bluuebunny/crossref_metadata_2025 huggingface dataset:
Experiencias alternativas de formación y prácticas docentes en la Argentina durante las primeras décadas del siglo XX. Las propuestas de Rosario Vera Peñaloza y Clotilde Guillén De Rezzano
Authors: Dono Rubio Sofia
Published: December 2023

Reseña de tesis de maestría. Experiencias alternativas de formación y prácticas docentes en la Argentina durante las primeras décadas del siglo XX. Las propuestas de Rosario Vera Peñaloza y Clotilde Guillén De Rezzano
Kulak Burun Boğaz Hastalıklarında Lazer Uygulamaları
Authors: Murat Yener Haydar , Aliyeva Chinara
Published: December 2023

Lazer, yoğun ışın üreten bir cihazdır. En sık kullanılan üç cerrahi lazer türü, elektromanyetik spektrumun görünür kısmı içinde olan argon lazer; neodim:itriyum–alüminyum–garnet (Nd:- YAG) lazer; ve karbondioksit (CO2) lazerdi. Lazerin doku üzerindeki etkileri absorpsiyon, saçılma, iletim veya yansıma şeklinde görülür. Lazere maruz kalan dokudaki değişiklikler, lazerin oluşturduğu ısı ile ilişkilidir. İlk tıbbi uygulama 1962’de dermatoloji alanında Leon Goldman tarafından rapor edilmiştir. 1965 yılında daha sonra tıpta ve Kulak Burun Boğaz ve Baş Boyun cerrahisinde yaygın uygulamalara sahip olacak olan karbondioksit (CO2) lazer geliştirilmiştir. CO 2 lazerler özellikleri nedeniyle özellikle fonocerrahi prosedürler için laringeal mukozanın çoğu patolojik durumu için en iyi araçlardır. Lenz ilk kez 1970’lerin sonunda alt konka küçültülmesi için argon lazer kullanmıştır. O zamandan beri de özellikle endoskopik yöntemlerin gelişmesiyle lazerlerin rinoloji alanında kullanımı gittikçe artmaktadır. Lazerler, kulak mikrocerrahisi için hassas aletler olarak kullanılabilir. CO 2 lazer stapes mikrocerrahisi için mükemmel bir alettir. Özellikle fiber optik mikro manipülatör ile güvenlik seviyesini artırılabilir ve güvenli ve başarılı şekilde stapes cerrahisinde kullanılabilir.
Doğum Korkusunu Azaltmaya Yönelik Bir Yaklaşım: Duygusal Özgürleşme Tekniği
Authors: GÜVERİ Hilal , BEKAR Mine
Published: December 2023

Doğum eyleminin başlaması, gebenin yaşadığı fizyolojik ve psikolojik stres düzeyini artırabilmektedir. Doğum korkusuna bağlı ağrıyı azaltmaya yönelik tıbbi olmayan teknikler mevcuttur. Bunlar arasında akupunktur, refleksoloji, hipnoz, müzik terapisi, duygusal özgürleşme tekniği, aromaterapi gibi birçok teknik vardır. Duygusal Özgürleşme Tekniği (EFT), bireyin sahip olduğu rahatsız edici duygu ve düşüncenin bedenindeki enerji akışını bozarak tıkanıklık yaratması ilkesine dayanan enerji psikoterapisidir. EFT, Enerji bedeninde olumlu enerji akışı olduğunda kişiler olumlu duygular (mutluluk, kendini iyi hissetme gibi) hissetmekte, ancak enerji bedeninde blokajlar (tıkanıklık) olduğunda, enerji akışı kesintiye uğramaktadır. Enerji blokajlarının sonucunda zihin /beden /enerji sisteminin dengesi bozulmakta, olumsuz duygular (stres, panik, öfke gibi) ortaya çıkmaktadır. EFT uygulamasında izlenmesi gereken basamaklar mevcuttur; telkin cümleleriyle duygu bedenine (bilinçaltına) mesaj vererek on iki enerji meridyen uç noktasına (akupresür noktaları) tıklamalar yapılır. Günümüzde EFT bağımlılık, öfke, yas, ölüm, ağrı, ilişkiler, cinsellik, fobiler, depresyon, yeme bozuklukları gibi birçok alanda kullanılabilmektedir. Gebeler, doğum dalgalarıyla baş etmeyi başardığında korku azalmakta ve gevşeme sağlanabilmektedir. EFT, gebelerde duygusal sorunları çözer, kaygıyı azaltır, daha sakin ve olumlu düşündürerek anne ve fetüsün sağlığını destekler. Aynı zamanda, EFT, gebeyi travay ve doğum sırasında, kontraksiyonların hissedilen ağrısını azaltmaya ve travay süresinin kısalmasına yardımcı olmak için güvenle ve etkili bir şekilde uygulanabilmektedir. Sonuç olarak doğum korkusuna bağlı yaşanan ağrı kadının doğum sürecini olumsuz yönde etkileyen ciddi bir sorundur. Gebelerin korku ve ağrıyı kontrol etme yöntemleri ebelik bakımının önemli unsurlarındandır. Kadınlar farmakolojik olmayan ağrı kontrol etme yöntemlerini ilk tercih olarak kullanabilmektedir. Ebeler doğum korkusu olan kadınları desteklemeli ve gebe ile birlikte karar vererek farmakolojik olmayan yöntemleri uygulayabilmelidir.
Solidarity and the protection of migrants under European Union law
Authors: Braga Guimarães Gabriel
Published: December 2023

The management of migration flows in the European Union (EU) faces significant challenges due to the substantial increase in migrants and refugees. The lack of cohesion and modernization in the common migration policy weakens the protection of their rights. In this context, solidarity plays a vital role in addressing legal demands, particularly in EU Law, where it serves as a fundamental principle. This study aims to analyze the legal concept of solidarity within EU Law, with a specific focus on the protection of migrant rights. Adopting a theoretical approach, the research utilizes documental and bibliographical analysis. The study is divided into two parts. The first part examines solidarity in the context of international law and EU law, considering its challenges and significance in state-to-state relations. The second part explores solidarity as a fundamental principle for safeguarding the rights of migrants in the EU. It investigates the role and operationalization of solidarity within specific legal frameworks. The findings reveal that the unique social, political, and economic circumstances of each state or group of states present significant obstacles to the effective implementation of solidarity and the protection of migrant rights. The future of common migration policies in the EU remains uncertain. Therefore, it is crucial to harmonize regulatory instruments, enhance migration management, and address the socio-political and economic challenges to ensure adequate protection for migrant rights. This study emphasizes the need for a more cohesive and comprehensive approach to managing migration flows within the EU, aiming to guarantee the fundamental rights of migrants and refugees. Overcoming existing obstacles and promoting the effective implementation of solidarity are essential in improving migration policies and strengthening mechanisms for the protection of human rights.
THE ROLE OF AGRICULTURAL EXTENSIONERS IN THE DYNAMICS OF FARMER GROUP IN TANJUNG MEDAN SUB DISTRICT, ROKAN HILIR DISTRICT
Authors: Addindi Bendri , Arifudin  , Cepriadi
Published: December 2023

The importance of the role of agricultural extension workers is carried out to bring up human resources in Tanjung Medan District so that they are able and willing to move dynamically to manage and develop farming activities in order to create prosperity. The large number of passive farmer groups is a problem in today's agricultural institutions. Therefore, quality improvement in agricultural activities will be supported and created if farmer groups and extension workers work together to achieve common goals. This research was conducted to determine the level of the instructor's role, the level of group dynamics and the influence of the instructor's role on group dynamics. This study used a survey method with 114 farmers as respondents who were selected by cluster sampling. Data were analyzed using a Likert scale and SEM test using Amos 24. Agricultural extension workers had carried out their role very well because they were in the very high category, namely the role of extension workers as facilitators, innovators, motivators, dynamists, educators, and consultants. The dynamics of farmer groups are classified as very dynamic because they are in a very high category, namely group objectives, group structure, group functions, group coaching and development, group cohesiveness, group atmosphere and group effectiveness. Then the role of agricultural extension agents has a significant effect on the dynamics of farmer groups, which means that the increasing role of agricultural extension agents will increase the dynamics of farmer groups in Tanjung Medan Sub District.
PREVALÊNCIA DE DISMENORREIA EM UNIVERSITÁRIAS E SUA RELAÇÃO COM ABSENTEÍSMO ESCOLAR
Authors: Arcaminho Ágda Karolyne Ferreira de , Nascimento Laís de Caldas , Dias Júnior Walter
Published: December 2023

A dismenorreia é popularmente conhecida como cólica menstrual e é caracterizada por uma dor na parte inferior do abdômen, se manifestando no período pré e intra-menstrual. O presente estudo tem por objetivo estimar a prevalência de dismenorreia primaria em universitárias, e sua relação com a frequência de absenteísmo escolar. Trata-se de um estudo descritivo, realizado com universitárias do curso de Enfermagem, por meio de um questionário auto aplicado e formulado por Rodrigues (2011). Posteriormente os dados foram analisados por meio de estatística descritiva. A amostra constou com 78 universitárias, com idade entre 18 e 55 anos (idade média de 24,2±6,1 anos). Sessenta e quatro (82,05%) universitárias apresentavam queixa de dismenorreia, que predominaram na faixa etária de 18 a 41 anos de idade. Quanto ao grau de intensidade de dismenorreia, 85,93% descreveram a dor como moderada e severa. Catorze (21,87%) participantes afirmaram já ter faltado à aula por causa das cólicas menstruais. Os métodos mais utilizados para alivio da dor foram medicamentos (81,25). Trinta e três universitárias (51,56%) consideravam estar informadas o suficiente sobre a dismenorreia. O estudo revelou uma alta prevalência de dismenorreia entre as universitárias, com o grau de dor variando entre moderado e severo. Apesar da intensidade da dor, observou-se um baixo índice de absenteísmo escolar, possivelmente devido ao amplo uso de medicamentos para o alívio da dor.
Palavras – chaves: Cólicas Menstruais; Dor pélvica; Ausência Escolar; Acadêmicas.
SAÚDE MENTAL DO ENFERMEIRO NA PANDEMIA COVID- 19
Authors: Jesus Joseane Fernandes de Lima de , Souza Luciene Ferreira de , Machado Luana Costa da Cruz
Published: December 2023

Introdução: De acordo com a Organização Mundial da Saúde (OMS), a saúde mental é o completo bem-estar físico, mental e social, e não consiste apenas na ausência de doença ou de enfermidade. Objetivo: Identificar as evidências científicas sobre a saúde mental dos enfermeiros que atuaram na linha de frente durante a pandemia COVID-19 e assim compreender a importância do bem estar mental do mesmo. Métodos: Trata- se de estudo baseado na revisão de literatura na plataforma BIREME, utilizando os bancos de dados da LILACS e BDENF, com recorte temporal de cinco anos. Os dados foram coletados no período de abril a  maio de 2022. Resultados e Discussão: Foram selecionados ao final dos refinamentos 11 artigos e após a leitura surgiram três categorias : Principais recursos de apoio e desenvolvimento dos profissionais em enfermagem mediante a pandemia do COVID- 19; A saúde mental e a recorrência de depressão e ansiedade nos profissionais de enfermagem de frente a pandemia do COVID- 19 e O impacto psicossocial causado em profissionais de enfermagem durante a pandemia do COVID- 19. Conclusão: Quando observado os aspectos da “Saúde Mental do Enfermeiro Durante a Pandemia”, podemos observar que houve o aumento da depressão e da ansiedade desses profissionais da saúde.
A PRISÃO DOMICILIAR E A NECESSIDADE DE ADEQUAÇÃO À MULHER PRESA
Authors: Costa Ana Clara de Sousa , Cunha Alves Bomfim Brenda , Freitas de Gondra Lima Marcílio Rikardo , De Sousa Lima Jairo
Published: December 2023

A necessidade de conversão da prisão para prisão domiciliar para as mulheres reclusas faz-se necessário para a garantia e seguridade de diversos direitos, desde a assistência jurídica essencial, às condições básicas de subsistência das mesmas. O referido trabalho busca estudar as principais situações de possibilidade da aplicabilidade da prisão domiciliar à mulheres presas, visando discutir a possibilidade de ampliar a utilização do instituto em cumprimento aos preceitos constitucionais, em especial a dignidade humana, refutando a separação forçada entre mães, seus filhos e familiares. O método de pesquisa utilizado é a análise bibliográfica onde foi utilizada a literatura já existente cumulada aos dados dos diversos grupos de pesquisa, elucidamos a situação da mulher presa no Brasil. O trabalho foi estruturado em dois capítulos. O primeiro aborda, O conceito histórico e origem da prisão domiciliar no Brasil. O segundo, traz as possibilidades de prisão domiciliar da mulher encarcerada. Ao final, conclui-se que, é necessário que o judiciário dê visibilidade a problemática, aumentando assim os deferimentos a favor da conversão da prisão preventiva para prisão domiciliar, com o intuito de ampliar as possibilidades de concessão dessa progressão de regime,incluindo então alguns casos não previstos expressamente em leis.
O USO DE ANTIDEPRESSIVOS NA ADOLESCÊNCIA DECORRENTES DA PANDEMIA COVID-19
Authors: Gonzaga Larissa do Nascimento , Rinaldi Neto Sebastian
Published: December 2023

Na sociedade em que vivemos houve um aumento notório no número de patologias mentais na população, sendo perceptível que se agravaram na pandemia gerando um grande problema para população. O presente estudo diz respeito ao uso de antidepressivos na adolescência decorrente da pandemia covid-19, apontando os possíveis impactos psíquicos e emocionais, descrevendo os resultados do consumo do medicamento por adolescentes. A metodologia utilizada para a realização do estudo foi um levantamento de dados de artigos científicos, revistas eletrônicas e impressas, jornais e livros que já desenvolveram textos relevantes ao assunto. Em resumo, o uso de medicamentos é essencial no tratamento, mas podem expor o usuário a eventos adversos e interações medicamentosas.
The sensitivity of Southern Ocean atmospheric dimethyl sulfide (DMS) to modeled oceanic DMS concentrations and emissions
Authors: Bhatti Yusuf A. , Revell Laura E. , Schuddeboom Alex J. , McDonald Adrian J. , Archibald Alex T. , Williams Jonny , Venugopal Abhijith U. , Hardacre Catherine , Behrens Erik
Published: December 2023

Abstract. The biogeochemical formation of dimethyl sulfide (DMS) from the Southern Ocean is complex, dynamic, and driven by physical, chemical, and biological processes. Such processes, produced by marine biogenic activity, are the dominant source of sulfate aerosol over the Southern Ocean. Using an atmosphere-only configuration of the United Kingdom Earth System Model (UKESM1-AMIP), we performed eight 10-year simulations for the recent past (2009–2018) during austral summer. We tested the sensitivity of atmospheric DMS to four oceanic DMS datasets and three DMS transfer velocity parameterizations. One oceanic DMS dataset was developed here from satellite chlorophyll a. We find that the choice of oceanic DMS dataset has a larger influence on atmospheric DMS than the choice of DMS transfer velocity. Simulations with linear transfer velocity parameterizations show a more accurate representation of atmospheric DMS concentration than those using quadratic relationships. This work highlights that the oceanic DMS and DMS transfer velocity parameterizations currently used in climate models are poorly constrained for the Southern Ocean region. Simulations using oceanic DMS derived from satellite chlorophyll a data, and when combined with a recently developed linear transfer velocity parameterization for DMS, show better spatial variability than the UKESM1 configuration. We also demonstrate that capturing large-scale spatial variability can be more important than large-scale interannual variability. We recommend that models use a DMS transfer velocity parameterization that was developed specifically for DMS and improvements to oceanic DMS spatial variability. Such improvements may provide a more accurate process-based representation of oceanic and atmospheric DMS, and therefore sulfate aerosol, in the Southern Ocean region.
AN EVALUATION OF STEREO AND MULTIVIEW ALGORITHMS FOR 3D RECONSTRUCTION WITH SYNTHETIC DATA
Authors: Fuentes Reyes M. , d’Angelo P. , Fraundorfer F.
Published: December 2023

Abstract. The reconstruction of 3D scenes from images has usually been addressed with two different strategies, namely stereo and multiview. The former requires rectified images and generates a disparity map, while the latter relies on the camera parameters and directly retrieves a depth map. For both cases, deep learning architectures have shown an outstanding performance. However, due to the differences between input and output data, the two strategies are difficult to compare on a common scene. Moreover, for remote sensing applications multi-view data is hard to acquire and the ground truth is either sparse or affected by outliers. Hence, in this article we evaluate the performance of stereo and multi-view architectures trained on synthetic data resembling remote sensing images. The data has been and processed and organized to be compatible with both kind of neural networks. For a fair comparison, training and testing are done only with two views. We focus on the accuracy of the reconstruction, as well as the impact of the depth range and the baseline of the stereo array. Results are presented for deep learning architectures and non-learning algorithms.
3D RECONSTRUCTION FROM MULTI-VIEW GOOGLE EARTH SATELLITE STEREO IMAGES BY GENERATING VIRTUAL RPC BASED ON 3D HOMOGRAPHY-BASED GEOREFERENCING
Authors: Seo D. U. , Park S. Y.
Published: December 2023

Abstract. In this paper, we propose a method for performing 3D reconstruction by generating virtual RPC parameters from multi-view satellite stereo images provided by Google Earth (GE) software. In the multi-view stereo (MVS) image in a general case, after the pose and parameters of the camera are estimated, a dense 3D surface can be reconstructed. However, in the case of satellite images, it is not easy to obtain the original images with pose parameters of an area of interest. In the case of GE software, which can obtain images across the globe, the images provided are georeferenced and modified to fit the ground control point (GCP), so there is no camera model to explain the projection relationship. Therefore, the purpose of the proposed method is to perform 3D reconstruction by generating virtual camera parameters in modified satellite images obtained from GE software. In the proposed method, satellite images obtained from GE are estimated to be pinhole images using structure from motion (SfM) for initial reconstruction. After initial reconstruction, the 3D model is transformed from a distorted hexahedral space formed along a pixel ray to a UTM coordinate system metric space through a 3D homography-based georeferencing. A virtual rational polynomial camera (RPC) parameter is calculated through the satellite images and the 3D interspace correspondence point of UTM coordinates. The result is generated by virtual RPC and the MVS method using the RPC model. The reconstructed DSM using virtual RPC is improved over the initial reconstruction of the proposed process, and error measurement in the area with GT obtained significant results with an average of 1.366m on an MAE method.
FILLING GAPS BETWEEN MESHES OF TREE CROWN AND TREE TRUNK BASED ON BOUNDARY CONSTRAINTS AND COORDINATE PROJECTION FOR 3D TREE MODELLING
Authors: Wang W. X. , Hong L. P. , Huang H. S. , Li X. M. , Tang S. J. , Guo R. Z. , Xie L. F.
Published: December 2023

Abstract. In order to reconstruct high-quality 3D tree models, trunks and crowns could be reconstructed using appropriate methods separately and merged together. During this process, gaps will appear after tree models are spliced, which will affect the models' topological connectivity and visual effects. In this paper, a gap-repair algorithm for tree mesh models based on boundary restriction and coordinates projection is proposed. The algorithm first extracts all the holes in the tree trunk meshes and crown meshes and matched them according to their relative positions. Then, the gaps in the tree meshes are identified. After that, based on the projection of the hole vertices from 3D space to 2D space, the relative positions of the hole vertices were determined, and vertex connection and surface addition were carried out to generate a 2-manifold patch. Finally, the patch was refined to keep its density of vertices similar to the surrounding meshes. Real 3D Tree meshes of different species were used to conduct experiments, and the quality of the repaired tree models are evaluated qualitatively and quantitatively. Experimental results revealed that the proposed algorithm could fill gaps in tree meshes quickly and effectively, so as to achieve the topology connection and smooth transition between the trunk and crown meshes.
IMPROVING GNSS POSITIONING RELIABILITY AND ACCURACY BASED ON FACTOR GRAPH OPTIMIZATION IN URBAN ENVIRONMENT
Authors: Zhang Y. , Zhu F. , Zhang X.
Published: December 2023

Abstract. Global navigation satellite system (GNSS) can provide global, precise, and continuous positioning in open-sky environments. However, urban environments with frequent outliers and cycle slips degrade the traditional Extended Kalman Filter (EKF) positioning performance. The susceptibility of EKF to outliers is attributed to its inherent structure. To mitigate, the GNSS positioning based on the Factor Graph Optimization (FGO) structure is adopted. FGO can enhance time correlation among observations and enable the updating of historical information, thereby improving resistance against outliers. In this study, we proposed a single-differenced GNSS-FGO model instead of the double-differenced model to preserve the sparsity of FGO, and outlier detection and PAR methods are employed to ensure urban positioning performance. To evaluate the proposed structure, experiments are conducted in both urban and open-sky environments. The results demonstrate the improvement of positioning accuracy and reliability, compared to EKF.
EVALUATION OF INTEL REALSENSE D455 CAMERA DEPTH ESTIMATION FOR INDOOR SLAM APPLICATIONS
Authors: Hübner P. , Hou J. , Iwaszczuk D.
Published: December 2023

Abstract. The aim of this study is to propose evaluation methodology for the quality assessment of depth cameras for indoor mapping applications. Specifically, we evaluate the RGBD sensor Intel Realsense D455 w.r.t. measurement accuracy and noise while investigating their dependence on two central parameters characterizing the measurement scenario simultaneously: measurement distance and inclination of observed surfaces. The evaluation results are presented two-dimensionally as a function of both parameters. To this aim, two evaluation studies are conducted. First, a checkerboard pattern is used as reference object in a controlled setting. Secondly, actual indoor mapping data resulting from the deployment of the evaluated sensor in the context of an RGBD-SLAM application is used to conduct a similar evaluation in representative conditions for the intended usage scenario of indoor mapping. In this case, a TLS scan of the respective indoor environment is used as reference for evaluation.
DEFORMATION MONITORING AND SENSITIVITY ANALYSIS OF UNDER-CONSTRUCTION BRIDGES CONSIDERING PS OPTIMIZATION
Authors: Xu Z. , Zhang X. , Xie H. , Chen B. , Li Z. , Zhang Y.
Published: December 2023

Abstract. During the construction and operation of bridges, safety accidents can occur due to improper design, construction, development of structural diseases, and inadequate maintenance measures. Such incidents can lead to significant property damage and casualties. InSAR technology is increasingly playing a critical role in the deformation monitoring of linear projects, such as bridges and roads because it is not affected by light and weather conditions. However, in the process of bridge construction, the instability of the environment often results in low scattering intensity, which can make it challenging to obtain a sufficient number of permanent scatterer (PS) points. This study proposes a method to optimize the identification of PS points by combining amplitude dispersion index, statistical median of amplitude mean, and temporal coherence coefficient, based on TerraSAR-X data. We then employed PS-InSAR technology to monitor the deformation of the under-construction bridge over the JingXiong Expressway-Yongding River, China. Furthermore, we conducted temporal subsidence analysis for different structural locations of the bridge while combining temperature data from weather stations to carry out a sensitivity analysis of the bridge deformation. The study results demonstrated that (1) the proposed method for optimizing the identification of PS points outperformed the two traditional methods in terms of increasing the selection of PS candidates by 14% and 10% respectively, while also leading to better quality identification of the PS candidates; (2) the main body of the under-construction bridge appeared relatively stable at present, with the deformation of the bored cast-in-situ piles and the connection of the approach span and abutment showing greater magnitude compared to other areas. Thus, it is essential to conduct regular monitoring of these regions and implement preventive measures in the future; and (3) the deformation of the under-construction bridge is correlated with the ambient temperature, and different structural locations display varying sensitivity to temperature changes. The findings of this study can help guide the subsequent construction and safe operation of the under-construction bridge after completion.
ON THE ASSESSMENT OF INSTANCE SEGMENTATION FOR THE AUTOMATIC DETECTION OF SPECIFIC CONSTRUCTIONS FROM VERY HIGH RESOLUTION AIRBORNE IMAGERY
Authors: Achanccaray P. , Gerke M. , Wesche L. , Hoyer S. , Thiele K. , Knufinke U. , Krafczyk C.
Published: December 2023

Abstract. During the High Modernism period spanning from approximately 1914 to 1970, the manufacturing of steel-constructed system halls witnessed a significant surge to accommodate the growing demand across various sectors such as industry, commerce, and agriculture. Surprisingly, these specific types of buildings have been largely overlooked in the realm of construction history research, resulting in a dearth of knowledge regarding their construction methods, distribution patterns, and contextual significance for assessing their historical value. This study aims to address this gap by exploring the potential of instance segmentation methods for the automated detection of system halls using high-resolution aerial imagery. To achieve this objective, state-of-the-art deep learning models are evaluated in terms of their ability to localize and delineate system halls accurately. Our experiments reveal that Mask R-CNN yields the most accurate results both quantitatively and qualitatively, closely followed by Cascade Mask R-CNN. However, it is important to note that multi-scale methods may introduce false positives since system halls possess distinct geometric dimensions that necessitate careful consideration during the detection process.
THE EFFECTS OF LAND COVER CHANGES ON LAND SURFACE TEMPERATURES
Authors: Aslan N. , Koc-San D.
Published: December 2023

Abstract. The aims of this study are to detect the land-cover maps and land surface temperatures using Landsat time series and analyse the relation between the land-cover and land surface temperatures (LST) and their changes in time. For these purposes initially, land-cover maps were generated rapidly using land cover indices and automatic thresholding. The land-cover indices used in this study are Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Index-Based Built-Up Index (IBI), Modified Bare-Soil Index (MBI), Plastic-Mulched Landcover Index (PMLI), Plastic Greenhouse Index (PGI) and Normalized Burn Ratio Thermal (NBRT) Index. Then, using the thermal bands of Landsat satellites, LST maps were created. Finally, the land-cover and LST changes were examined. The Kumluca district of Antalya, which includes extensive greenhouse areas as well as urban, vegetation, bareland, water, was selected as study area. Between the years 2004 and 2021, within the study area the greenhouse areas increased significantly, the urban area expanded and some areas exposed to fire, especially the fire in 2016. Therefore, the images within this time period were used. The overall accuracies for land-cover maps were computed as 76%, 79%, 79%, 89% and 86% for the years 2004, 2009, 2013, 2017 and 2021, respectively. The results obtained from the study reveal that while greenhouse and urban areas were increased, the vegetation areas were decreased significantly within this time period. In addition, generally increases were observed for LST values of all land-cover classes and the highest LST values were detected for the burned, bareland, urban and greenhouse areas.
RESEARCH ON COOPERATION STRATEGY BASED ON SATELLITE REMOTE SENSING DATA SERVICE AND TECHNOLOGY APPLICATION BETWEEN CHINA AND ASEAN
Authors: Dong L. , Lyu S. , Wang L. , Gao X.
Published: December 2023

Abstract. Remote sensing (RS) and earth observing technology are flourished with the development of a series of high-resolution earthobservation satellites. As the improvement of China’s earth observation data acquisition capability, one critical issue is put on the agenda that is what kind of models and techniques can promote the future data processing into a new level in terms of service model, massive data processing, development methods, business models, resource sharing, and system sustainability (1). In order to embed domestic satellite advantages into global world and provide increasingly more Chinese wisdom and solution to support the ASEAN regional development, China highlights the propositions on ASEAN-China remote sensing cooperation. On November 1, 2022, the ASEAN-China Satellite Remote Sensing Application Centre (hereinafter referred to as the ACSAC) was officially inaugurated in Beijing. The ACSAC will mainly focus on the establishment of a system and mechanism for a series of substantive operation, promoting the comprehensive sharing of China's land and ocean satellite data, comprehensively rich the international application scenarios of Chinese satellites, promoting applications in multiple fields and carrying out satellite remote sensing application promotion and typical demonstration, continuing to carry out technical exchanges and training with mutual demands and development. At present, ACSAC has stepped into the substantive construction stage. It will give full play to the advantages of China's natural resources land and ocean satellite remote sensing resources, to form a multi-scale, full coverage data resource support, jointly carry out the construction of the ASEAN-China satellite remote sensing data network platform based on the cloud environment, and to jointly build an integrated service open portal for land and ocean satellite data products to ASEAN region. Focusing on the core construction content of ACSAC, this paper systematically collects, summarizes and analyse the data and application needs of satellite remote sensing in ASEAN countries, finds out the current needs to meet the gap, and puts forward some thoughts and ideas on cooperation mechanism, data sharing, customized products and application demonstration of advanced products, aiming to lay a solid foundation for the substantial construction of ACSAC.
URBAN GREEN SPACE IDENTIFICATION BY FUSING SATELLITE IMAGES FROM GF-2 AND SENTINEL-2
Authors: Kang B. , Cai G.
Published: December 2023

Abstract. This paper combines class hierarchy construction and feature-preferred random forest classification method, and the classification results are the best. In the urban center area with complex features, this method can be used to extract small and complex features more accurately, and for urban green spaces, small auxiliary green spaces between houses can be accurately extracted. This method first constructs a class hierarchy of four sizes, and then extracts different features from simple to complex, from large to small, and classifies them by membership function for the direct selection feature rules of easily extracted features. For the subdivision of green space and the classification of features in central complex areas, feature optimization is carried out, and the optimal feature combination is selected and then extreme random tree (ERT) classification is performed. The classification accuracy is the best 89.5%, and the classification results are analyzed correctly, which correctly distinguishes the smaller land categories in the central area, reduces the misclassification of grassland and agricultural land, and the classification results are optimal.
APPLICATION OF DEEP LEARNING CROP CLASSIFICATION MODEL BASED ON MULTISPECTRAL AND SAR SATELLITE IMAGERY
Authors: Qi Y. , Bitelli G. , Mandanici E. , Trevisiol F.
Published: December 2023

Abstract. Classifying crops using satellite data is a challenge, especially since most crops have similar growth cycles. Due to their different characteristics and chlorophyll content, different crops exhibit subtle differences in their reflectance spectra. This study uses a data-driven approach to build a series of deep learning models to classify 36 different land covers in Steele County and Traill Country, North Dakota, US. A Google Earth Engine workflow was implemented to generate a composite layer containing Sentinel 1 and Sentinel 2 satellite data and surface crop data over the study area. 200,000 sample points were generated on this layer, 140,000 for training dataset, 30,000 for validation dataset and 30,000 for testing dataset. Each sample point contains the values of 12 months of SAR and spectral data. In this way, a two-dimensional feature matrix of the time dimension and spectral band dimension (bands refer to specific wavelengths of data in remote sensing imagery and other type of data like NDVI) is generated for each sample point. The training dataset of the model is composed of the feature matrix of these sample points, and the surface crops as labels correspond to the feature matrix. Since this is a dataset with two-dimensional features, this research uses four deep learning models: Dense Neural Network (DNN), Long short-term memory (LSTM), Convolutional neural network (CNN) and Transformer. Among them, the Transformer model based on the self-attention mechanism performed the best, with a comprehensive accuracy rate of 85%, and the classification accuracy rate of crops with more than 2,000 sample points in the training data set reached more than 90%.
UNCERTAINTY MODELING AND ANALYSIS OF SPACEBORNE INFRARED HYPERSPECTRAL IMAGES OVER RUGGED LAND SURFACE
Authors: Qiu X. , Li Z. , Liu S. , Liu T. , Jia G.
Published: December 2023

Abstract. Infrared hyperspectral imaging is an important technical means to obtain the emissivity spectra and temperature of land surface target, and is an important development direction of spaceborne optical remote sensing in the future. Under the natural rugged land surface condition, the quality of infrared hyperspectral imaging data is affected by terrain condition, atmospheric condition and instrument performance. Therefore, the instrument signal-to-noise ratio and the calibration accuracy could not directly describe the measurement accuracy of the hyperspectral characteristics of target. An uncertainty prediction model of spaceborne infrared hyperspectral images over rugged land surface is established, in this paper. This model could simulate the surface scene, the atmospheric radiation transfer over rugged land surface, and the imaging process of the spaceborne spectrometer. At the same time, the uncertainty transfer from the surface signal to the restored radiance data product could be realized. The generated uncertainty results include the fluctuation of the surface signal, the error of the atmospheric transmission model, the influence of topographic relief, the response characteristics of the imaging spectrometer and the calibration uncertainty. Based on this model, we can also realize the ranking of the uncertainty contribution of the above links, which could help to identify the weak link in the remote sensing measurement chain. The random simulation experiments over a rugged desert scene were conducted to verified the model. It is indicated that more than 99.9% of the stochastic simulation radiance spectra are in the range of the predicted uncertainty.
GRASS COVER, TREE DENSITY, AND LEAF DEVELOPMENT OF MEDITERRANEAN ORCHARDS FROM HIGH RESOLUTION DATA
Authors: Rouault P. , Courault D. , Pouget G. , Flamain F. , Lopez-Lozano R. , Doussan C. , Debolini M. , McCabe M.
Published: December 2023

Abstract. The study focused on Mediterranean orchards and aimed to explore different remote sensing data (Sentinel 2 data (2016–2023), 1 Pleiades image (2022) and the extraction of Google-satellite-hybrid images (GSH,2017)) to compute key variables affecting water requirements such as tree age and density per plot, leaf development, the inter-row management. Surveys were conducted on 22 farms where accurate information on agricultural practices was collected. The results have shown that a thresholding on the NDVI Sentinel 2 in the summer period allowed the identification of young orchards with an accuracy of 98%. The analysis of temporal profiles of FAPAR allowed the identification of key phenological stages such as flowering and fruit set. Supervised classification was employed to separate grassed and non-grassed plots using three spectral bands of Sentinel 2. Classifications performed from GSH images gave more accurate results (81% well classified) compared with Sentinel 2 (79%) and Pleiades (57%) when identifying grassed plots. The methods presented in this study propose methods easily accessible based on free-to-download data, making them applicable in diverse orchard contexts.
SPATIO-TEMPORAL DYNAMICS OF URBAN THERMAL ENVIRONMENT IN UDAIPUR CITY, RAJASTHAN, INDIA
Authors: Sharma U. , Jalan S. , Kant Y. , Vyas A.
Published: December 2023

Abstract. The Udaipur urban agglomeration was selected to analyse the urban heat island (UHI) effect in the area from 2005 to 2017. Landsat 7 ETM+ sensor data was used to derive land surface temperatures (LST) and map landscape characteristics. The agglomeration was classified into seven land use land cover classes including agriculture cropped, agriculture fallow, barren, built up, scrub, vegetation and water using unsupervised classification method. The LST results were obtained using NDVI method. Urban heat island intensities were mapped using z-score method. Regions with UHI values of above 2 standard deviations were considered to reflect UHI effect. Results show an overall decrease of 10.2 percent in agricultural cropped and fallow lands. The scrub class also shows a moderate decline of 2.3 percent. Increase in area were observed for built up, barren and vegetation classes by 8.8, 2.1 and 1.9 percent respectively. The dominant LULC change was the transformation of agricultural lands to built-up class. The class-wise mean LST observations increase in order of water, vegetation, cropped, fallow, built up, scrub and barren land. The mean LST records an increase of 1.7° C from 30.1° C to 31.8° C over the study period. Results suggest that UHI effects are more prominent in urban fringe area corresponding with the built up and barren land cover classes contrary to its core area. Built up areas surrounded by barren lands left vacant for city’s sprawl in the future exhibit highest UHI intensities.
A CORRELATION ANALYSIS OF LAND SURFACE TEMPERATURE AND EVAPOTRANSPIRATION IN AN URBAN SETTING
Authors: Singh S. , Kushwaha S. K. P. , Jain K.
Published: December 2023

Abstract. Urbanisation is found to increase the Land Surface Temperature (LST), which results in the formation of Urban Heat Islands (UHI). This effect is a result of the natural land cover being replaced with impermeable surfaces like buildings, roads, and pavements, which absorb and hold onto heat more. As a result, metropolitan regions frequently experience substantially hotter temperatures than their nearby rural counterparts, especially during heat waves. This arises partly due to reduction in Actual Evapotranspiration (AET). AET and LST have a close relationship. AET rates are greatly influenced by the amount of vegetation and their transpiration capacity, which in turn can have an influence on LST in urban regions. The type of Land Use and Land Cover (LULC) has a significant impact on how LST affects the interchange of energy between the earth's surface and the atmosphere. Vegetation AET has a huge potential to reduce both temperatures. The temperature of a water body is lower than that of the nearby urban. The objective of this research is to determine the variation in AET and LST with regards to varying types of land cover by finding correlation between them. The spatio-temporal analysis is done for the summer and winter season of 2020. The correlation is studied between LST and AET for each land cover class and for both seasons for 2020 and results are plotted. The green areas and lakes of the city showed a higher AET and lower LST, whereas the built environment behaved in just the opposite manner. It can be inferred that it is essential to comprehend the local context to effectively determine the relationship between LST and AET in a particular scenario.
FLOOD MAPPING IN MOUNTAINOUS AREAS USING SENTINEL-1 & 2 DATA AND GLCM FEATURES
Authors: Tavus B. , Kocaman S.
Published: December 2023

Abstract. Flooding events have been frequently observed throughout the world and may have devastating effects on the environment. Mapping of flood extent is important for taking the necessary mitigation measures for future. The freely available Sentinel-1 radar and Sentinel-2 optical images allow analysis of flood extent with adequate spatial resolution. However, temporal resolution may be insufficient, and currently only events with the suitable satellite orbital passes can be analyzed with Sentinel sensors. In addition, clouds are often in scene during and shortly after a flood event, which hinders the use of optical imagery. Here, we investigated the complementary use of Sentinel-1 and Sentinel-2 data with a land cover classification approach based on random forest over a part of northern Türkiye, which frequently confronts floods and landslides. We expanded the feature set with principal components (PC) of gray-level co-occurrence matrix (GLCM) variables obtained from Sentinel-1 polarization and Sentinel-2 spectral bands, and also the normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI) images produced from the optical data. The training and test data were manually extracted from pre- and post-event optical data. The findings demonstrated that using GLCM PCs significantly increased the overall accuracy (OA = 99% with GLCM and OA = 93% without GLCM) of the classification. Furthermore, the flooded vegetation differs in textural features when compared with the other inundated surfaces, and also permanent water. Therefore, by allowing the separation of flooded vegetation and the other flooded areas, the GLCM data considerably increased the map quality.
FLASH LiDAR SINGLE PHOTON IMAGING OVER 50 KM
Authors: Xia Z. Q.
Published: December 2023

Abstract. In order to demonstrate the feasibility of single-photon imaging of flash lidar in the permanent shadow area of the moon, a set of space-based single-photon imaging system is designed, including the lidar based on VCSEL array, the optical emitting system based on the uniform beam shaping meta-lens using propagation phase and geometric phase joint control method, the two-axis three-mirror optical receiving system, and the single-photon detector array based on photon counting mode. According to the heavy-tailed pulse laser function, Poisson statistical filtering theory and Monte Carlo simulation method, the echo photon number, the photon counting process, the ranging accuracy and the intensity image are simulated in the condition of 50 km detection distance by setting different of the object reflectivity, the repetition times and the gating interval time. The results show that according to the parameter settings in this paper, the number of echo photons is as low as about 10-4 orders. However, the photon counting waveform can better restore the transmission waveform. The setting of the repetition number and the gating interval time should not only consider the missing detection phenomenon, but also consider the noise accumulation. When the repetition number is 2000 and the gate number is 200, the ranging accuracy can reach 0.075m, and the imaging in the crater without light is realized.
INTEGRATING MOTION PRIORS FOR END-TO-END ATTENTION-BASED MULTI-OBJECT TRACKING
Authors: Ali R. , Mehltretter M. , Heipke C.
Published: December 2023

Abstract. Recent advancements in multi-object tracking (MOT) have heavily relied on object detection models, with attention-based models like DEtection TRansformer (DETR) demonstrating state-of-the-art capabilities. However, the utilization of attention-based detection models in tracking poses a limitation due to their large parameter count, necessitating substantial training data and powerful hardware for parameter estimation. Ignoring this limitation can lead to a loss of valuable temporal information, resulting in decreased tracking performance and increased identity (ID) switches. To address this challenge, we propose a novel framework that directly incorporates motion priors into the tracking attention layer, enabling an end-to-end solution. Our contributions include: I) a novel approach for integrating motion priors into attention-based multi-object tracking models, and II) a specific realisation of this approach using a Kalman filter with a constant velocity assumption as motion prior. Our method was evaluated on the Multi-Object Tracking dataset MOT17, initial results are reported in the paper. Compared to a baseline model without motion prior, we achieve a reduction in the number of ID switches with the new method.
INSTANCE SEGMENTATION OF 3D MESH MODEL BY INTEGRATING 2D AND 3D DATA
Authors: Wang W. X. , Zhong G. X. , Huang J. J. , Li X. M. , Xie L. F.
Published: December 2023

Abstract. Buildings are an important part of the urban scene. In this paper, a novel instance segmentation framework for 3D mesh models in urban scenes is proposed. Unlike existing works focusing on semantic segmentation of urban scenes, this work focuses on detecting and segmenting 3D building instances even if they are attached and occluded in a large and imprecise 3D surface model. Multi-view images are first enhanced to RGBH images by adding a height map and are segmented to obtain all roof instances using Mask R-CNN. The 2D roof instances are then back-projected onto the 3D scene, the accurate 3D roof instances are obtained using a novel 3D clustering method and two post-processing steps which preserve the largest connected region and remove the model ambiguity. Finally, the 2D convex hull of each 3D roof instance is calculated and the model is divided within the range into building instances. The performance of the proposed methods is evaluated using real UAV images and the corresponding 3D mesh models qualitatively and quantitatively. Results revealed that the proposed method could effectively segment the model of the urban scenes and building instance is obtained, the over-segmentation masks can be clustered correctly into roof instances and the under-segmentation masks caused by image segmentation errors are eliminated.