maselli, Tiziana De Filippis, Maurizio Romani

Proceedings Volume 2357, (1994) https://doi.org/10.1117/12.182799

KEYWORDS: Data integration, Landsat, Satellites, Raster graphics, Geographic information systems, Satellite imaging, Earth observing sensors, Data modeling, Francium, Protactinium

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Showing 5 of 16 publications

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