Hasil untuk "Cartography"

Marco Nisi

The EUSATfinder project addresses the critical challenge of unreliable communications during emergency and rescue operations, particularly in remote or disaster-stricken areas. The solution is centered on the Mobile Operation Center (MOC), a deployable vehicle designed to manage a fleet of drones for in-situ data collection (images, videos, telemetry) and to act as a crucial communication gateway. EUSATfinder synergistically integrates European space assets: it utilizes Satellite Backhaul (SAT- COM), including priority GOVSATCOM services, for the secure transmission of data to remote control centers. It leverages Copernicus services (Rapid Mapping) for enhanced situational awareness. Furthermore, to ensure the secure navigation of Unmanned Aerial Vehicles (UAVs), the system implements Galileo OSNMA signal authentication and advanced GNSS Spoofing Detection (GSD) techniques based on AI. This system establishes a resilient and efficient model for modern disaster management and support for First Responders.

R. C. E. da Silva, A. M. G. Tommaselli, N. N. Imai et al.

Nitrogen content is essential for grass growth, grassland management and forage productivity. In general, the nitrogen amount is indirectly estimated using manual techniques for sample acquisition and laboratory analysis, which are a costly endeavour, mainly in large agricultural areas. In this context, remote sensing technologies allow monitoring important parameters for agriculture, fast, non-destructively and on a large scale, using aerial images obtained by Unmanned Aerial Vehicles (UAV) and analysed through spectral indices and structural variables of the vegetation. However, further studies are needed that use more affordable sensor systems that can be used in large areas, such as in Brazil. This work assesses the feasibility of employing GoPro wide-angle RGB camera onboard a UAV to estimate the nitrogen content of an experimental grassland area. Different data scenarios were evaluated, incorporating combinations of vegetation indices (VIs) and three-dimensional (3D) metrics derived from the Canopy Height Model (CHM): all available metrics (ALL), a subset of three VIs combined with four 3D metrics (VI₃+ CHM₄), and 3D metrics only. To estimate nitrogen content, the Random Forest (RF) machine learning algorithm was applied. The most accurate model, yielding the lowest error, resulted from integrating data from two acquisition dates, achieving a coefficient of determination (R²) of 0.83 for the model, a Pearson Correlation Coefficient (PCC) of 0.82 in the validation trials, and a Root Mean Square Error expressed as a percentage (RMSE%) of 19.62%. These findings highlight the potential of UAV-mounted RGB sensors as an effective tool for estimating pasture parameters.

Redazione MediaGEO

Felipe de Oliveira Passos, Bruno Vargas Adorno, Rodrigo Silva do Carmo et al.

The Atlantic Forest is a global hotspot rich in biodiversity, but highly threatened by deforestation. The study addresses the PRODES Atlantic Forest monitoring system and its remote sensing techniques, as well as the challenges with the adoption of semi-automatic classification algorithms to process time series of images. We highlight the benefits of transitioning from Landsat series to high spatial resolution Sentinel-2 images, and the combination of Sentinel-2 and Sentinel-1 data to improve visualization in some areas where the landscape is impaired due to clouds. We reviewed existing approaches in the literature for semi-automated deforestation detection, including optical data fusion and SAR, discussing the need to improve the monitoring methodology. We emphasize considering local and seasonal factors to accurately detect the removal of the natural vegetation in the Atlantic Forest and we recommend further testing of algorithms based on time series images. Even though it reveals significant patterns, validation still heavily relies on visual interpretation.

Ariel Mera Valverde

Descreveremos a seguir a aplicação do efeito Doppler na determinação das coordenadas de um ponto partindo das informações emitidas pelo Satélite. Relembremos rapidamente que o efeito Doppler é produzido pela variação da frequência de uma onda ao propagar-se com uma certa velocidade, dentro de um meio elástico contínuo, emitida por uma fonte que se desloca também no mesmo meio, e recebida por um ponto em movimento neste mesmo meio.

Lei Huang, Jie Liu, Zhongchang Sun et al.

ABSTRACTIn the past decades, the environment has changed drastically in China with rapid economic development. Lack of data, especially data with spatiotemporal information, has however hindered evaluating progress of environmental indicators in the global Sustainable Development Goal (SDG) framework. Here, we evaluate and explore geospatial information of 20 environmental SDG indicators from six SDGs in China from 2010 to 2020 using big data. We show China has improved rapidly in most of the 20 indicators, except for indicator 13.2.2 (CO2 emission). 63.5% of China’s land mass showed improved states for the SDG indicators. By 2020, four of the indicators were found to have achieved their 2030 targets. It is predicted from the existing data that 10 of the 20 indicators can achieve their targets smoothly by 2030, but two indicators will lag behind. We quantitatively show China’s progress towards the environmental SDG indicators, and put forward timelines and suggestions for policy makers.

Atınç Pırtı

In various parts of the globe, there have been several earthquakes of a modest size. Monitoring the change of the points over time is a key component of typical techniques for extracting dynamic responses. This technique was unable to completely extract all of the earthquake’s dynamic properties. The GNSS precise point positioning (PPP) may be a useful tool for obtaining values of the point’s displacement that are more exact up to millimeters, which can help to overcome these flaws and evaluate the seismic wave of such earthquakes. Ultimately, PPP is a crucial tool for getting the precise observations. In this study, Canadian Spatial Reference System Precise Point Positioning (CSRS-PPP) approach to analyze the station’s displacement components and the station’s heights in periods from the two Kahramanmaraş earthquakes. The earthquake sequences that occurred in Turkey’s Kahramanmaraş in 2023 is an example of complicated faulting brought on by interactions between three plates close to the Hatay Triple Junction (HTJ). While the relative plate movements in this area are minimal (usually less than 10 mm/year), even sluggish plate motion zones may nevertheless see earthquakes that are quite destructive. Due to the three-plate system’s unusual geometry, a number of large earthquakes with very varied fault orientations were active throughout this series. A 7.8-magnitude earthquake happened on February 6, 2023 in southern Turkey, close to Syria’s northern border. A magnitude 7.5 earthquake, situated about 95 kilometers to the southwest, was occurred nine hours after the first one. The first earthquake was as big as the most powerful one ever recorded there in 1939 and was the most catastrophic to strike earthquake-prone Turkey in more than 20 years. In this study, the effects of two earthquakes in Kahramanmaraş were investigated on the Cyprus Arc, the Dead Sea fault, Hatay and the points close to two earthquakes zone. In the obtained results, it was computed that the greatest horizontal displacement occurred at the HAT2 station with 68.97 cm.

R. Shepard, S. Chipman

C. Jiao, M. Heitzler, L. Hurni

Long-term retrospective road data are required for various analyses (e.g., investigation of urban sprawl, analysis of road network evolution). Yet, it is challenging to extract roads from scanned historical maps due to their dissatisfying quality. Although deep learning has been exerting its superiority in image segmentation, its application to road extraction from historical maps is rarely seen in existing studies. Deep learning usually requires quite large amounts of training data, which is time-consuming and tedious to label. Data augmentation can to some extent solve this issue. The existing data augmentation techniques vary each training sample as a whole (e.g., rotation, flipping). But some features or symbols on maps will never occur in practice when they are rotated or flipped (e.g., numbers, labels). To solve this problem and to further improve the diversity of training samples, we propose a novel data augmentation method, which varies the target features instead of the whole training sample. The method is validated by applying it to road extraction from the historical Swiss Siegfried map. The experiment results show the effectiveness of the proposed method.

Sergey N. Krivoshapko, Mathieu Gil-oulbé

A class of developable surfaces contains cylindrical, conical, and tangential developable surfaces. Tangential developable surfaces are ruled surfaces of zero Gaussian curvature with cuspidal edges. They give great opportunities to architects and engineers for realization of their creative projects. Both the theoretical researches in the area of geometry of torses and strength analysis of shells and the influence of these researches on the application of torses in practice are shown. A presented research demonstrated that torses found the application in shipbuilding, aircraft construction, mechanical engineering, in architecture and building, engineering equipment and communications, in road building, in anti-erosive banks, topography, and cartography, clothing articles of light industry, in sculptural forms, and in modelling with developable surfaces. It was confirmed by the references on great number of published works on the subject, real examples from practice, and by handing in 14 illustrations of real objects.

GRZEGORZ FRANCZAK

This paper focuses on one particular aspect of the way in which 16th-century Polish authors ghostmapped the European East: the semantics assumed by the choronym “Russia” in Renaissance cartography which reflected the long‐lasting rivalry between Polish-Lithuanian Commonwealth and Muscovy for the possession of the territories of the former Kievan Rus’. After a brief sketch of the theoretical and historical framework, I provide an overview of European cartographical texts, from Beneventano to Waldseemüller and Mercator, influenced by the Polish ghostmappers of Muscovy – Wapowski, Miechowita, and Strubicz – who tried to narrow the toponym “Russia” to the lands controlled by Poland and Lithuania.

G. Andrienko, N. Andrienko

Samuli Laato, Tarja Pietarinen, Sampsa Rauti et al.

Studies on location-based games ubiquitously report positive learning outcomes for the players. Particularly these games are shown to promote exercise, encourage to social interaction and increase geographical and cartographical knowledge. To find out whether these positive effects are game-specific or characteristic to all location-based games, we conduct a software search for available location-based games on iOS and Android platforms and evaluate if and how exercise, cartographical training and social interaction are supported. Based on our results we were able to identify six sub-genres of location-based games, and the positive effects associated with each genre. The most popular category in terms of number of games was scavenger hunts and the most popular category in terms of active installs on Android and iOS was location-based MMORPG’s. Presence of factors associated with immersion and mixed reality were paired with the popularity and positive outcomes of the games. Cartographical practise, social interaction and exercise were supported the most in the location-based MMORPG sub-genre, to which, for example, Pokémon GO belongs to.

Simon Iain Hay, K. Battle, D. Pigott et al.

The primary aim of this review was to evaluate the state of knowledge of the geographical distribution of all infectious diseases of clinical significance to humans. A systematic review was conducted to enumerate cartographic progress, with respect to the data available for mapping and the methods currently applied. The results helped define the minimum information requirements for mapping infectious disease occurrence, and a quantitative framework for assessing the mapping opportunities for all infectious diseases. This revealed that of 355 infectious diseases identified, 174 (49%) have a strong rationale for mapping and of these only 7 (4%) had been comprehensively mapped. A variety of ambitions, such as the quantification of the global burden of infectious disease, international biosurveillance, assessing the likelihood of infectious disease outbreaks and exploring the propensity for infectious disease evolution and emergence, are limited by these omissions. An overview of the factors hindering progress in disease cartography is provided. It is argued that rapid improvement in the landscape of infectious diseases mapping can be made by embracing non-conventional data sources, automation of geo-positioning and mapping procedures enabled by machine learning and information technology, respectively, in addition to harnessing labour of the volunteer ‘cognitive surplus’ through crowdsourcing.

F. O. Bjørnson, Torgeir Dingsøyr

Software engineering is knowledge-intensive work, and how to manage software engineering knowledge has received much attention. This systematic review identifies empirical studies of knowledge management initiatives in software engineering, and discusses the concepts studied, the major findings, and the research methods used. Seven hundred and sixty-two articles were identified, of which 68 were studies in an industry context. Of these, 29 were empirical studies and 39 reports of lessons learned. More than half of the empirical studies were case studies. The majority of empirical studies relate to technocratic and behavioural aspects of knowledge management, while there are few studies relating to economic, spatial and cartographic approaches. A finding reported across multiple papers was the need to not focus exclusively on explicit knowledge, but also consider tacit knowledge. We also describe implications for research and for practice.

D. Cosgrove

G. Dall’O’, Annalisa Galante, M. Torri

D. Ballas, D. Dorling, Benjamin D. Hennig

ABSTRACT Analysing the regional geography of poverty, austerity and inequality in Europe: a human cartographic perspective. Regional Studies. This paper presents a human cartographic approach to the analysis of the impact of austerity and the economic crisis across Europe’s regions. It reflects on past insights and debates on the analysis and mapping of poverty and wealth, and of the effects of austerity in particular. It then presents a wide range of cartograms highlighting social and spatial inequalities across Europe. Finally, the paper highlights the increasingly important role of the field of regional studies in current debates about the future of the European project and of the possibility of a Europe of regions rather than a Europe of nation-states.

Donato Abruzzese, Enrico Lo Re, Silvio Pierdiluca et al.

Nuovo sistema di database con strumenti GIS e BIM per la gestione intelligente e funzionale di risorse sul territorio. Applicazione a progetto pilota sul territorio della cittí  di Roma.

Maneesh Agrawala, Chris Stolte