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Introduction
Dr. Andrea Nascetti is a research scientist at the Department of Urban Planning and Environment at KTH Royal Institute of Technology in Stockholm, Sweden. Before joining KTH, from 2013 he was a postdoc researcher at the University of Rome “La Sapienza” and during his studies he acquired a significant background in Geomatics, Remote Sensing (Photogrammetry, SAR, Radargrammetry) and in Computer Vision. Main research activities:
Earth Observation & Remote Sensing
Models and algorithms for processing optical and radar high resolution satellite im- agery using different techniques (i.e Photogrammetry, Radargrammetry and Interferometry). Development and implementation of feature extraction, off-set tracking and matching algorithms; stereoscopic digital surface models generation. Co-registrati
Additional affiliations
June 2013 - present
Publications
Publications (102)
Wildfires play a crucial role in the transformation of forest ecosystems and exert a significant influence on the global climate over geological timescales. Recent shifts in climate patterns and intensified human–forest interactions have led to an increase in the incidence of wildfires. These fires are characterized by their extensive coverage, hig...
By deploying remotely sensed data together with spatial statistical modeling, we use regression modeling to investigate the relationship between the density of the built environment and two types of crime. We show how the Global Human Settlement Layer (GHSL) data set, which is a measure of building density generated from Sentinel 2A satellite image...
Urbanization is progressing at an unprecedented rate in many places around the world. The Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) missions, combined with deep learning, offer new opportunities to accurately monitor urbanization at a global scale. Although the joint use of SAR and optical data has rece...
The assessment of cracks in civil infrastructures commonly relies on visual inspections carried out at night, resulting in limited inspection time and an increased risk of crack oversight. The Digital Image Correlation (DIC) technique, employed in structural monitoring, requires stationary cameras for image collection, which proves challenging for...
Accurate estimation of building heights is essential for urban planning, infrastructure management, and environmental analysis. In this study, we propose a supervised Multimodal Building Height Regression Network (MBHR-Net) for estimating building heights at 10m spatial resolution using Sentinel-1 (S1) and Sentinel-2 (S2) satellite time series. S1...
Change detection using earth observation data plays a vital role in quantifying the impact of disasters in affected areas. While data sources like Sentinel-2 provide rich optical information, they are often hindered by cloud cover, limiting their usage in disaster scenarios. However, leveraging pre-disaster optical data can offer valuable contextua...
Land Use/Land Cover (LULC) mapping is the first step in monitoring urban sprawl and its environmental, economic and societal impacts. While satellite imagery and vegetation indices are commonly used for LULC mapping, the limited resolution of these images can hamper object recognition for Geographic Object-Based Image Analysis (GEOBIA). In this stu...
Accurate urban maps provide essential information to support sustainable urban development. Recent urban mapping methods use multi-modal deep neural networks to fuse Synthetic Aperture Radar (SAR) and optical data. However, multi-modal networks may rely on just one modality due to the greedy nature of learning. In turn, the imbalanced utilization o...
Floods are one of the most frequent natural disasters worldwide. Although the vulnerability varies from region to region, all countries are susceptible to flooding. Mozambique was hit by several cyclones in the last few decades, and in 2019, after cyclones Idai and Kenneth, the country became the first one in southern Africa to be hit by two cyclon...
Floods are occurring across the globe, and due to climate change, flood events are expected to increase in the coming years. Current situations urge more focus on efficient monitoring of floods and detecting impacted areas. In this study, we propose two segmentation networks for flood detection on uni-temporal Sentinel-1 Synthetic Aperture Radar da...
Human civilization has an increasingly powerful influence on the earth system. Affected by climate change and land-use change, natural disasters such as flooding have been increasing in recent years. Earth observations are an invaluable source for assessing and mitigating negative impacts. Detecting changes from Earth observation data is one way to...
Today, Digital Image Correlation (DIC) has become a standardized method to track displacements and crack-propagation of civil engineering structures in a laboratory environment. The benefit of using DIC over other standard methods is that it is contact-free and only requires a standard DSLR camera. Moreover, the displacement can be tracked over the...
Accurate and up-to-date maps of built-up areas are crucial to support sustainable urban development. Earth Observation (EO) is a valuable data source to cover this demand. In particular, Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) missions offer new opportunities to map built-up areas on a global scale. U...
Tunnels in hard rock are typically supported with a thin layer of fibre-reinforced shotcrete in combination with rock bolts. Cracks in the shotcrete could lead to corrosion of the fibres, which reduces the residual strength and could lead to downfall of shotcrete. Therefore, routine inspections are carried out to maintain a safe tunnel. Today, visu...
Building change detection is essential for monitoring urbanization, disaster assessment, urban planning and frequently updating the maps. 3D structure information from airborne light detection and ranging (LiDAR) is very effective for detecting urban changes. But the 3D point cloud from airborne LiDAR(ALS) holds an enormous amount of unordered and...
Urban Heat Islands (UHI) phenomenon is a pressing problem for highly industrialized areas with serious risks for public health. Weather stations guarantee long-term accurate observations of weather parameters, such Air Temperature (AT), but lack appropriate spatial coverage. Numerous studies have argued that satellite Land Surface Temperature (LST)...
In this study, a Semi-Supervised Learning (SSL) method for improving urban change detection from bi-temporal image pairs was presented. The proposed method adapted a Dual-Task Siamese Difference network that not only predicts changes with the difference decoder, but also segments buildings for both images with a semantics decoder. First, the archit...
Building change detection is essential for monitoring urbanization, disaster assessment, urban planning and frequently updating the maps. 3D structure information from airborne light detection and ranging (LiDAR) is very effective for detecting urban changes. But the 3D point cloud from airborne LiDAR(ALS) holds an enormous amount of unordered and...
Due to climate and land-use change, natural disasters such as flooding have been increasing in recent years. Timely and reliable flood detection and mapping can help emergency response and disaster management. In this work, we propose a flood detection network using bi-temporal SAR acquisitions. The proposed segmentation network has an encoder-deco...
More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain...
Urbanization is progressing rapidly around the world. With sub-weekly revisits at global scale, Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 multispectral imager (MSI) data can play an important role for monitoring urban sprawl to support sustainable development. In this letter, we proposed an urban change detection (CD) approach featur...
Global environmental changes have increased the frequency of natural disasters and the demand for rapid post-disaster mapping. In this regard, Remote Sensing (RS) is a leading technology because it provides consistent near-real-time images. In this chapter, we studied different disasters, Joplin MO Tornado (2011), Hurricane Harvey (2017), and Hurri...
Sentinel-2 MultiSpectral Instrument (MSI) data exhibits the great potential of enhanced spatial and temporal coverage for monitoring biomass burning which could complement other coarse active fire detection products. This paper aims to investigate the use of reflective wavelength Sentinel-2 data to classify unambiguous active fire areas from inacti...
Wildfires are increasing in intensity and frequency across the globe due to climate change and rising global temperature. Development of novel approach to Monitor wildfire progressions in near real-time is therefore of critical importance for emergency responses. The objective of this research is to investigate continuous learning with U-Net by exp...
Accurate burned area information is needed to assess the impacts of wildfires on people, communities, and natural ecosystems. Various burned area detection methods have been developed using satellite remote sensing measurements with wide coverage and frequent revisits. Our study aims to expound on the capability of deep learning (DL) models for aut...
Producing accurate land cover maps is time-consuming and estimating land cover changes between two generated maps is affected by error propagation. The increased availability of analysis-ready Earth Observation (EO) data and the access to big data analytics capabilities on Google Earth Engine (GEE) have opened the opportunities for continuous monit...
Civil infrastructures, such as tunnels and bridges, are directly related to the overall economic and demographic growth of countries. The aging of these infrastructures increases the probability of catastrophic failures that results in loss of lives and high repair costs; all over the world, these factors drive the need for advanced infrastructure...
In recent years, the world witnessed many devastating wildfires that resulted in destructive human and environmental impacts across the globe. Emergency response and rapid response for mitigation calls for effective approaches for near real-time wildfire monitoring. Capable of penetrating clouds and smoke, and imaging day and night, Synthetic Apert...
Mapping Earth’s surface and its rapid changes with remotely sensed data is a crucial task to understand the impact of an increasingly urban world population on the environment. However, the impressive amount of available Earth observation data is only marginally exploited in common classifications. In this study, we use the computational power of G...
Compared with optical sensors, the all-weather and day-and-night imaging ability of Synthetic Aperture Radar (SAR) makes it competitive for burnt area mapping. This study investigates the potential of Sentinel-1 C-band SAR sensors in burnt area mapping with an implicit Radar Convolutional Burn Index (RCBI). Based on multitemporal Sentinel-1 SAR dat...
There has been substantial urban growth in Stockholm, Sweden, the fastest-growing capital in Europe. The intensifying urbanization poses challenges for environmental management and sustainable development. Using Sentinel-2 and SPOT-5 imagery, this research investigates the evolution of land-cover change in Stockholm County between 2005 and 2015, an...
The emergence of high-resolution satellite data, such as WorldView-2, has opened the opportunity for urban land cover mapping at fine resolution. However, it is not straightforward to map detailed urban land cover and to detect urban deprived areas, such as informal settlements, in complex urban environments based merely on high-resolution spectral...
Thanks to the advances in computer power, memory storage and the availability of low-cost and high resolution digital cameras, Digital Image Correlation (DIC) is currently one of the most used optical and non-contact techniques for measuring material deformations. A free and open source 2D DIC software, named py2DIC, was developed at the Geodesy an...
DATE (Digital Automatic Terrain Extractor) is a Free and Open Source Software for Geospatial (FOSS4G), which combines photogrammetric and computer vision algorithms in order to automatically generate DSMs from multi-view SAR and optical high resolution satellite imagery, following an iterative and pyramidal workflow in order to refine a coarse DSM...
All over the world, the rapid urbanization process is challenging the sustainable development of our cities. In 2015, the United Nation highlighted in Goal 11 of the SDGs (Sustainable Development Goals) the importance to “Make cities inclusive, safe, resilient and sustainable”. In order to monitor progress regarding SDG 11, there is a need for prop...
In the last few decades, there has been a growing interest in studying non-contact methods for full-field displacement and strain measurement. Among such techniques, Digital Image Correlation (DIC) has received particular attention, thanks to its ability to provide these information by comparing digital images of a sample surface before and after d...
Today, range cameras represent a cheap, intuitive and effective technology for collecting the 3D geometry of objects and environments automatically and practically in real time. Such features can make these sensors a valuable tool for documenting archaeological small finds, especially when not expert users are involved. Therefore, in this work, Sca...
The glaciers are a natural global resource and one of the principal climate change indicator at global and local scale, being influenced by temperature and snow precipitation changes. Among the parameters used for glacier monitoring, the surface velocity is a key element, since it is connected to glaciers changes (mass balance, hydro balance, glaci...
The aim of this work is to exploit the large-scale analysis capabilities of the innovative Google Earth Engine platform in order to investigate the temporal variations of the Urban Heat Island phenomenon as a whole. A intuitive methodology implementing a largescale correlation analysis between the Land Surface Temperature and Land Cover alterations...
The glaciers are a natural global resource and one of the principal climate change indicator at global and local scale, being influenced by temperature and snow precipitation changes. Among the parameters used for glacier monitoring, the surface velocity is a key element, since it is connected to glaciers changes (mass balance, hydro balance, glaci...
The glaciers are a natural global resource and one of the principal climate change indicator at global and local scale, being influenced by temperature and snow precipitation changes. Among the parameters used for glacier monitoring, the surface velocity is a key element, since it is connected to glaciers changes (mass balance, hydro balance, glaci...
The topic of this research is the identification of an innovative strategy for DSMs generation from optical satellite tri-stereo imagery, exploiting efficient dense matching algorithms from computer vision, without losing a rigorous photogrammetric approach. The main challenge is related to the epipolarity resampling for satellite images, for which...
Archaeological small finds provide a variegated myriad of data of crucial importance to the study of their finding contexts. Anyway, only a close all-around examination can give a full comprehension of their multiple functions. The production of reliable documentation is thus an essential process and this paper illustrates a fast, reliable and easy...
Nowadays, the increasing availability of low-cost sensors, Free and Open Source Software and High Performance Computing infrastructures allows Geomatics to widen its application scope, by stimulating new challenging investigations related to the modeling of the observations provided by these new tools.
In this review, some methodologies and applica...
Recently, there has been a growing interest in studying non-contact techniques for strain and displacement measurement. Within photogrammetry, Digital Image Correlation (DIC) has received particular attention thanks to the recent advances in the field of lowcost, high resolution digital cameras, computer power and memory storage. DIC is indeed an o...
This article presents a new application of the SAR-SIFT algorithm proposed by Dellinger et al. (IEEE Trans Geosci Remote Sens 53:453–466, 2015) for the automatic generation of tie points (TPs). In particular, SAR-SIFT is applied on stereo-SAR images to extract corresponding points and determine their 3D position. Furthermore, the potential of the c...
The ISPRS Working Group 4 Commission I on “Geometric and Radiometric Modelling of Optical Spaceborne Sensors”, provides a
benchmark dataset with several stereo data sets from space borne stereo sensors. In this work, the Worldview-1 and Cartosat-1 datasets
are used, in order to test the Free and Open Source Software for Geospatial (FOSS4G) Digital...
The high-performance cloud-computing platform Google Earth Engine has been developed for global-scale analysis based on the Earth observation data. In particular, in this work, the geometric accuracy of the two most used nearly-global free DSMs (SRTM and ASTER) has been evaluated on the territories of four American States (Colorado, Michigan, Nevad...
The production of reliable documentation of small finds is a crucial process during archaeological excavations. Range cameras can be a valid alternative to traditional illustration methods: they are veritable 3D scanners able to easily collect the 3D geometry (shape and dimensions in metric units) of an object/scene practically in real-time.
This...
The fully automatic generation of digital surface models (DSMs) is still an open research issue. From recent years, computer vision algorithms have been introduced in photogrammetry in order to exploit their capabilities and efficiency in three-dimensional modelling. In this article, a new tool for fully automatic DSMs generation from high resoluti...
Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns. Few years ago, a first attempt was made in the framework of project SISMA, funded by Italian Space Agency, to jointly use seismological tools, like CN algorit...
Nowadays, the availability of novel high-resolution synthetic aperture radar (SAR) spaceborne sensors offers new interesting potentialities for the acquisition of data useful for the generation of secondary products as digital surface models (DSMs), orthoimages, and displacement maps. SAR technology provides for low-cost, fast data acquisition and...
At the beginning of 2012, a new optical satellite, called ZiYuan-3 (ZY-3), was launched from the Taiyuan Satellite Launch Centre. This article is aimed at the analysis and the assessment of the digital surface models (DSMs) and orthophotos from a ZY-3 triplet acquired over the city of Bolzano and the surrounding areas. The imagery processing chain...
The SAR (Synthetic Aperture Radar) imagery are widely used in order to monitor displacements impacting the Earth surface and infrastructures. The main remote sensing technique to extract sub-centimeter information from SAR imagery is the Differential SAR Interferometry (DInSAR), based on the phase information only. However, it is well known that DI...
The leading idea of this work is to continuously retrieve glaciers surface velocity through SAR imagery, in particular using the amplitude data from the new ESA satellite sensor Sentinel-1 imagery. These imagery key aspects are the free access policy, the very short revisit time (down to 6 days with the launch of the Sentinel-1B satellite) and the...
Synthetic Aperture Radar (SAR) satellite systems may give important contribution in terms of Digital Surface Models (DSMs) generation considering their complete independence from logistic constraints on the ground and weather conditions. In recent years, the new availability of very high resolution SAR data (up to 20 cm Ground Sample Distance) gave...
The leading idea of this work is to continuously retrieve glaciers surface velocity through SAR imagery, in particular using the amplitude data from the new ESA satellite sensor Sentinel-1 imagery. These imagery key aspects are the free access policy, the very short revisit time (down to 6 days with the launch of the Sentinel-1B satellite) and the...
The SAR (Synthetic Aperture Radar) imagery are widely used in order to monitor displacements impacting the Earth surface and infrastructures. The main remote sensing technique to extract sub-centimeter information from SAR imagery is the Differential SAR Interferometry (DInSAR), based on the phase information only. However, it is well known that DI...