101,918 research outputs found
2nd edition of instrumenting smart city applications with big sensing and earth observatory data: Tools, methods and techniques
No full textIn lieu of an abstract, this is an excerpt from the first page.
The exponential growth in the volume of Earth observation data and the increasing quality and availability of high-resolution imagery are increasingly making more applications possible in urban environments. In particular, remote sensing information, especially when combined with location-specific data collected locally or through connected devices, presents exciting opportunities for smart city applications, such as risk analysis and mitigation, climate prediction, and remote surveillance. On the other hand, the exploitation of this great amount of data poses new challenges for big data analysis models and requires new spatial information frameworks capable of integrating imagery, sensor observations, and social media in geographic information systems (GIS)
On the IR/UV mixing and experimental limits on the parameters of canonical noncommutative spacetimes
No full textWe investigate some issues that are relevant for the derivation of experimental limits on the parameters of canonical noncommutative spacetimes. By analyzing a simple Wess-Zumino-type model in canonical noncommutative spacetime with soft supersymmetry breaking we explore the implications of ultraviolet supersymmetry on low-energy phenomenology. The fact that new physics in the ultraviolet can modify low-energy predictions affects significantly the derivation of limits on the noncommutativity parameters based on low-energy data. These are, in an appropriate sense here discussed, ``conditional limits''. We also find that some standard techniques for an effective low-energy description of theories with non-locality at short distance scales are only applicable in a regime where theories in canonical noncommutative spacetime lack any predictivity, because of the strong sensitivity to unknown UV physics. It appears useful to combine high-energy data, from astrophysics, with the more readily available low-energy data
Uso di dati telerilevati nella caratterizzazione di un’area della regione del Fayyum (Egitto)
No full textIl lavoro illustra alcuni aspetti di una ricerca in atto volta alla caratterizzazione morfologica, geologica e limnologica del lago Qarun e delle aree circostanti nella regione del Fayyum (Egitto), area di grande interesse anche per la ricerca archeologica. Vengono affrontati in particolare la valutazione di modelli digitali del terreno ottenuti da immagini satellitari e da cartografia ed alcuni aspetti legati all’analisi di dati multispettrali di sensori diversi ed acquisiti ad epoche diverse. Lo studio multitemporale, condotto anche avvalendosi della elaborazione di indici vegetazionali, può supportare un’analisi di change detection che metta in evidenza l’espansione delle aree agricole nel processo di bonifica in corso e le modifiche al territorio intervenute negli ultimi decenni
Utilizzo del modello OC-4 con dati iperspettrali per la caratterizzazione di acque lacustri
No full textLa ricerca presentata intende valutare l’applicabilità del modello OC4 (Ocean Chlorophyll 4), originariamente sviluppato per acque costiere, allo studio di acque lacustri, attraverso l’impiego di immagini satellitari iperspettrali e differenti modelli di correzione atmosferica. L’analisi è stata condotta su due casi di studio specifici, il lago di Garda ed il lago Qarun (Egitto), rappresentativi di due condizioni climatiche ed idrologiche opposte. I primi risultati mostrano un buon accordo tra i valori forniti dal modello OC4 e i dati di letteratura per il lago di Garda, mentre i valori appaiono sottostimati per quanto riguarda le acque del lago Qarun. Ulteriori approfondimenti sono necessari per interpretare correttamente tali discrepanze
A Technical Note on AI-Driven Archaeological Object Detection in Airborne LiDAR Derivative Data, with CNN as the Leading Technique
No full textArchaeological research fundamentally relies on detecting features to uncover hidden historical information. Airborne (aerial) LiDAR technology has significantly advanced this field by providing high-resolution 3D terrain maps that enable the identification of ancient structures and landscapes with improved accuracy and efficiency. This technical note comprehensively reviews 45 recent studies to critically examine the integration of Machine Learning (ML) and Deep Learning (DL) techniques, particularly Convolutional Neural Networks (CNNs), with airborne LiDAR derivatives for automated archaeological feature detection. The review highlights the transformative potential of these approaches, revealing their capability to automate feature detection and classification, thus enhancing efficiency and accuracy in archaeological research. CNN-based methods, employed in 32 of the reviewed studies, consistently demonstrate high accuracy across diverse archaeological features. For example, ancient city walls were delineated with 94.12% precision using U-Net, Maya settlements with 95% accuracy using VGG-19, and with an IoU of around 80% using YOLOv8, and shipwrecks with a 92% F1-score using YOLOv3 aided by transfer learning. Furthermore, traditional ML techniques like random forest proved effective in tasks such as identifying burial mounds with 96% accuracy and ancient canals. Despite these significant advancements, the application of ML/DL in archaeology faces critical challenges, including the scarcity of large, labeled archaeological datasets, the prevalence of false positives due to morphological similarities with natural or modern features, and the lack of standardized evaluation metrics across studies. This note underscores the transformative potential of LiDAR and ML/DL integration and emphasizes the crucial need for continued interdisciplinary collaboration to address these limitations and advance the preservation of cultural heritage
Atmospheric correction issues for water quality assessment from Remote Sensing: the case of Lake Qarun (Egypt)
No full textWater quality assessment and monitoring from remote sensing data is strongly affected by the accuracy of the atmospheric effect correction. Two algorithms, based respectively on Modtran 4 and on 6SV radiative transfer codes, and an empirical image-based method have been compared, also examining the sensitivity to different parameterizations of water vapour content and aerosols. The experimentation has been carried out on a specific case study, lake Qarun, a conservation area located in the Fayyum Oasis (Egypt). Water quality indicators have been computed by multispectral and hyperspectral data and compared to literature data
Rilievi topografici sull'area archeologica di Bakchias
No full textDurante la campagna di scavo 2010 dell’Università di Bologna, il Dipartimento di Ingegneria Civile Ambientale e dei Materiali (DICAM), ha condotto una serie di operazioni di rilievo topografico sull’intera area di scavo ed in particolare nel settore denominato “kom sud”. Tali operazioni si inseriscono nel contesto di un’attività di rilievo geodetico, topografico e fotogrammetrico, iniziata nel 1994 e condotta con l’integrazione di differenti tecniche e metodologie dell’Ingegneria Geomatica. Tra gli scopi principali di tali attività rientravano l’inquadramento del sito di Bakchias nel sistema di riferimento internazionale ed il supporto delle operazioni di mappatura delle emergenze archeologiche. Le nuove misurazioni rispondono alle necessità di aggiornamento e ripristino della rete topografica appositamente istituita nelle prime campagne ed all’esigenza di informazioni più dettagliate sulle aree non ancora scavate
Urban energetics applications and Geomatic technologies in a Smart City perspective
No full textThe management of an urban context in a Smart City perspective requires the development of innovative projects, with new applications in multidisciplinary research areas. They can be related to many aspects of city life and urban management: fuel consumption monitoring, energy efficiency issues, environment, social organization, traffic, urban transformations, etc.
Geomatics, the modern discipline of gathering, storing, processing, and delivering digital spatially referenced information, can play a fundamental role in many of these areas, providing new efficient and productive methods for a precise mapping of different phenomena by traditional cartographic representation or by new methods of data visualization and manipulation (e.g. three-dimensional modelling, data fusion, etc.). The technologies involved are based on airborne or satellite remote sensing (in visible, near infrared, thermal bands), laser scanning, digital photogrammetry, satellite positioning and, first of all, appropriate sensor integration (online or offline).
The aim of this work is to present and analyse some new opportunities offered by Geomatics technologies for a Smart City management, with a specific interest towards the energy sector related to buildings. Reducing consumption and CO2 emissions is a primary objective to be pursued for a sustainable development and, in this direction, an accurate knowledge of energy consumptions and waste for heating of single houses, blocks or districts is needed.
A synoptic information regarding a city or a portion of a city can be acquired through sensors on board of airplanes or satellite platforms, operating in the thermal band.
A problem to be investigated at the scale of the whole urban context is the Urban Heat Island (UHI), a phenomenon known and studied in the last decades. UHI is related not only to sensible heat released by anthropic activities, but also to land use variations and evapotranspiration reduction. The availability of thermal satellite sensors is fundamental to carry out multi-temporal studies in order to evaluate the dynamic behaviour of the UHI for a city.
Working with a greater detail, districts or single buildings can be analysed by specifically designed airborne surveys. The activity has been recently carried out in the EnergyCity project, developed in the framework of the Central Europe programme established by UE. As demonstrated by the project, such data can be successfully integrated in a GIS storing all relevant data about buildings and energy supply, in order to create a powerful geospatial database for a Decision Support System assisting to reduce energy losses and CO2 emissions.
Today, aerial thermal mapping could be furthermore integrated by terrestrial 3D surveys realized with Mobile Mapping Systems through multisensor platforms comprising thermal camera/s, laser scanning, GPS, inertial systems, etc. In this way the product can be a true 3D thermal model with good geometric properties, enlarging the possibilities in respect to conventional qualitative 2D images with simple colour palettes.
Finally, some applications in the energy sector could benefit from the availability of a true 3D City Model, where the buildings are carefully described through three-dimensional elements. The processing of airborne LiDAR datasets for automated and semi-automated extraction of 3D buildings can provide such new generation of 3D city models
Quantitative GIS-based analysis of archaeological data of the archaic state of Tell Mardikh/Ebla (3rdmillennium BC): The Big-DEA project
No full textThe paper provides an overview on Big-DEA, a multidisciplinary project aimed at developing a comprehensive multi-level explanatory model for the development of an archaic State in the ancient Near East, using the exceptional case of Tell Mardikh, ancient Ebla (Syria), during the second half of the 3rd millennium. The project's goal is the reconstruction of the archaic state organization through an integrated analysis of archaeological and epigraphic data. The interaction between humanities and hard sciences is adopted in order to build a multi-tier explanatory model regarding the territory under the control of the Ebla kingdom, considering anthropic and environmental data deriving from excavations, survey and textual sources. The way to managing and study such a large Big Data archive, which includes different datasets, is itself the main challenge of the project: the creation of a dedicated relational database management system (RDBMS) functional to the implementation of the available GIS platform and the development of an appropriate simulation framework
Comparison between empirical and physically based models of atmospheric correction
No full textA number of methods have been proposed for the atmospheric correction of the multispectral satellite images, based on either atmosphere modelling or images themselves. Full radiative transfer models require a lot of ancillary information about the atmospheric conditions at the acquisition time. Whereas, image based methods cannot account for all the involved phenomena. Therefore, the aim of this paper is the comparison of different atmospheric correction methods for multispectral satellite images. The experimentation was carried out on a study area located in the catchment area of Yialias river, 20 km South of Nicosia, the Cyprus capital. The following models were tested, both empirical and physically based: Dark object subtraction, QUAC, Empirical line, 6SV, and FLAASH. They were applied on a Landsat 8 multispectral image. The spectral signatures of ten different land cover types were measured during a field campaign in 2013 and 15 samples were collected for laboratory measurements in a second campaign in 2014. GER 1500 spectroradiometer was used; this instrument can record electromagnetic radiation from 350 up to 1050 nm, includes 512 different channels and each channel covers about 1.5 nm. The spectral signatures measured were used to simulate the reflectance values for the multispectral sensor bands by applying relative spectral response filters. These data were considered as ground truth to assess the accuracy of the different image correction models. Results do not allow to establish which method is the most accurate. The physics-based methods describe better the shape of the signatures, whereas the image-based models perform better regarding the overall albedo
- …
