bluuebunny/crossref_metadata_2025 huggingface dataset:
DIGITAL LEARNING WITH COVID-19 IN ALGERIA
Authors: ZERMANE Hanane , AITOUCHE Samia
Published: August 2020

The coronavirus (COVID-19) pandemic poses an unprecedented global challenge, impacting profoundly on health and wellbeing, daily life, and the economy around the world. The COVID-19 pandemic has also changed education forever. The COVID-19 has resulted in schools shut all across the world. Globally, all children at schools or students at universities are out of the classroom. As a result, education has changed dramatically, with the notable rise of e-learning, whereby teaching is undertaken remotely and on digital platforms. Batna 2 University -situated in East of Algeria- is one of the universities suggested after the spread of COVID-19 in March, that online learning has been shown to increase retention of information, and take less time, meaning the changes coronavirus have caused might be here to stay. All institutes and departments, including the Industrial Engineering department, are started using the e-learning Moodle platform to publish courses for all degrees of study and establish online sessions, especially for Ph.D. students.
Composición fitoquímica de la Satureja brevicalyx Epling
Authors: Andamayo Flores Diana Esmeralda , Valderrama Sueldo Martha Raquel , Castillo Andamayo Diana , Junchaya Yllescas Vilma Amparo , Camposano Córdova Yda Flor , Espinoza Castillo D. , Canales Tupac M.
Published: August 2020

Satureja brevicalyx Epling crece en la parte sur andina del Perú (Ayacucho, Apurimac, Cuzco y Puno), entre las altitudes de 3300-3800 msnm, dentro de la composición química del aceite e s e n c i a l d e S a t u r e j a b r e v i c a l y x p o d e m o s encontrar varios constituyentes como mentonas, pulegonas, linalol. Tradicionalmente se ha usado como digestivo, contra la gastritis, ﬂatulencia y antiespasmódica.OBJETIVO:Identiﬁcar la composición química del extracto etanólico,Hexano/etanol y acuoso de la Satureja brevicalyx Epling para conocer los metabolitos secundarios que sean de interés biológico en la terapeútica. MÉTODOS:Las hojas fueron exudadas y deshidratadas a temperatura ambiente, obteniéndose un polvo seco de color verdoso al cual se sometieron a extracciones sucessivas com solventes  de polaridad creciente. A los extractos obtenidos se realizaron ensayos ﬁtoquímicos de identiﬁcación. RESULTADOS:El tamizaje ﬁtoquímico ,efectuado a los extractos etanólico, hexano/etanol y acuoso de la hojas,demostró la existencia de varias familias de meta bolitos secundarios de interés biológico y farmacológico, entre los que se destacan, por su signiﬁcativa presencia las, quinonas, ﬂavonoides, alcaloides ,fenoles , taninos. CONCLUSIONES : De acuerdo a la presencia de los metabolitos secundarios presentes en las hojas de la Satureja brevicalyx Epling , así  como los efec tos farmacológicos reportados para el aceite esencial de la especie, sería importante efectuar nuevos estudios que sirvan como evidencias para avalar su empleo tradicional teniendo en cuenta la eﬁcacia y seguridad de esta planta.
Técnicas de enseñanza en prótesis parcial removible, estudiantes de odontología de una universidad de Huancayo
Authors: Cueva Buendia Luis Alberton , Jesús Balbín Evelyn Jeannet , Buendía Suazo Juan Jesús , Buendia Suazo Raquel Teodosia
Published: August 2020

OBJETIVOS: Determinar si el empleo de las técnicas de enseñanza, inciden en el aprendizaje de la asignatura de la prótesis parcial removible en estudiantes del VII ciclo de odontología de la Universidad Peruana Los Andes. MÉTODOS: La presente investigación de tipo descriptivo y nivel aplicativo, se realizó en una población de 130 estudiantes del VII ciclo de la Facultad de Odontología del curso de Prótesis Dental de la UPLA durante el período 2011-2012; la muestra fue 97 estudiantes los mismos que fueron seleccionados de manera aleatoria. Primero se analizaron las técnicas de enseñanza en estudiantes de Odontología de la UPLA, luego se trabajó la prótesis parcial removible también aplicados a dichos estudiantes, para lo cual se empleó una encuesta. El instrumento utilizado fue un cuestionario de 15 preguntas cerradas. Los datos se analizaron cuantitativamente y cualitativamente. RESULTADOS: Se evidenció que un 95% de la muestra está de acuerdo que las técnicas de enseñanza ayudan a conocer la prótesis parcial removible. CONCLUSIÓN: Se ha determinado que el empleo de las técnicas de enseñanza, inciden favorablemente en el aprendizaje de la asignatura de la prótesis parcial removible en estudiantes del VII ciclo de odontología de la Universidad Peruana Los Andes.
NOVAS PRÁTICAS JUVENIS DE LEITURA – CULTURA DIGITAL E FORMAS DE APROPRIAÇÃO
Authors: Aparecida Machado Patrícia , Hessel Silveira Rosa Maria
Published: August 2020

O presente trabalho, de cunho teórico, propõe-se a discutir como as práticas de leitura de jovens inseridos na cultura digital vêm se redefinindo na contemporaneidade, considerando os lugares onde circula a literatura, suas múltiplas configurações e novas formas de apropriação. As reflexões trazidas são inspiradas, entre outros autores, por Cerrillo, em sua ênfase à literatura juvenil para a formação de leitores, Colomer , ao caracterizar a literatura juvenil contemporânea como um lugar de fronteira, Cosson, que explora o processo de alargamento do fenômeno literário, e Lluch, que analisa as transformações da literatura e do leitor atravessadas pelo mercado e mundo digital.

Palavras-chave: Leitura juvenil. Práticas de leitura. Cultura digital.
Sistem Informasi Kependudukan Pada Kantor Lurah Sangaji Berbasis Web
Authors: Priyanto Moch Teguh , Samad Abjan , Hadad Sitna Hajar
Published: August 2020

Abstrak: Sistem informasi penduduk dimaksud untuk meningkatkan efisiensi dalam hal pelayanan dalam masyarakat. Kelurahan Sangaji kota ternate utara selama ini mempunyai sistem informasi yang masih dalam bentuk manual sehingga menyulitkan dan memperlambat dalam proses penambahan, penghapusan (atau pembuatan surat). Oleh sebab itu perlu dilakukan penelitian untuk merancang aplikasi sistem informasi penduduk. Tujuan dari sistem informasi ini adalah untuk memberikan kemudahan kepada masyarakat dalam melakukan pengurusan dokumen kelurahan, serta menginformasikan pelayanan masyarakat yang efisiensi. Langkah-langkah yang dilakukan dalam hal ini adalah analisis kebutuhan sistem, perancangan sistem. Dalam implementasi ini digunakan bahasa pemograman PHP dan sebagai databasenya digunakan MySQL.Kata Kunci: Sistem Informasi, Kependudukan, PHP, Database, MySQL.Abstract: The population information system is intended to improve efficiency in terms of service in the community. Sangaji Urban Village North Ternate City has an information system that is still in the manual form which makes it difficult and slow in the process of adding, deleting (or making letters). Therefore it is necessary to do research to design a population information system application. The purpose of this information system is to provide convenience to the community in managing urban village documents, as well as providing efficient public services. The steps taken in this case are system requirements analysis, system design. In this implementation, the PHP programming language is used and the database is used by MySQL.Keywords: Information Systems, Population, PHP, Database, MySQL
Sistem Informasi Data Beras pada Kantor Perum Bulog Sub Divre Wilayah I Ternate
Authors: . Kasmawati , Hadad Sitna Hajar , Samad Abjan
Published: August 2020

Abstrak: Seiring dengan perkembangan teknologi infomasi saat ini dilihat dari perkembangan teknologi informasi yang sangat pesat telah merambat penggunaanya diberbagi sektor baik digunakan untuk sektor perdagangan,maupun pemberian pelayanaan publik. Perum BULOG merupakan salah satu perusahaan BUMN yang bergerak di bidang logistik beras dan ketahanan pangan. Sebagai perusahaan yang tetap mengemban tugas publik dari pemerintah, BULOG dalam melakukan kegiatan yang dapat melakukan kestabilan harga dasar pembelian untuk gabah, stabilisasi harga khususnya harga pokok, menyalurkan beras untuk orang miskin (Raskin) dan pengelolaan stok pangan. Perum Bulog Sub Divre Wilayah I Ternate masih menggunakan Microsoft excel sehingga masih kurang ofisien, cepat dan tepat dalam pengolahan data beras. Dengan melihat kekurangan pengolahan data tersebut, maka dibutuhkan sebuah sistem baru yang mampu melakukan pengolahan data secara cepat dan akurat. Salah satu bentuk pengolahan informasi berbasis komputerisasi yaitu sebuah sistem yang memanfaatkan aplikasi web dengan menggunakan pemrograman PHP dan MySQL sebagai basis datanya sehingga memberi kemudahan serta kecepatan pengiriman, penyampaian dan penerimaan informasi bagi penggunaKata Kunci: Sistem Informasi, BULOG, PHP, MySQLAbstract: Along with the development of information technology today seen from the development of information technology that has been very rapid has spread its use in various sectors, both used for the trade sector, as well as providing public services. Public Corporation Bulog is a state-owned company engaged in rice logistics and food security. As a company that continues to carry out general duties from the government, BULOG in carrying out activities that can stabilize the basic purchase price for grain, stabilize prices especially basic prices, distribute rice to the poor (Raskin) and manage food stocks. Perum Bulog Sub Divre Region I Ternate still uses Microsoft Excel so it is even less efficient, fast, and precise in processing rice data. By looking at the lack of data processing, we need a new system that can do data processing quickly and accurately. One form of computerized based information processing is a system that utilizes web applications using PHP and MySQL programming as a database to provide convenience and speed of sending, delivering and receiving information for usersKeywords: Information Systems, BULOG, PHP, MySQL
Sociedade Brasileira de Física – SBF: 50 anos (1966-2016)
Authors: Silva Jr Romualdo S.
Published: August 2020

Apresenta-se uma resenha crítica do livro “Sociedade Brasileira de Física - SBF: 50 anos (1966-2016)", editado pelo físico Marcelo Knobel, do Instituto de Física Gleb Wataghin, Universidade Estadual de Campinas (Unicamp). O livro relata a trajetória histórica do estudo de física no Brasil, e a criação da Sociedade Brasileira de Física (SBF), além do estado da arte das pesquisas Brasileiras nas mais diversas áreas da física.
Física e Poesia: diálogos e potencialidades no ensino de Física
Authors: Wippel Monikeli , Silveira Camila
Published: August 2020

Versos de Mário de Sá-Carneiro, James Clerk Maxwell, Manuel Bandeira, Vinicius de Moraes, António Gedeão, Cecília Meireles, entre outros(as) podem carregar nas entrelinhas temas da Física e possibilidades para explorar conteúdos científicos. Objetivamos, a partir de um diálogo sobre Física e Poesia, apresentar a análise de alguns poemas e as potencialidades didáticas e formativas que eles revelam para o ensino de Física. O diálogo com a Poesia permite que o ensino de Física considere os contextos histórico, cultural, social, científico e artístico, visando a uma compreensão mais ampla do conhecimento científico e da realidade.
Contribuições das produções sobre a complexidade: aportes para a educação científica escolar
Authors: Watanabe Giselle , Kawamura Maria Regina Dubeux
Published: August 2020

A perspectiva da complexidade anuncia uma forma de pensar e agir frente às situações da realidade que, de modo geral, referem-se a sistemas abertos e dinâmicos. Para buscar aproximações com essa perspectiva e propor sua efetiva incorporação nas ações dos sujeitos, nos parece fundamental considerá-la no processo educacional, por meio de diferentes dimensões: Dimensão Educacional, Dimensão de Ensino-Aprendizagem e Dimensão Epistemológica. Cada uma dessas Dimensões incorpora a complexidade em contextos distintos da educação e formação científica escolar. Elas, ainda em construção, buscam organizar alguns elementos da complexidade que podem mobilizar os sujeitos para uma mudança de paradigma.  Nossa hipótese é a de que essas Dimensões, ao permear os discursos e as ações docentes, contribuam para uma formação mais complexa, próxima da realidade dos sujeitos. Diante disso, esse artigo busca investigar de que forma as questões da complexidade estão presentes nas produções de membros de grupos de pesquisa espanhóis que as incorporam no contexto da educação científica escolar. Ao investigar tais grupos, pretende-se aprofundar o sentido dessas Dimensões e suas especificidades, através de aproximações não nacionais. Metodologicamente, a pesquisa compreende dois momentos: (1) identificação dos pontos de partida de aspectos da complexidade na Dimensão Educacional, na Dimensão Ensino-Aprendizagem e na Dimensão Epistemológica; e (2) identificação desses aspectos, tomando como material de referência as produções em periódicos de alguns grupos educacionais espanhóis especialistas no assunto. Para análise dos dados, considerar-se-á a Análise Textual Discursiva, tomando como parâmetro a perspectiva da complexidade e as estratégias usuais em estudos etnográficos. Dentre os resultados, constata-se uma significativa convergência de perspectivas, ainda que com matizes. Reitera-se que uma mudança nas propostas de educação científica, que busquem ir além de um pensamento simples e trabalhar na perspectiva mais complexa, é potencializada quando a complexidade leva em conta, de forma articulada, aspectos de todas suas Dimensões. Ou seja, uma educação para a complexidade requer que ela seja incorporada em um conjunto de ações/ atitudes/ reflexões; caso contrário, a escola está apenas acentuando alguns modos de pensar e atuar que podem levar apenas às mudanças pontuais e individualizadas.
Possíveis percursos no imaginário de estudantes de licenciatura em Física sobre funções e funcionamento da avaliação
Authors: Almeida Maria José Pereira Monteiro de , Nardi Roberto , Parma Fabiano Willian
Published: August 2020

Dada a complexidade e os múltiplos sentidos que podem ser atribuídos à palavra avaliação, pensada, entre outras possibilidades, enquanto verificação de conhecimento, de disciplina, de controle de valores e atitudes, neste estudo, buscamos compreendê-la a partir de estudos voltados para essa atividade e de noções da análise de discurso pecheutiana. Na parte empírica analisamos respostas, de três licenciandos em quatro anos consecutivos, para a questão: Qual o significado da "prova" (avaliação) para você? Nessa análise buscamos responder a seguinte questão: Como o imaginário, sobre função e funcionamento da prova/avaliação, de estudantes de um curso de formação inicial de professores de física, se modificou ao longo do curso? Os resultados apontam o papel da memória discursiva dos estudantes em seus imaginários.
Relato de um Processo Investigativo a partir de Proposições Orientadas de Problemas no Ensino de Acústica
Authors: Sartori Paulo Henrique Dos Santos , Freitas Graciela De Lima
Published: August 2020

O presente estudo trata de uma proposta no âmbito do Ensino de Física, sobre o tema “Estudo do Som”. Neste trabalho discute-se o papel das atividades experimentais investigativas em sala de aula relacionadas à Física, por meio do que denominamos Proposições Orientadas de Problemas (POP). Analisa-se como os alunos de um terceiro ano do Ensino Médio Integrado de uma escola pública do município de Caçapava do Sul, RS, se apropriam e interagem com o processo de investigação e quais as relações empíricas são capazes de inferir. Constatou-se que o grupo de alunos realizou as POP de forma autônoma, colaborativa e criteriosa; evidenciando a capacidade de refletir criticamente sobre o processo e denotando um saber-fazer muito próximo ao que se esperaria de uma abordagem típica de investigações científicas, obtendo relações empíricas pertinentes às diversas situações enfrentadas.
Ozonolysis of fatty acid monolayers at the air–water interface: organic films may persist at the surface of atmospheric aerosols
Authors: Woden Ben , Skoda Max W. A. , Milsom Adam , Maestro Armando , Tellam James , Pfrang Christian
Published: August 2020

Abstract. Ozonolysis of fatty acid monolayers was studied to understand the fate of organic-coated aerosols under realistic atmospheric conditions. Specifically, we investigated the effects of temperature and salinity on the degradation of oleic acid at the air–water interface and the persistence of the aged surfactant film at the surface. The presence of a residual film is of atmospheric importance, as surface monolayers affect the physical properties of the droplets and because of the role they play in cloud formation. This occurs via several effects, most notably via surface tension reduction. The interplay between atmospheric aerosol loading and the formation, nature, and persistence of clouds is a key uncertainty in climate modelling. Our data show that a residual surface film, which we suspect to be formed of nonanoic acid and a mixture of azelaic and 9-oxononanoic acids, is retained at the interface after ozonolysis at near-freezing temperatures, but not at room temperature. Given the low temperature conditions used here are atmospherically realistic, the persistence of a product film must be considered when assessing the impact of unsaturated fatty acid partitioned to the air–water interface. The presence of stable (non-oxidisable) reaction products also opens the possibility of build-up of inert monolayers during the aerosol life-cycle with potential implications for cloud formation. We also measured the kinetic behaviour of these films and found that the reactions are not significantly affected by the shift to a lower temperature with rate coefficients determined to be (2.2 ± 0.4) × 10−10 cm2 s−1 at 21 ± 1 °C, and (2.2 ± 0.2) × 10−10 cm2 s−1 at 2 ± 1 °C.
A global model perturbed parameter ensemble study of secondary organic aerosol formation
Authors: Sengupta Kamalika , Pringle Kirsty , Johnson Jill S. , Reddington Carly , Browse Jo , Scott Catherine E. , Carslaw Ken
Published: August 2020

Abstract. A global model perturbed parameter ensemble of 60 simulations was used to explore how combinations of six parameters related to secondary organic aerosol (SOA) formation affect particle number concentrations and organic aerosol mass. The parameters represent the formation of organic compounds with different volatilities from biogenic and anthropogenic sources. The most plausible parameter combinations were determined by comparing the simulations against observations of the number concentration of particles larger than 3 nm diameter (N3), the number concentration of particles larger than 50 nm diameter (N50), and the organic aerosol (OA) mass concentration. The simulations expose a high degree of model equifinality in which the skill of widely different parameter combinations cannot be distinguished against observations. We therefore conclude that, based on the observations we have used, a 6-parameter SOA scheme is under-determined. Nevertheless, the model skill in simulating N3 and N50 is clearly determined by the low and extremely low volatility compounds that affect new particle formation and growth, and the skill in simulating OA mass is determined by the low volatility and semi-volatile compounds. The biogenic low volatility class of compounds that grow nucleated clusters and condense on all particles is found to have the strongest effect on the model skill in simulating N3, N50 and OA. The simulations also expose potential structural deficiencies in the model: we find that parameter combinations that are best for N3 and N50 are worst for OA mass, and the ensemble exaggerates the observed seasonal cycle of particle concentrations – a deficiency that we conclude requires an additional anthropogenic source of either primary or secondary particles.
Biodegradation by bacteria in clouds: An underestimated sink for some organics in the atmospheric multiphase system
Authors: Khaled Amina , Zhang Minghui , Amato Pierre , Delort Anne-Marie , Ervens Barbara
Published: August 2020

Abstract. Water-soluble organic compounds represent a significant fraction of total atmospheric carbon. The main oxidants towards them in the gas and aqueous phases are OH and NO3 radicals. In addition to chemical solutes, a great variety of microorganisms (e.g. bacteria, viruses, fungi) has been identified in cloud water. Previous lab studies suggested that for some organics, biodegradation by bacteria in water is comparable to their loss by chemical processes. We perform model sensitivity studies over large ranges of biological and chemical process parameters using a box model with a detailed atmospheric multiphase chemical mechanism and biodegradation processes to explore the importance of biodegradation of organics in the aqueous phase. Accounting for the fact that only a small number fraction of cloud droplets (~ 0.0001–0.001) contains active bacteria cells, we consider only a few bacteria-containing droplets in the model cloud. We demonstrate that biodegradation might be most efficient for volatile organic compounds (VOC) with intermediate solubility (~ 104 ≤ KH(eff) [M atm−1] ≤ 106, e.g., formic and acetic acids). This can be explained by the transport limitation due evaporation of organics from bacteria-free droplets to the gas phase, followed by the dissolution into bacteria-containing droplets. For non-volatile organics (NVOC), such as dicarboxylic acids, the upper limit of organic loss by biodegradation can be approximated by the amount of organics dissolved in the bacteria-containing droplets (
Sun-induced Fluorescence and Near Infrared Reflectance of vegetation track the seasonal dynamics of gross primary production over Africa
Authors: Mengistu Anteneh Getachew , Mengistu Tsidu Gizaw , Koren Gerbrand , Kooreman Maurits L. , Boersma K. Folkert , Tagesson Torbern , Ardö Jonas , Nouvellon Yann , Peters Wouter
Published: August 2020

Abstract. The carbon cycle of tropical terrestrial vegetation plays a vital role in the storage and exchange of atmospheric CO2. But large uncertainties surround the impacts of land-use change emissions, climate warming, the frequency of droughts, and CO2 fertilization. This culminates in poorly quantified carbon stocks and carbon fluxes even for the major ecosystems of Africa (savannas, and tropical evergreen forests). Contributors to this uncertainty are the sparsity of (micro-)meteorological observations across Africa's vast land area, a lack of sufficient ground-based observation networks and validation data for CO2, and incomplete representation of important processes in numerical models. In this study, we, therefore, turn to two remotely-sensed vegetation products that have shown to correlate highly with Gross Primary Production (GPP): Sun-Induced Fluorescence (SIF) and Near-Infrared Reflectance of vegetation (NIRv). The former is available from an updated product that we recently published (SIFTER v2), which specifically improves retrievals in tropical environments. A comparison against flux tower observations of daytime-partitioned Net Ecosystem Exchange from six major biomes in Africa shows that SIF and NIRv reproduce the seasonal patterns of GPP well, resulting in correlation coefficients of > 0.9 (N = 12 months, 4 sites) over savannas in the northern and southern hemispheres. These coefficients are slightly higher than for the widely used MPI-BGC GPP products and Enhanced Vegetation Index (EVI). Similar to SIF signals in the neighboring Amazon, peak productivity occurs in the wet season coinciding with peak soil moisture, and is followed by an initial decline during the early dry season, that reverses when light availability peaks. This suggests similar leaf dynamics are at play. Spatially, SIF and NIRv show a strong linear relation (R > 0.9, N = 250 + pixels) with multi-year MPI-BGC GPP even within single biomes. Both MPI-BGC GPP and EVI show saturation relative to peak NIRv and SIF signals during high productivity months, which suggests that GPP in the most productive regions of Africa might be larger than suggested.
Estimating maximum mineral associated organic carbon in UK grasslands
Authors: Paterson Kirsty C. , Cloy Joanna M. , Rees Robert M. , Baggs Elizabeth M. , Martineau Hugh , Fornara Dario , Macdonald Andrew J. , Buckingham Sarah
Published: August 2020

Abstract. Soil organic carbon (SOC) sequestration across agroecosystems worldwide can contribute to mitigate the effects of climate change by reducing levels of atmospheric CO2. Mineral associated organic carbon (MAOC) is considered an important long-term store of SOC and the saturation deficit (difference between measured MAOC and estimated maximum MAOC) is frequently used to assess SOC sequestration potential following the linear regression equation developed by Hassink (1997). However, this approach is often taken without any assessment of the fit of the equation to the soils being studied. The statistical limitations of linear regression have previously been noted, giving rise to the proposed use of boundary line (BL) analysis and quantile regression (QR) to provide more robust estimates of maximum SOC stabilisation. The objectives of this work were to assess the suitability of the Hassink (1997) equation to estimate maximum MAOC in UK grassland soils of varying sward ages and to evaluate the linear regression, BL and QR methods to estimate maximum MAOC. A chronosequence of 10 grasslands was sampled, in order to assess the relationship between sward age (time since last reseeding event) and current and predicted maximum MAOC. Significantly different regression equations show that the Hassink (1997) equation does not accurately reflect maximum MAOC in UK grasslands when determined using the proportion of fine soil fraction and current MAOC. The QR estimate of maximum SOC stabilisation was almost double that of linear regression and BL analysis (0.89 ± 0.074, 0.43 ± 0.017 and 0.57 ± 0.052 g C kg−1 soil, respectively). Sward age had an inconsistent effect on the measured variables and potential maximum MAOC. MAOC across the grasslands made up 4.5 to 55.9 % of total SOC, implying that there may be either high potential for additional C sequestration in the mineral fraction of these soils, or stabilisation in aggregates is predominant in these grassland soils. This work highlights the need to ensure that methods used to predict maximum MAOC reflect the soil in situ, resulting in more accurate assessments of carbon sequestration potential.
How Hack distributions of rill networks contribute to nonlinear slope length–soil loss relationships
Authors: Doane Tyler H. , Pelletier Jon D. , Nichols Mary H.
Published: August 2020

Abstract. Surface flow on rilled hillslopes tends to produce sediment yields that scale nonlinearly with total hillslope length. The widespread observation lacks a single unifying theory for such a nonlinear relationship. We explore the contribution of rill network geometry to the observed yield–length scaling relationship. Relying on an idealized network geometry, we formally develop probability functions for topological variables of contributing area and rill length. In doing so, we contribute towards a complete probabilistic foundation for the Hack distribution. Using deterministic and empirical functions, we then extend the probability theory to the hydraulic variables that are related to sediment detachment and transport. A Monte Carlo simulation samples hydraulic variables from hillslopes of different lengths to provide estimates of sediment yield. The results of this analysis demonstrate a nonlinear yield–length relationships as a result of the rill network geometry. Theory is supported by numerical modeling wherein surface flow is routed over an idealized numerical surface and a natural one from northern Arizona. Numerical flow routing demonstrates probability functions that resemble the theoretical ones. This work provides a unique application of the Scheidegger network to hillslope settings which, because of their finite lengths, result in unique probability functions. We have addressed sediment yields on rilled slopes and have contributed to an understanding Hack's law from basic probabilistic reasoning.
Alluvial cover on bedrock channels: applicability of existing models
Authors: Mishra Jagriti , Inoue Takuya
Published: August 2020

Abstract. Several studies have demonstrated the importance of
alluvial cover; furthermore, several mathematical models have also been
introduced to predict the alluvial cover on bedrock channels. Here, we
provide an extensive review of research exploring the relationship between
alluvial cover, sediment supply and bed topography of bedrock channels,
describing various mathematical models used to analyse the deposition of
alluvium. To test one-dimensional theoretical models, we performed a series
of laboratory-scale experiments with varying bed roughness under simple
conditions without bar formation. Our experiments show that alluvial cover
is not merely governed by increasing sediment supply and that bed roughness
is an important controlling factor of alluvial cover. A comparison between
the experimental results and the five theoretical models shows that (1) two
simple models that calculate alluvial cover as a linear or exponential
function of the ratio of the sediment supplied to the capacity of the channel produce good results
for rough bedrock beds but not for smoother bedrock beds; (2) two roughness
models which include changes in roughness with alluviation and a model
including the probability of sediment accumulation can accurately predict
alluvial cover in both rough and smooth beds; and (3), however, except for a
model using the observed hydraulic roughness, it is necessary to adjust
model parameters even in a straight channel without bars.
CO3D MISSION DIGITAL SURFACE MODEL PRODUCTION PIPELINE
Authors: Melet O. , Youssefi D. , L'Helguen C. , Michel J. , Sarrazin E. , Languille F. , Lebègue L.
Published: August 2020

Abstract. Earth Observation (EO) remote sensing missions are producing an increasing volume of data due to higher spatial and spectral resolutions, and higher frequency of acquisitions. Thus, in order to prepare the future of image processing pipelines, CNES has carried out Research & Development studies related to the use of Big Data and Cloud technologies for image processing chains made. Since mid-2019, CNES in partnership with Airbus Defense & Space, has started a new High Resolution Optical EO mission dedicated to very high resolution 3D observation called CO3D (“Constellation Optique 3D”). To achieve those objectives, a new image processing pipeline prototype is being developed taking in consideration the lessons learned from the previous studies. The paper will introduce this new image processing pipeline, the processing paradigms used to take advantage of big data technologies and the results of production benchmarks at a large scale. The on-going works to optimize the processing pipeline and Cloud cluster will be also discussed.
STREET TREE INFORMATION EXTRACTION AND DYNAMICS ANALYSIS FROM MOBILE LIDAR POINT CLOUD
Authors: Li Y. Q. , Liu H. Y. , Liu Y. K. , Zhao S. B. , Li P. P. , Xiao W.
Published: August 2020

Abstract. Street trees are common features and important assets in urban scenes. They are huge in numbers and are constantly changing, thus are difficult to monitor on a regular basis. A method of automatic extraction and dynamic analysis of street trees based on mobile LiDAR data is proposed. First, ground and low objects are filtered from the point clouds. Then, based on a geometric tree model and semantic information, each tree point cloud is extracted, and geometrical parameters such as location, trunk diameter, trunk structure line, tree height, crown width, and crown volume of each tree is obtained. A dynamic analysis combined with the growing characteristics of trees is conducted to compare and analyse the street trees from different epochs, in order to understand whether the trees have grown or been pruned, replanted, or displaced. The proposed algorithm was tested on three epochs of mobile LiDAR data, obtained in 2010, 2016 and 2018, respectively. Experimental results showed that the proposed method was able to accurately detect trees and extract tree parameters for detailed dynamics analysis.
TERRAIN-ADAPTIVE GROUND FILTERING OF AIRBORNE LIDAR DATA BASED ON SALIENCY-AWARE THIN PLATE SPLINE
Authors: Liu X. , Zhang Y. , Huang X. , Wan Y. , Zhang Y. , Wang S.
Published: August 2020

Abstract. Ground filtering separates the ground and non-ground points from point clouds, which is the essential process for DEM generation, semantic segmentation, model reconstruction and so forth. Considering the topologically complex terrain environments, the segmentation results are prone to be disturbed dealing with steep slopes, buildings, bridges, cliffs, etc. from Airborne LiDAR point clouds. In this paper, a saliency-aware Thin-Plate-Spline (SATPS) interpolation method is proposed including two steps: saliency division and adaptive regularized TPS interpolation with relative variance coefficient. Firstly, the point clouds are indexed in 2D grids and segments are clustered step probing toward 8-adjacent scanning directions. Then, the saliency of each grid is calculated according to the elevation variance of adjacent segments towards each scanning direction. Subsequently, grids of high ground saliency are considered as candidates for seed point selection and then clustered by region growing. The TPS surface is interpolated for each cluster loosely fitting to the seed points involving an adaptive relative variance coefficient which is according to ground saliency and elevation deviation. And finally, the ground points are extracted around the TPS surface. Experimental results indicate that the proposed SATPS algorithm achieves better Type 1 accuracy and total accuracy than the state-of-the-art algorithms in scenes with complex terrain structures, which is practical to generate DEM products.
TAILORED FEATURES FOR SEMANTIC SEGMENTATION WITH A DGCNN USING FREE TRAINING SAMPLES OF A COLORED AIRBORNE POINT CLOUD
Authors: Widyaningrum E. , Fajari M. K. , Lindenbergh R. C. , Hahn M.
Published: August 2020

Abstract. Automation of 3D LiDAR point cloud processing is expected to increase the production rate of many applications including automatic map generation. Fast development on high-end hardware has boosted the expansion of deep learning research for 3D classification and segmentation. However, deep learning requires large amount of high quality training samples. The generation of training samples for accurate classification results, especially for airborne point cloud data, is still problematic. Moreover, which customized features should be used best for segmenting airborne point cloud data is still unclear. This paper proposes semi-automatic point cloud labelling and examines the potential of combining different tailor-made features for pointwise semantic segmentation of an airborne point cloud. We implement a Dynamic Graph CNN (DGCNN) approach to classify airborne point cloud data into four land cover classes: bare-land, trees, buildings and roads. The DGCNN architecture is chosen as this network relates two approaches, PointNet and graph CNNs, to exploit the geometric relationships between points. For experiments, we train an airborne point cloud and co-aligned orthophoto of the Surabaya city area of Indonesia to DGCNN using three different tailor-made feature combinations: points with RGB (Red, Green, Blue) color, points with original LiDAR features (Intensity, Return number, Number of returns) so-called IRN, and points with two spectral colors and Intensity (Red, Green, Intensity) so-called RGI. The overall accuracy of the testing area indicates that using RGB information gives the best segmentation results of 81.05% while IRN and RGI gives accuracy values of 76.13%, and 79.81%, respectively.
QUALITY IMPROVEMENT FOR AIRBORNE LIDAR DATA FILTERING BASED ON DEEP LEARNING METHOD
Authors: Yotsumata T. , Sakamoto M. , Satoh T.
Published: August 2020

Abstract. In this paper, we discuss how to improve the quality of classification results when deep learning is applied for the filtering of airborne LiDAR point cloud. We introduce the baseline method which utilizes convolutional neural network (CNN) based on voxelization, and then we propose three methods to improve the quality of classification result. The first method is data pre-processing that aims to exclude data in advance that is clearly not on the ground surface in order to efficiently extract the ground surface data. Data pre-processing can greatly reduce the number of target points and the subsequent processing can be performed efficiently. It also has the effect of preventing noise-like points floating in the air from being misclassified as the ground surface, as compared to the case without pre-processing. The second method is changing the network structure. In recent years, various networks have been proposed for classifying point clouds. In our study, the baseline is using very simple networks. In order to improve the classification result of the baseline method, the layer depth and the range size of convolution are changed, and we investigated about the improvements of the results. The current discussion can be used as a guidance when considering new networks. The third method is the integration of classification results from multiple networks. We integrated individual results from multiple networks with varying layer depths and convolution sizes, starting with the baseline, and investigated whether the results improved. We observed that even if the individual results were similar, the classification results can be improved by integrating the results.
WIRE STRUCTURE IMAGE-BASED 3D RECONSTRUCTION AIDED BY DEEP LEARNING
Authors: Kniaz V. V. , Zheltov S. Y. , Remondino F. , Knyaz V. A. , Bordodymov A. , Gruen A.
Published: August 2020

Abstract. Objects and structures realized by connecting and bending wires are common in modern architecture, furniture design, metal sculpting, etc. The 3D reconstruction of such objects with traditional range- or image-based methods is very difficult and poses challenges due to their unique characteristics such as repeated structures, slim elements, holes, lack of features, self-occlusions, etc. Complete 3D models of such complex structures are normally reconstructed with lots of manual intervention as automated processes fail in providing detailed and accurate 3D reconstruction results.This paper presents the image-based 3D reconstruction of the Shukhov hyperboloid tower in Moscow, a wire structure built in 1922, composed of a series of hyperboloid sections stacked one to another to approximate an overall conical shape. A deep learning approach for image segmentation was developed in order to robustly detect wire structures in images and provide the basis for accurate corresponding problem solutions. The developed WireNet convolution neural network (CNN) model has been used to aid the multi-view stereo (MVS) process and to improve robustness and accuracy of the image-based 3D reconstruction approach, otherwise not feasible without masking the images automatically.
DETECTION OF INDOOR ATTACHED EQUIPMENT FROM TLS POINT CLOUDS USING PLANAR REGION BOUNDARY
Authors: Takahashi H. , Date H. , Kanai S. , Yasutake K.
Published: August 2020

Abstract. Laser scanning technology is useful to create accurate three-dimensional models of indoor environments for applications such as maintenance, inspection, renovation, and simulations. In this paper, a detection method of indoor attached equipment such as windows, lightings, and fire alarms, from TLS point clouds, is proposed. In order to make the method robust against to the lack of points of equipment surface, a footprint of the equipment is used for detection, because the entire or a part of the footprint boundary shapes explicitly appear as the boundary of base surfaces, i.e. walls for windows, and ceilings for lightings and fire alarms. In the method, first, base surface regions are extracted from given TLS point clouds of indoor environments. Then, footprint boundary points are detected from the region boundary points. Finally, target equipment is detected by fitting or voting using given target footprint shapes. The features of our method are footprint boundary point extraction considering occlusions, shape fitting with adaptive parameters based on point intervals, and robust shape detection by voting from multiple footprint boundary candidates. The effectiveness of the proposed method is evaluated using TLS point clouds.
AN AUTOMATIC KEY-FRAME SELECTION METHOD FOR VISUAL ODOMETRY BASED ON THE IMPROVED PWC-NET
Authors: Chen Y. , Yan L. , Lin X.
Published: August 2020

Abstract. In order to quick response to the rapid changes of mobile platforms in complex situations such as speedy changing direction or camera shake, visual odometry/visual simultaneous localization and mapping (VO/VSLAM) always needs a high frame rate vision sensor. However, the high frame rate of the sensor will affect the real-time performance of the odometry. Therefore, we need to investigate how to make a balance between the frame rate and the pose quality of the sensor. In this paper, we propose an automatic key-frame method based on the improved PWC-Net for mobile platforms, which can improve the pose tracking quality of odometry, the error caused by dynamic blur and the global robustness. First, a two-step decomposition is used to calculate the change of inter-frame attitude, and then, key-frames are added by the improved PWC-Net or automatically selected based on the motion state of the vehicle predicted by pose change with a short time interval. To evaluate the method, we conduct extensive experiments on KITTI dataset based on monocular visual odometry. The results indicate that our method can keep the pose tracking quality while ensuring the real-time performance.
IMPROVING THE CLASSIFICATION OF LAND USE OBJECTS USING DENSE CONNECTIVITY OF CONVOLUTIONAL NEURAL NETWORKS
Authors: Gujrathi A. , Yang C. , Rottensteiner F. , Buddhiraju K. M. , Heipke C.
Published: August 2020

Abstract. Land use is an important variable in remote sensing which describes the functions carried out on a piece of land in order to obtain benefits and is especially useful to the personnel working in the fields of urban management and planning. The land use information is maintained by national mapping agencies in geo-spatial databases. Commonly, land use data is stored in the form of polygon objects; the label of the object indicates land use. The main goal of classification of land use objects is to update an existing database in an automatic process. Recently, Convolutional Neural Networks (CNN) have been widely used to tackle this task utilizing high resolution aerial images (and derived data such as digital surface model). One big challenge classifying polygons is to deal with the large variation in their geometrical extent. For this challenge, we adopt the method of Yang et al. (2019) to decompose polygons into regular patches of fixed size. The decomposition leads to two sets of polygons: small and large, where the former suffers from a lower identification rate. In this paper, we propose CNN methods which incorporate dense connectivity and integrate it with intermediate information via global average pooling to improve land use classification, mainly focusing on small polygons. We present different network variants by incorporating intermediate information via global average pooling from different stages of the network. We test our methods on two sites; our experiments show that the dense connectivity and integration of intermediate information has a positive effect not only on the classification accuracy on the whole but also on the identification of small polygons.
CURRENT CHALLENGES IN OPERATIONAL VERY HIGH RESOLUTION LAND-COVER MAPPING
Authors: Mallet C. , Le Bris A.
Published: August 2020

Abstract. Many land-cover products have been made available for a large range of end-users over the last ten years, even at global scales. In particular, remote sensing data analysis has proved to be the most feasible solution for automation purposes, at multiple spatial scales. However, current solutions are not sufficient for designing better products, adapted to real-case applications, operational constraints, and the generation of services, built upon these core layers. In this paper, we review the main requirements and the recent changes in remote sensing for the specific case of very high resolution land-cover mapping. We also comment current and evaluate challenges for the optimal exploitation of Earth Observation images with the aim of automatically generating maps tailored to specific end-users’ needs. We advocate for more challenging large-scale benchmarks and for human-in-the-loop solutions.
OBLIQUE IMAGES AND DIRECT PHOTOGRAMMETRY WITH A FIXED WING PLATFORM: FIRST TEST AND RESULTS IN HIERAPOLIS OF PHRYGIA (TK)
Authors: Sammartano G. , Chiabrando F. , Spanò A.
Published: August 2020

Abstract. The complex archaeological site documentation benefits for a long time now from the aerial point of view and remote sensing methods. Moreover, the recent research on UAV photogrammetry platform equipment and flight planning actively contribute in this sense for a scaling improvement and cost-benefits balance. Frequently, the experiences on articulated topographic profiles in archaeological excavations require not only a multi-sensor approach but also and above all a multiscale one. According to this line, in a general time-cost ration framework, the geometric content of the generated DSMs should be complete of nadir and oblique point of view for the accurate 3D reconstruction of both upstanding buildings and excavations. In the same way, also the radiometric content closely depends on sensor payload quality and is strictly affected by excavation site condition, related to the site material and light. In this research, carried out in the impressive archaeological site of the ancient city of Hierapolis in Phrygia (Turkey) in the autumn 2019 campaign, the main goal was to evaluate and validate the overall performance of a novel UAV fix-wing ultralight platform with onboard GNSS receiver for RTK/PPK processing of cameras positioning and with the possibility of oblique images capturing. The expected contribute in terms of the acquisition, processing time, radiometric enhancement and geometry 3D reconstruction will be explored with preliminary test and outcomes, and with the results of the high-scale DSM and orthoimage generation of the complete Hierapolis site.
DIGITAL PHOTOGRAMMETRY, TLS SURVEY AND 3D MODELLING FOR VR AND AR APPLICATIONS IN CH
Authors: Scianna A. , Gaglio G. F. , La Guardia M.
Published: August 2020

Abstract. The world of valorization of Cultural Heritage is even more focused on the virtual representation and reconstructions of digital 3D models of monuments and archaeological sites. In this scenario the quality and the performances offered by the virtual reality (VR) and augmented reality (AR) navigation take primary importance, improving the accessibility of cultural sites where the real access is not allowed for natural conditions or human possibilities. The creation of a virtual environment useful for these purposes requires a specific workflow to follow, combining different strategies in the fields of survey, 3D modelling and virtual navigation. In this work a specific case of study has been analyzed as a practical example, the church of ‘San Giorgio dei Genovesi’, settled in the Historic Centre of Palermo (Italy). The acquisition of geometric information has been obtained with the integration of Terrestrial Laser Scanner (TLS) technologies and the photogrammetric reconstruction from mini Unmanned Aerial Vehicle (UAV) equipment. The obtained point cloud has been georeferred considering a network of Ground Control Points (GCP) acquired by a Global Navigation Satellite System (GNSS) receiver. The final point cloud has been processed and properly simplified through 3D modelling procedures, to obtain a realistic and light 3D model reconstruction. The model has hence employed into a VR WEB navigation system and will be used for AR outdoor application in the future, allowing to obtain different solutions for empowering the accessibility of the cultural good. The strategy of 3D CH model reconstruction, followed in this work, could be considered a reference methodology for the development of VR gaming applications finalized to CH valorization and AR applications, applied to museums or touristic paths in historical centres.