The NextGenerationEU–funded pro- ject GreatT (Global Research on Environmental and Territorial Transformations) focused on the archaeological evidence of the Etrusco-Roman city of Rusellae (Roselle), near Grosseto (Tuscany, Italy). The project foresees the interpretation of the historical landscape as a single evolving ecosystem shaped by both human and natural processes.
Building on earlier archaeological excavations, GreatT integrated non-invasive and multidisciplinary methods—geophysical surveys, 3D laser scanning, and drone-based imaging—with historical sources such as maps, aerial photographs, and excavation archives.
The altimetric values of measured and interpreted data have been converted into stratigraphic information for RT3D, a 3D geospatial platform that facilitates the visualization, analysis and elaboration of very heterogeneous data, supporting a dynamic reconstruction of the ancient city and its living landscape through digital elevation models.
The Stonex X200GO laser scanner and the S999 GNSS receiver introduce a comprehensive, hybrid approach to modern geomatic surveying. By integrating high-precision laser scanning, advanced satellite positioning and dual-camera photogrammetric acquisition, these systems enable the rapid generation of dense and reliable point clouds across a wide range of operational scenarios.
Zihan Zhang, Abhijit Ravichandran, Pragnya Korti
et al.
High-definition (HD) maps are essential for autonomous driving, providing precise information such as road boundaries, lane dividers, and crosswalks to enable safe and accurate navigation. However, traditional HD map generation is labor-intensive, expensive, and difficult to maintain in dynamic environments. To overcome these challenges, we present a real-world deployment of an online mapping system on a campus golf cart platform equipped with dual front cameras and a LiDAR sensor. Our work tackles three core challenges: (1) labeling a 3D HD map for campus environment; (2) integrating and generalizing the SemVecMap model onboard; and (3) incrementally generating and updating the predicted HD map to capture environmental changes. By fine-tuning with campus-specific data, our pipeline produces accurate map predictions and supports continual updates, demonstrating its practical value in real-world autonomous driving scenarios.
The ability to generate online maps using only onboard sensory information is crucial for enabling autonomous driving beyond well-mapped areas. Training models for this task -- predicting lane markers, road edges, and pedestrian crossings -- traditionally require extensive labelled data, which is expensive and labour-intensive to obtain. While semi-supervised learning (SSL) has shown promise in other domains, its potential for online mapping remains largely underexplored. In this work, we bridge this gap by demonstrating the effectiveness of SSL methods for online mapping. Furthermore, we introduce a simple yet effective method leveraging the inherent properties of online mapping by fusing the teacher's pseudo-labels from multiple samples, enhancing the reliability of self-supervised training. If 10% of the data has labels, our method to leverage unlabelled data achieves a 3.5x performance boost compared to only using the labelled data. This narrows the gap to a fully supervised model, using all labels, to just 3.5 mIoU. We also show strong generalization to unseen cities. Specifically, in Argoverse 2, when adapting to Pittsburgh, incorporating purely unlabelled target-domain data reduces the performance gap from 5 to 0.5 mIoU. These results highlight the potential of SSL as a powerful tool for solving the online mapping problem, significantly reducing reliance on labelled data.
We completely classify the orientable infinite-type surfaces $S$ such that $\operatorname{PMap}(S)$, the pure mapping class group, has automatic continuity. This classification includes surfaces with noncompact boundary. In the case of surfaces with finitely many ends and no noncompact boundary components, we prove the mapping class group $\operatorname{Map}(S)$ does not have automatic continuity. We also completely classify the surfaces such that $\overline{\operatorname{PMap}_c(S)}$, the subgroup of the pure mapping class group composed of elements with representatives that can be approximated by compactly supported homeomorphisms, has automatic continuity. In some cases when $\overline{\operatorname{PMap}_c(S)}$ has automatic continuity, we show any homomorphism from $\overline{\operatorname{PMap}_c(S)}$ to a countable group is trivial.
Javier Aramayona, Julio Aroca, María Cumplido
et al.
A Cantor surface $\mathcal C_d$ is a non-compact surface obtained by gluing copies of a fixed compact surface $Y^d$ (a block), with $d+1$ boundary components, in a tree-like fashion. For a fixed subgroup $H<Map(Y^d)$ , we consider the subgroup $\mathfrak B_d(H)<Map(\mathcal C_d)$ whose elements eventually send blocks to blocks and act like an element of $H$; we refer to $\mathfrak B_d(H)$ as the block mapping class group with local action prescribed by $H$. The family of groups so obtained contains the asymptotic mapping class groups of \cite{SW21a,ABF+21, FK04}. Moreover, there is a natural surjection onto the family symmetric Thompson groups of Farley--Hughes \cite{FH15}; in particular, they provide a positive answer to \cite[Question 5.37]{AV20}. We prove that, when the block is a (holed) sphere or a (holed) torus, $\mathfrak B_d(H)$ is of type $F_n$ if and only if $H$ is of type $F_n$. As a consequence, for every $n$, $Map(C_d)$ has a subgroup of type $F_n$ but not $F_{n+1}$ which contains the mapping class group of every compact subsurface of $\mathcal C_d$.
The space mapping technique is used to efficiently solve complex optimization problems. It combines the accuracy of fine model simulations with the speed of coarse model optimizations to approximate the solution of the fine model optimization problem. In this paper, we propose novel space mapping methods for solving shape optimization problems constrained by partial differential equations (PDEs). We present the methods in a Riemannian setting based on Steklov-Poincaré-type metrics and discuss their numerical discretization and implementation. We investigate the numerical performance of the space mapping methods on several model problems. Our numerical results highlight the methods' great efficiency for solving complex shape optimization problems.
Maryam Barzegar, Abbas Rajabifard, Mohsen Kalantari
et al.
Property boundaries have a significant importance in cadaster as they define the legal extent of the ownership rights. Among 3D data models, Industry Foundation Class (IFC) provides the potential capabilities for modelling property boundaries in a 3D environment. In some jurisdictions, such as Victoria, Australia, some property boundaries are assigned to the faces of building elements which are modelled as solids in IFC. In order to retrieve these property boundaries, boundary identification analysis should be performed, and faces of building elements should be extracted. However, extracting faces of solids from an IFC file is not possible as faces of solids are not considered as a separate object-type. Therefore, this paper aims to develop a spatial query approach for the identification of property boundaries using 3D spatial operators of a database to address this problem. The viability of the developed approach is tested using an IFC-based 3D cadastral database with two real datasets and one test dataset. The proposed methodology not only supports vertical walls and horizontal roofs but can also be used for detecting boundaries in properties surrounded by complex building structures such as oblique and curved walls and roofs.
The raw-RGB colors of a camera sensor vary due to the spectral sensitivity differences across different sensor makes and models. This paper focuses on the task of mapping between different sensor raw-RGB color spaces. Prior work addressed this problem using a pairwise calibration to achieve accurate color mapping. Although being accurate, this approach is less practical as it requires: (1) capturing pair of images by both camera devices with a color calibration object placed in each new scene; (2) accurate image alignment or manual annotation of the color calibration object. This paper aims to tackle color mapping in the raw space through a more practical setup. Specifically, we present a semi-supervised raw-to-raw mapping method trained on a small set of paired images alongside an unpaired set of images captured by each camera device. Through extensive experiments, we show that our method achieves better results compared to other domain adaptation alternatives in addition to the single-calibration solution. We have generated a new dataset of raw images from two different smartphone cameras as part of this effort. Our dataset includes unpaired and paired sets for our semi-supervised training and evaluation.
Carolyn R. Abbott, Hannah Hoganson, Marissa Loving
et al.
We explicitly construct new subgroups of the mapping class groups of an uncountable collection of infinite-type surfaces, including, but not limited to, free groups, Baumslag-Solitar groups, mapping class groups of other surfaces, and a large collection of wreath products. For each such subgroup $H$ and surface $S$, we show that there are countably many non-conjugate embeddings of $H$ into $\textrm{Map}(S)$; in certain cases, there are uncountably many such embeddings. The images of each of these embeddings cannot lie in the isometry group of $S$ for any hyperbolic metric and are not contained in the closure of the compactly supported subgroup of $\textrm{Map}(S)$. In this sense, our construction is new and does not rely on previously known techniques for constructing subgroups of mapping class groups. Notably, our embeddings of $\textrm{Map}(S')$ into $\textrm{Map}(S)$ are not induced by embeddings of $S'$ into $S$. Our main tool for all of these constructions is the utilization of special homeomorphisms of $S$ called shift maps, and more generally, multipush maps.
We show that a novel, general phase space mapping Hamiltonian for nonadiabatic systems, which is reminiscent of the renowned Meyer-Miller mapping Hamiltonian, involves a commutator variable matrix rather than the conventional zero-point-energy parameter. In the exact mapping formulation on constraint space for phase space approaches for nonadiabatic dynamics, the general mapping Hamiltonian with commutator variables can be employed to generate approximate trajectory-based dynamics. Various benchmark model tests, which range from gas phase to condensed phase systems, suggest that the overall performance of the general mapping Hamiltonian is better than that of the conventional Meyer-Miller Hamiltonian.
The recovery of sports facilities, especially those considered particularly interesting from an historical and cultural perspective, appears today as one of the main challenges to the enhancement of the architectural heritage. In fact, alongside the issues linked to the maintenance of their formal characteristics, the conversion of these spaces into flexible, multifunctional and modern facilities is central to ensuring the economic sustainability of their management, increasingly entrusted to private investors.
This paper presents a hypothesis for the enhancement of the Fausto Coppi Motovelodrome in Turin, a famous facility which was a landmark for cycling and sports lovers in the past century. Together the enhancement of the existing structures, the design proposal provides for the addition of a new building for sports and commercial use. The methodology applied aims at evaluating the benefits of the proposal through a preliminary estimate of the construction costs and the definition of a catchment area and of a possible management scheme, with its costs and revenues. Finally, by simulating alternative scenarios, the incidence of the increase of the commercial surface on the revenues is explored. Lastly, by pointing out which possible future scenarios are plausible for the recovery of the site, the main design proposal relates
to the Feasibility Study and the Call for the assignment of the Motovelodrome, published by the Municipality of Turin in February 2020.
The article deals with the peculiarities of the transformation of the Srivashshya soil in an example of a comparative analysis of soil transformation in the Novotroitsky region and the Azov-Sivash National Natural Park under the influence of natural and anthropogenic factors. Soils of the Northern Pryvashshya, namely Novotroitskiy district, undergo significant transformations caused by anthropogenic activity, quickly lose their positive properties when irrational agricultural use. Long-term use of soils in arable land and, in particular, the use of reclamation measures, predetermine the existence of soil processes that differ from those existing in the natural environment and are currently poorly understood. In todays conditions of use of land resources, precise information is needed on the features of the qualitative state of saline soils for monitoring and rational agricultural use, in connection with which the issues studied are of particular scientific and practical significance. On the basis of the comparative analysis, the differences between soils of agricultural use and soils, which do not undergo anthropogenic influence, that is, are in the natural state within the protected areas, are determined. It is proved that the soils of the protected area in comparison with the soil cover of Novotroitsky district, will not undergo significant anthropogenic influence. The territory of the Novotroitsky district is characterized by large scale devastation of agricultural land.
Abotaleb Sheikhali, Ali Ebadian, Kazem Haghnejad Azar
Let $X,Y,Z$ and $W$ be normed spaces and $f:X\times Y\times Z\longrightarrow W $ be a bounded tri-linear mapping. In this Article, we define the topological centers for bounded tri-linear mapping and we invistagate thier properties. We study the relationships between weakly compactenss of bounded linear mappings and regularity of bounded tri-linear mappings. For both bounded tri-linear mappings $f$ and $g$, let $f$ factors through $g$, we present necessary and suficient condition such that the extensions of $f$ factors through extensions of $g$. Also we establish relations between regularity and factorization property of bounded tri-linear mappings.
This paper introduces an incremental semantic mapping approach, with on-line unsupervised learning, based on Self-Organizing Maps (SOM) for robotic agents. The method includes a mapping module, which incrementally creates a topological map of the environment, enriched with objects recognized around each topological node, and a module of places categorization, endowed with an incremental unsupervised learning SOM with on-line training. The proposed approach was tested in experiments with real-world data, in which it demonstrates promising capabilities of incremental acquisition of topological maps enriched with semantic information, and for clustering together similar places based on this information. The approach was also able to continue learning from newly visited environments without degrading the information previously learned.
A big leap in the agricultural sector is expected thanks to the operational deployment of Copernicus data and services, the new Earth Observation
program of the European Commission. The huge quantity of data delivered freely along with the good level of resolution (spatial, temporal and
spectral) will open up new opportunities for achieving the well-known sustainability of agriculture. At the same time, the new trends of crowdsourcing and citizen science are delivering a great deal of geographical data collected by ordinary users with a bottom-up process. The two type of data and their integration will be the base for the future application in the agricultural sector, albeit management of big geospatial dataset and quality of
user generated data are issues to be addressed.
For today, the main development of a democratic state is to ensure
the improvement of the well-being of each individual citizen.
Having analyzed the experience of the developed European countries,
achievement of this goal is possible only in the conditions of high-quality public
administration, which strengthens democratic institutions, eliminates the inequality of
access to public goods, improves the quality of public services and the standard of
living of the population.
At the present stage, Ukraine, in accordance with the basic provisions of the
European Charter of Local Self-Government, continues to focus its efforts on the
implementation of the European integration course on the development of local and
regional democracy. And decentralization itself is, today, one of the most successful
reforms that is being implemented effectively in the country.
In the context of reforming the public finance system, a tendency towards
decentralization in public administration is relevant, as a result of which a certain
number of powers are transferred to the local authorities.
Thus, financial decentralization can balance the mechanisms of providing
public services with the needs and preferences of local communities.