bluuebunny/crossref_metadata_2025 huggingface dataset:
Academic education data as a source for analysis of the migration process for training
Authors: Mascarenhas Higor Alexandre Duarte , Dias Thiago Magela Rodrigues
Published: May 2022

In recent years, a fact that stands out in other locations on the planet is the displacement of individuals to different areas at some point in their lives. Several causes motivate displacement. Among them, one of the main reasons for training at a high level of academic training. Given this scenario, this work aims to analyze how Brazilian academic mobility occurs through data extracted from the Lattes Platform. They were filtered after extracting the data, thus obtaining only the data relevant to the research. After processing the extracted data, removing irrelevant and incomplete terms and, finally, improving the data with information on the geographic location of each institution analyzed. As a result, it was possible to obtain a picture of how scientific training in Brazil takes place, making it possible to measure the migratory flow of individuals and trends in training processes.
Kajian Pembentukan Identitas Jalan Diponegoro, Surabaya
Authors: Suwarlan Stivani Ayuning
Published: May 2022

Abstrak

Identitas lingkungan merupakan aspek penting dalam penyelenggaraan RTBL. Dengan adanya identitas lingkungan maka memudahkan dalam penyusunan rencana serta mempermudah dalam mengidentifikasi karakteristik wilayah perencanaan. Adanya identitas lingkungan yang menarik akan dapat mempermudah orang untuk mengenali suatu koridor dan menangkap karakteristik koridor yang ada, serta dapat menimbulkan sebuah persepsi tertentu pada koridor tersebut. Jalan Diponegoro Surabaya merupakan kawasan yang memiliki nilai sejarah arsitektur Kolonial yang dalam perkembangannya mengalami perubahan fungsi yang berdampak hilangnya nilai sejarah tersebut. Untuk itu penelitian ini dibuat guna mempertahankan dan memperkuat identitas dari koridor Jalan Diponegoro. Metode yang digunakan pada penelitian ini adalah metode diakronik melalui penelusuran sejarah dan potensi lingkungan, identifikasi unsur-unsur lingkungan yang potensial, dan menciptakan wujud identitas yang bisa ditangkap secara inderawi dan mudah dikenali oleh masyarakat. Hasil dari penelitian ini memberikan skenario pembentukan identitas lingkungan pada koridor Jalan Diponegoro Surabaya melalui pembentukan pada citiy gate (landmark), city hall (nodes), dan city corridor (path).

 

Kata Kunci: Identitas, citiy gate, city hall, city corridor.

 

 

Abstract

Environmental identity is an important aspect in the implementation of RTBL. With the identity of the environment, it makes it easier to prepare plans and makes it easier to identify the characteristics of the planning area. The existence of an attractive environmental identity will make it easier for people to recognize a corridor and capture the characteristics of the existing corridor and can give rise to a certain perception of the corridor. Jalan Diponegoro Surabaya is an area that has a historical value of colonial architecture which in its development underwent a change in function which resulted in the loss of that historical value. For this reason, this research was made to maintain and strengthen the identity of the Jalan Diponegoro corridor. The method used in this research is the diachronic method through tracing the history and potential of the environment, identifying potential environmental elements, and creating a form of identity that can be sensed and easily recognized by the public. The results of this study provide a scenario for the formation of environmental identity in the Jalan Diponegoro Surabaya corridor through the formation of the city gate (landmark), city hall (nodes), and city corridor (path).

 

Keywords: Identity, city gate, city hall, city corridor.
Desain Berkelanjutan Pada Pemenuhan Kebutuhan Air (Studi Kasus Daerah Industri DAS Cileungsi)
Authors: Sihombing Wenny Hamilton , Krisnandini Anggita , Syafina Paramastri Rahmi , Nugroho Adecar , . Nurisa , Puspita Titia Yudha Sarah
Published: May 2022

Pemenuhan akan kebutuhan air bersih menjadi hal yang esensial dalam kehidipan sehari hari. Adapun jumlah kebutuhan air berdeda beda untuk setiap sektornya. Sektor industri menjadi sektor yang cukup menarik dalam pembahasan pemenuhan kebutuhan air ini dimana sektor industri menjadi sektor penggerak roda perekonomian negara yang cukup besar sehingga memiliki tingkat kepentingan yang cukup tinggi. Di saat yang bersamaan dengan tingginya kebutuhan air sektor industri, dampaknya terhadap sekitar (masyarakat dan lingkungan)  juga relatif signifikan di mana hal ini memberikan tantangan sendiri bagi pihak perencana. Di cetuskan pada 1987 prinsip desain yang berkelanjutan memberikan arahan nyata bagi perencana untuk dapat memberikan solusi dengan dampak samping seminimal mungkin dengan nilai manfaat yang setinggi tingginya. Studi kasus Daerah Industri pada DAS Cileungsi memberikan daya tarik khusus di karenakan jenis industri yang cukup besar dengan kepentingan sektor sektor lain di dalam DAS tersebut, menjadikan kasus ini sangat relevan untuk pembahasan perencanaan yang berkelanjutan.
AÇÕES COLETIVAS NA PRODUÇÃO DE BIODIESEL: O ÓLEO DE FRITURA RESIDUAL COMO MATÉRIA-PRIMA
Authors: Stocker Lago Sandra Mara , Schmidt Carla Maria , Freitas de Campos Lediany
Published: May 2022

Este estudo tem por objetivo identificar as ações coletivas existentes no processo que envolve a coleta de óleo de fritura residual direcionada à produção de biodiesel, no Brasil. Optou-se por um levantamento, no sentido de buscar as diversas ações realizadas por associações em conjunto com a comunidade e indústrias, configurando-se em uma análise qualitativa. Constatou-se que além das associações, com estruturas de governança híbridas, atuam também nesse processo escolas, universidades, prefeituras, empresas, usinas, supermercados, entre outras organizações. As ações realizadas sofrem forte influência do ambiente institucional, e são colocadas em prática por atores de características distintas que se organizam por uma sucessão de etapas. Os membros recebem incentivos econômicos à parte para que ajam em prol do objetivo coletivo. A ação gera benefícios coletivos para os indivíduos envolvidos, além de externalidades positivas a montante e a jusante do processo, sobretudo para o meio ambiente. Em suma, a ação conjunta resulta em ganhos coletivos que individualmente não seriam atingidos.
Editorial
Authors: Strassburg Udo
Published: May 2022

Editorial Edição Especial
DİŞ KIRMA SUÇUNA KARŞI OSMANLI HUKUKUNDA UYGULANAN YAPTIRIMLAR
Authors: ÇELİK Buket
Published: May 2022

Osmanlı halkı çeşitli sorunları için mahkemelere ve divana başvurarak adalet karşısında hakkını arayabilmiştir. Arşiv kayıtlarında kaba sözler söyleme ve küfretmeye dayalı rencide etme ile silah, bıçak, taş, sopa gibi aletlerle yaralama olaylarına dair şikâyetlere rastlanmaktadır. Bunlar haricinde evinde ya da sokak, çarşı, pazar, hamam gibi umuma açık yerlerde yumruk yumruğa yapılmış kavgalar da şikâyet sebebi olarak mahkemelere taşınmıştır.

Yakın temasla gerçekleşmiş kavgalarda yüze ve ağza alınan darbeler diş kırılmasıyla sonuçlandığında dişi kırılan kişi şikâyetçi olmuştur. Bu çalışmada Şer‘iye Sicili, Mühimme Defterleri, Ahkâm-ı Şikâyet Defterleri ve çeşitli perakende evraklara yansımış diş kırılması hadiselerinin İslam ve Osmanlı hukukunda ele alınması ve suçluya ne gibi yaptırımlar uygulandığı üzerinde durulmuştur. Arşivde örneğine çok sık rastlanan bir suç türü olmadığı için çalışmanın kapsamı geniş tutulmuş, zaman ve mekân sınırlamasına gidilmemiştir.

Dişlerin dış görünüş, konuşma ve beslenme üzerindeki önemli etkilerinden dolayı diş kırılması olayları Osmanlı hukukunda önemsenen davalar arasında yerini almış ve dişi kırana çeşitli yaptırımlar uygulanmıştır. Bunların başında diyet gelmiştir. Ayrıca diş kırma suçu nedeniyle hapis, küreğe gönderme gibi ta‘zir cezalarının verilmiş olduğu da görülmüştür. Kısas yapılabileceğine dair ceza maddeleri de olmakla birlikte bunun örneklerine az rastlanmış, genellikle diyet tercih edilmiştir.
Pela Estrada de São José, produção do espaço e patrimônio: o exemplo da Avenida 16 de Novembro, Belém-PA
Authors: Santos Jorge Sales dos , Tavares Maria Goretti da Costa
Published: May 2022

A análise da produção do espaço urbano de Belém, à luz da construção de identidades patrimoniais, mostra que a avenida 16 de Novembro exemplifica essa dinâmica cultural, tornando-a importante para a identidade territorial de Belém. O estudo que se propõe visa analisar a produção do espaço e espaços patrimonializados através do processo de (re)construção da estrada de São José (hoje avenida 16 de Novembro) em Belém. A metodologia é central na construção do plano de pesquisa, pois permite a visualização completa da hipótese estruturadora, aplicada à ideia de produção do espaço patrimonializado na avenida 16 de Novembro em Belém, com base no roteiro Geoturístico “Pela Estrada de São José”, além de expor a maneira pela qual se deu a (re)funcionalização no espaço urbano patrimonializado na avenida.
A Proposta Psicoeducativa: Um Recurso à Psicanálise Frente as Implicações Capitalistas Atuais?
Authors: Cossi Rafael Kalaf
Published: May 2022

Trata-se da resenha do livro Žižek in the clinic: a revolucionary proposal for a new endgame in psychoterapy. Seu autor, Eliot Rosenstock, considera que os preceitos do capitalismo atual e da lógica do mercado moldam as práticas clínicas comportamentais e engendram a indústria da psicoterapia. Como reação, o autor propõe a estratégia da psicoeducação, munido das contribuições que Slavoj Žižek traz para a psicanálise. A intenção seria desalienar o sujeito contemporâneo imerso no modelo neoliberal e desarticular as proposições psicoterapêuticas condizentes a ele. O livro convida à reflexão crítica sobre renovações clínicas compelidas pelo nosso cenário político e econômico.
Dispositivos de Manipulação da Subjetividade no Cotidiano das Mulheres Executivas
Authors: Vaz Elem Rabello Duarte , Gallon Shalimar
Published: May 2022

As rápidas mudanças que acontecem no mundo do trabalho impactam a forma de viver e trabalhar dos indivíduos. Nesse contexto, a gestão utiliza estratégias e manipulações que limitam os modos de trabalhar e viver das executivas e tenta delas se apropriar por meio de sedução, justificação, sofisticação e sutileza. Considerando os aspectos atuais da vida de executivas inseridas na sociedade moderna, os dispositivos surgem como forma de capturar, modelar e controlar as condutas e os discursos desses sujeitos. O objetivo do presente estudo é analisar quais são e como se expressam os dispositivos de manipulação de si no cotidiano de mulheres executivas. Assim, realizou-se uma pesquisa descritiva e qualitativa por meio de roteiro semiestruturado, com 30 executivas que estão em cargos que possuem poder de decisão. Para a análise de dados utilizou-se a técnica de análise de conteúdo com o auxílio do software Maxqda. Os resultados evidenciam que as executivas estão envolvidas por dispositivos individuais, sociais, organizacionais e de apoio, que controlam e sustentam sua posição. Conclui-se, então, que os dispositivos atuam na normalização das executivas, levando-as a se enquadrarem em perfis-padrão, de acordo com sua posição hierárquica.
Alat Monitoring Dan Kontrol Peralatan Listrik Pada Ruangan Berbasis Internet Of Things
Authors: Mangani Sandy Apriyansa , Shadiq Jafar
Published: May 2022

Saat ini kebutuhan akan energi listrik semakin meningkat. Semua perangkat rumah tangga membutuhkan energi listrik untuk dapat bekerja. Hal ini menyebabkan konsumsi akan energi listrik semakin boros. Terkadang tak jarang manusia kurang bijaksana dalam menggunakan energi listrik. Melihat kondisi ini, sangat diperlukan adanya sebuah sistem yang mampu mengontrol penggunaan energi listrik sekaligus menghitung daya listrik agar konsumsi listrik tidak berlebihan. Kemajuan ilmu pengetahuan memungkinkan perangkat elektronik dapat terkoneksi dengan internet. Begitu juga kemajuan teknologi di bidang telekomunikasi saat ini yaitu IoT, teknologi IoT tidak hanya dapat dimanfaatkan untuk mengontrol perangkat elektronik, namun memungkinkan untuk dapat melakukan monitoring pengunaan listrik yang digunakan dan mengukur suhu yang ada. Berdasarkan kondisi tersebut, maka dirancang sebuah alat yang mampu mengontrol ON-OFF peralatan listrik saat tidak berada dilokasi sekaligus melakukan perhitungan daya listrik yang terpakai dari pemakaian perangkat listrik tersebut secara real time. Sistem yang dirancang ini berbasis IoT, menggunakan NodeMCU sebagai pengendali utama, LCD menampilkan apa yang tercaba, DHT11 untuk membaca suhu,Relay untuk saklar otomatis dan sensor PZEM-004T untuk membaca daya dan MQ-2 untuk mendeteksi adannya gas yang akan dihubungkan dengan smartphone menggunakan aplikasi Blynk
Apresentação
Authors: Bordini Santina Célia
Published: May 2022

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Panorama do uso das tecnologias na alfabetização matemática para adolescentes privados de liberdade no Paraná
Authors: Junior Nadir Teixeira , Fujii Luciene Yuri
Published: May 2022

O presente artigo pretende analisar a formação escolar nos centros socioeducativos, em particular na área de matemática, principalmente em relação à utilização das Tecnologias de Comunicação e Informação – TICs –, entre os adolescentes privados de liberdade no estado do Paraná. O objetivo é refletir e evidenciar a real necessidade de capacitação técnica e profissionalizante dos adolescentes privados de liberdade com intuito de facilitar sua recolocação social e profissional. A ideia é trabalhar alguns conceitos e aplicações práticas na disciplina de matemática por meio do uso de algumas tecnologias voltadas para a educação com o intuito de facilitar o processo do ensino-aprendizagem na formação escolar e capacitação profissional desses adolescentes. Considero que a aprendizagem de conceitos por meio de ferramentas tecnológicas matemáticas inclusas nas medidas socioeducativas tem um papel muito importante na vida profissional desses jovens e adolescentes, pois irá contribuir no processo de ressocialização.
(Des) Necessidade de Autorização Legislativa para a Venda de Subsidiárias de Estatais
Authors: Casal Vinícius Adami
Published: May 2022

O presente artigo, adotando o método dedutivo, estuda a necessidade, ou não, de autorização legislativa para a venda de subsidiárias de estatais a partir do julgamento do Supremo Tribunal Federal (STF) no referendo da medida cautelar na ADIN 5.624. Far-se-á uma análise das disposições constitucionais da matéria e dos votos que formaram a corrente majoritária a respeito da desnecessidade de tal medida para, posteriormente, enfrentar os seus argumentos em algumas categorias por nós divididas a partir da análise dos posicionamentos dos(as) julgadores(as). Tal metodologia visa a demonstrar a impropriedade da decisão exarada pela Corte Suprema no que tange a matéria constitucional, principalmente a Constituição Econômica. Na conclusão faremos uma retomada da matéria e uma defesa da Constituição Econômica e de sua ideologia constitucionalmente adotada.
EVALUATION OF UAV-BORNE PHOTOGRAMMETRY AND LASER SCANNING FOR 3D TOPOGRAPHIC CHANGE ANALYSIS AT AN ACTIVE ROCK GLACIER
Authors: Zahs V. , Winiwarter L. , Anders K. , Bremer M. , Rutzinger M. , Potůčková M. , Höfle B.
Published: May 2022

Abstract. Point clouds derived from UAV-borne laser scanning and UAV-borne photogrammetry provide new opportunities for 3D topographic monitoring in geographic research. The airborne acquisition strategy overcomes common challenges of ground-based techniques, such as limited spatial coverage or heterogeneous measurement distribution, and allows flexible repeated acquisitions at high temporal and spatial resolution. While UAV-borne 3D sensing techniques are expected to thereby enhance geographic monitoring, their specific potential for methods and algorithms of 3D change analysis is yet to be investigated. In our study, we assess point clouds originating from UAV-borne photogrammetry using dense image matching (DIM) and UAV-borne laser scanning (ULS) as input for 3D topographic change analysis at an active rock glacier in the Austrian Alps. We analyse surface change by using ULS and DIM point clouds of 2019 and 2021 as input for two state-of-the-art methods for pairwise surface change analysis: (1) The Multiscale Model to Model Cloud Comparison (M3C2) algorithm and (2) a recent M3C2-based approach (CD-PB M3C2) using plane correspondences to reduce the uncertainty of quantified change. We evaluate ULS-based and DIM-based change analysis regarding their performance in (1) achieving high spatial coverage of derived changes, (2) accurately quantifying magnitudes and uncertainty of change, and (3) detecting significant change (change magnitudes > associated uncertainty). As reference we use change quantified between two terrestrial laser scanning (TLS) surveys undertaken simultaneously with the ULS and DIM data acquisitions. Our study shows the improved spatial coverage of M3C2 achieved with point clouds acquired with UAVs (+ 60% of core points used for change analysis). For CD-PB M3C2, ULS and DIM point clouds enabled a spatially more uniform distribution of plane pairs used for change quantification and a slightly higher spatial coverage (+6% – +7% of core points used for change analysis) compared to the TLS reference. Magnitudes of M3C2 change were closer to the TLS reference for ULS-ULS (mean difference: 0.04 m; std. dev.: 0.05 m) compared to ULS-DIM (mean difference: 0.12 m; std. dev.: 0.08 m). Similar results were obtained for CD-PB M3C2 using ULS-ULS (mean difference: 0.02 m; std. dev.: 0.01 m) and ULS-DIM (mean difference: 0.06 m; std. dev.: 0.01 m). Moreover, magnitudes of change were above the associated uncertainty in 82% – 89% (M3C2) and 89% – 90% (CD-PB M3C2) of the area of change analysis. Our findings demonstrate the potential of ULS and DIM point clouds as input for accurate 3D topographic change analysis for the study at hand and can support the design and setup of 3D/4D Earth observation systems for rock glaciers and natural scenes with complex topography, such as landslides or debris covered glaciers.
HANDCRAFTED AND LEARNING-BASED TIE POINT FEATURES – COMPARISON USING THE EUROSDR RPAS BENCHMARK DATASET
Authors: Peppa M. V. , Morelli L. , Mills J. P. , Penna N. T. , Remondino F.
Published: May 2022

Abstract. The identification of accurate and reliable image correspondences is fundamental for Structure-from-Motion (SfM) photogrammetry. Alongside handcrafted detectors and descriptors, recent machine learning-based approaches have shown promising results for tie point extraction, demonstrating matching success under strong perspective and illumination changes, and a general increase of tie point multiplicity. Recently, several methods based on convolutional neural networks (CNN) have been proposed, but few tests have yet been performed under real photogrammetric applications and, in particular, on full resolution aerial and RPAS image blocks that require rotationally invariant features. The research reported here compares two handcrafted (Metashape local features and RootSIFT) and two learning-based methods (LFNet and Key.Net) using the previously unused EuroSDR RPAS benchmark datasets. Analysis is conducted with DJI Zenmuse P1 imagery acquired at Wards Hill quarry in Northumberland, UK. The research firstly extracts keypoints using the aforementioned methods, before importing them into COLMAP for incremental reconstruction. The image coordinates of signalised ground control points (GCPs) and independent checkpoints (CPs) are automatically detected using an OpenCV algorithm, and then triangulated for comparison with accurate geometric ground-truth. The tests showed that learning-based local features are capable of outperforming traditional methods in terms of geometric accuracy, but several issues remain: few deep learning local features are trained to be rotation invariant, significant computational resources are required for large format imagery, and poor performance emerged in cases of repetitive patterns.
MONOCULAR DEPTH PREDICTION IN PHOTOGRAMMETRIC APPLICATIONS
Authors: Welponer M. , Stathopoulou E. K. , Remondino F.
Published: May 2022

Abstract. Despite the recent success of learning-based monocular depth estimation algorithms and the release of large-scale datasets for training, the methods are limited to depth map prediction and still struggle to yield reliable results in the 3D space without additional scene cues. Indeed, although state-of-the-art approaches produce quality depth maps, they generally fail to recover the 3D structure of the scene robustly. This work explores supervised CNN architectures for monocular depth estimation and evaluates their potential in 3D reconstruction. Since most available datasets for training are not designed toward this goal and are limited to specific indoor scenarios, a new metric, large-scale synthetic benchmark (ArchDepth) is introduced that renders near real-world scenarios of outdoor scenes. A encoder-decoder architecture is used for training, and the generalization of the approach is evaluated via depth inference in unseen views in synthetic and real-world scenarios. The depth map predictions are also projected in the 3D space using a separate module. Results are qualitatively and quantitatively evaluated and compared with state-of-the-art algorithms for single image 3D scene recovery.
LANDSLIDE SURVEYS USING LOW-COST UAV AND FOSS PHOTOGRAMMETRIC WORKFLOW
Authors: Yordanov V. , Biagi L. , Truong X. Q. , Brovelli M. A.
Published: May 2022

Abstract. Unmanned Aerial Vehicle have found their usage in various academic and industry domains, mainly due to the versatility of options that one aircraft can offer from onboard sensors for data acquisition and positioning, through different weight and size categories allowing different applications, including landslide mapping and surveying. Survey-grade UAVs can provide very precise flight and data but usually are very costly, and their use can be further bounded by many regulations. In this work, we have adopted a low-cost consumer-grade UAV to do multitemporal monitoring of an active landslide (Ruinon) in Northern Italy to evaluate the applicability of such setup in the landslide hazard domain. Moreover, for flight planning, photogrammetric reconstruction, and comparative analyses we have adopted free and open-source software solutions. The resulted dense point clouds and orthophotos yielded very satisfactory results from accuracies of few meters and even sub-meter level when reconstructed with field-surveyed ground control points. As a result, from the two surveys comparisons, July and October 2021, several displaced boulders and debris were detected where no significant reactivations were detected from our surveys. Such low-cost setup can be used also from non-professionals and in citizen science campaigns which can significantly contribute to additional landslide mapping and analyses by providing valuable datasets.
PLASTIC COVER GREENHOUSES REFLECTANCE SPECTRA FROM DIFFERENT OPTICAL SATELLITE IMAGERY
Authors: Jiménez-Lao R. , Aguilar M. A. , Aguilar F. J.
Published: May 2022

Abstract. Mapping the distribution of plastic covered greenhouses (PCG) is essential for any attempts to manage these complex areas of intensive agriculture. It is therefore important to understand how the spectrum of different PCG varies in order to establish its unique absorption features and how these can be utilised for mapping PCG from remote sensing imagery. This paper presents an analysis of the surface reflectance values of satellite image spectra for 50 PCG. The reflectance of these PCG, located in Almería (Spain), was studied in two seasons of the year (summer and winter). All single bands of WorldView-3 (WV3), Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2), together with Normalized Difference Plastic Index (NDPI) and Normalized Difference Vegetation Index (NDVI), were generated through an object-based image analysis (OBIA) approach for each PCG and season. The results showed the variability of absorption features and overall shape of the spectra for all PCG. The main differences in reflectance were attributed to the crops and the specific characteristics of their local management. A relationship between brightness and whitewashing (greenhouse roof painted with lime to provide shade and reduce the temperature inside the greenhouse, especially in summer) was found, showing the ability of whitewashing to temporally mask the spectral signature of the plastic film.
IMAGE-BASED DEEP LEARNING FOR RHEOLOGY DETERMINATION OF BINGHAM FLUIDS
Authors: Ponick A. , Langer A. , Beyer D. , Coenen M. , Haist M. , Heipke C.
Published: May 2022

Abstract. In this work, a method to predict the rheological properties of ultrasonic gel, as a reference substance of cement paste, is presented. For this purpose, images are taken with a stereo camera system which show a mixing paddle moving through the ultrasonic gels of different consistency, thus setting them in motion. A digital elevation model (DEM) and a corresponding orthophoto are created from the image pairs using classical image matching and orthoprojection methods. These are used as inputs into a Convolutional Neural Network (CNN), which predicts the support points of a flow curve which classically have to be determined in a rheometer in the laboratory. A simple network architecture consisting of a small number of convolution layers is compared with a pre-trained ResNet-18, which is fine-tuned using gel images. In a second series of experiments, rheological parameters, which alternatively need to be deduced from the flow curve in a separate step, are determined directly from the images. In the third series of experiments, the influence of different factors is tested, such as the position of the cameras relative to the direction of paddle movement and the importance of the DEMs and orthophotos in the training. It is shown in this paper that it is possible to predict the rheological properties of the ultrasonic gels with a suitable setup with a satisfying accuracy.
SIGNIFICANCE. STOP ILLICIT HERITAGE TRAFFICKING WITH ARTIFICIAL INTELLIGENCE
Authors: Abate D. , Paolanti M. , Pierdicca R. , Lampropoulos A. , Toumbas K. , Agapiou A. , Vergis S. , Malinverni E. , Petrides K. , Felicetti A. , Zingaretti P.
Published: May 2022

Abstract. The inability to prevent or eliminate illicit trafficking of cultural goods is not limited to failed-state environments or any specific part of the globe. While the antiquities market denies that this illicit trade is a widespread phenomenon, the international community and Law Enforcement Agencies (LEAs) overwhelmingly recognize the problem indicating that organized crime is involved at all stages. Nowadays, web platforms play host to groups dedicated to illegal archaeological excavations and Illicit trade of cultural goods. Looters have the freedom to connect online with potential buyers around the world. At the same time, social media platform monitoring in search of criminal activities conducted by LEAs is poor due to the lack of expertise, efficient tools to scan the massive amounts of data, and funds. The COVID-19 crisis has compounded the problem by driving more and more dealers and buyers online – where they are discovering that by joining certain unmonitored groups, they can enter the illegal market with ease. The EU funded SIGNIFICANCE project (Stop Illicit heritaGe traffickiNg wIth artiFICiAl iNtelligenCE) has been designed to boost LEAs investigation capabilities in monitoring online illegal activities on social media platforms, the web and the dark web for the identification of cultural property crimes, exploiting Artificial Intelligence and Deep Learning algorithms for guaranteeing the successful prosecution of perpetrators unveiling criminal networks.
FROM SCAN-TO-BIM TO HERITAGE BUILDING INFORMATION MODELLING FOR AN ANCIENT ARAB-NORMAN CHURCH
Authors: Aricò M. , Lo Brutto M.
Published: May 2022

Abstract. One of the most significant issues in Cultural Heritage is the management of ancient buildings to monitor their state of conservation or to plan actions in their maintenance; this issue can be now approached thanks to the use of the Scan-to-BIM process. This method allows the creation of parametric models into a BIM environment, which are capable of enhancing the geometrical representation of building elements and integrating different types of data.This paper shows the results of the research activities carried out by the Department of Engineering at University of Palermo (Italy) on applying the Scan-to-BIM approach to the survey and the modelling of an ancient Arab-Norman church in Palermo. This activity was motivated by a renewed interest from the local Administration towards the Arab-Norman Cultural Heritage in the city, since other more famous coeval monuments were included in the UNESCO World Heritage Sites list in 2015. The morpho-typological style of the church has been spotlighted by a high-detailed 3D laser scanner and photogrammetric survey. The aim of the modelling phase was to obtain a parametric model which was suit to render the peculiarity of this building at its best. Extensive knowledge about historical building techniques has been needed in order to model all the architectural elements. The results of this study allowed to obtain a HBIM of an Arab-Norman building and to reveal the weaknesses affecting the whole workflow; these were mainly due to the approach chosen for the modelling of the most particular architectural elements.
HYPERSPECTRAL INVERSION OF SOLUBLE SALT CONTENT IN MURAL PAINTING
Authors: Guo Z. Q. , Lyu S. Q. , Hou M. L. , Huang M.
Published: May 2022

Abstract. Mural painting is one of the carriers expressing history and culture. Due to the natural and anthropogenic factors, the salt in mural painting and environment is enriched in the surface layer with temperature change. It will induce irreversible diseases such as crispy alkali, which is not conducive to the survival of mural painting in the present. An efficient and non-destructive method to detect salt in murals is of great importance. Therefore, we proposed a method to predict the soluble salt content of mural paintings based on hyperspectral techniques. First, simulated samples with different salt concentrations were measured by a special spectroradiometer to acquire their spectra. Next, breakpoint correction and average smoothing preprocessing are performed and the data set is divided. Then, the spectra were enhanced by continuum removal (CR) and the logarithm of reciprocal (LR). The salt concentration was correlated with the spectra to extract 10 characteristic bands. Finally, the salt content prediction model was established by simple linear regression (SLR) and multiple linear regression (MLR). The accuracy of the model was evaluated with the coefficient of determination R2, root mean square error RMSE, and relative percent deviation RPD. The experimental results show that the best inversion fit is based on the combination of the CR-MLR model at the strong correlation bands of 420nm, 584nm, and 2379nm (Calibration Set R2 = 0.846, RMSE = 0.138, and RPD = 3.240). This paper provides a new technical means for the non-destructive detection of salt content in murals.
APPLICATION OF CONSUMER–LEVEL UAV PHOTOGRAMMETRY IN DIGITAL SURVEY OF CLIFF-BURIAL CULTURE RELICS: A CASE STUDY OF MOUNT WUYI
Authors: Lin Z. , Wu X. , Liao L. , Xu T. , Zhang Y. , Calia M.
Published: May 2022

Abstract. The cliff-burial was an ancient funerary ritual once popular in the Far East Asia (Figure 1), in which the dead were buried high on the cliffs with log coffins (the “hanging coffins”) left in the natural caves, excavated grottoes or on some wood piles.In view of the fact that the cliff-burial sites are usually located on the escarpments overlooking the rivers and with great slope, where the conventional 3D survey means, such as ground laser scanning and traditional aerial photogrammetry, is out of option. This study explores the possibility of using UAV (consumer–level drone) with substantial improvement in survey accuracy, range and flight control (Figure 2), which aims to lay the foundation for the global cliff-burial culture heritage research. A survey method extendible on other excavated funeral sites would be tested and codified, as a possible follow up of the research on some study cases in Far East Asia and Europe.
A COMPARISON BETWEEN UWB AND LASER-BASED PEDESTRIAN TRACKING
Authors: Masiero A. , Dabove P. , Di Pietra V. , Piragnolo M. , Vettore A. , Guarnieri A. , Toth C. , Gikas V. , Perakis H. , Chiang K.-W. , Ruotsalainen L. M. , Goel S. , Gabela J.
Published: May 2022

Abstract. Despite the availability of GNSS on consumer devices enabled personal navigation for most of the World population in most of the outdoor conditions, the problem of precise pedestrian positioning is still quite challenging when indoors or, more in general, in GNSS-challenging working conditions. Furthermore, the covid-19 pandemic also raised of pedestrian tracking, in any environment, but in particular indoors, where GNSS typically does not ensure sufficient accuracy for checking people distance. Motivated by the mentioned needs, this paper investigates the potential of UWB and LiDAR for pedestrian positioning and tracking. The two methods are compared in an outdoor case study, nevertheless, both are usable indoors as well. The obtained results show that the positioning performance of the LiDAR-based approach overcomes the UWB one, when the pedestrians are not obstructed by other objects in the LiDAR view. Nevertheless, the presence of obstructions causes gaps in the LiDAR-based tracking: instead, the combination of LiDAR and UWB can be used in order to reduce outages in the LiDAR-based solution, whereas the latter, when available, usually improves the UWB-based results.
2D TO 3D LABEL PROPAGATION FOR THE SEMANTIC SEGMENTATION OF HERITAGE BUILDING POINT CLOUDS
Authors: Pellis E. , Murtiyoso A. , Masiero A. , Tucci G. , Betti M. , Grussenmeyer P.
Published: May 2022

Abstract. During the last decade, the use of semantic models of 3D buildings and structures kept growing, fostered in particular by the spread of Building Information Models (BIMs), becoming quite popular in several civil engineering and geomatics applications. Nevertheless, semantic model production usually requires quite a lot of human interaction, which may result in quite long and annoying procedures for human operators. The production of 3D semantic models of buildings often takes advantage of already available 3D reconstructions of the considered objects. Given the ever increasing resolution of 3D reconstructions, obtained thanks to the recently developed laser scanners and photogrammetric software, the availability of tools for supporting the automatic or semi-automatic generation of semantic models represents a key step for easing and speeding up the process of semantic model production. In particular, the correct semantic interpretation of the different parts of a 3D point cloud, can be seen as the basic step for the production of a BIM model. The most frequently used methods for point cloud semantic segmentation can be separated in two categories: those directly segmenting the point clouds and those based on the ancillary semantic segmentation of images representing the object of interest, then transferring back the segmentation results to the point cloud. This work focuses on the latter method, considering more specifically the application of heritage building semantic segmentation. To be more specific, this paper investigates the semantic segmentation performance on a set of four heritage buildings, obtained first applying deep-learning based image semantic segmentation and then propagating back the semantic information to the point cloud by means of a voting strategy. The obtained results are quite encouraging, motivating future investigations on improvements of this strategy, in particular when including more buildings in the considered dataset.
SURFACE HANDWRITING ENHANCEMENT OF ARTIFACTS BASED ON MANIFOLD LEARNING AND MIXED PIXEL DECOMPOSITION
Authors: Wang S. H. , Lyu S. Q. , Hou M. L. , Gao Z. H. , Huang M.
Published: May 2022

Abstract. Written information on the surface of cultural relics can record important historical events. Due to the influence of natural and human factors, the surface of cultural relics fades and the words are difficult to identify. Take advantage of the hyperspectral data image and spectral unity and wide spectral range, a cultural relics surface handwriting enhancement method based on manifold learning and mixed pixel decomposition was proposed. First, the minimum noise fraction (MNF) transformation was carried out on the hyperspectral image, and then the top 10 bands were selected for inverse MNF transformation to reduce noise of the hyperspectral image. Then, the reconstructed image was dimensionally reduced by locally linear embedding (LLE) to obtain a gray image with the maximum amount of information. At the same time, the spectral features of the handwriting and background area in the reconstructed image were analysed. The automatic target generation process (ATGP) was adopted for endmember extraction on the reconstructed image to identify the endmember of handwriting. The abundance map of handwriting area was obtained by the fully constrained least squares (FCLS). Finally, the gray image and the abundance map of the handwriting region were weighted together to obtain the handwriting enhanced image. The true color image was synthesized from the reconstructed image, Then the true color image and the handwriting enhancement image were fused to obtain the handwritting fusion image. The hyperspectral image of a faded text in Shuozhou City, Shanxi Province, China, was used as an example for verification, and the results showed that the method can effectively enhance the text on the surface of the artifacts.
COMPARISON OF VEGETATION ANOMALIES TO EL NIÑO-SOUTHERN OSCILLATION IN CHINA AND AUSTRALIA
Authors: Wang C.
Published: May 2022

Abstract. The El Niño-Southern Oscillation (ENSO), as one of the main factors driving extreme climate events, exerts a major influence on interannual climate variability around the world. However, ENSO effects on vegetation, especially regarding the extent, intensity, direction, are not well understood. Here, we characterize and compare the variability in vegetation response to ENSO across China and Australia and explore their underlying mechanisms. Results show that the spatial extent of ENSO-sensitive vegetation differed between China and Australia and across land cover types. For both China and Australia, the intensity and direction of vegetation anomalies were closely related to the type of ENSO events. In particular, vegetation anomalies to the Central-Pacific (CP) type ENSO events were stronger than that to the Eastern-Pacific (EP) type events of the same intensity and generally responded in an opposite way, resulting from different controls of CP-type and EP-type ENSO on precipitation and temperature. Our findings highlight the diverse response of vegetation triggered by different types of ENSO in China and Australia, which can improve our understanding of ENSO impacts on ecosystems in the northern and southern hemispheres.
USING LONG SHORT-TERM MEMORY MODEL FOR CLOUD FOREST VEGETATION GROWTH STATUS PREDICTION – A CASE STUDY IN SHEI-PA NATIONAL PARK
Authors: Wang G. G. , Tsai H. P.
Published: May 2022

Abstract. Cloud Forests (CFs) are characterized by their persistent foggy environment, in which fog can save two times the amount of precipitation in the dry season and increase water storage by 10% in the rainy season. CFs play an important role in ecosystems as high biodiversity and abundant endemic species live within CFs. However, CFs are sensitive to environmental changes, especially in current global climate warming conditions. Therefore, a typical cloud forest in Taiwan, Shei-Pa National park, was chosen as the study area. Specifically, the Normalized Difference Vegetation Index (NDVI) with meteorological factors including rainfall, average temperature, maximum temperature, and minimum temperature were obtained to assess the overall CFs trend from 2001 to 2017. Moreover, the Long Short-Term Memory neural network model (LSTM) was implemented to predict the future vegetation status. Preliminary results have shown that vegetation condition in Shei-Pa National park was getting better; rainfall, average temperature, and minimum temperature represented an upward trend while maximum temperature showed a downward trend. Furthermore, the LSTM- maximum temperature model displayed the highest prediction power with the MAPE index of 4.84%. The results provide a valuable reference for forest resource conservation and future climate adaptation strategies in Taiwan.
USING OPEN DATA CUBE ON THE CLOUD TO INVESTIGATE FOOD SECURITY BY MEANS OF CROPLAND CHANGES IN DJIBOUTI
Authors: Wardle J. A. , Sagan V. , Mohammed F.
Published: May 2022

Abstract. Addressing hunger is one of the greatest unsolved challenges Humanity has ever faced. Africa is one of the most fragile ecosystems strongly affected by numerous factors ranging from climate change, increasing population, decreasing water resources, and undeveloped hydrological infrastructure. These factors make it exceptionally vulnerable to food insecurity. The purpose of this study was to establish the feasibility and methodology of using Open Data Cube (ODC) and conventional machine learning algorithms to determine the extent of decrease in cropped area in the desert climate of Djibouti, the smallest Horn of Africa country (by landmass) over a thirty-year period. The research question was answered using Landsat 5, 7, and 8 imagery taken during the month of June from 1990, 2000, 2010, and 2020 then classified through machine learning algorithms - including decision tree and random forest. The data acquisition, analysis, and modeling were completed in an Open Data Cube environment using a cloud-based user computational platform running completely in-browser, and all necessary software was provided as part of the environment. The research identified a decreasing trend in vegetative areas but was limited in determining whether the vegetative areas were purely agricultural cropland in nature or included native vegetation. While the research reveals a concerning decline in total vegetation over the thirty-year period, the lack of other data variables (such as weather and climate patterns) provides too narrow a picture to determine causation. Several areas for further research are outlined.
LARGE-SCALE MAPPING OF FLOOD USING SENTINEL-1 RADAR REMOTE SENSING
Authors: Haghighi M. H.
Published: May 2022

Abstract. Sentinel-1 Synthetic Aperture Radar (SAR), with its extensive coverage and regular data acquisition all over the globe, has become one of the most valuable assets for flood monitoring in recent years. However, the strong influence of incidence angle on backscatter measurement of Sentinel-1 data makes it challenging to mosaic Sentinel-1 tracks for systematic flood mapping over large areas. This study uses a cosine squared normalization of Sentinel-1 data based on Lambert´s law for optics to homogenize SAR data from different tracks. Then, it combines normalized data from ascending and descending passes forms 12-day mosaics covering Bangladesh from January 2017 to December 2021. Afterward, it estimates flood evolution by segmentation of the country-wide mosaics of data and calculates a flood frequency map. The flood frequency map, along with the population information, is then used to estimate the flood risk to the Bangladesh population. The results show that normalization can reduce inconsistencies between different tracks of Sentinel-1 data. Furthermore, it shows the potential of Sentinel-1 data for systematic flood mapping at large scales. Such analysis can help implement flood management measures on a national scale to reduce the flood risk.
ANALYSIS OF QUALITY REVIEW OF LAND COVER CLASSIFICATION PRODUCT IN GEOGRAPHIC NATIONAL CONDITIONS MONITORING
Authors: Li C. , Zhao H. , Mao W. , Guo J. , Chen C.
Published: May 2022

Abstract. To the land cover classification product of geographic national conditions monitoring, how to scientifically and objectively inspect and evaluate the results is a problem that if quality review can play a key role in quality control. Based on the characteristics of the land cover classification product, it was carried out a quality inspection for important quality elements and key contents on the basis of quality acceptance to ensure the consistency and compliance of the national results. This paper put forward the content and method of review. The results over the years since the review showed that the classification accuracy was not only a difficulty but also a short board in quality control. Through summarizing the main problems of the land cover classification product found in the review, the causes were analyzed, and suggestions were put forward for production.
MULTI-TIER STORAGE MANAGEMENT AND APPLICATION OF REMOTE SENSING IMAGE DATA
Authors: Liu J. , Liu L. , Xing X. , Zheng X. , Gao Y. , Xu Q. , Du J.
Published: May 2022

Abstract. With the rapid development of the remote sensing platform and sensor technology, remote sensing image data presents the typical characteristics of the massive complex, multi-source heterogeneous, spatial-temporal intensive, which puts forward higher requirements for data storage management efficiency and real-time online service capability. Combined with the demand for remote sensing image data, the multi-tier migration strategy and approach based on the thermal evaluation model of remote sensing image data are proposed, considering the file size and data activity of remote sensing image data. The linkage between local storage cluster and cloud storage implements multi-tier migration and dynamic flow of remote sensing image data, improves the utilization of storage devices and the rationality of storage resource allocation, and enhances the capability of fast, dynamic, and real-time online service of remote sensing image data.
THE SETTLEMENT OF HONG KONG INTERNATIONAL AIRPORT BASED ON THE INTERFEROMETRIC POINT TARGET ANALYSIS
Authors: Zhang Z. , Ding X.-L. , Wu S. , Kang Q.
Published: May 2022

Abstract. Hong Kong International Airport (HKIA) is one of the famous airports built by reclamation of the sea platform. However, the reclaimed area of the airport, which cost about $9 billion, has shown uneven displacement. Over the past two decades, researchers have used different methods to monitor the deformation of HKIA. As an emerging deformation monitoring technology, Interferometric synthetic aperture radar (InSAR), has been widely used to monitoring the deformation of HKIA in the last ten years. In this study, different from conventional interferometry, the target of this interference processing is single look complex (SLC) point data, which was extracted by points in the SLC data stacks (filtered by spectrum and backscatter intensity). We used 40 scenes of COSMO-SkyMed (CSK) SAR images to generate the differential interferogram point data. After multiple phase regression analysis, the SLC point data interferometric processing model can effectively eliminate baseline errors and atmospheric distortions, obtain highly reliable phase unwrapping results.