1,720,987 research outputs found
Precision agriculture by proximal and remote sensing: from the 3D modelling and tree metrics computation to the analysis of rural landscape
Full text linkL'agricoltura di precisione (AP) rappresenta un nuovo modo di impiegare la tecnologia digitale per rendere l'agricoltura più efficiente e produttiva utilizzando dati accurati. Le principali soluzioni tecnologiche di PA oggi disponibili appartengono ai campi del telerilevamento e del rilevamento prossimale. Tra queste, l'uso dei sistemi Lidar (light detection and ranging) e di visione stereoscopica sono utilizzati per la modellazione tridimensionale degli elementi vegetali (modelli 3D, point clouds, mesh, etc.). In merito a quest'ultimo aspetto la maggior parte degli studi è in ambito forestale, mentre l'utilizzo dei sistemi modellazione 3D presenta ampi spazi di studio e applicazione nel settore delle colture permanenti. Come vedremo in successivamente, il lavoro di dottorato si è concentrato su sistemi agricoli per la coltivazione dell'olivo. In particolare perché concentrarsi sul settore olivicolo ci permette di testare le potenzialità della PA in un settore cruciale non solo dal punto di vista produttivo delle culture permanenti, ma anche ecologico e paesaggistico. Questo approccio del lavoro ci permette di avere impatto in un promettente campo di innovazione tecnologica. Pertanto, il progetto di dottorato si concentra su tre linee di ricerca principali. La prima linea di ricerca mira a dimostrare l'elevata accuratezza dei dati metrici estratti da test su singoli alberi mediante ricostruzione del modello a partire da nuvole di punti campionati attraverso un dispositivo Mobile Laser Scanner Lidar (MLS). La seconda linea di ricerca si concentra sul rilevamento con Laser Scanner Mobile delle strutture arboree in oliveti specializzati. Applicando diversi algoritmi di classificazione degli alberi e di mashing delle chiome per derivare il volume di singole chiome con elevata precisione. L'analisi è condotta confrontando i volumi ottenuti dal rilievo MLS con due verità a terra o primitive (forme toroidali e paraboloidi).
La terza e linea di ricerca si è concentrata sull'analisi del paesaggio all'interno in un caso di studio in centro Italia (DOP Cartoceto). L'analisi del paesaggio è condotta adottando diversi approcci di analisi diacronica dei cambiamenti di uso del suolo e metriche del paesaggio. Per l'analisi è stato necessario costruire un robusto dataset multi temporale (ortofoto aeree, carte storiche, etc.). In particolare è stato possibile ricostruire lo stato di uso del suolo per cinque periodi nell'arco di oltre 70 anni, in ambiente GIS, individuando le diverse tipologie di modelli colturali di oliveto all'interno del territorio indagato. Successivamente è stato possibile misurare un pool di metriche del paesaggio (diversità, entropia, forma, frequenza, etc.) per analizzare le trasformazioni del paesaggio fornendo una chiara visione delle dinamiche di cambiamento avvenute in quelle aree. I risultati complessivi conseguiti nello sviluppo di queste tre linee di ricerca appaiono molto soddisfacenti. Essi rappresentano quindi un significativo stimolo sia per i singoli olivicoltori sia per le strutture associative che gestiscono il comparto olivicolo locale, in particolare il consorzio di produzione dell’olio extravergine di oliva di Cartoceto DOP, per introdurre pratiche innovative fondate sull’utilizzo di tecnologie digitali avanzate all’interno di questo importante comparto agricolo.Precision agriculture PA is a new concept adopted worldwide. Precision farming methods use large amounts of data and information to improve agricultural resource use and crop quality. In essence, PA is the science of improving agriculture sustainability by assisting farmers' decisions using high-tech sensors and analytical tools. The main PA technology solutions available today belong to remote and proximal sensing fields. Among them, Lidar (light detection and ranging) and stereoscopic vision systems are used for the three-dimensional modelling of plant elements (3D models, point clouds, meshes, etc.). Regarding the latter, most studies are in forestry, while the use of 3D modelling systems has a broad scope for study and application in permanent crops. As we will see in the following paragraphs, the doctoral work focused on agricultural systems for olive cultivation. Above all because focusing on the olive sector has a twofold significance. On the one hand, it allows us to test the potential of PA in a crucial sector from the production point of view of permanent crops. On the other, to test the seminal contribution of PA from the ecological and landscape point of view. This approach of the work allows us to seek to have an impact in the promising field of farming technological innovation. Therefore, the PhD project focuses on three main lines of research. The first line of research aims to demonstrate the high accuracy of metric data extracted from single tree tests by model reconstruction starting from point clouds sampled through a Mobile Laser Scanner Lidar (MLS) device. The second line of research focuses on the Mobile Laser Scanner survey of tree structures in specialised olive groves by applying different tree classification and canopy mashing algorithms to derive the volume of individual canopies with high accuracy. The analysis is conducted by comparing the volumes obtained from the MLS survey with two ground truths or primitives (toroidal and paraboloid shapes). The third line of research focused on landscape analysis inside a case study in central Italy (PDO Cartoceto). The landscape analysis is conducted by adopting different approaches of diachronic analysis of land use changes and landscape metrics. The analysis uses a robust multi-temporal dataset (orthophoto maps, historical maps, aerial images, etc.) to reconstruct the land use for five periods over more than 70 years in a GIS environment. The dataset allowed for identifying the different types of olive grove cropping patterns within the investigated area. Further, the landscape transformations have been analysed by measuring a pool of landscape metrics (diversity, entropy, shape, frequency, etc.) to provide a clear view of the dynamics of change that occurred in those areas. The overall results achieved in the development of these three lines of research appear very satisfactory. They, therefore, represent a significant stimulus for both individual olive growers and the associative structures that manage the local olive sector, particularly the Cartoceto DOP extra virgin olive oil production consortium, to introduce innovative practices based on the use of advanced digital technologies in the agricultural sector
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Geomatics and Environmental Engineering
Full text linkHydrogeological risks that are associated with rivers have emerged as a significant concern worldwide, impacting both natural ecosystems and human settlements. This contribution presents an interdisciplinary project that leverages many technologies for data-acquisition and modeling to comprehensively analyze and manage risks in riverine environments. The project integrates geomatics, geological, and hydrological techniques to provide a holistic understanding of river dynamics and their associated hazards. As a central component of this project, geomatics plays a pivotal role in instrumental field surveying through the deployment of photogrammetry and LiDAR instruments. Remote-sensing data from satellite imagery further enriches the project’s temporal analysis capabilities. By analyzing this data over time, researchers can monitor changes in river patterns, land use, and climate-related variables, this helps identify trends and potential triggers for hydrological events. To manage and integrate the vast amount of geospatial information that is generated, a geodatabase within a geographic information system (GIS) has been established. It enables efficient data storage, retrieval, and analysis, fostering collaboration among multidisciplinary researcher teams. This system offers tools for risk-assessment, modeling, and scenario planning, these allow for proactive measures for mitigating hydrological risks.Krakówwersja wydawnicz
Urban Land-Cover Classification Utilizing Sentinel 2 Data for Landscape Planning and Management in Vietnam
No full textThe Copernicus Sentinel 2 data could be essential for an effective land-cover classification for urban policymakers. While huge expenses and complicated post-processing issues are well-recognized by the city authorities, a convenient approach is hardly available to apply with other commercially available data sources. Freely available Sentinel 2 data, even with 10–60 m resolution, could be an essential addition for policymakers, especially for classifying urban landscapes. Here, the Geographic Object-based Image Analysis (GEOBIA) approach has been applied in the eCognition platform utilizing a Sentinel 2 image for the urban land-cover classification in Hue, Vietnam. Currently, four different classes, i.e., streets, buildings, vegetation, and water resources, have been applying the GEOBIA approach. Concerning the data availability and post-processing approach, this study could be a way out for urban policymakers due to the convenience and simplicity of the applied algorithms. So, this study will certainly assist city planners either in the case of developed or third-world developing ones, where it is much more necessary for efficient urban space management
A Multisensor-Based Measurement Procedure for Seismic Damage Identification in Buildings
No full textEffectively and precisely identifying damages after a seismic event is fundamental to ensuring timely intervention and optimizing the building life cycle. The combination of multisensor inspection and artificial intelligence (AI) technologies is powerful in this context. This work presents the results of the development of a multisensor measurement procedure relying on drone-embedded visible and thermal cameras and a terrestrial laser scanner (TLS) to acquire data on a masonry church damaged by an earthquake. These data were carefully aligned into a unified reference system and enabled the reconstruction of high-resolution 3-D models of the building, from which multichannel orthophotos were extracted, with visible, thermal, and depth data, to identify surface lesions. The analysis procedure involved three main stages: 1) preprocessing using principal component analysis (PCAs) to improve feature separability and reduce redundancy between channels; 2) lesion detection using a deep learning U-Net segmentation model trained to identify surface cracks; and 3) morphological postprocessing to refine the predicted masks and eliminate (or reduce) false positives predictions. The combination of multimodal data improves lesion detection, highlighting cracks that are not immediately visible, particularly when thermal gradients or geometric discontinuities provided complementary evidence. The results are promising and demonstrate both the feasibility of lesion identification and the validity of the proposed approach in the context of structural health monitoring. The use of sensors that can acquire data remotely and without contact offers significant advantages in terms of safety in a postearthquake context
Comparing the accuracy of 3D urban olive tree models detected by smartphone using LiDAR sensor, photogrammetry and NeRF: a case study of ’Ascolana Tenera’ in Italy
No full textRapid urban growth makes green space management crucial to improve citizens' well-being. Urban olive trees characterize the Italian landscapes and their culture. This study explores different methodologies for urban tree assessment in this context, using an iPhone 14 Pro Max. These included: 1) its integrated Light Detection and Ranging (LiDAR) sensor using the Recon3D app, 2) its camera with Structure from Motion (SfM) techniques, and 3) its camera for generating 3D models using Neural Radiance Fields (NeRF). Additionally, a professional Mobile Laser Scanner (MLS), was used for comparison. Total height (H), canopy base height (CBH) and canopy volume (CV) measurements were extracted using both CloudCompare and allometric formulas. The main aim of this paper is to compare the 3D models of olive trees obtained from low-cost sensors with those generated from the MLS, which is a more accurate device but comes with significantly higher costs. The results, in terms of RMSE (iPhone LiDAR - H: 0.46 m, CBH: 0.12 m, CV: 15.66 m3; iPhone-SfM - H: 0.95 m, CBH: 0.19 m, CV: 25.85 m3; iPhone-NeRF - H: 1.26 m, CBH: 0.31 m, CV: 33.79 m3), bias and volume differences, reveal that the smartphone, in all the methodologies, tends to underestimate measurements as the size of the trees increases. This is due to the higher MLS range of acquisition. Despite these limitations, low-cost solutions like smartphone-based methods can be a viable alternative given their economic accessibilit
Time series analysis of olive orchard coverage in the rural landscape: a case study of the Cartoceto Municipality
No full textThe temporal transformation of the rural landscape of Cartoceto municipality over a period of 42 years has been analyzed in this study by using the QGIS software, Land use maps, aerial photos, photo interpretation, and standardization of land use classes nomenclature and topographic data were utilised. The study area is the municipality of Cartoceto (PU), lacated in the Marche region of Central Italy, and, it is recognized as a Geographical Indication (GI) called Cartoceto DOP, which is famous for producing extra virgin olive oil. The multidisciplinary analysis allowed for the identification of factors that have influenced the temporal evolution of the study area, with particular attention to olive cultivation. These insights contribute to the understanding of land use dynamics and olive landscapes, offering the opportunity to make informed decisions to ensure the sustainability and resilience of rural landscapes
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