Dario Spiller

Sapienza University of Rome | la sapienza · Aerospace Research Center [CRAS]

One of the United Nations (UN) Sustainable Development Goals is climate action (SDG-13), and wildfire is among the catastrophic events that both impact climate change and are aggravated by it. In Australia and other countries, large-scale wildfires have dramatically grown in frequency and size in recent years. These fires threaten the world's fores...

Climate action (SDG-13) is an integral part of the Sustainable Development Goals (SDGs) set by the United Nations (UN), and wildfire is one of the catastrophic events related to climate change. Large-scale forest fires have drastically increased in frequency and size in recent years in Australia and other nations. These wildfires endanger the fores...

This paper deals with detection and temperature analysis and of wildfires using PRISMA imagery. Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral...

This paper focuses on the development of a guidance methodology for the planning of multiple ground target acquisition. Specifically, the work addresses the problem of the lack of an attitude guidance planner (AGP) aboard a remote sensing satellite. In general, the guidance is computed offline and uploaded by ground control to the space segment, i....

This paper introduces an innovative approach to explore the capabilities of Quantum Annealing (QA) for trajectory optimization in dynamic systems. The proposed method involves transforming trajectory optimization problems into equivalent binary optimization problems using Quadratic Unconstrained Binary Optimization (QUBO) representation. The proced...

This research explores the potential use of artificial intelligence techniques and edge computing approaches to detect wildfires directly from satellite platforms. The study is based on PRISMA (Hyperspectral Precursor of the Application Mission), an Italian hyperspectral satellite launched in 2019 that provides hyperspectral imagery in the spectral...

Within this study, we examined the correlation between tree canopy temperature, canopy height, and vegetation types. Furthermore, we conducted a similar analysis in the southern region of the island of Sardinia, renowned for its dense forests and frequent wildfires. We successfully mapped the vegetation types in the region using PRISMA hyperspectra...

Accurate fuel mapping is crucial for effectively determining wildfire risk and implementing management strategies. The primary challenge in fuel type mapping lies in the need to develop accurate and efficient methods for identifying and categorizing the various combustible materials present in an area, often on a large scale. In response to this ne...

The exacerbation of wildfires, attributed to the effects of climate change, presents substantial risks to ecological systems, infrastructure, and human well-being. In the context of the Sustainable Development Goals (SDGs), particularly those related to climate action, prioritizing the assessment and management of the occurrence and intensity of ex...

Accurate fuel mapping plays a crucial role in fire detection and management strategies. This paper presents a method for discriminating between wildfire fuel types by exploiting together remote sensing data and Convolutional Neural Networks (CNN). Specially, a CNN-based classification approach that leverages Sentinel-2 imagery is exploited to accur...

This technical report examines the connection between climate change and livestock, focusing on the impacts on livestock production systems. The study explores various methodologies from the literature and analyses their application in a practical test case in the Lao People's Democratic Republic. The assessment estimates direct and indirect effect...

Volcanic eruptions are a natural hazard that can devastate people and property. In recent years, the number of volcanic eruptions has been on the rise, and the effects of climate change are making them more frequent and more powerful. This research proposes a new methodology for monitoring volcanoes in real-time or very close to real-time using an...

Recent developments in Distributed Satellite Systems (DSS) have undoubtedly increased mission value due to the ability to reconfigure the spacecraft cluster/formation and incrementally add new or update older satellites in the formation. These features provide inherent benefits, such as increased mission effectiveness, multi-mission capabilities, d...

Over the course of several decades, there has been a consistent push toward replacing monolithic satellite systems with distributed ones. Because of the growing number of operational satellites in orbit above the Earth, it is anticipated that this will result in an increase in both the value of the mission and the capabilities of its payload. Missi...

A robust multi-baseline along-track interferometric Synthetic Aperture Radar (SAR) formation flying concept is proposed to combine effectively several along-track baseline observations for real-time single-pass acquisition purposes. Simulation results are given to support the feasibility of implementing this acquisition mode with autonomous orbit c...

COVID-19 had a strong and disruptive impact on our society, and yet further analyses on most relevant factors explaining the spread of the pandemic are needed. Interdisciplinary studies linking epidemiological, mobility, environmental, and socio-demographic data analysis can help understanding how historical conditions, concurrent social policies a...

Space-based Earth Observation (EO) systems have undergone a continuous evolution in the twenty-first century. With the help of space-based Maritime Domain Awareness (MDA), specially Automatic Identification Systems (AIS), their applicability across the world's waterways, among others, has grown substantially. This research work explores the potenti...

This paper investigates the opportunity to use artificial intelligence methodologies and edge computing approaches for wildfire detection directly from satellite platforms. The test case for our study is PRISMA (Precursore IperSpettrale della Missione Applicativa-Hyperspectral Precursor of the Application Mission), the Italian hyperspectral satelli...

This paper investigates the effects of an imbalanced distribution of crater mask labels in datasets used for image segmentation. It can be regarded as an addendum to existing works delving with autonomous Crater Detection tasks neglecting non uniform pixel distribution. In fact, the craters edge pixels represent approximately only 3% of each single...

This work presents MONSTER, a Moon optical navigation robotic facility on simulated terrain, i.e., an experimental facility that can be used to simulate lunar navigation problems. The facility consists of a 3D Cartesian manipulator that, once fully operative, will be equipped with a spherical joint allowing to simulate both attitude and orbital dyn...

This paper shows the application of autonomous Crater Detection using the U-Net, a Fully-Convolutional Neural Network, on Ceres. The U-Net is trained on optical images of the Moon Global Morphology Mosaic based on data collected by the LRO and manual crater catalogues. The Moon-trained network will be tested on Dawn optical images of Ceres: this ta...

This article aims to investigate how circuit-based hybrid Quantum Convolutional Neural Networks (QCNNs) can be successfully employed as image classifiers in the context of remote sensing. The hybrid QCNNs enrich the classical architecture of CNNs by introducing a quantum layer within a standard neural network. The novel QCNN proposed in this work i...

This article aims to investigate how circuit-based hybrid Quantum Convolutional Neural Networks (QCNNs) can be successfully employed as image classifiers in the context of remote sensing. The hybrid QCNNs enrich the classical architecture of CNNs by introducing a quantum layer within a standard neural network. The novel QCNN proposed in this work i...

In recent years, the growth of Machine Learning (ML) algorithms has raised the number of studies including their applicability in a variety of different scenarios. Among all, one of the hardest ones is the aerospace, due to its peculiar physical requirements. In this context, a feasibility study, with a prototype of an on board Artificial Intellige...

The problem of real-time optimal guidance is extremely important for successful autonomous missions. In this paper, the last phases of autonomous lunar landing trajectories are addressed. The proposed guidance is based on the Particle Swarm Optimization, and the differential flatness approach, which is a subclass of the inverse dynamics technique....

Over the last few years, crop type mapping has gained importancein remote sensing as it represents one of the most challenging prob-lems in this field. Precise and continuous spectral signatures cansignificantly help to obtain a unambiguous distinction among thetypes of crop. This paper presents a discussion about the applica-tion of different type...

Crop type mapping represents one of the most challenging problemsin remote sensing. Spatial, spectral, and temporal information arerequired in order to obtain a unambiguous distinction among thetypes of crop. This paper presents a multi-sensor approach, wherelabelled high-resolution images from drones, limited to small areas,are used to enhance the...

In recent years, the growth of Machine Learning algorithms in a variety of different applications has raised numerous studies on the applicability of these algorithms in real scenarios. Among all, one of the hardest scenarios, due to its physical requirements, is the aerospace one. In this context, the authors of this work aim to propose a first pr...

This paper deals with the analysis and detection of wildfires by using PRISMA imagery. Precursore IperSpettrale della Mis­sione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images...

Crop type mapping currently represents an important problem in remote sensing. Accurate information on the extent and types of crops derived from remote sensing can help managing and improving agriculture especially for developing countries where such information is scarce. In this paper, high-resolution RGB drone images are the input data for the...

This concept paper aims to provide a brief outline of quantum computers, explore existing methods of quantum image classification techniques, so focusing on remote sensing applications, and discuss the bottlenecks of performing these algorithms on currently available open source platforms. Initial results demonstrate feasibility. Next steps include...

Dengue fever is one of the most common and rapidly spreading arboviral diseases in the world, with major public health and economic consequences in tropical and sub-tropical regions. Countries such as Peru, 17.143 cases of dengue were reported in 2019, where 81.4% of cases concentrated in five of the 25 departments. When predicting infectious disea...

In this paper, a geometrical investigation of the star sensor image is performed under dynamic conditions where the angular velocity effects are non-negligible. It is shown that, when the spacecraft is rotating, the streaks left by the stars’ signal onto the star sensor detector belong to portions of conic sections which features depend on the angl...

The paper focuses on the opportunity to use star sensors to help space situational awareness and space surveillance. Catalogs of orbiting satellites around Earth are usually established on ground-based measurements that rely on optical or radar data provided by instruments on Earth. However, space-based observations offer new opportunities, as they...

The development of fast and reliable optimization algorithms is required in order to obtain real-time optimal trajectory on-board spacecraft. In addition, the wide spread of small satellites, due to their low costs, is leading to a greater number of satellite formations in space. This paper presents an Improved version of the Magnetic Charged Syste...

A study on reconfiguration manoevres applied to a tetrahedral formation in highly elliptical orbits is proposed, by using a propellantless solution. The manoeuvring strategy consists in exploiting certain environmental forces, specifically those provided by solar radiation pressure and atmospheric drag, by actively controlling the satellites’ attit...

This paper is devoted to the implementation and application of an improved version of the metaheuristic algorithm called magnetic charged system search. Some modifications and novelties are introduced and tested. Firstly, the authors’ attempt is to develop a self-adaptive and user-friendly algorithm which can automatically set all the preliminary p...

This paper addresses the problem of star identification in the presence of high slew rates, false objects and image deformations introduced by the rolling shutter. These problems can affect the operating life of star trackers and worsen the nominal performances. The proposed methodology relies on a technique named Improved Multi-Poles Algorithm, es...

This paper presents the control solutions to the spacecraft formation reconfiguration problem when impulsive or extended maneuvers are considered, and the reference orbit is circular. The proposed approach for the derivation of the control solutions is based on the inversion of the linearized equations of relative motion parameterized using the mea...

This paper addresses the minimum-fuel spacecraft formation reconfiguration maneuver in J2 perturbed near-circular orbits. In this study, only the deputy is assumed to be maneuverable and capable of providing a piecewise constant control thrust. The optimal control problem is formulated as a mixed-integer linear programming problem. To make the prop...

The paper described the most recent advances in the development of the Inverse-dynamics Particle Swarm Optimization technique for determining approximate solutions to constrained optimal control problems. Near-optimal solutions are searched for using a differential flatness approach such that the kinematic of the problem is directly approximated wh...

Analysing the trend of the aerospace technology market, two of the most prominent research and development areas are represented by completely autonomous spacecraft and space robotics technology advancement. To satisfy this development, the near future space missions will increasingly need enhanced computational capabilities to fulfil the demand of...

This paper presents an open-loop planner for near-time-optimal maneuvers performed by satellite formations during proximity operations and reconfiguration maneuvers. Using a differential flatness parameterization, which is an inverse-dynamics method with a minimal set of independent functions, a new optimization technique based on the differential...

The paper deals with the problem of time-optimal spacecraft reorientation maneuvers by means of reaction wheels, with boundary and path constraints. When searching for solutions to optimal attitude-control problems, spacecraft can be easily modeled as controlled by external torques. However, when using actuators such as reaction wheels, conservatio...

This paper presents the solutions to the spacecraft relative trajectory reconfiguration problem when a continuous thrust profile is used, and the reference orbit is circular. Given a piecewise continuous thrust profile, the proposed approach enables the computation of the control solution by inverting the linearized equations of relative motion par...

This thesis deals with solving optimal control problems via swarm intelligence. Great emphasis is given to the formulation of the optimal control problem regarding fundamental issues such as unknowns identification, numerical transcription and choice of the nonlinear programming solver. The Particle Swarm Optimization is taken into account, and most...

The possibility to reconfigure satellite formations with utilization of the drag and the solar radiation pressure has been established with previous works. Passive formation reconfiguration maneuvers may be achieved by controlling the attitude of the satellites and varying the area exposed to the perturbation forces. This paper deals with the devel...

This paper deals with a fast and efficient Lost in Space algorithm for stars pattern recognition in harsh environments using star trackers. Typically, the attitude determination system for CubeSats is based on low accuracy instruments such as sun sensors and magnetometers. However, it is expected that next CubeSat generations will require more accu...

A numerical approach for minimum-time maneuvers, based on the Particle Swarm Optimization, is proposed. The external control structure is assigned as a Bang-Bang control policy whilst the search space is divided into several sub-domains. Each sub-domain is defined by the number of switches per axis and by the sign of the bangs. The algorithm searche...

Star trackers can offer a unique opportunity for the observation of orbiting objects helping space surveillance and increasing space situational awareness. When star trackers operate in attitude estimation mode, information from observed moving objects are usually discarded. However, these data could be very useful for monitoring the space environm...