Davide De Santis

Davide De Santis
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Davide verified their affiliation via an institutional email.
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Davide verified their affiliation via an institutional email.
University of Rome Tor Vergata | UNIROMA2 · Department of Civil Engineering and Computer Science Engineering

PhD

About

35
Publications
2,106
Reads
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114
Citations
Introduction
My research interests mainly include optical remote sensing, machine learning and climate change. My current research activities are focused on atmospheric composition monitoring with Earth Observation data and Neural Networks.
Additional affiliations
November 2018 - present
University of Rome Tor Vergata
Position
  • Research Fellow
Description
  • Atmospheric composition monitoring with satellite data and machine leaning

Publications

Publications (35)
Article
Full-text available
Our work investigates the potential of high resolution hyperspectral satellite data for detecting atmospheric methane concentrations. We employ the MAG1C algorithm, which integrates a sparsity prior, a matched filter, and albedo correction techniques. For the analysis, we utilize hyperspectral data from the PRISMA mission, leveraging its high spati...
Article
This study uses Earth observation data to measure illegal activities and investigates possible relationships with local governments. We have collected satellite images, digital maps, and geospatial data for over a decade to detect potential illegal constructions in protected burned forest areas in Sardinia, Italy. We create a database of buildings...
Conference Paper
The presented methodology aims to create a daily Aerosol Optical Depth (AOD) fusion product by integrating observations and forecasts from various EO data sources. The data used for this purpose are from the Ocean and Land Colour Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) sensors on Sentinel−3, the Second Generation G...
Conference Paper
Land surface temperature (LST) is one of the most important variables for the terrestrial ecosystem. [1] It stands as a fundamental Essential Climate Variable (ECV) [2] and hold paramount significance across different environmental and agricultural domains [3].Temperature estimation from satellites is increasingly widespread, which allows to obtain...
Conference Paper
The PRIMARY (PRIsma for Monitoring AiR quality) project objective is to address air quality monitoring, especially in urban areas, exploiting the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission. Utilizing PRISMA's hyperspectral data, the project aims to gain insights into atmospheric aerosol content and composition, crucial for...
Conference Paper
The activities undertaken within the EcoNet project aim at the design and development of an integrated system for the monitoring of changes in surface waters natural status based on different sensoristic techniques. The proposed integration approach combines ground measurements and hyperspectral satellite images. The promising dialogue that occurs...
Article
Full-text available
Monitoring particulate matter (PM) air pollution in terms of both concentration and composition, is very important due to its effects on human health and climate. In the PRIMARY project we aim at retrieving the aerosol composition from space using the hyperspectral observations from the Italian Space Agency’s PRISMA mission. To this end, we are dev...
Article
Full-text available
The need for enhancing image spatial resolution has motivated the researchers to propose numerous super-resolution techniques, including those developed specifically for hyperspectral data. Despite significant advancements in this field attributed to deep learning, little attention has been given to evaluating the practical value of super-resolved...
Conference Paper
Full-text available
EcoNet is a joint project between the Italian Space Agency (ASI) and the Institute of Nanostructured Materials of the National Research Council of Italy (CNR-ISMN) with the participation of University of Tor Vergata (UTOV) that aims to develop an integrated sensor-driven system managed by artificial intelligence (AI) for monitoring surface waters n...
Conference Paper
Full-text available
Air pollution and its effects on human health pose a significant challenge in modern society. The PRIMARY (PRIsma for Monitoring AiR quality) research project aims to utilize the capabilities of the Italian Space Agency's (ASI) PRISMA (PRecursor HyperSpectral Application Mission) to enhance air quality monitoring, particularly in urban areas. In pa...
Conference Paper
There is an urgent need to assess the condition of transport network in many countries all over the world as in Italy and, in this context, the consideration of non-destructive techniques has particular importance. These techniques, such as space-born systems, laser scanners, ground-penetrating radar (GPR), and monitoring tests, provide valuable da...
Article
Full-text available
The implications of the COVID-19 outbreak are subjected to an increasing number of studies. So far, air quality trends related to the lockdown due to the pandemic have been analysed in large cities or entire regions. In this work, the region studied is the metropolitan area of Cagliari, which is the main city on the island of Sardinia (Italy) and c...
Article
Full-text available
In Italy, 25 percent of the 7903 municipalities include protected areas, while 6.4 percent—which we define as park municipalities—are national parks. Using data from the Copernicus programme databases, we investigated the relationship between park municipalities and the air quality, and we found that the air pollution levels in these areas were muc...
Article
Full-text available
Remote sensing can represent an important instrument for monitoring landfills and their evolution over time. In general, remote sensing can offer a global and rapid view of the Earth's surface. Thanks to a wide variety of heterogeneous sensors, it can provide high-level information, making it a useful technology for many applications. The main purp...
Article
Full-text available
Accurate automatic volcanic cloud detection by means of satellite data is a challenging task and is of great concern for both the scientific community and aviation stakeholders due to well-known issues generated by strong eruption events in relation to aviation safety and health impacts. In this context, machine learning techniques applied to satel...
Conference Paper
Full-text available
In this work the classification of Sentinel-3 Sea and Land Surface Temperature (S3-SLSTR) images with a focus on volcanic cloud detection through a Neural Networks (NNs) approach is presented. Since the hazardous nature of eruptions, a fast and reliable method to monitor the evolution of volcanic clouds in real time is of primary interest. NNs repr...
Preprint
Full-text available
The accurate automatic volcanic cloud detection by means of satellite data is a challenging task and of great concern for both scientific community and stakeholder due to the well-known issues generated by a strong eruption event in relation to aviation safety and health impact. In this context, machine learning techniques applied to recent spacebo...
Article
Full-text available
InnEO’Space PhD project is preparing young researchers for a successful career by developing modernised and transferable PhD courses and learning resources based on innovation skills and employers’ needs as well as in-depth knowledge of high stakes and approaches of Earth Observation in many application domains. The mains objectives of Inn’EO Space...
Article
We investigate the time-varying effect of particulate matter (PM) on COVID-19 deaths in Italian municipalities. We find that the lagged moving averages of PM2.5 and PM10 are significantly related to higher excess deceases during the first wave of the disease, after controlling, among other factors, for time-varying mobility, regional and municipali...
Article
Full-text available
Evaluation of the impact of climate change on water bodies has been one of the most discussed open issues of recent years. The exploitation of satellite data for the monitoring of water surface temperatures, combined with ground measurements where available, has already been shown in several previous studies, but these studies mainly focused on lar...
Cover Page
Full-text available
This research presents a novel application of Earth-Observation (EO) data to monitor and detect illegal buildings in burned forest areas. We collect satellite imagery, digital maps and geospatial data over a decade and undertake a pilot study across municipalities of Sardinia (Italy). Buildings erected in forbidden forest areas are a clear example...
Conference Paper
Full-text available
In recent years many studies concerning the monitoring of volcanic activity have been carried out to develop ever more accurate and refine methods which allow to face the emergencies related to an eruption event. In our work we present different approaches for the volcanic ash cloud detection and retrieval using Sentinel-3 Sea and Land Surface Temp...
Conference Paper
Full-text available
Machine learning can be considered as a very important area within artificial intelligence and it is characterized by algorithms and techniques that learn by examples. In the last decade, mainly due to the improvements obtained in the field of high performance computing, such as the enhanced exploitation of cloud technology and of graphics processi...
Conference Paper
During a volcanic eruption, large quantities of Sulphur dioxide (SO2) are sometimes emitted into the atmosphere. Rapid detection and tracking ofvolcanic SO2 clouds might be beneficial to air traffic security and to predict any correlated impact on the environment; for example, the possibility of acid rain events. Within the presented work, we explo...
Article
Background The questioned link between air pollution and coronavirus disease 2019 (COVID-19) spreading or related mortality represents a hot topic that has immediately been regarded in the light of divergent views. A first “school of thought” advocates that what matters are only standard epidemiological variables (i.e. frequency of interactions in...
Preprint
We test the effect of the first wave COVID-19 lockdown on quality of air across Italian municipalities. We show that lockdown measures, as expected, reduced outdoor (car transit and workplace) mobility, while increasing (indoor) residential stay. We expect the first effect to contribute to better quality of air, although counterbalanced by the seco...
Preprint
In Italy, 23 percent of the 7,903 municipalities include protected areas, while 6.4 percent (which we define as park municipalities) national parks. We investigate the relationship between park areas and quality of air and find that park municipalities experienced far lower levels of air pollution in the last three years, the gross difference rangi...
Article
A research hypothesis on the nexus between air pollution and adverse COVID-19 outcomes postulates that particulate matter (PM) can be a carrier of the virus. Preliminary evidence through analysis of small PM samples has shown that this is the case but the strength of the transmission channel (impact of it on confirmed cases and deaths) has not been...
Conference Paper
Full-text available
This study aims at analysing local government efficiency using EO data to focus on the construction of new buildings in burned areas. We detected all forests and pastures of Sardinia (Sardinia) that witnessed at least a one-hectare wildfire, for biennium 2005-2006, using Landsat-TM data. We then monitored all the burned areas for a period of at lea...

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