Prof. Simone Lolli Profile

Prof. Simone Lolli

Assistant Research Professor at Istituto di Metodologie per l'Analisi Ambientale

SPIE Involvement:

Conference Chair | Editor | Author

Publications (22)

Proceedings Article | 20 November 2024 Presentation + Paper

Comparative analysis of precipitation scavenging effects on aerosol loading in Shanghai: seasonal variability and implications for air quality management

Andreu Salcedo-Bosch, Lian Zong, Jason Cohen, Yuanjing Yang, Simone Lolli

Proceedings Volume 13193, 1319304 (2024) https://doi.org/10.1117/12.3031200

KEYWORDS: Pollution, Atmospheric modeling, Air quality, Windows, Aerosols, Meteorology, Data modeling, Machine learning, Analytical research, Systems modeling

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Proceedings Article | 20 November 2024 Presentation + Paper

Enhancing spatial resolution of OLI 100m thermal bands through hypersharpening of 30m spectral bands

Andrea Garzelli, Alberto Arienzo, Luciano Alparone, Simone Lolli

Proceedings Volume 13196, 1319603 (2024) https://doi.org/10.1117/12.3031446

KEYWORDS: Image sharpness, Image fusion, Landsat, Spatial resolution, Image resolution, Thermography, Data fusion, Short wave infrared radiation, Resolution enhancement technologies, Reflectivity

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SPIE Journal Paper | 13 December 2023 Open Access

Special Section Guest Editorial: Integrating Remote Sensing, Machine Learning, and Data Science for Air Quality Management

Kaixu Bai, Simone Lolli, Yuanjian Yang

JARS, Vol. 18, Issue 01, 012001, (December 2023) https://doi.org/10.1117/12.10.1117/1.JRS.18.012001

KEYWORDS: Remote sensing, Machine learning, Air quality, Satellites, Environmental monitoring, Pollution, Environmental sensing, Aerosols, Atmospheric modeling, Transmittance

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Proceedings Article | 19 October 2023 Presentation + Paper

Full-scale assessment of pansharpening: why literature indexes may give contradictory results and how to avoid such an inconvenience

Luciano Alparone, Andrea Garzelli, Simone Lolli, Claudia Zoppetti

Proceedings Volume 12733, 1273302 (2023) https://doi.org/10.1117/12.2684389

KEYWORDS: Image fusion, Image quality, Distortion, Image sensors, Spatial resolution, Image resolution, Data fusion, Image sharpness

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Proceedings Article | 19 October 2023 Presentation + Paper

Analysis of atmospheric aerosol properties using lidar measurements and their impact on radiative budget in Barcelona over the past 20 years

Simone Lolli, Michaël Sicard, Adolfo Comerón, Cristina Gil-Díaz, Daniel Camilo Dos Santos Oliveira, Tony Landi, Alejandro Rodríguez-Gómez, Constantino Munoz-Porcar, Francesc Rocadenbosch, Federico Dios

Proceedings Volume 12730, 1273007 (2023) https://doi.org/10.1117/12.2685167

KEYWORDS: Aerosols, LIDAR, Atmospheric particles, Backscatter, Climatology, Atmospheric modeling, Environmental sensing, Clouds, Air quality, Raman spectroscopy

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Proceedings Article | 26 October 2022 Presentation + Paper

Fusion of optical and SAR satellite data for environmental monitoring: assessment of damages and disturbances originated by forest fires

Luciano Alparone, Alberto Arienzo, Andrea Garzelli, Simone Lolli, Claudia Zoppetti

Proceedings Volume 12267, 122670E (2022) https://doi.org/10.1117/12.2638984

KEYWORDS: Synthetic aperture radar, Polarimetry, Vegetation, Image enhancement, Spatial resolution, Reflectivity, Data fusion, Near infrared, Modulation, Atmospheric modeling

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Proceedings Article | 30 September 2020 Poster + Presentation + Paper

HEAD: a robust high-resolution satellite image-based aerosol optical depth retrieval algorithm in the blue wavelength range using Kalman filters

Simone Lolli, Gemine Vivone, Alberto Arienzo, Andrea Garzelli, Luciano Alparone, Muhammad Bilal

Proceedings Volume 11531, 115310W (2020) https://doi.org/10.1117/12.2574277

KEYWORDS: Aerosols, Head, Satellite imaging, Earth observing sensors, Satellites, Filtering (signal processing), Atmospheric particles, Atmospheric modeling, Solar radiation models, Algorithm development

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Proceedings Article | 9 October 2019 Presentation + Paper

An automatic light rain detection algorithm on NASA MPLNET lidar observations in the frame of WMO GALION project

Simone Lolli, Michaël Sicard, Gemine Vivone, Jasper Lewis, Ellsworth Welton, Adolfo Comerón

Proceedings Volume 11152, 1115208 (2019) https://doi.org/10.1117/12.2533571

KEYWORDS: LIDAR, Clouds, Algorithm development, Meteorology, Detection and tracking algorithms, Aerosols, Signal detection, Composites, Atmospheric optics, Image processing

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The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics. Results from the algorithm, besides filling a gap in precipitation and virga detection by radars, are of particular interest for the scientific community because will help to better understand long-term aerosol-cloud interactions and aerosol atmospheric removal (scavenging effect) by rain as multi-year database being available for several MPLNET permanent observational sites across the globe. Moreover, we developed the automatic algorithm at Universitat Politecnica de Catalunya (UPC) Barcelona, the unique permanent observation station member of MPLNET and the European Aerosol Lidar Network (EARLINET) In the future the algorithm can be then easily applied to any other lidar and/or ceilometer network infrastructure in the frame of World Meteorological Organization (WMO) Global Aerosol Watch (GAW) aerosol lidar observation network (GALION)

Proceedings Article | 7 October 2019 Presentation + Paper

Fast multispectral pansharpening based on a hyper-ellipsoidal color space

Bruno Aiazzi, Luciano Alparone, Alberto Arienzo, Andrea Garzelli, Simone Lolli

Proceedings Volume 11155, 1115507 (2019) https://doi.org/10.1117/12.2533481

KEYWORDS: Atmospheric modeling, Picosecond phenomena, Image fusion, Atmospheric corrections, Air contamination, Remote sensing, Multispectral imaging, Spectral resolution, Spatial resolution, Spatial frequencies

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Proceedings Article | 9 October 2018 Presentation + Paper

High-resolution satellite aerosol optical depth retrieval and its variability over highly industrialized hotspots in the Po Valley, Italy

Simone Lolli, Luciano Alparone, Muhammad Bilal, Andrea Garzelli, Gemine Vivone

Proceedings Volume 10786, 1078606 (2018) https://doi.org/10.1117/12.2325853

KEYWORDS: Aerosols, Atmospheric modeling, Atmospheric particles, Atmospheric optics, Radiative transfer, Satellites, Polonium, Earth observing sensors, Image fusion, Data modeling

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Proceedings Article | 13 October 2017 Presentation + Paper

Assessment of cirrus cloud and aerosol radiative effect in South-East Asia by ground-based NASA MPLNET lidar network data and CALIPSO satellite measurements

Simone Lolli, James Campbell, Jasper Lewis, Ellsworth Welton, Paolo Di Girolamo, Fatkhuroyan Fatkhuroyan, Yu Gu, Jared Marquis

Proceedings Volume 10424, 1042405 (2017) https://doi.org/10.1117/12.2278987

KEYWORDS: Aerosols, Clouds, LIDAR, Atmospheric modeling, Atmospheric particles, Satellites, Atmospheric optics, Radiative transfer, Ocean optics, Analytical research

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Aerosol, together with cirrus clouds, play a fundamental role in the earth-atmosphere system radiation budget, especially at tropical latitudes, where the Earth surface coverage by cirrus cloud can easily reach 70%. In this study we evaluate the combined aerosol and cirrus cloud net radiative effects in a wild and barren region like South East Asia. This part of the world is extremely vulnerable to climate change and it is source of important anthropogenic and natural aerosol emissions. The analysis has been carried out by computing cirrus cloud and aerosol net radiative effects through the Fu-Liou-Gu atmospheric radiative transfer model, adequately adapted to input lidar measurements, at surface and top-of-the atmosphere. The aerosol radiative effects were computed respectively using the retrieved lidar extinction from Cloud-Aerosol Lidar with Orthogonal Polarization in 2011 and 2012 and the lidar on-board of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations for the South East Asia Region (27N-12S, 77E-132E) with 5° x 5° spatial resolution. To assess the cirrus cloud radiative effect, we used the ground-based Micro Pulse Lidar Network measurements at Singapore permanent observational site. Results put in evidence that strong aerosol emission areas are related on average to a net surface cooling. On the contrary, cirrus cloud radiative effect shows a net daytime positive warming of the system earth-atmosphere. This effect is weak over the ocean where the albedo is lower and never counter-balances the net cooling produced by aerosols. The net cooling is stronger in 2011, with an associated reduction in precipitations by the four of the five rain-gauges stations deployed in three regions as Sumatra, Kalimantan and Java with respect to 2012. We can speculate that aerosol emissions may be associated with lower rainfall, however some very important phenomena as El Nino Southern Oscillation , Madden-Julian Oscillation, Monsoon and Indian Dipole are not considered in the analysis.

Proceedings Article | 4 October 2017 Presentation + Paper

Benefits of haze removal for modulation-based pansharpening

Simone Lolli, Luciano Alparone, Andrea Garzelli, Gemine Vivone

Proceedings Volume 10427, 1042707 (2017) https://doi.org/10.1117/12.2279086

KEYWORDS: Atmospheric modeling, Radiative transfer, Image fusion, Earth observing sensors, High resolution satellite images

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Proceedings Article | 20 October 2015 Paper

One-year monitoring of the atmosphere over Penang Island using a ground-based lidar

Wei Ying Khor, Mohd Zubir Matjafri, Hwee San Lim, Wan Shen Hee, Simone Lolli

Proceedings Volume 9645, 96450M (2015) https://doi.org/10.1117/12.2195440

KEYWORDS: Atmospheric particles, Aerosols, LIDAR, Mass attenuation coefficient, Earth's atmosphere, Atmospheric monitoring, Combustion, Signal processing, Atmospheric modeling, Signal attenuation

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Proceedings Article | 20 October 2014 Paper

High Spectral Resolution Lidar (HSRL) and MPLNET Micro Pulse Lidar (MPL) aerosol optical property retrieval intercomparison during the 2012 7-SEAS field campaign at Singapore

Simone Lolli, Ellsworth Welton, James Campbell, Edwin Eloranta, Brent Holben, Boom Ning Chew, Santo Salinas

Proceedings Volume 9246, 92460C (2014) https://doi.org/10.1117/12.2067812

KEYWORDS: LIDAR, Aerosols, Backscatter, Atmospheric particles, Optical properties, Signal attenuation, Spectral resolution, Troposphere, Lawrencium, Clouds

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Proceedings Article | 20 October 2014 Paper

MPLNET lidar data assimilation in the ECMWF MACC-II Aerosol system: evaluation of model performances at NCU lidar station

Simone Lolli, Ellsworth Welton, Angela Benedetti, Luke Jones, Martin Suttie, Sheng-Hsiang Wang

Proceedings Volume 9246, 92460I (2014) https://doi.org/10.1117/12.2068201

KEYWORDS: Atmospheric modeling, Data modeling, Aerosols, LIDAR, Performance modeling, Meteorology, Systems modeling, Atmospheric particles, Atmospheric optics, MODIS

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Proceedings Article | 20 October 2014 Open Access

Tropospheric Raman Lidar measurements of the vertical aerosol backscattering with range-dependent Lidar ratio in Penang Island, Malaysia, during the dry season (withdrawal notice)

Wan Shen Hee, Wei Ying Khor, Fuyi Tan, Hwee San Lim, Mohamad Matjafri, Simone Lolli

Proceedings Volume 9246, 92460Q (2014) https://doi.org/10.1117/12.2067003

KEYWORDS: LIDAR, Aerosols, Atmospheric particles, Backscatter, Raman spectroscopy, Combustion, Oceanography, Air contamination, Clouds, Data acquisition

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Proceedings Article | 30 September 2011 Paper

Planetary boundary layer height retrieval at UMBC in the frame of NOAA/ARL campaign

S. Lolli, R. Delgado, J. Compton, R. Hoff

Proceedings Volume 8182, 81820R (2011) https://doi.org/10.1117/12.898352

KEYWORDS: LIDAR, Continuous wavelet transforms, Atmospheric particles, Aerosols, Atmospheric modeling, Troposphere, Wind measurement, Atmospheric sensing, Clouds, Temporal resolution

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Proceedings Article | 2 November 2010 Paper

Eyjafjallajökull volcano ash plume detection in the frame of the new constituting lidar network Leonet

S. Lolli, S. Conil, A. Dabas, D. Donovan, S.-E. Gryning, T. Mikkelsen, H. Ricketts, L. Sauvage, G. Vaughan, J. Walter, F. Wienhold

Proceedings Volume 7832, 78320K (2010) https://doi.org/10.1117/12.868517

KEYWORDS: LIDAR, Backscatter, Aerosols, Atmospheric particles, Network architectures, Atmospheric optics, Telescopes, Clouds, Cobalt, Time metrology

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Proceedings Article | 26 October 2010 Paper

An automatic planetary boundary layer height detection with a compact aerosol UV lidar

L. Sauvage, S. Loaëc, S. Lolli, M. Boquet, A. El Filali

Proceedings Volume 7832, 783203 (2010) https://doi.org/10.1117/12.865020

KEYWORDS: Clouds, LIDAR, Head, Aerosols, Image processing, Ultraviolet radiation, Atmospheric sensing, Atmospheric particles, Signal detection, Wavelets

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