bluuebunny/crossref_metadata_2025 huggingface dataset:
O "NOVO CANGAÇO": ENQUADRAMENTO TÍPICO E DESDOBRAMENTO DO FATO CRIMINOSO À LUZ DO ORDENAMENTO JURÍDICO
Authors: Oliveira Tarsis Barreto , Souza João Victor Ribeiro de
Published: December 2023

O presente trabalho busca situar o leitor a respeito do fenômeno criminal do novo cangaço, expondo a gênese dos assaltos a banco no Brasil e como estes evoluíram até culminar na modalidade do novo cangaço, além de relatar o modus operandi das quadrilhas criminosas envolvidas nestas ações. Também esclarece a origem do termo “novo cangaço” e quais semelhanças existem entre os cangaceiros do século XXI e os grupos criminosos que agiram na primeira metade do século XX nas regiões do sertão nordestino, tendo como seu principal expoente Virgulino Ferreira da Silva, vulgo Lampião. Ademais, são tratadas as ações tomadas pelo legislativo e a postura do Judiciário frente ao sério problema de segurança pública promovida pelos ataques a instituições financeiras. Por fim, é feita uma análise se os crimes existentes no ordenamento jurídico pátrio são suficientes para o adequado enquadramento típico normativo ou se faz necessária a edição de um novo tipo penal eivado de elementos compatíveis com as características do novo cangaço. O método de pesquisa utilizado foi o bibliográfico, com pesquisa de jurisprudência e doutrina relativas ao tema.
A UTILIZAÇÃO DO COMPLIANCE CONTÁBIL NA GESTÃO DE PESSOAS: UMA REVISÃO DE LITERATURA
Authors: Oliveira Adeniza Santos , Silva Jaqueline Aparecida da , Costa Lívia Cristina Pereira , Feltrin Paula Tainá Nunes , Ribeiro Rogerio de Jesus , Boreli Daniela
Published: December 2023

O Compliance Contábil é uma abordagem que visa garantir o cumprimento de leis, regulamentos, normas contábeis, éticas e integridade nas organizações. Tradicionalmente, essa prática tem sido associada à gestão financeira e ao controle de processos internos. No entanto, a literatura tem apontado para a importância do Compliance Contábil também na gestão de pessoas. Esta revisão de literatura tem como objetivo explorar a utilização do Compliance Contábil na gestão de pessoas, destacando seus benefícios e desafios. A literatura indica que o Compliance Contábil pode contribuir para a melhoria da transparência, ética e integridade nas práticas de gestão de pessoas. Ao adotar princípios de Compliance Contábil na gestão de pessoas, as organizações podem estabelecer diretrizes claras, promover a conformidade com leis trabalhistas e previdenciárias, prevenir fraudes, descumprimento das normas e corrupção, além de fortalecer a cultura organizacional baseada na ética e no respeito. No entanto, a implementação do Compliance Contábil na gestão de pessoas também apresenta desafios, como a necessidade de capacitação dos profissionais envolvidos, o alinhamento das práticas com as demandas legais e a criação de uma cultura de conformidade.
O USO INDEVIDO DE ANABOLIZANTE PARA FINS ESTÉTICOS
Authors: Mendes Érica de Sousa , Rinaldi Sebastian
Published: December 2023

Este trabalho tem como objetivo geral analisar e conscientizar sobre os impactos negativos do uso indevido de anabolizantes na saúde humana. O uso indevido de anabolizantes, ou seja, sem prescrição médica e supervisão adequada, é ilegal e pode ser extremamente prejudicial à saúde. Para atingir os objetivos propostos, será realizada uma pesquisa de natureza exploratória.  Revisão bibliográfica: Será realizada uma extensa pesquisa em bases de dados científicas, para identificar estudos, artigos científicos e teses relacionados ao uso indevido de anabolizantes. A revisão bibliográfica permitirá obter informações atualizadas e embasadas sobre os aspectos fisiológicos, efeitos colaterais, impactos psicológicos e implicações legais do uso indevido dessas substâncias. Análise documental: Serão analisadas legislações, regulamentos e normas relacionadas ao uso de anabolizantes, como as determinações da Agência Nacional de Vigilância Sanitária (ANVISA) e do Conselho Federal de Medicina (CFM), a fim de compreender as implicações legais e éticas dessa prática. Em resumo, o uso indevido de anabolizantes pode oferecer benefícios de curto prazo, mas está associado a riscos significativos para a saúde a longo prazo. É importante buscar orientação médica adequada e informações educativas para tomar decisões informadas sobre seu uso, caso seja necessário, e entender os riscos envolvidos.
ANÁLISE DO TRABALHO ANÁLOGO À ESCRAVIDÃO NO PIAUÍ, DURANTE O PERÍODO DE 2020 A 2022
Authors: Costa Camille Lopes da , Silva Iracema Érica Saraiva da
Published: December 2023

A presente pesquisa tem como objetivo analisar o trabalho análogo à escravidão no Estado do Piauí, durante o período de 2020 a 2022, a fim de investigar a ocorrência de trabalho escravo contemporâneo no Piauí, para se identificar uma possível evolução ou redução desse cenário, muito recorrente na sociedade. Para isso, foi realizado um estudo de inquérito investigativo em base de dados de acesso aberto, através das plataformas do Ministério Público do Trabalho do Piauí e do Observatório da Erradicação do Trabalho Escravo e  Tráfico de Pessoas. Os resultados apontam que houve um aumento consecutivo no número de trabalhadores resgatados, além de apontar as cidades com maiores índices de resgatados e as atividades socioeconômicas mais recorrentes. A pesquisa conclui que a fragilidade da legislação atual e das medidas de erradicação pode ter causado um ambiente de permanência desse fenômeno.
ABORDAGENS CIRÚRGICAS PARA O TRATAMENTO DA OBESIDADE MÓRBIDA
Authors: Correia Lucas de Araujo , Briro Fernanda Scaglioni Reis , Raposo Maria Rafaela Amaral , Sousa Daniela de Melo , Tostes Luíza Novaes Figueireso
Published: December 2023

A obesidade mórbida, caracterizada pelo índice de massa corporal (IMC) igual ou superior a 40 kg/m², representa um desafio significativo para a saúde pública. Associada a uma série de comorbidades, como diabetes tipo 2, hipertensão arterial e doenças cardiovasculares, a obesidade mórbida demanda abordagens terapêuticas eficazes. Entre as opções disponíveis, as intervenções cirúrgicas, conhecidas como cirurgias bariátricas, emergiram como uma estratégia eficaz para promover a perda de peso sustentada e melhorar os resultados de saúde a longo prazo. Objetivo: Analisar criticamente as abordagens cirúrgicas utilizadas no tratamento da obesidade mórbida, explorando sua eficácia, segurança e impacto nos desfechos clínicos. Buscamos identificar padrões comuns e discrepâncias nas evidências científicas, considerando artigos, estudos e livros científicos publicados nos últimos 10 anos. Metodologia: A metodologia da revisão seguiu as diretrizes do checklist PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). A busca abrangeu as bases de dados PubMed, Scielo e Web of Science, utilizando cinco descritores principais: obesidade mórbida, cirurgia bariátrica, intervenções cirúrgicas, desfechos clínicos e estudos de longo prazo. Os critérios de inclusão contemplaram estudos que investigaram abordagens cirúrgicas para obesidade mórbida, com foco em desfechos a longo prazo, e foram publicados nos últimos 10 anos. Por outro lado, foram excluídos estudos duplicados, relatos de casos e aqueles que não forneceram informações relevantes para a análise. Resultados: A análise dos resultados revelou uma variedade de abordagens cirúrgicas, como a banda gástrica, o bypass gástrico e a gastrectomia vertical, cada uma demonstrando diferentes graus de eficácia na perda de peso e na melhoria das comorbidades associadas. Os estudos também abordaram complicações pós-cirúrgicas, taxas de sucesso a longo prazo e a qualidade de vida dos pacientes submetidos a essas intervenções. Destacam-se ainda as implicações para a prática clínica e as lacunas que requerem investigação futura. Conclusão: Em síntese, esta revisão sistemática fornece uma visão abrangente das abordagens cirúrgicas para o tratamento da obesidade mórbida, destacando a importância da personalização do tratamento com base nas características individuais do paciente. As evidências apresentadas contribuem para a compreensão dos resultados a longo prazo dessas intervenções, permitindo uma tomada de decisão informada por parte dos profissionais de saúde. No entanto, são necessárias mais pesquisas para elucidar questões específicas e otimizar a seleção de abordagens cirúrgicas para maximizar os benefícios a longo prazo.
Evaluation of modelled climatologies of O3, CO, water vapour and NOy in the upper troposphere–lower stratosphere using regular in situ observations by passenger aircraft
Authors: Cohen Yann , Hauglustaine Didier , Sauvage Bastien , Rohs Susanne , Konjari Patrick , Bundke Ulrich , Petzold Andreas , Thouret Valérie , Zahn Andreas , Ziereis Helmut
Published: December 2023

Abstract. Evaluating global chemistry models in the upper troposphere–lower stratosphere (UTLS) is an important step toward an improved understanding of the chemical composition in this region. This composition is regularly sampled through in situ measurements based on passenger aircraft, in the framework of the In-service Aircraft for a Global Observing System (IAGOS) research infrastructure. This study focuses on the comparison of the IAGOS measurements in ozone, carbon monoxide (CO), nitrogen reactive species (NOy) and water vapour, with a 25-year simulation output from the LMDZ-OR-INCA chemistry–climate model. For this purpose, we present and apply an extension of the Interpol-IAGOS software that projects the IAGOS data onto any model grid, in order to derive a gridded IAGOS product and a masked (sub-sampled) model product that are directly comparable to one another. Climatologies are calculated in the upper troposphere (UT) and in the lower stratosphere (LS) separately but also in the UTLS as a whole, as a demonstration for the models that do not sort out the physical variables necessary to distinguish between the UT and the LS. In the northern extratropics, the comparison in the UTLS layer suggests that the geographical distribution in the tropopause height is well reproduced by the model. In the separated layers, the model simulates well the water vapour climatologies in the UT and the ozone climatologies in the LS. There are opposite biases in CO in both UT and LS, which suggests that the cross-tropopause transport is overestimated. The NOy observations highlight the difficulty of the model in parameterizing the lightning emissions. In the tropics, the upper-tropospheric climatologies are remarkably well simulated for water vapour. They also show realistic CO peaks due to biomass burning in the most convective systems, and the ozone latitudinal variations are well correlated between the observations and the model. Ozone is more sensitive to lightning emissions than to biomass burning emissions, whereas the CO sensitivity to biomass burning emissions strongly depends on location and season. The present study demonstrates that the Interpol-IAGOS software is a tool facilitating the assessment of global model simulations in the UTLS, which is potentially useful for any modelling experiment involving chemistry climate or chemistry transport models.
Characterizing the near-global cloud vertical structures over land using high-resolution radiosonde measurements
Authors: Xu Hui , Guo Jianping , Tong Bing , Zhang Jinqiang , Chen Tianmeng , Guo Xiaoran , Zhang Jian , Chen Wenqing
Published: December 2023

Abstract. Cloud remains one of the largest uncertainties in weather and climate research due to the lack of fine-resolution observations of cloud vertical structure (CVS) on a large scale. In this study, near-global CVS is characterized by high-vertical-resolution twice-daily radiosonde observations from 374 stations over land, which are distributed in Europe, North America, East Asia, Australia, the Pacific Ocean, and Antarctica. To this end, we initially develop a novel method to determine CVS, by combining both the vertical gradients of air temperature and relative humidity (RH) and the altitude-dependent thresholds of RH. It is found that the cloud base heights (CBHs) from radiosondes have a higher correlation coefficient (R= 0.91) with the CBHs from a millimeter-wave cloud radar than those from the ERA5 reanalysis (R= 0.49). Overall, cloudy skies occur 65.3 % (69.5 %) of the time, of which 55.4 % (53.8 %) are one-layer clouds at 00:00 (12:00) UTC. Most multi-layer clouds are two-layer clouds, accounting for 62.2 % (61.1 %) among multi-layer clouds at 00:00 (12:00) UTC. Geographically, one-layer clouds tend to occur over arid regions, whereas two-layer clouds do not show any clear spatial preference. The cloud bases and tops over arid regions are higher compared with humid regions albeit with smaller cloud thickness (CT). Clouds tend to have lower bases and thinner layer thicknesses as the number of cloud layer increases. The global-mean CT, CBH, and cloud top height (CTH) are 4.89 ± 1.36 (5.37 ± 1.58), 3.15 ± 1.15 (3.07 ± 1.06), and 8.04 ± 1.60 (8.44 ± 1.52) km above ground level (a.g.l.) at 00:00 (12:00) UTC, respectively. The occurrence frequency of clouds is bimodal, with lower peaks between 0.5 and 3 km a.g.l. and upper peaks between 6 and 10 km a.g.l. The CBH, CTH, and CT undergo almost the same seasonality; namely, their magnitudes in boreal summer are greater than in boreal winter. As expected, the occurrence frequencies of clouds exhibit pronounced diurnal cycles in different seasons. In boreal summer, clouds tend to form as the sun rises and the occurrence frequencies increase from morning to late afternoon, with the peak in the early afternoon at the altitude of 6–12 km a.g.l., while in boreal winter, clouds have peak occurrence frequencies in the morning. The relations between surface meteorological variables and moisture with CBH are investigated as well, showing that CBHs are generally more significantly correlated with 2 m relative humidity (RH2 m) and 2 m air temperature (T2 m) than with surface pressure and 10 m wind speed. Larger T2 m and smaller RH2 m always correspond to higher CBH. In most cases CBHs are negatively correlated to soil water content. The near-global CVS obtained from high-vertical-resolution radiosondes in this study can provide key data support for improving the accuracy of cloud radiative forcing simulation in climate models.
Field comparison of dual- and single-spot aethalometers: Equivalent black carbon, light absorption, and Ångström exponent and secondary brown carbon estimations
Authors: Wu Liangbin , Wu Cheng , Deng Tao , Wu Dui , Li Mei , Li Yong Jie , Zhou Zhen
Published: December 2023

Abstract. Aethalometer is a widely used instrument for black carbon (BC) mass concentration and light absorption coefficient (babs) measurements around the world. However, field intercomparison of the two popular models, dual-spot (AE33) and single-spot (AE31) aethalometers, remain limited; in addition, the difference in secondary brown carbon (BrCsec) light absorption estimation between the two models is largely unknown. We performed full-year collocated AE33 and AE31 measurements in a megacity in southern China – Guangzhou. The babs values agree well between the two aethalometers (R2 > 0.95), with AE33/AE31 slopes ranging from 0.87 to 1.04 for 7 wavelengths. AE33 consistently exhibits lower limits of detection (LOD) than AE31 for time resolutions of 2 to 60 min. The AE33/AE31 slope for equivalent BC (eBC) was 1.2, implying the need for site-specific post-correction. The Ångström exponent (AAE) obtained from different approaches agrees not very well between the two models, with the biggest discrepancy found in AAE880/950. The estimated BrCsec light absorption at 370 nm (babs370_BrCsec) was calculated using the minimum R squared method (MRS) for both Aethalometers. The babs370_BrCsec comparison yields a slope of 0.78 and an R2 of 0.72 between the two models, implying a non-negligible inter-instrument difference. This study highlights the high consistency in babs but less so in AAE between AE31 and AE33, and reveals site-specific correction for eBC estimation and non-negligible difference in BrCsec estimation. The results are valuable for data continuity in long-term aethalometer measurements when transiting from the older (AE31) to the newer (AE33) model, as anticipated in permanent global-climate and air-quality stations.
New straightforward formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
Authors: Mailler Sylvain , Mallios Sotirios , Cholakian Arineh , Amiridis Vassilis , Menut Laurent , Pennel Romain
Published: December 2023

Abstract. We propose two direct expressions to calculate the settling speed of atmospheric particles with prolate spheroidal shapes under the hypothesis of horizontal and vertical orientation. The first formulation is extremely simple and based on theoretical arguments only. The second method, valid for particles with mass-median diameter up to 1000 µm, is based on recent heuristic drag expressions based on CFD numeric simulations. We show that these two formulations show equivalent results within 2 % for deq ≤ 100 µm, and within 10 % for particles with deq ≤ 500 µm falling with a horizontal orientation, showing that the first, more simple method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid. Finally, in order to facilitate the use of our results in chemistry-transport models, we provide an implementation of the first of these methods in AerSett v2.0.2, a module written in Fortran.
AMOC Stability Amid Tipping Ice Sheets: The Crucial Role of Rate and Noise
Authors: Sinet Sacha , Ashwin Peter , von der Heydt Anna S. , Dijkstra Henk A.
Published: December 2023

Abstract. The Atlantic Meridional Overturning Circulation (AMOC) has recently been categorised as core tipping element, for it is believed to be prone to critical transition under climate change, implying drastic consequences on a planetary scale. Moreover, the AMOC is strongly coupled to polar ice sheets via meltwater fluxes. On one hand, most studies agree on the fact that a collapse of the Greenland ice sheet would result in a weakening of AMOC. On the other hand, the consequences of a collapse of the West Antarctica ice sheet are less well understood. However, some studies suggest that meltwater originating from the Southern Hemisphere is able to stabilize the AMOC. Using a conceptual model of the AMOC and a minimal parameterization of ice sheet collapse, we investigate the origin and relevance of this stabilization effect in both the deterministic and stochastic cases. While a substantial stabilization is found in both cases, we find that important rate and noise-induced effects result in bifurcation-induced tipping approaches to be inaccurate for predicting the AMOC stability.
The effects of warm air intrusions in the high arctic on cirrus clouds
Authors: Dekoutsidis Georgios , Wirth Martin , Groß Silke
Published: December 2023

Abstract. Warm Air Intrusions (WAI) are responsible for the transportation of warm and moist airmasses from the mid-latitudes into the high arctic (>70° N). In this work, we study cirrus clouds that form during WAI events (WAI cirrus) and during undisturbed arctic conditions (AC cirrus) and investigate possible differences between the two cloud types based on their macrophysical and optical properties with a focus on Relative Humidity over ice (RHi). We use airborne measurements from the combined high spectral resolution and differential absorption lidar, WALES, performed during the HALO-(AC)3 campaign. We classify each research flight and the measured clouds as either AC or WAI, based on the ambient conditions and study the macrophysical, geometrical and optical characteristics for each cirrus group. As our main parameter we choose the Relative Humidity over ice (RHi) which we calculate RHi by combining the lidar water vapor measurements with model temperatures. RHi is affected by and can be used as an indication of the nucleation process and the structure of cirrus clouds. We find that during WAI events the arctic is warmer and moister and WAI cirrus are both geometrically and optically thicker compared to AC cirrus. WAI cirrus and the layer directly surrounding them, are more frequently supersaturated, also at high supersaturations over the threshold for homogeneous ice nucleation (HOM). AC cirrus have a supersaturation dominated cloud top and a subsaturated cloud base. WAI cirrus also have high supersaturations at cloud top, but also at cloud base.
Changes in the North Atlantic Oscillation over the 20th Century
Authors: Outten Stephen , Davy Richard
Published: December 2023

Abstract. The North Atlantic Oscillation explains a large fraction of the climate variability across the North Atlantic from the eastern seaboard of North America across the whole of Europe. Many studies have linked the North Atlantic Oscillation to climate extremes in this region, especially in winter, which has motivated considerable study of this pattern of variability. However, one overlooked feature of how the North Atlantic Oscillation has changed over time is the explained variance of the pattern. Here we show that there has been a considerable increase in the percentage variance explained by the NAO over the 20th century from 32 % in 1930 to 53 % by the end of the 20th century. Whether this change is due to natural variability, a forced response to climate change, or some combination remains unclear. However, we found no evidence for a forced response from an ensemble of 50 CMIP6 models. These models did all show substantial internal variability in the strength of the North Atlantic Oscillation, but it was biased towards being too high compared to the reanalysis and with too little variation over time. Since there is a direct connection between the North Atlantic Oscillation and climate extremes over the region, this has direct consequences for both the long term projection and near term prediction of changes to climate extremes in the region.
Does high-latitude ionospheric electrodynamics exhibit hemispheric mirror symmetry?
Authors: Hatch Spencer Mark , Vanhamäki Heikki , Laundal Karl Magnus , Reistad Jone Peter , Burchill Johnathan , Lomidze Levan , Knudsen David , Madelaire Michael , Tesfaw Habtamu
Published: December 2023

Abstract. Ionospheric electrodynamics is a problem of mechanical stress balance mediated by electromagnetic forces. Joule heating (the total rate of frictional heating of thermospheric gases and ionospheric plasma) and ionospheric Hall and Pedersen conductances comprise three of the most basic descriptors of this problem. More than half a century after identification of their central role in ionospheric electrodynamics several important questions about these quantities, including the degree to which they exhibit hemispheric symmetry under reversal of the sign of dipole tilt and the sign of the y component of the interplanetary magnetic field (so-called "mirror symmetry"), remain unanswered. While global estimates of these key parameters can be obtained by combining existing empirical models, one often encounters some frustrating sources of uncertainty: the measurements from which such models are derived, usually magnetic field and electric field or ion drift measurements, are typically measured separately and do not necessarily align. The models to be combined moreover often use different input parameters, different assumptions about hemispheric symmetry, and/or different coordinate systems. We eliminate these sources of uncertainty in model predictions of electromagnetic work J⋅E (in general not equal to Joule heating ηJ2) and ionospheric conductances by combining two new empirical models of the high-latitude ionospheric electric potential and ionospheric currents that are derived in a mutually consistent fashion: these models do not assume any form of symmetry between the two hemispheres; are based on Apex coordinates, spherical harmonics, and the same model input parameters; and are derived exclusively from convection and magnetic field measurements made by the Swarm and CHAMP satellites. The model source code is open source and publicly available. Comparison of high-latitude distributions of electromagnetic work in each hemisphere as functions of dipole tilt and interplanetary magnetic field clock angle indicate that the typical assumption of mirror symmetry is largely justified. Model predictions of ionospheric Hall and Pedersen conductances exhibit a degree of symmetry, but clearly asymmetric responses to dipole tilt and solar wind driving conditions are also identified. The distinction between electromagnetic work and Joule heating allows us to identify where and under what conditions the assumption that the neutral wind corotates with the earth is not likely to be physically consistent with predicted Hall and Pedersen conductances.
IPB-MSA&SO4: a daily 0.25° resolution dataset of In-situ Produced Biogenic Methanesulfonic Acid and Sulfate over the North Atlantic during 1998–2022 based on machine learning
Authors: Mansour Karam , Decesari Stefano , Ceburnis Darius , Ovadnevaite Jurgita , Russell Lynn M. , Paglione Marco , Poulain Laurent , Huang Shan , O'Dowd Colin , Rinaldi Matteo
Published: December 2023

Abstract. Accurate long-term marine-derived biogenic sulfur aerosol concentrations at high spatial and temporal resolutions are critical for a wide range of studies including climatology, trend analysis, model evaluation, accurate investigation of their contribution to aerosol burden, or to elucidate their radiative impacts and to provide boundary conditions for regional models. By applying machine learning algorithms, we constructed the first, publicly available, daily gridded dataset of in-situ produced biogenic methanesulfonic acid (MSA) and sulfate (SO4) concentrations covering the North Atlantic Ocean. The dataset is of high spatial resolution of 0.25° × 0.25°, spanning 25 years (1998–2022), far exceeding what observations alone could achieve both space- and time-wise. The machine learning models were generated by combining in-situ observations of sulfur aerosol data at Mace Head research station, west coast of Ireland, and from NAAMES cruises in the NW Atlantic, combined with the constructed sea-to-air dimethylsulfide flux (FDMS) and ECMWF-ERA5 reanalysis datasets. To determine the optimal method for regression, we employed four machine learning model types: support vector machines, ensemble, Gaussian process, and artificial neural networks. A comparison of the mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) revealed that the Gaussian process regression (GPR) was the most effective algorithm, outperforming the other models in simulating the biogenic MSA and SO4 concentrations. For predicting daily MSA (SO4), GPR displayed the highest R2 value of 0.86 (0.72) and the lowest MAE of 0.014 (0.10) µg m–3. The GPR partial dependence analysis suggests that the relationships between predictors and MSA and SO4 concentrations are complex rather than linear. Using the GPR algorithm, we produced a high-resolution daily dataset of In-situ Produced Biogenic MSA and SO4 sea-level concentrations over the North Atlantic, which we named IPB-MSA&SO4. The obtained IPB-MSA&SO4 data allowed us to analyze the spatiotemporal patterns of MSA, SO4, and the ratio between them (MSA:SO4). A comparison with the existing CAMS-EAC4 reanalysis suggests that our high-resolution dataset reproduces with high accuracy the spatial and temporal patterns of the biogenic sulfur aerosol concentration and has high consistency with independent measurements in the Atlantic Ocean. The IPB-MSA&SO4 is publicly available at https://doi.org/10.17632/j8bzd5dvpx.1 (Mansour et al., 2023b).
A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)
Authors: Brondex Julien , Fourteau Kévin , Dumont Marie , Hagenmuller Pascal , Calonne Neige , Tuzet François , Löwe Henning
Published: December 2023

Abstract. The poor treatment (or complete omission) of water vapor transport has been identified as a major limitation suffered by currently available snowpack models. As vapor and heat fluxes are closely intertwined, their mathematical representation amounts to a system of nonlinear and tightly coupled partial differential equations that are particularly challenging to solve numerically. The choice of the numerical scheme and the representation of couplings between processes are crucial to ensure an accurate and robust solution that guarantees mass and energy conservation while also allowing time steps in the order of 15 min. To explore the numerical treatments fulfilling these requirements, we have developed a highly modular finite-element program. The code is written in Python. Every step of the numerical formulation and solution is coded internally, except for the inversion of the linearized system of equations. We illustrate the capabilities of our approach to tackle the coupled problem of heat conduction, vapor diffusion, and settlement within a dry snowpack by running our model on several test cases proposed in recently published literature. We underline specific improvements regarding energy and mass conservation as well as time step requirements. In particular, we show that a fully coupled and fully implicit time-stepping approach enables accurate and stable solutions with little restriction on the time step.
A COMPARISON OF DEEP LEARNING-BASED SUPER-RESOLUTION FRAMEWORKS FOR SENTINEL-2 IMAGERY IN URBAN AREAS
Authors: Seydi S. T. , Arefi H.
Published: December 2023

Abstract. The high-resolution images are in demand for many applications in the monitoring of urban areas. The advent of remote sensing satellites such as Sentinel-2 has made data more accessible as it provides free multispectral imagery. However, the spatial resolution of these images is not sufficient for many of the tasks. With the advent of deep learning techniques, significant progress has been made in the field of super-resolution, which has shown promising results in the improvement of the spatial resolution of satellite images. In this study, we compare four the most common deep learning-based models for the super-resolution of Sentinel-2 imagery in dense urban areas using aerial images. These methods are including enhanced deep super-resolution network (EDSR), super-resolution generative adversarial networks (ESRGAN), residual feature distillation network (RFDN), and Super-Resolution Convolutional Neural Network (SRCNN). To determine the effectiveness of the models in improving image resolution, they were evaluated using visual quality and quantitative metrics. The super-resolution results show that deep learning-based models have high potential for the generation of the high-resolution dataset from Sentinel-2 imagery in urban areas. The RFDN outperformed other deep learning-based models that achieved the peak signal-to-noise ratio (PSNR) more than 17.8.
HIGH DYNAMIC RANGE IMAGE COMPRESSION ON COMMODITY HARDWARE FOR REAL-TIME MAPPING APPLICATIONS
Authors: Frommholz D. , Hein D. , Bock M.
Published: December 2023

Abstract. This paper describes a lossy compression scheme for high dynamic range graylevel and color imagery for data transmission purposes in real-time mapping scenarios. The five stages of the implemented non-standard transform coder are written in portable C++ code and do not require specialized hardware to run. Storage space occupied by the bitmaps is reduced via a color space change, 2D integer discrete cosine transform (DCT) approximation, coefficient quantization, two-size run-length encoding and dictionary matching hinged on the LZ4 algorithm. Quantization matrices to eliminate insignificant DCT coefficients are derived from a representative image set through genetic optimization. The underlying fitness function incorporates the obtained output size, classic image quality metrics and the unique color count. Together with a zone-based adaptation mechanism, this allows to specify target bitrates instead of percentage values or abstract quality factors for the reduction rate to be directly matched to the available communication channel capacities. Results on a camera control unit of a fixed-wing unmanned aircraft system built around entry-level PC hardware revealed single-thread compression and decompression throughputs of several hundred mebibytes per second for full-swing 16 and 32 bit RGB imagery at medium compression ratios. A degradation in image quality compared to popular compression libraries could be identified, however, at acceptable levels statistically and visually.
ASSESSMENT OF LIGHT ENVIRONMENT FOR HERBACEOUS VEGETATION IN SEMI-NATURAL GRASSLAND USING TIME-SERIES UAV DATA
Authors: Miura N. , Niwa Y. , Yamada S.
Published: December 2023

Abstract. Grasslands are important ecosystems containing unique biodiversity. It has been reported that some herbaceous species inhabiting grassland reduced its number and became extremely rare. Restoring these species as well as maintaining the grassland are key issues. Light environment is crucial for plant growth and survival. It is particularly important to evaluate light environment of microsite for herbaceous vegetation. In this paper, NDVI, vegetation biomass and gap fraction were estimated using time-series UAV data, and compared to photosynthetic photon flux density (PPFD), solar radiation and gap fraction measured by traditional ground-based techniques to validate its utility in accessing light environment for herbaceous vegetation in semi-natural grassland. The results showed that UAV derived variables displayed overall good correlations with ground derived variables: relative PPFD, relative solar radiation and gap fraction. Analysis of time-series UAV data revealed that UAV derived NDVI and vegetation biomass were not suitable for evaluating light environment when vegetation attains its maturity. UAV derived gap fraction was most resilient to change of vegetation growth. UAV derived methods have advantage in evaluating light environment in microsite without disturbing valuable plants and would help restoring semi-natural grassland.
EFFICIENT UAV FLIGHT PLANNING FOR LOD2 CITY MODEL IMPROVEMENT
Authors: Wu Y.-L. , Alsadik B. , Oude Elberink S. , Vosselman G.
Published: December 2023

Abstract. Geometric errors in LoD2 building models can be caused by the modeling algorithm but are often related to the quality of input data. One approach to tackling the modeling errors caused by the quality of input data is to collect additional data with a UAV and remodel the buildings. However, no flight planning approach exists specifically designed for efficient data recollection for model improvement. In this paper, we propose an innovative flight planning approach for this purpose. Contrary to the conventional method that recollects the data covering the entire building roof, our approach only collects the data over the erroneous region and uses it to improve the erroneous model part later. Our algorithm utilizes the existing LiDAR survey data to automatically detect model errors and design the camera networks by considering the roof geometry. We optimize the trajectory that connects the viewpoints with a genetic algorithm and develops an obstacle avoidance function with ray-casting to ensure a collision-free path. The proposed flight plan is implemented in a real-world scene. Our result shows an improved point cloud created through dense image matching with the collected UAV image data. The generated point cloud is successfully used for creating partial building models for improving the original models.
PARAMETER OPTIMIZATION FOR A THERMAL SIMULATION OF AN URBAN AREA
Authors: Kottler B. , Fischer S. , Strauss E. , Bulatov D. , Helmholz P.
Published: December 2023

Abstract. Urban heat island (UHI) phenomenon is a significant challenge in urban planning, and accurate temperature predictions are crucial for effective decision-making. The choice of material parameters is crucial to simulate a realistic temperature distribution and identify potential UHIs. This paper introduces a framework for optimizing the material properties based on sensors boxes placed upon surfaces made up by different materials. The methodology covers an optimization approach for the material properties to achieve accurate surface temperature simulation. The results, which involved close-range validation and macro-scale validation, show a significant improvement in the agreement between the simulated and measured temperature time series, especially for tiled roofs and asphalt roads. However, the accuracy for grassland areas decreased, possibly due to differences in soil moisture. Overall, the proposed framework shows promising results for future work in improving the accuracy of thermal simulation of urban areas.
ENTROPY-BASED INDOOR CHANGE DETECTION USING LIDAR DATA AND A 3D MODEL
Authors: Zhao H. , Tomko M. , Khoshelham K.
Published: December 2023

Abstract. Indoor change detection is important for building monitoring, building management and model-based localization and navigation systems because the real building environment may not always be the same as the design model. This paper presents a novel indoor building change detection method based on entropy. A sequence of real LiDAR scans is acquired with a static LiDAR scanner and the pose of the LiDAR scanner for each scan is then estimated. Synthetic LiDAR scans are generated with the pose of the LiDAR scanner using the 3D model. The real LiDAR scans and synthetic LiDAR scans are sliced horizontally with a certain angular interval and the entropy of all slices of LiDAR scans is then calculated. Differenced entropy between two corresponding slices of real LiDAR scans and synthetic LiDAR scans is calculated for the classification of the changes. Each slice of real LiDAR scans will be classified into one of the four categories of changes: unchanged, moving objects, structural change and non-structural change. Experimental results show that unchanged slices and slices containing moving objects can be accurately detected, achieving 100% accuracy while non-structural and structural changes are detected with an accuracy of 98.5% and 86.3% respectively.
A COMPREHENSIVE MEASUREMENT MODEL FOR JOB-HOUSING BALANCE CONSIDERING SPATIAL INTERACTIONS: A CASE STUDY IN SHANGHAI
Authors: Chen Y. , Jing C. , Xu G.
Published: December 2023

Abstract. Assessing jobs-housing balance (JHB) is crucial for the optimization of urban spatial pattern and transportation planning. However, due to the limitations of traditional data and the inability to integrate evaluation indicators, the evaluation results may be bias, conflicting with common sense. Considering interaction of multiple factors, a Job-housing balance measurement model (JHBM-SEM) was proposed to accurately evaluate the degree of JHB in a certain area. To address the problem of multi-indicator fusion, the structural equation model is used to incorporate the advantages, limitations and complementary relationships of each evaluation indicator into the evaluation process. A function relationship is defined between factor loadings, path coefficients, and variable scores to construct the measurement model and obtain comprehensive evaluation results. In addition, by integrating multi-source spatiotemporal big data mainly based on mobile signaling data, the paper can effectively mine the current status of job-housing balance in cities, and solve problems such as low precision and granularity of traditional data. The model was validated using Shanghai as an example, and the results show that compared with classical methods, the model's results are more consistent with the real situation of regional jobhousing patterns. It can identify the pseudo-balance phenomenon in underdeveloped areas of the suburbs and make reasonable evaluations, and the intermediate process can explain the direction of the imbalance factors in the region.
A DEEP LEARNING APPROACH USING VERY-HIGH SPATIAL RESOLUTION GAOFEN-2 IMAGES TO SUPPORT THE UNITED NATIONS SUSTAINABLE DEVELOPMENT GOAL INDICATOR 11.7.1 ASSESSMENT
Authors: Chen J. , Zhang P. , Zhang J. , Wu H.
Published: December 2023

Abstract. Since the proposal of the "2030 Agenda", the United Nations Sustainable Development Goal indicator 11.7.1 aims to calculate the accessibility and quality of urban open spaces(UOS). An accurate and rapid assessment framework of UOS is of great significance for urban sustainable development. Previous research on UOS has mainly focused on the evolution patterns of UOS, with little research on assessments of their accessibility for different population structures (i.e., men vs. women, young vs. older). In this study, a U-Net deep learning network was used for training from 3072 annotated samples of urban green spaces(UGS) which was created based on Gaofen-2 remote sensing images. The trained model was used to identify UGS within five districts of Beijing at sub-meter level, incorporated with Open Street Map and area of interest data. A spatial analysis was conducted for accessibility of UOS, finding that most of the UOS in the central urban area of Beijing can be reached within 10 minutes, but access to the eastern and western edges is poorer (more than 30 minutes). Finally, using Worldpop data, the accessibility of UOS was statistically analyzed for different ages and genders. The results show that UOS accessibility rate for the elderly and children reaches over 90% (10 minutes accessibility).
TEHRAN AIR POLLUTION MODELING USING LONG-SHORT TERM MEMORY ALGORITHM: AN UNCERTAINTY ANALYSIS
Authors: Ghorbani M. , Delavar M. R. , Nazari B. , Shiran G. , Ghaffarian S.
Published: December 2023

Abstract. Air pollution is a major environmental issue in urban areas, and accurate forecasting of particles 10 μm or smaller (PM10) level is essential for smart public health policies and environmental management in Tehran, Iran. In this study, we evaluated the performance and uncertainty of long short-term memory (LSTM) model, along with two spatial interpolation methods including ordinary kriging (OK) and inverse distance weighting (IDW) for mapping the forecasted daily air pollution in Tehran. We used root mean square error (RMSE) and mean square error (MSE) to evaluate the prediction power of the LSTM model. In addition, prediction intervals (PIs), and Mean and standard deviation (STD) were employed to assess the uncertainty of the process. For this research, the air pollution data in 19 Tehran air pollution monitoring stations and temperature, humidity, wind speed and direction as influential factors were taken into account. The results showed that the OK had better RMSE and STD in the test (32.48 ± 9.8 μg/m3) and predicted data (56.6 ± 13.3 μg/m3) compared with those of the IDW in the test (47.7 ± 22.43 μg/m3) and predicted set (62.18 ± 26.1 μg/m3). However, in PIs, IDW ([0, 0.7] μg/m3) compared with the OK ([0, 0.5] μg/m3) had better performance. The LSTM model achieved in the predicted values an RMSE of 8.6 μg/m3 and a standard deviation of 9.8 μg/m3 and PIs between [2.7 ± 4.8, 14.9 ± 15] μg/m3.
ANALYSIS OF THE SPATIOTEMPORAL HETEROGENEITY OF DRIVERS ON PROVINCE-LEVEL SYNERGY OF AIR POLLUTION CONTROL AND CARBON MITIGATION IN CHINA
Authors: Guo M. , Chen B. , Hamm N.
Published: December 2023

Abstract. Confronting the dual challenges of air pollution control and carbon mitigation, China is seeking a "win-win" pathway to achieve the co-reduction of air pollution and CO2 emission. In this study, taking 31 provinces in China as research objects, a novel index system, characterized by total emission, emission intensity and emission per capita, was established to evaluate the coupling coordination degree between the air pollution control (AP) subsystem and carbon mitigation (CM) subsystem at the provincial scale from 2013 to 2017. Local Geary’s C Index was performed to determine where the coupling coordination was correlated to its neighbour provinces. Considering the discrepancy of the socio-economic status, industrial and energy structure among provinces, Geographically and Temporally Weighted Regression (GTWR) was employed to measure the spatiotemporal heterogeneity of the influences of the driving factors on the coupling coordination degree, aiming to reduce uncertainty in the interpretation of spatial and temporal variability. Results show that: (1) Since the implementation of "Clean Air Action" in 2013, there has been an obvious improving trend of synergistic governance of air pollution control and carbon mitigation.  (2) The synergy of air pollution control and carbon mitigation did not achieve good joint governance, locally. (3) The influence of drivers presents significant spatiotemporal heterogeneity among provinces. Generally, the improvement of the coupling coordination is greatly affected by the local energy structure and economic level. This conclusion has propounded practical significance for synergistic governance of air quality improvement and low-carbon development in the context of carbon neutrality achievement.
TOWARDS ASSESSING SANDSTONE SURFACE MOISTURE AND DEGRADATION LEVEL FROM RADIOMETRICALLY CORRECTED TLS INTENSITY DATA
Authors: Laasch H. , Medic T. , Wieser A.
Published: December 2023

Abstract. Water is a prevalent deterioration agent for historic masonry works, especially those made of clay-bearing sandstones. To preserve cultural heritage made of sandstone, it is important to monitor, and then detect the regions with water retention or stone deterioration. To that aim, we investigate the prospects of terrestrial laser scanner (TLS) intensities for quantifying moisture in sandstone. Through a series of experiments following the drying processes of sandstone samples, we verify that TLS intensities can serve as moisture proxies for remote-sensing water retention. We identify the theoretically most suitable wavelengths, systematic effects requiring mitigation, and promising mitigation strategies. However, we also observe that the intensities are significantly affected by the type of sandstone and its level of degradation. Our results indicate that it is possible to distinguish different sandstones and levels of artificial degradation by observing and analyzing TLS-intensity time series during the drying process.
TOWARDS ACCURATE INSTANCE SEGMENTATION IN LARGE-SCALE LIDAR POINT CLOUDS
Authors: Xiang B. , Peters T. , Kontogianni T. , Vetterli F. , Puliti S. , Astrup R. , Schindler K.
Published: December 2023

Abstract. Panoptic segmentation is the combination of semantic and instance segmentation: assign the points in a 3D point cloud to semantic categories and partition them into distinct object instances. It has many obvious applications for outdoor scene understanding, from city mapping to forest management. Existing methods struggle to segment nearby instances of the same semantic category, like adjacent pieces of street furniture or neighbouring trees, which limits their usability for inventory- or management-type applications that rely on object instances. This study explores the steps of the panoptic segmentation pipeline concerned with clustering points into object instances, with the goal to alleviate that bottleneck. We find that a carefully designed clustering strategy, which leverages multiple types of learned point embeddings, significantly improves instance segmentation. Experiments on the NPM3D urban mobile mapping dataset and the FOR-instance forest dataset demonstrate the effectiveness and versatility of the proposed strategy.