bluuebunny/crossref_metadata_2025 huggingface dataset:
Rembrandt Seen Through Jewish Eyes
Authors: Knotter Mirjam , Schwartz Gary
Published: December 2023

The earliest painting by Rembrandt whose owner is documented depicts the prophet Balaam, on his way to blessing Israel. The man who bought it was a Sephardi Jew in the service of Cardinal Richelieu of France. The first known buyer of an etching plate by Rembrandt, depicting Abraham Dismissing Hagar and Ishmael, was a Sephardi Jew of Amsterdam. Seen through their eyes, Rembrandt was the creator of images with a special meaning to Jews. They have been followed through the centuries by Jewish collectors, Jewish art historians, Jewish artists who saw their own deepest concerns modelled in his art and life, and even prominent rabbis, one of whom said that Rembrandt was a Tzadik, a holy man blessed by God.

This book is the first study in depth of the potent bond between Rembrandt and Jews, from his time to ours, a bond that has penetrated the image of the artist and the people alike.
The current status and implications of the medical insurance fee schedule in Japan
Authors: Shin Yohan , Kim Kye Hyun , Moon Sung Je , Kang Joohyun
Published: December 2023

Background: Korea has the most rapidly aging population in the world. Medical costs for the elderly are quickly increasing, which raises concerns about the sustainability of health insurance finances. Accordingly, the need to allocate limited medical resources efficiently has increased, with improving the fee schedule seen as an effective way to achieve this. Japan has experienced a super-aging society for at least 20 years prior to Korea and has been successful in improving its fee schedule. Korea’s fee schedule, however, needs to overcome the challenge of being relatively limited in type and simplicity.Current Concepts: The new patient consultation fee in Japan is the same regardless of the type of medical institution and is approximately 40% higher than found in Korea. In the case of established patient consultations, the fee for medical institutions with fewer than 200 beds are substantially higher than for large medical institutions, thereby suppressing re-examination at large hospitals. Japan’s additional points consist of 71 types of items, which is more diverse than Korea’s 28 types, and the additional points for children under six years of age, holidays, and late nights are set significantly higher than that found in Korea.Discussion and Conclusion: Japan designed its fee schedule to structurally reduce the consumption of medical resources and to effectively compensate for the behavior of medical providers. This policy is a standard which Korea’s fee schedule should aim for. In the future, it will be necessary to prepare measures to respond to the super-aging environment through detailed research concerning Japan’s fee schedule.
Casa de vó (ou 20 metros de papéis sociais)
Authors: Miola Gabriela Canale
Published: December 2023

Este ensaio visual é composto por fotoperformances que refletem as relações entre gênero, papeis sociais e arquitetura por meio de ações realizadas durante uma residência artística no interior de Minas Gerais em 2023. Na parte mais distante do espaço da residência, há uma pequena casa, a qual guarda uma arquitetura de ressonância colonial. A escala é reduzida, dando a sensação de se estar em uma casinha de brinquedo de crianças. “Parece uma casa de vó” e “parece uma casa de mãe” eram algumas das frases que repetiam os artistas quando conheciam o espaço. O feminino costurado ao doméstico me espanta: à casa se devota o corpo, os tempos e a força de trabalho gratuita feminina doméstica. Você sabe o nome que tem a força de trabalho gratuita, mas vou evitar escrever porque estes séculos, repetindo que ela era sinônimo de dom e de amor, nos impedem.
Na pequenina sala da ‘casa de vó’, me dedico um dia todo a preencher 20 metros de uma bobina de papel daqueles em que se registram valores de compras nas lojas. Registram o dinheiro que se trocar por um bem ou serviço. Neste suporte, me dedico a uma escrita rápida: quero enchê-lo com uma lista de produtos e serviços cujo valor nossa sociedade não contabiliza. Para isso, este formato de bobina de nota fiscal é interessante. Também uso uma metáfora óbvia e até mesmo ingênua: listo os papéis sociais nos 20 metros de papel. Jogo com o sentido de papel, no sentido de papel social “role”, to play, to perform, do inglês sobreposto ao sentido de “papel” de paper. Escrevo sobre o papel uma lista de papeis sociais performáticos (Taylor, 2013) desempenhados gratuitamente (Federici, 2021), forçosa e sutilmente (Butler, 2003) por seres humanos a quem se atribui o epíteto de mulheres.
Improving Data Analysis by Testing by Betting: Optional Continuation and Descriptive Statistics
Authors: Shafer Glenn
Published: December 2023

When testing a statistical hypothesis, is it legitimate to deliberate on the basis of initial data about whether and how to collect further data? Game-theoretic probability’s fundamental principle for testing by betting says yes, provided that you are testing the hypothesis’s predictions by betting and do not risk more capital than initially committed. Standard statistical theory uses Cournot’s principle, which does not allow such optional continuation. Cournot’s principle can be extended to allow optional continuation when testing is carried out by multiplying likelihood ratios, but the extension lacks the simplicity and generality of testing by betting.
Testing by betting can also help us with descriptive data analysis. To obtain a purely and honestly descriptive analysis using competing probability distributions, we have them bet against each other using the principle. The place of confidence intervals is then taken by sets of distributions that do relatively well in the competition. In the simplest implementation, these sets coincide with R. A. Fisher’s likelihood ranges.
Image-Maker in Residence: Year-End Editorial 2023
Authors: Kalivis George
Published: December 2023

From the smell of politics to the power of archives, and from colonial sandwiches to more-than-human agriculture: curator George Kalivis looks back on the breadth and depth of 2023’s sociologically rich and visually inventive Image-Makers in Residence at the Sociological Review Foundation.
Comentarios en dos tiempos para introducir un dossier sobre 40 años de democracia en Argentina (scriptum y postscriptum en tiempos electorales)
Authors: Diamant Ana , García Natalia
Published: December 2023

Comentarios en dos tiempos para introducir un dossier sobre 40 años de democracia en Argentina (scriptum y postscriptum en tiempos electorales)
Carrizo, B. y Giménez, J. C. (coordinadores) (2022). Sinfonía Mantovani. Polifonía de un intelectual entre educación y política. 1ra edición. Rosario: CB Ediciones, 340 pp. ISBN 978-987-48133-8-1
Authors: Guida María Eugenia
Published: December 2023

Carrizo, B. y Giménez, J. C. (coordinadores) (2022). Sinfonía Mantovani. Polifonía de un intelectual entre educación y política. 1ra edición. Rosario: CB Ediciones, 340 pp. 
ISBN 978-987-48133-8-1
Peran Kepemimpinan Kepala Sekolah Perempuan Pada Sekolah Negeri Di UPTD SMPN 4 Pesawaran
Authors: Kohar Koharuddin , Patimah Siti
Published: December 2023

Penelitian ini bertujuan untuk mendeskripsikan kepemimpinan seorang kepala sekolah perempuan di UPTD SMPN 4 Pesawaran. Penelitian ini merupakan penelitian kualitatif dengan desain studi kasus. Prosedur pengumpulan data meliputi observasi, wawancara mendalam, dan studi dokumentasi. Analisis data dilakukan dengan menggunakan pola data interaktif. Validitas data diperiksa melalui metode triangulasi dan pemeriksaan oleh anggota. Hasil penelitian menunjukkan bahwa efektivitas kepemimpinan dalam mewujudkan sekolah yang efektif tidak ditentukan oleh karakteristik gender. Kunci keberhasilan kepala sekolah perempuan dalam mewujudkan sekolah yang efektif ditentukan oleh kemampuannya untuk merancang dan mewujudkan visi, misi, dan tujuan sekolah serta kemampuannya dalam mengelola sekolah secara efektif melalui pemanfaatan seluruh potensi sekolah serta kolaborasi sinergis dengan para pemangku kepentingan sekolah.
Afrontando la exclusión y la brecha digital mediante un uso humano de las TIC
Authors: PEÑACOBA ARRIBAS ALEJANDRA , Muñoz Alcón Ana Isabel , PARRA BERNAL LINA ROSA , GONZÁLEZ CASTRO CLAUDIA
Published: December 2023

Las tecnologías digitales ofrecen un acceso universal e instantáneo a la información y la comunicación, incrementando con ello las oportunidades de aprendizaje, innovación, inclusión educativa y participación social de las personas. No obstante, en la última década se han acentuado en un mundo globalizado profundas diferencias en el acceso y uso de las TIC. Al mismo tiempo, existe el riesgo de que éstas se vacíen de contenido y de valores y no respeten los derechos o la dignidad de las personas. El presente artículo pretende dar respuesta, a través de una revisión bibliográfica de fuentes, tanto de la literatura educativa como oficiales, a los retos planteados por el rápido desarrollo de las tecnologías digitales y por el sentido y las implicaciones éticas de la innovación y el desarrollo tecnológico educativo en el marco de la brecha digital. Los resultados encontrados detectan una doble vertiente de usos positivos como negativos de las TIC y apuntan a la educación como elemento clave para promover la formación en el uso crítico de las tecnologías digitales. Asimismo se muestra necesario fomentar el compromiso ético en la competencia digital, que permita un uso más humano e inclusivo de los medios tecnológicos.
El papel de la cosmovisión cristiana en el origen y la preservación del conocimiento científico
Authors: Baviera Tomás
Published: December 2023

Cuando algunos científicos reivindican una visión atea, en realidad perjudican más a la ciencia que a la fe. La ciencia moderna solo pudo nacer en una cosmovisión moldeada por el Dios bíblico. El marco de la Creación y el hecho de la Resurrección hicieron posible el desarrollo del método científico. Por este motivo, cuando la ciencia se desarraiga del entorno que la hizo florecer, de hecho, se vuelve más frágil. Una ciencia sin Dios corre el riesgo de quedar sometida a la arbitrariedad del poder. De ahí que la fe y la razón se necesiten mutuamente hoy más que nunca.
Editorial
Authors: Beltrame de Moura Aline , Posenato Naiara
Published: December 2023

The Latin American Journal of European Studies (ISSN 2763-8685) is a publication of the Latin American Center of European Studies, created from the BRIDGE Project of Jean Monnet Network with funding from the Erasmus + Program of the European Commission. With a focus on the editorial lines on European Union Law and Policies and International Relations of the European Union with third countries and Latin America, the sixth edition of the Journal also has a thematic dossier on “Regional Data Protection Policy and Artificial Intelligence”, organized by Naiara Posenato of the Università degli Studi di Milano, (Italy). The sixth edition of the Journal is open for submissions until November 1st, 2023.
The biometric habeas data in the digital and algorithmic era in the European Union
Authors: Fanni Simona
Published: December 2023

The advent of artificial intelligence and of the Big Data has affected the use of biometric data in the digital and algorithmic era, posing some critical challenges, especially in relation to the risk of surveillance, data scraping and profiling. In this context, the emergence of a novel “informationally projected corporality” requires law to rethink its approach to data protection and to define an Habeas Data for this transformation, and, in this sense, the European Union (EU) has been demonstrating to be a global leader. Under this premise, the purpose of this paper is to explore the relevant primary and secondary EU law sources, in order to provide a critical assessment of their role with respect to the challenges related to the protection of biometric data in the digital and algorithmic era. In light of this reflection, the paper develops some final considerations. In particular, it takes the view that the EU, so far, has defined a significant framework for the protection of the regional Habeas Data with respect to biometric data. However, the most pioneering change is still to come. In this respect, the paper suggest that the AI Act Proposal has the potential for bridging the current legal landscape and the future horizons of EU law and its biometric Habeas Data. Some reference is made to justiciability and to the role that the Court of Justice of the European Union (ECJ) may play, also by promoting judicial dialogue with the European Court of Human Rights (ECtHR). From the methodological viewpoint, an in-depth analysis of the relevant EU law sources and of the relevant case law of the ECJ was carried out, and some critical comparison with the jurisprudence of the ECtHR was made. Moreover, scholarship in English, Spanish and Italian was widely explored.
EFETIVIDADE DAS AUDIÊNCIA DE MEDIAÇÃO E CONCILIAÇÃO ONLINE
Authors: Bessa Adriana Damas , Nascimento Alaide Custodia Lima
Published: December 2023

Com a rápida digitalização, compreender os pontos fortes e fracos das audiências online torna-se essencial para aprimorar e desenvolver estratégias mais efetivas na resolução de disputas. Sendo assim, o estudo em questão teve como objetivo explorar, mediante emprego da revisão bibliográfica, sobre a efetividade das audiências de mediação e conciliação online em relação às suas contrapartes presenciais. As audiências de mediação e conciliação digitais representarem atualmente uma abordagem da política judiciária de acesso à justiça, porém, persistem dúvidas quanto à sua implementação. Assim sendo, embora as sessões online possam ser tão eficazes quanto as presenciais, é crucial considerar esses aspectos para manter a qualidade e a eficiência do processo na busca por acordos satisfatórios. Apesar dos desafios, as audiências virtuais têm conquistado aceitação e popularidade, especialmente em situações onde a presença física não é crucial. Com avanços tecnológicos e diretrizes claras para sua realização, elas continuam a ser uma opção valiosa e conveniente para resolver conflitos Portanto, apesar dos desafios inerentes às sessões virtuais, é inegável que elas oferecem uma alternativa valiosa e eficaz para a busca de acordos satisfatórios.
Long-term Variability in Black Carbon Emissions Constrained by Gap-filled Absorption Aerosol Optical Depth and Associated Premature Mortality in China
Authors: Zhao Wenxin , Zhao Yu , Zheng Yu , Chen Dong , Xin Jinyuan , Li Kaitao , Che Huizheng , Li Zhengqiang , Ma Mingrui , Hang Yun
Published: December 2023

Abstract. Black carbon (BC) plays an important role in air quality, public health, and climate, while its long-term variations in emissions and health effect were insufficiently understood for China. Here, we present the spatiotemporal evolution of BC emissions and the associated premature mortality in China during 2000–2020 based on an integrated framework combining satellite observations, a machine learning technique, a “top-down” inversion approach, and an exposure-response model. We found that the “bottom-up” approach likely underestimated BC emissions, particularly in less developed western and remote areas. Pollution controls were estimated to reduce the annual BC emissions by 26 % during 2010–2020, reversing the 8 % growth during 2000–2010. BC emissions in the main coal-producing provinces declined by 2010 but rebounded afterwards. By contrast, provinces with higher economic and urbanization levels experienced emission growth (0.05–0.10 Mg/km2/yr) by 2010 and declined greatly (0.07–0.23 Mg/km2/yr) during 2010–2020. The national annual BC-associated premature mortality ranged between 733,910 (95 % confidence interval: 676,790–800,250) and 937,980 cases (864,510–1,023,400) for different years. The changing BC emissions contributed 78,590 cases (72,520–85,600) growth within 2000–2005 and 133,360 (123,150–145,180) reduction within 2010–2015. Strategies differentiated by region are needed for further reducing BC emissions and its health and climate impacts.
RoadSurf 1.1: open-source road weather model library
Authors: Karsisto Virve Eveliina
Published: December 2023

Abstract. Icy and snowy road conditions cause problems in many countries where temperature often drops below zero degrees. Preventive actions are necessary to keep roads ice-free and to optimize maintenance operations. Accurate road surface temperature and road condition forecasts are an essential help for road maintenance crews to plan their actions. Finnish Meteorological institute (FMI) has produced road weather forecasts for many years with the house-made road weather model RoadSurf to aid local road authorities. Recently, FMI published an open-source road weather model library that consists of RoadSurf functions. The open publication provides an opportunity for many institutes and companies to use the library in road weather forecasting. The evaluation of the library shows that it is well suited for forecasting road surface temperature.
Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling
Authors: Araya Diego , Mendoza Pablo A. , Muñoz-Castro Eduardo , McPhee James
Published: December 2023

Abstract. Dynamical (i.e., model-based) methods are widely used by forecasting centers to generate seasonal streamflow forecasts, building upon process-based hydrological models that require parameter specification (i.e., calibration). Here, we investigate the extent to which the choice of calibration objective function affects the quality of seasonal (spring–summer) streamflow hindcasts produced with the traditional ensemble streamflow prediction (ESP) method and explore connections between hindcast skill and hydrological consistency – measured in terms of biases in hydrological signatures – obtained from the model parameter sets. To this end, we calibrate three popular conceptual rainfall-runoff models (GR4J, TUW, and Sacramento) using 12 different objective functions, including seasonal metrics that emphasize errors during the snowmelt period, and produce hindcasts for five initialization times over a 33-year period (April 1987–March 2020) in 22 mountain catchments that span diverse hydroclimatic conditions along the semiarid Andes Cordillera (28–37∘ S). The results show that the choice of calibration metric becomes relevant as the winter (snow accumulation) season begins (i.e., 1 July), enhancing inter-basin differences in hindcast skill as initializations approach the beginning of the snowmelt season (i.e., 1 September). The comparison of seasonal hindcasts shows that the hydrological consistency – quantified here through biases in streamflow signatures – obtained with some calibration metrics (e.g., Split KGE (Kling–Gupta efficiency), which gives equal weight to each water year in the calibration time series) does not ensure satisfactory seasonal ESP forecasts and that the metrics that provide skillful ESP forecasts (e.g., VE-Sep, which quantifies seasonal volume errors) do not necessarily yield hydrologically consistent model simulations. Among the options explored here, an objective function that combines the Kling–Gupta efficiency (KGE) and the Nash–Sutcliffe efficiency (NSE) with flows in log space provides the best compromise between hydrologically consistent simulations and hindcast performance. Finally, the choice of calibration metric generally affects the magnitude, rather than the sign, of correlations between hindcast quality attributes and catchment descriptors, the baseflow index and interannual runoff variability being the best predictors of forecast skill. Overall, this study highlights the need for careful parameter estimation strategies in the forecasting production chain to generate skillful forecasts from hydrologically consistent simulations and draw robust conclusions on streamflow predictability.
THE IMPACT OF ORBITAL AND CLOCK ERRORS ON POSITIONING FROM LEO CONSTELLATIONS AND PROPOSED ORBITAL SOLUTIONS
Authors: El-Mowafy A. , Wang K. , Li Y. , Allahvirdi-Zadeh A.
Published: December 2023

Abstract. Two approaches are discussed for the estimation and prediction of the orbits of low earth orbit (LEO) satellites that can be used for navigation. The first approach relays on using a ground monitoring network of stations. The procedures to generate the LEO orbital products in this approach are proposed at two accuracy levels to facilitate different positioning applications. The first type targets producing orbits at meter-level accuracy, defined here as LEO-specific broadcast ephemeris. The second type of products would produce orbits with an accuracy of cm as polynomial corrections to the first type of orbits. Real and simulated LEO satellite data is used for testing, mimicking LEO satellites that can be used for positioning. For the first type of products, it was found that orbital prediction errors play the dominant role in the total error budget, especially in cases of mid and long-term prediction. For the second type of products, the predicted orbits within a short period of up to 60 s generate errors at a few cm, and fitting the corrections with a quadratic polynomial reduced the fitting range errors to the cm level compared to the case of applying a linear polynomial. This level of accuracy can fulfill the requirement for precise point positioning (PPP). The second approach is computing the orbits in real time applying the kinematic or reduced-dynamic mode, where the orbits are computed in the PPP mode using GNSS observations collected onboard LEO satellites and the GNSS orbits and clock products are received through inter-satellite links such as the free-access SouthPAN service in Australia, Galileo HAS, or Beidou (BDS-3, PPP-B2b service). The limitations of this approach and preliminary results are given. Furthermore, the LEO satellite clocks determined together with the orbits in the reduced-dynamic LEO satellite orbit process in near-real-time are also analysed. Finally, the impact of possible orbital and clock errors in the range of decimetres to several meters of LEO satellites on positioning performance is analysed.
QUALITY ANALYSIS OF SMARTPHONE GNSS OBSERVATIONS AND IMPACT ON PRECISE POSITIONING
Authors: Zangenehnejad F. , Gao Y.
Published: December 2023

Abstract. The use of low-cost and ultra-low-cost receivers such as smartphones and wearables has been raising these days due to their affordability and widespread availability. Along with the release of Android Version 7 in 2016, the raw GNSS measurements became accessible through the location API, which includes the GNSSMeasurement class and GNSSClock class. However, the users are required to extract the typical GNSS observations, such as pseudorange, carrier-phase, and Doppler observations, from the raw data coming from these two classes. It should be mentioned some quality concerns may arise during the conversion process from the raw GNSS measurements to the typical GNSS measurements. These quality concerns would subsequently affect GNSS data processing such as cycle slip detection, code smoothing and ultimately positioning performance. In this paper, we first analyse the quality of GNSS observations logged from smartphones. Furthermore, we address potential issues that can arise during the generation of GNSS observations. We also introduce our developed in-house software, UofC CSV2RINEX, which is designed to convert CSV files into RINEX files.
KEY TECHNOLOGIES FOR 1:10,000 RAPID MAPPING BASED ON GF-7 SATELLITE
Authors: Liu J. W. , Liu J. J. , Zhao B. L. , He X. , Zhao S. Q. , Wu C. C.
Published: December 2023

Abstract. In order to solve the problems of low efficiency, high cost and long cycle of the traditional 1:10000 basic geographic information data production method (aerial photography combined with field mapping), this paper proposes a 1:10000 rapid mapping method based on GF-7 satellite data. It solves the key technical difficulties of automatic information recognition, extraction, integration and mapping of water body, building, road, vegetation, contour, and other elements. And an automatic software system of “image -> patch -> data -> map” is developed, which realizes the rapid production of 1:10000 basic geographic information data products and improves the ability of high-precision basic geographic information resource construction.
BEDOI: BENCHMARKS FOR DETERMINING OVERLAPPING IMAGES WITH PHOTOGRAMMETRIC INFORMATION
Authors: Zhan H. , Yu Y. F. , Xu Y. W. , Hou Q. B. , Xia R. , Wang X. , Feng Y. , Zhan Z. Q. , Li M. L. , Gruber M. , Hänsch R. , Heipke C.
Published: December 2023

Abstract. For conventional SfM pipeline, image matching is enduring limitation when considering the time efficiency. In the last few years, to speed up image matching procedure, many image retrieval works were proposed to fast find overlapping image pairs, e.g., bag-of-word that clusters hand-crafted local features in a hierarchical way for efficient similar image retrieval, or learning-based global features (such as, VGG or ResNet) are used to represent image in a global compact manner. However, there are rarely benchmarks with referenced overlapping information to: first, evaluate the retrieval performance; second, fine tune deep-learning models along the direction that is more capable to deal with overlapping image pairs.In this work, based on traditional photogrammetric procedures, relevant photogrammetric information is obtained including image orientation parameters, 3D mesh model and etc., we then generate a benchmark for determining Overlapping Images - BeDOI, in which referenced pairwise overlapping relationships are estimated via rigorous photogrammetric geometry. To extend the generality, in total, BeDOI contains 13667 images which are basically UAV and close-range images of various scene categories, e.g., urban cities, campus, village, historical relics, green land, buildings and etc. Lastly, to demonstrate the efficacy of the proposed BeDOI, several image retrieval methods are tested and the experimental results are reported as a competition challenge.
LOW-COST WORKFLOW FOR 3D URBAN FOREST VIRTUAL RECONSTRUCTION
Authors: Chioni C. , Murtiyoso A. , Favargiotti S. , Massari G. A.
Published: December 2023

Abstract. This contribution addresses, on one hand, the increasing need and demand of 3D data (e.g., point clouds) in urban forestry – for monitoring, analysis, and visualisation purposes –, on the other, the lack of standardised procedures to manage them, also towards engaging and empowering the broader audience. Practitioners in landscape architecture – as a potential bridging field between forestry, geomatics and computer science – could ‘smartly’ manage dynamic ecosystems as forests, parks, and gardens in urban contexts if efficiently provided with digital tools, technologies and techniques for design-oriented information. To this end, a low-cost workflow for 3D virtual reconstruction of under-storey urban vegetation is here proposed to allow exploiting the aesthetic, analytical, and generative potential of 3D point clouds in landscape and urban design. As a proof-of-concept, a combination of a wide range of methods (e.g., spherical photogrammetry, point cloud modelling, virtual reality), tools (e.g., 360° camera, tablet with lidar sensor), and software (e.g., Agisoft Metashape, 3DF Zephyr, CloudCompare, Unity) is tested in the development of a virtual plot of the Mesiano University park in Trento (Italy). Covering all the different steps of the information management activities (namely acquisition, processing, and visualisation), the presented workflow enables a GIS-based, texturized, real-world 3D point cloud rendering of urban forests to be intuitively and interactively experienced in Virtual Reality.
CLASSIFICATION OF TREES IN HYPERSPECTRAL CANOPY DATA USING MACHINE LEARNING: COMPARATIVE ANALYSIS OF FOREST STRUCTURE COMPLEXITY
Authors: Galdames F. , González P. , Magni-Pérez F. , Funk S. M. , Lepín F. , Saavedra R. , Hernández H. J.
Published: December 2023

Abstract. The classification of tree species by remote sensing is an important task with a broad range of applications, including forest management, environmental monitoring, and climate change studies. Hyperspectral imaging has proven to be a valuable tool for this classification. Additionally, deep learning techniques have obtained outstanding results in hyperspectral classification. In this study, we apply a neural network to the classification of aerial hyperspectral images of trees. The study was conducted at a research station in southern Chile with 32 tree species. Our database has 3080 tree canopies that have been manually segmented and classified. The goal of the work was to study the correlation between forest structure complexity and classification performance across three different forest conditions: native forest, plantation of native species, and plantation of exotic species. The results show that classification performance is higher when forest structure and composition are simpler. We used a ResNet neural network as classifier and compared its performance with support vector machine and random forest. The best performance was obtained using ResNet in exotic plantations, the forest condition with the simplest structure, achieving an F1-score of 85.23%.
TREE-LEVEL FUEL CONNECTIVITY TO ASSESS CROWN WILDFIRE POTENTIAL BY UAS-BASED PHOTOGRAMMETRY
Authors: Herrero-Huerta M. , Sánchez-Jiménez D. , del Campo-Sanchez A. , Cifuentes-Jimenez D. , Piedelobo-Martín L. , de Andres-Anaya P. , Gonzalez-Gonzalez E. , Yali Samaniego R. , del Pozo S. , Hernandez-Lopez D. , Lagüela S. , González-Aguilera D.
Published: December 2023

Abstract. Evaluating the potential for crown fires remains a pivotal concern in wildfire management because it affects fire behavior, causing them to spread further. In this work, we propose a methodology to assess crown fire potential based on the tree connectivity at crown level from UAS (Unmanned Aircraft Systems)-based Structure-from-Motion Photogrammetry. The approach is usable in a large landscape with the aim of reducing crown fire potential by considering the spatial variability of fuels within a stand. The utilization of UAS for photogrammetry holds immense promise in transforming the approach to assessing and managing forest fires. This cutting-edge technology offers the potential to deliver highly precise and comprehensive data concerning forest structure and connectivity, thereby presenting a groundbreaking opportunity for enhanced forest fire analysis and control.
UPDATING ABOVEGROUND BIOMASS AT A PAN-EUROPEAN SCALE THROUGH SATELLITE DATA AND ARTIFICIAL INTELLIGENCE
Authors: Pirotti F. , González-Olabarria J. R. , Kutchartt E.
Published: December 2023

Abstract. In this work, an ensemble of machine learning algorithms was trained using stratified sampling from an existing European-scale biomass map from 2018 to predict an updated version for 2020. The objective of stratification is to make sure that the full range of biomass values is represented. The sampled biomass values from 2018 were filtered to remove areas that did were subject to forest disturbances between 2018 and 2020. This information was available from forest cover/loss/gain maps derived from satellite imagery. We train using a total of 49 features derived from the following sources: bioclimatic data, maps of land-cover, tree cover, tree height, annual composites of vegetation indices per pixel (EVI and NDVI) obtained from Sentinel-2, radar backscatter median annual values from Sentinel-1 and ALOS-2, and the ALOS DSM (3D) elevation grid. A model was created dividing Europe into 19 tiles to limit variability due to very different bioclimatic zones. The result is a raster with 100 m × 100 m resolution and an estimated value of biomass (Mg ha−1) at each node. Overall results on validation data over Europe report a root mean square error (RMSE) of 32.4 Mg ha−1 and a mean absolute error (MAE) of 21.5 Mg ha−1; when considering single tiles, the largest RMSE was 54.7 Mg ha−1 in tile D2, which can be explained by the very high variance of climate, environment, terrain topography and biomass values as the tile enclosed the Alpine region and the western part of Eastern Europe.
COMBINING YOLO V5 AND TRANSFER LEARNING FOR SMOKE-BASED WILDFIRE DETECTION IN BOREAL FORESTS
Authors: Raita-Hakola A.-M. , Rahkonen S. , Suomalainen J. , Markelin L. , Oliveira R. , Hakala T. , Koivumäki N. , Honkavaara E. , Pölönen I.
Published: December 2023

Abstract. Wildfires present severe threats to various aspects of ecosystems, human settlements, and the environment. Early detection plays a critical role in minimizing the destructive consequences of wildfires. This study introduces an innovative approach for smoke-based wildfire detection in Boreal forests by combining the YOLO V5 algorithm and transfer learning. YOLO V5 is renowned for its real-time performance and accuracy in object detection. Given the scarcity of labelled smoke images specific to wildfire scenes, transfer learning techniques are employed to address this limitation. Initially, the generalisability of smoke as an object is examined by utilising wildfire data collected from diverse environments for fine-tuning and testing purposes in Boreal forest scenarios. Subsequently, Boreal forest fire data is employed for training and fine-tuning to achieve high detection accuracy and explore benchmarks for effective local training data. This approach minimises extensive manual labelling efforts while enhancing the accuracy of smoke-based wildfire detection in Boreal forest environments. Experimental results validate the efficacy of the proposed approach. The combined YOLO V5 and transfer learning framework demonstrates a high detection accuracy, making it a promising solution for automated wildfire detection systems. Implementing this methodology can potentially enhance early detection and response to wildfires in Boreal forest regions, thereby contributing to improved disaster management and mitigation strategies.
AUTOMATIC VIDEO DETECTION FOR GOLDEN MONKEYS IN SHENNONGJIA NATIONAL PARK, CHINA
Authors: Sui H. , Wei T. , Wang J. , Hua L. , Xiong N.
Published: December 2023

Abstract. Infrared-triggered cameras serve as essential tools for wildlife resource surveys, allowing camera traps to capture wildlife activity while minimizing the impact on the ecosystem. Traditional monitoring methods heavily rely on human resources for visual discrimination, which is inefficient and susceptible to environmental influences. Therefore, this paper focuses on Shennongjia National Park as a case study to address the limitations of traditional approaches. We constructed a Shennongjia wildlife object detection dataset using video data from the fixed-erected infrared cameras and proposed a supervised learning-based automatic monitoring method for golden monkeys, aiming to achieve intelligent target detection. With these processing results, we were able to capture golden monkeys' tracks and conduct statistical analysis of their life range and distribution characteristics. Through the integration of sensors and deep learning techniques, we developed a golden monkeys detection monitoring system to visualize the monitoring results and assess the spatial and temporal distribution characteristics of golden monkeys’ activities.
A COMPARISON STUDY OF LOW-COST PERSONAL LASER SCANNING SYSTEMS FOR FOREST PLOT-LEVEL INVENTORIES
Authors: Wang X. , Yao H. , Ma Y. , Liang X.
Published: December 2023

Abstract. Forest resource is an essential part of the environment, and can be used for carbon sink, soil conservation, windbreak and sand fixation, which is of great significance to maintaining the balance of ecologic and sustainable city development. Due to the complexity of wildwood, the approach of traditional forest inventory is difficult, low-efficiency, and labour-intensive. Thus, a handheld personal laser scanning (PLShh) system is proposed in this paper. To solve the limitation of low-cost LiDAR’s FoV, two LiDAR scanners (Ouster OS-1-128 and Hesai PandarXT-32) are integrated in our PLShh system. The enhancement of our PLShh have be demonstrated by the experiments in field forest plots. The comparison of trajectory and the comparison of point cloud have been conducted extensively. Experiment results show that the trajectory estimated by two scanners (Ouster and Hesai) has a strong consistency with using one scanner (Ouster), with standard deviation at sub-centimetres level. And the trajectory deviation between two scanners and UWB is ∼15cm, which is consistent with the inherent positioning accuracy of UWB sensors. In addition, the point cloud data obtained by two scanners or one scanner have been quantitatively evaluated by the TLS (Leica RTC 360) muti-scan. The difference between tree height extracted from two scanners and TLS data was small, even at sub-meter level only. But the tree height extracted from one scanner is lower ~8m in comparison with TLS data, because of the limitation of vertical FoV. Therefore, the great potential of our PLShh system with two scanners has been shown in the application of forest inventory.
RESEARCH ON NAMED ENTITY RECOGNITION METHODS FOR URBAN UNDERGROUND SPACE DISASTERS BASED ON TEXT INFORMATION EXTRACTION
Authors: Li Z. , Zhang X.
Published: December 2023

Abstract. Urban underground space is a complex spatial scenario that is highly susceptible to disasters. To achieve entity recognition in textual information related to urban underground space disasters, this study proposes the ALBERT-BiLSTM-CRF model. The urban underground space disaster text data is firstly encoded using the ALBERT model, which captures the deep semantic information of words in the context. The encoded data is then fed into a BiLSTM network to obtain hidden state vectors for each word, enhancing the feature representation of words. Finally, these vectors are input into a CRF layer to obtain the optimal label sequence and complete named entity recognition. The proposed model achieves an accuracy of 95.41%, a recall of 94.08%, and an F1 score of 94.74%. Comparative experiments with the BiLSTM-CRF, BERT-CRF, and BERT-BiLSTM-CRF models are conducted on the Boson dataset and our experimental dataset, demonstrating the superior performance of the ALBERT-BiLSTM-CRF model.
ALTERNATIVE LIDAR TECHNOLOGIES FOR STOCKPILE MONITORING AND REPORTING
Authors: Koshan Y. , Manish R. , Joseph M. , Habib A.
Published: December 2023

Abstract. Accurate volume estimation of salt stockpiles stored in covered facilities is essential for effective management and budgeting in the transportation industry. Due to environmental concerns, salt is stored in indoor facilities. The surveying tools that are widely applied for outdoor stockpile estimation such as Global Navigation Satellite System (GNSS) Receivers and Uncrewed Aerial Vehicles (UAV) are not applicable for indoor mapping. To address this limitation, our prior research proposed and developed a Stockpile Monitoring and Reporting Technology (SMART) which was designed for indoor stockpile volume estimation. This study builds upon that prior research to evaluate the feasibility and performance of different LiDAR alternatives within the SMART system. Three LiDAR sensors (Velodyne VLP-16, Ouster OS1-32-U, and Blickfeld Cube 1) are compared in terms of system calibration, point cloud registration, and volume estimation. Results demonstrate the impact of LiDAR sensor choice on system performance, occlusion rates, and volumetric accuracy. The findings contribute to expanding the versatility and adaptability of LiDAR technology in SMART applications, allowing for more efficient and accurate stockpile volume estimation.
RADAR/INS TIGHTLY-COUPLED INTEGRATION FOR LAND VEHICLE NAVIGATION
Authors: Elkholy M. , Elsheikh M. , El-Sheimy N.
Published: December 2023

Abstract. Multisensor systems are essential for autonomous navigation applications to achieve reliable accuracy. Integrating the Global Navigation Satellite System (GNSS) and the Inertial Navigation System (INS) is the most common integration scheme. However, this integration is unreliable in different scenarios since the GNSS signal may deteriorate in downtown areas or suffer from a blockage in underground and indoor areas. Therefore, other sensors are integrated with INS to compensate for GNSS outages. This paper proposes a novel algorithm for radar/INS tightly-coupled integration for autonomous navigation applications. This algorithm is applied in multiple steps. Radar data analysis is the first and most crucial step to remove the noisy data and the outliers and keep the useful objects. Then, data association is done to match the detected objects between radar frames. The tightly-coupled integration is performed at the measurement level through an Extended Kalman Filter (EKF), where the distance between the INS and the detected objects can be predicted from the INS and measured from the radar. Real data was collected from four Frequency Modulated Continuous Wave (FMCW) radar units in Calgary's suburban areas and Toronto's downtown area. The proposed algorithm was tested and assessed by introducing simulated GNSS single outages with different durations. The results show an enhancement in the vehicle's position by about 94% to 96%.
LINE AND POLYGON TOPOLOGY IN OPENDRIVE MODELLING
Authors: Lógó J. M. , Barsi A.
Published: December 2023

Abstract. The paper discusses the importance of efficient methods in the automotive industry for the development of self-driving vehicles and advanced vehicle assistants, focusing on the use of high-definition (HD) maps. The integration of computer simulation and HD maps in the OpenDRIVE format is emphasized. A paradigm shift in map topology is highlighted, requiring a new map creation and usage approach. The article presents a methodology that addresses both geometric and topological aspects in creating accurate HD map models. The method focuses on the connection of linear and arc road elements and eliminating continuity/connectivity errors in lane descriptions. Real-world tests validate the implemented methodology and demonstrate the successful generation of topologically correct HD map models. The results show the potential of these models for various automotive applications, particularly in the development and testing of self-driving vehicles and advanced vehicle assistants. The methodology contributes to the advancement of HD map creation, providing valuable insights for researchers and map makers in the automotive industry.
The role of response efficacy and self-efficacy in disaster preparedness actions for vulnerable households
Authors: Qiu Dong , Lv Binglin , Cui Yuepeng , Zhan Zexiong
Published: December 2023

Abstract. The effects of response efficacy and self-efficacy on disaster preparedness have been widely reported. However, most studies only prove their relationship to disaster preparedness in general terms without ascertaining whether they also variously impact the disaster preparedness of diverse vulnerable families (i.e., caring for older and/or disabled adults (COD), caring for a child (CC), and low capacity (LC)). In this study, disaster preparedness is divided into two dependent variables: adequate and minimal preparedness. A quantitative analysis was conducted using 4559 samples drawn from the 2021 National Household Survey to investigate the relationship between response efficacy and self-efficacy with preparedness measures adopted by vulnerable households. Binary logistic regression results indicated that households with vulnerable groups are generally more likely to report lower disaster preparedness. Response efficacy is more critical to LC and COD families, while self-efficacy is more important to LC and CC families. Based on these findings, interventions can be tailored to suit different family types and help vulnerable families better prepare for disasters.
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
Authors: Felsberg Anne , Heyvaert Zdenko , Poesen Jean , Stanley Thomas , De Lannoy Gabriëlle J. M.
Published: December 2023

Abstract. In this study we present a model for the global Probabilistic Hydrological Estimation of LandSlides (PHELS). PHELS estimates the daily hazard of hydrologically triggered landslides at a coarse spatial resolution of 36 km, by combining landslide susceptibility (LSS) and (percentiles of) hydrological variable(s). The latter include daily rainfall, a 7 d antecedent rainfall index (ARI7) or root-zone soil moisture content (rzmc) as hydrological predictor variables, or the combination of rainfall and rzmc. The hazard estimates with any of these predictor variables have areas under the receiver operating characteristic curve (AUC) above 0.68. The best performance was found with combined rainfall and rzmc predictors (AUC = 0.79), which resulted in the lowest number of missed alarms (especially during spring) and false alarms. Furthermore, PHELS provides hazard uncertainty estimates by generating ensemble simulations based on repeated sampling of LSS and the hydrological predictor variables. The estimated hazard uncertainty follows the behaviour of the input variable uncertainties, is about 13.6 % of the estimated hazard value on average across the globe and in time and is smallest for very low and very high hazard values.
Southern Weddell Sea surface freshwater flux modulated by icescape and atmospheric forcing
Authors: Stulic Lukrecia , Timmermann Ralph , Paul Stephan , Zentek Rolf , Heinemann Günther , Kanzow Torsten
Published: December 2023

Abstract. Sea ice formation dominates surface salt forcing in the southern Weddell Sea. Brine rejected in the process of sea ice production results in the production of High Salinity Shelf Water (HSSW) that feeds the global overturning circulation and fuels the basal melt of the adjacent ice shelf. The strongest sea ice production rates are found in coastal polynyas, where steady offshore winds promote divergent ice movement during the freezing season. We used the Finite Element Sea ice–ice shelf–Ocean Model (FESOM) forced by output from the regional atmospheric model COSMO-CLM (CCLM) with 14 km horizontal resolution to investigate the role of polynyas for the surface freshwater flux of the southern Weddell Sea (2002–2017). The presence of stationary icescape features (i.e., fast-ice areas and grounded icebergs) can influence the formation of polynyas and, therefore, impact sea ice production. The representation of the icescape in our model is included by prescribing the position, shape and temporal evolution of a largely immobile ice mélange formed between the Filchner–Ronne Ice Shelf (FRIS) and a major grounded iceberg based on satellite data. We find that 70 % of the ice produced on the continental shelf of the southern Weddell Sea is exported from the region. While coastal polynyas cover 2 % of the continental shelf area, sea ice production within the coastal polynyas accounts for 17 % of the overall annual sea ice production (1509 km3). The largest contributions come from the Ronne Ice Shelf and Brunt Ice Shelf polynyas and polynyas associated with the ice mélange. Furthermore, we investigate the sensitivity of the polynya-based ice production to the (i) representation of the icescape and (ii) regional atmospheric forcing. Although large-scale atmospheric fields determine the sea ice production outside polynyas, both the treatment of the icescape and the regional atmospheric forcing are important for the regional patterns of sea ice production in polynyas. The representation of the ice mélange is crucial for the simulation of polynyas westward/eastward of it, which are otherwise suppressed/overestimated. Compared to using ERA-Interim reanalysis as an atmospheric forcing data set, using CCLM output reduces polynya-based ice production over the eastern continental shelf due to weaker offshore winds, yielding a more realistic polynya representation. Our results show that the location and not just the strength of the sea ice production in polynyas is a relevant parameter in setting the properties of the HSSW produced on the continental shelf, which in turn affects the basal melting of the Filchner–Ronne Ice Shelf.