bluuebunny/crossref_metadata_2025 huggingface dataset:
Karakter Eğitimi ve Karakter Eğitimi Programları
Authors: YILMAZ Ferat
Published: June 2021

Bu çalışmada eğitim fakültelerinin yenilenen lisans programları kapsamına seçmeli ya da zorunlu ders olarak alınan “karakter ve değer eğitimi” dersi için bir derleme yapılması amaçlanmıştır. Bu kapsamda öncelikle karakter eğitiminin ne olduğu ve nasıl olması gerektiği açıklanmaya çalışılmıştır. Daha sonra karakter eğitimi programlarının bileşenleri olan hedef, içerik, eğitimi durumları ve sınama durumları ayrıntılı bir şekilde incelenmiştir. Buna göre karakter eğitimi, toplumun daha iyi bir yer haline gelebilmesi için öğrencilere, davranışlarına güçlü birer ahlaki temel kazandırmaları ve edilgen bir durumda bulunan ahlaki değerleri için davranışsal formlar oluşturmaları için gerçekleştirilen rehberlik çalışmaları olarak tanımlanabilmektedir. Karakter eğitimi, disiplinler arası bir yaklaşımla okuldaki tüm akademik, sanatsal ve sportif bütün aktivitelere nüfuz ettirilmelidir. Karakter eğitim programlarıyla, öğrencilerin “iyiyi” bilmeleri, “iyiyi” hissetmeleri ve “iyiyi” gerçekleştirmeleri sağlanmaya çalışılmaktadır. Karakter eğitimin içeriğinin ne olması gerektiğine, karakter eğitimi kapsamında hangi öğrenme yaşantılarının sağlanmasına ve hangi değerlendirme yaklaşımlarından faydalanılmasına ilişkin farklı görüşler bulunmaktadır. Sonuç olarak bu çalışmanın öğretim üyeleri, öğretmenler ve öğretmen adayları için kuramsal bir başvuru kaynağı olabileceği düşünülmektedir.
Ortaokul Matematik Öğretmenlerinin Uzaktan Eğitimde Matematik Öğretim Deneyimleri
Authors: ÖZDEMİR BAKİ Gülşah , ÇELİK Elif
Published: June 2021

Covid-19 pandemisi sadece sağlık alanında değil birçok alanda etkilerini göstermeye devam etmektedir. Bu alanlardan biri de eğitimdir. Pandeminin hızlı bir şekilde yayılması sebebiyle birçok ülkede olduğu gibi Türkiye de eğitim sürecine uzaktan eğitim yoluyla devam etmektedir. Bu çalışma, Covid-19 nedeniyle ilk defa uzaktan eğitim süreciyle karşı karşıya gelen ortaokul matematik öğretmenlerinin bahar döneminde ne tür sorunlar yaşadıklarını ve bu sorunları çözmek için güz döneminde ne tür tedbirler aldıklarını, hangi yöntem ve teknikleri kullanmaya başladıklarını, başarılı bir ders için ne tür öğretimsel içerikler hazırladıklarını belirlemeyi amaçlamaktadır. Bu nedenle çalışma, nitel araştırma türlerinden biri olan fenomenolojik araştırma yaklaşımı çerçevesinde tasarlanmıştır. Çalışma, 2020 yılının Aralık ayında Türkiye’nin farklı bölgelerinde devlet okullarında ve özel okullarda görev yapan 25 ortaokul matematik öğretmeni ile yürütülmüştür. Katılımcıların belirlenmesinde kırsal, varoş ve şehir merkezinde görev yapan öğretmenlere ulaşılarak maksimum çeşitlilik sağlanmaya çalışılmıştır. Katılımcı öğretmenlerin deneyimleriyle ilgili kapsamlı bilgi elde etmek amacıyla görüşme tekniği kullanılmıştır. Pandemi nedeniyle görüşmeler online gerçekleştirilmiştir. Elde edilen verilerin incelenmesinde içerik analizi tekniği kullanılmıştır. Yapılan analizler sonucunda öğretmenlerin uzaktan eğitimde öğretim elemanları (öğrenci, öğretici, matematiğe özgü), teknoloji, dış faktör kaynaklı zorluklar yaşadıkları belirlenmiştir. Öğretmenlerin bu zorlukların üstesinden gelebilmek için teknolojiyi takip etme ve kullanma, doküman/materyal eksikliğini giderme, öğrencinin aktif katılımını sağlama, ders süresini etkin kullanma, iletişim yollarını artırma şeklinde önlemler aldıkları görülmüştür. Çalışmanın sonucunda, varoş ve kırsal bölgelerde görev yapan öğretmenler ile şehir merkezinde görev yapan öğretmenlerin uzaktan eğitim sürecinde karşılaştıkları sorunlara bağlı olarak aldıkları tedbirlerinin farklılaştığı söylenebilir. Bu durum, eğitimde fırsat eşitsizliğinin uzaktan eğitim sürecine yansıması olarak değerlendirilebilir.
Covid-19 Pandemi Sürecinde Bireylerin Sosyal Destek ve Aile İklimi Algılarının İncelenmesi
Authors: KABASAKAL Zekavet , AKTAŞ Aykut
Published: June 2021

Bu çalışmanın amacı Covid-19 pandemisi sürecinde bireylerin sosyal destek ve aile iklimi algılarının çeşitli sosyodemografik ve Covid-19’la ilişkili çeşitli değişkenler açısından incelenmesidir. Katılımcılar araştırmaya gönüllülük esasına göre Google formlar aracılığıyla katılmıştır. Çalışma grubu uygun örneklemeyle oluşturulan 684 kişiden oluşmaktadır. Araştırmanın yöntemi ilişkisel tarama modelindedir. Araştırma kapsamında veriler Kişisel Bilgi Formu, Çok Boyutlu Algılanan Sosyal Destek Ölçeği’nin Gözden Geçirilmiş Formu ve Algılanan Aile İklimi Ölçeği aracılığıyla elde edilmiştir. Araştırma bulguları incelendiğinde evli katılımcıların “aileden sağlanan sosyal destek”, “aile içi ilişkisellik” ve “bilişsel uyum” boyutları ortalama puanlarının, bekar katılımcıların ortalamalarından daha yüksek olduğu bulunmuştur. “Aileden”, “arkadaştan” ve “özel bir insandan sağlanan destek” boyutu ile “aile içi ilişkisellik” boyutu arasında pozitif yönlü, “kuşaklararası otorite” boyutu ile negatif yönlü ilişkili olduğu görülmüştür. “Aileden sağlanan destek”, ve “özel bir insandan sağlanan destek” boyutları ile “Bilişsel uyum” alt boyutu arasında pozitif yönlü anlamlı ilişkiler bulunmuştur. “Aileden”, “arkadaştan” ve “özel bir insandan sağlanan destek” puanları birlikte, aile içi ilişkisellik alt boyutundaki varyansın % 49’unu (R=.702; R2=.493; p
ОКСИДАЗИ L-АМІНОКИСЛОТ: ОДЕРЖАННЯ, ВЛАСТИВОСТІ ТА ПЕРСПЕКТИВИ ВИКОРИСТАННЯ
Authors: Гайда Галина
Published: June 2021

Проаналізовано наукову літературу за проблемою оксидаз L-амінокислот стосовно джерел їхнього накопичення, методів одержання, моніторингу каталітичної активності, характеристик ферментів та перспектив їхнього використання. Розроблено скринінгові кольорові експрес-тести виявлення L-аргініноксидази (ArgО), запропоновано схему очищення ArgО з шапинкового гриба Amanita phalloides. Препарати АргО виділено в аналітичних кількостях, вивчено деякі властивості ферменту, а саме, умови зберігання та субстратну специфічність.
Kültürel Coğrafya Bağlamında Temsil ve Temsil Ötesi Teoriler
Authors: OKUR Miyase , BİLGİLİ Münür
Published: June 2021

2000’li yıllardan önce kültürel coğrafyada temsile dayalı yaklaşım ve teoriler daha ön planda iken 2000’li yılların başından günümüze temsil ötesi teoriler daha görünür olmaya başlamıştır. Dönemsel olarak baskın bir teori ön plana çıkmasına karşın kültürel coğrafya içinde her iki yaklaşımda yaygın bir şekilde işlerliğe sahiptir. Bilindiği gibi kültürel yaşam çok farklı anlamlarla yüklü ve tek bir yaklaşımla ele alınamayacak zenginlikte bir içeriğe sahiptir. Bu nedenle sınırlı bir perspektif ve yaklaşımla ele alınması doğal olarak bu kültürel zenginliği yansıtmaya yetmeyecektir. Temsil ve temsil ötesi teoriler önemli oranda kültürel çeşitliliği daha iyi yansıtma düşüncesiyle coğrafi disipline taşınmıştır. Temsil, dünyada var olma biçimlerimizi oluşturup gerçeğe dönüştürme olarak tanımlanmaktadır. Bu gerçekliği önemli oranda dil ve söylemler yoluyla oluşturur.

Çalışma boyunca temsil teorileri, temsil ötesi teori ve mekan üzerine geliştirilmiş farklı teori, paradigma yaklaşımlardan konuya yaklaşılacaktır. İlk bölümde daha çok temsil ve temsil ötesi tartışmalarının sosyal bilimler içindeki yeri irdelenecektir. İkinci bölümde daha özele inilerek temsil ve kültürel coğrafya içindeki yeri üzerine odaklanılacaktır. Üçüncü bölümü ise temsil ötesi teori(ler) kültürel coğrafya ilişkisi oluşturacak; temsil ötesi teorilerin kültürel coğrafya içinde neden son yıllarda ön plana çıktığı incelenecektir. Sonuç bölümde ise genel bir değerlendirmeye gidilecektir.
İklim Değişikliği Endişesi Ölçeği: Türkçeye Uyarlama Çalışması
Authors: GEZER Melehat , İLHAN Mustafa
Published: June 2021

Bu çalışmada, Stewart (2021) tarafından geliştirilen İklim Değişikliği Endişesi Ölçeği (İDEÖ) Türkçeye uyarlanmıştır. Araştırma 236 öğretmen adayından oluşan bir çalışma grubu üzerinde yürütülmüştür. Yapı geçerliği kapsamında uygulanan doğrulayıcı faktör analizinde (DFA), İDEÖ’nün orijinal formundaki tek faktörlü yapının Türk kültüründe doğrulanmadığı tespit edilmiştir. Bundan dolayı ölçeğin Türkçe formundaki faktör yapısını belirlemek üzere açımlayıcı faktör analizi (AFA) gerçekleştirilmiştir. AFA’da toplam varyansın %64,17’sini açıklayan iki faktörlü bir yapıya ulaşılmıştır. Ortaya çıkan faktörler kaygı ile çaresizlik hissi şeklinde isimlendirilmiştir. Bu iki faktörlü yapı üzerinden yürütülen DFA’da, rapor edilen uyum indekslerinin kabul edilebilir sınırlar içerisinde kaldığı saptanmıştır. Güvenirlik analizinde kaygı ve çaresizlik hissi boyutlarına ait Cronbach alfa katsayıları sırasıyla 0,87 ve 0,83 olarak bulunmuştur. Ölçeğin geneline ait tabakalı Cronbach alfa katsayısı ise 0,91 olarak kestirilmiştir. Madde analizinde, ölçekteki tüm maddeler için madde korelasyonlarının 0,30 ölçüt değerini aştığı sonucuna varılmıştır. Elde edilen sonuçlar, İDEÖ’nün Türkçe formu ile elde edilen ölçümlerin geçerli ve güvenilir olduğunu yansıtmaktadır.
Katse sisäänpäin
Authors: Poutanen Mikko , Tervasmäki Tuomas , Harju Auli
Published: June 2021

Tutkijoiden omat työorganisaatiot, yliopistot, ovat muuttuessaan luonnollisen kiinnostavia mutta yhtäaikaisesti haastavia tutkimuskohteita. Positivististen etäisyys- ja objektiivisuusvaateiden ohella tutkijat kohtaavat organisaation sisäiset poliittiset jännitteet. Tämän ei kuitenkaan tulisi estää tutkijoita perehtymästä oman organisaationsa muutokseen. Hyödyntäen läheisyyden ja osallistuvuuden mahdollistavia tutkimusmetodologioita, kuten kotietnografiaa, tutkijan on mahdollista luodata organisaatiota muutoksessa jännitteet tiedostaen ja samalla reflektoida aktiivisesti omaa asemaansa. Tässä artikkelissa yliopistoreformiin syventyvää tutkimushanketta kuvataan kotietnografian viitekehyksen kautta. Saavutettavan laajemman ymmärryksen ja tiedon potentiaali avaa uusia näkökulmia paitsi tutkimuskohteeseen, myös tutkimukseen ja tutkijoihin itseensä.
Sumbangsih Pemikiran Poskolonial Bagi Gagasan Misi Injili
Authors: Margaret Carmia
Published: June 2021

Artikel ini membahas sebuah pertanyaan: apa sumbangsih pemikiran poskolonial, jika ada, bagi pengayaan wawasan misi Injili? Prasuposisi yang dimiliki adalah bahwa sejatinya kaum Injili sudah memiliki wawasan misi yang utuh dan komprehensif tetapi dalam praktiknya seringkali tidak holistik. Gagasan poskolonial dapat memberi sumbangsih bagi wawasan misi Injili dalam hal penajaman kesadaran misional,  perluasan cakupan misi dan keterlibatan misional, pengembangan hermeneutika orang lokal dan penyetaraan antara yang menginjili dan yang diinjili. Sumbangsih ini dapat dielaborasi dari keprihatinan utama gagasan poskolonial yang ingin menghapuskan dominasi, menghapuskan biner, dan mengupayakan peleburan identitas. Akan tetapi, gagasan poskolonial itu sendiri tetap perlu dicermati, agar tidak serta-merta menjadi kolonialisme baru sebagaimana yang dikritisinya sendiri.
Characteristics of Tibetan pig lung tissue in response to a hypoxic environment on the Qinghai–Tibet Plateau
Authors: Yang Yanan , Gao Caixia , Yang Tianliang , Sha Yuzhu , Cai Yuan , Wang Xinrong , Yang Qiaoli , Liu Chengze , Wang Biao , Zhao Shengguo
Published: June 2021

Abstract. To adapt to the plateau environment, Tibetan pigs' lungs have developed a
unique physiological mechanism during evolution. The vascular corrosion
casting technique and scanning electron microscopy were used to understand
arterial architecture. Blood physiological index and quantitative real-time PCR (qRT-PCR) were used for
assessing whether the lung can regulate the body through anatomical, physiological
and molecular mechanisms to adapt to hypoxic environments. Our study showed
that the lungs of Tibetan pigs were heavier and wider and that the pulmonary
arteries were thicker and branched and had a denser vascular network than
those of Landrace pigs. The hemoglobin (HGB), mean corpuscular hemoglobin
concentration (MCHC) values of high-altitude pigs were significantly higher
than those of low-altitude pigs. The expression levels of HIF-1α,
EPAS1, EPO and VEGF, but not those of eNOS and EGLN1, were significantly higher in the lungs of
high-altitude pigs than in those from pigs at a lower altitude (P<0.05). These findings and a comprehensive analysis help elucidate the
pulmonary mechanism of hypoxic adaptation in pigs.
Causes of the extensive hypoxia in the Gulf of Riga in 2018
Authors: Stoicescu Stella-Theresa , Laanemets Jaan , Liblik Taavi , Skudra Māris , Samlas Oliver , Lips Inga , Lips Urmas
Published: June 2021

Abstract. The Gulf of Riga is a relatively shallow bay connected to the deeper central Baltic Sea (Baltic Proper) via straits with sills. The decrease in the near-bottom oxygen levels from spring to autumn is a common feature in the gulf, but in 2018, hypoxia was exceptional. We analyzed temperature, salinity, oxygen, and nutrient data collected in 2018 and historical data available from environmental databases. Forcing data from the study year were compared with their long-term means and variability. The year 2018 was exceptional due to occasionally dominating north-easterly winds supporting the inflow of saltier waters from the Baltic Proper and meteorological conditions causing fast development of thermal stratification in spring. Existing stratification hindered vertical transport between the near-bottom layer (NBL) and the water layers above it. The estimated oxygen consumption rate at the sediment surface in spring-summer 2018 was about 1.7 mmol O2 m−2 h−1 that exceeded the oxygen input to the NBL due to advection and mixing. We suggest that the observed pronounced oxygen depletion was magnified by the prolonged stratified season and haline stratification in the deep layer that maintained a decreased water volume between the seabed and the pycnocline. The observed increase in phosphate concentrations in the NBL in summer 2018 suggests a significant sediment phosphorus release in hypoxic conditions counteracting the mitigation measures to combat eutrophication. We conclude, if similar meteorological conditions as in 2018 could occur more frequently in the future, such extensive hypoxia would be more common in the Gulf of Riga and other coastal basins with similar morphology and human-induced elevated input of nutrients.
Parallel between the isotopic composition of coccolith calcite and carbon levels across Termination II: Developing a new paleo-CO2 probe
Authors: Godbillot Camille , Minoletti Fabrice , Bassinot Franck , Hermoso Michaël
Published: June 2021

Abstract. Beyond the pCO2 records provided by ice core measurements, the quantification of atmospheric CO2 concentrations and changes thereof relies on proxy data, the development of which represents a foremost challenge in paleoceanography. In the paleoceanographic toolbox, the coccolithophores occupy a notable place, as the magnitude of the carbon isotopic fractionation between ambient CO2 and a type of organic compounds that these photosynthetic microalgae synthesize (the alkenones) represents a relatively robust proxy to reconstruct past atmospheric CO2 concentrations during the Cenozoic. The isotopic composition of coeval calcite biominerals found in the sediments and also produced by the coccolithophores (the coccoliths) have been found to record an ambient CO2 signal through culture and sediment analyses. These studies have, however, not yet formalized a transfer function that quantitatively ties the isotopic composition of coccolith calcite to the concentrations of aqueous CO2, and, ultimately, to atmospheric CO2 levels. Here, we make use of a micro-separation protocol to compare the isotopic response of two size-restricted coccolith assemblages from the North Atlantic to changes in surface ocean CO2 during Termination II (ca. 130–140 ka). Performing paired measurements of the isotopic composition (δ13C and δ18O) of relatively large and small coccoliths provides an isotopic offset that can be designated as a “differential vital effect”. We find that the evolution of this offset follows that of aqueous CO2 concentrations computed from the ice core CO2 curve and an independent temperature signal. We interpret this biogeochemical feature to be the result of converging carbon fixation strategies between large and small cells as the degree of carbon limitation for cellular growth decreases across the deglaciation. We are therefore able to determine a transfer function between the coccolith differential vital effects and aqueous CO2 in the range of Quaternary CO2 concentrations. We here consolidate a new coccolith ∆δ13C proxy that overtakes the strong assumptions that have to be made pertaining to the chemistry of the carbonate system in seawater, as required in CO2 proxy methods such as the boron isotope and alkenone proxies.
Covariance-based selection of parameters for particle filter data assimilation in soil hydrology
Authors: Jamal Alaa , Linker Raphael
Published: June 2021

Abstract. Real-time in-situ measurements are increasingly used to improve the estimations of simulation models via data assimilation techniques such as particle filter. However, models that describe complex processes such as water flow contain a large number of parameters while the data available is typically very limited. In such situations, applying particle filter to a large, fixed set of parameters chosen a priori can lead to unstable behavior, i.e. inconsistent adjustment of some of the parameters that have only limited impact on the states that are being measured. To prevent this, in this study correlation-based variable selection is embedded in the particle filter, so that at each data assimilation step only a subset of the parameters is adjusted. More specifically, whenever measurements become available, the most influential (i.e., the most highly correlated) parameters are determined by correlation analysis, and only these are updated by particle filter. The proposed method was applied to a water flow model (Hydrus-1D) in which states (soil water contents) and parameters (soil hydraulic parameters) were updated via data assimilation. Two simulation case studies were conducted in order to demonstrate the performance of the proposed method. Overall, the proposed method yielded parameters and states estimates that were more accurate and more consistent than those obtained when adjusting all the parameters.
INVESTIGATING THE PERFORMANCE OF A HANDHELD MOBILE MAPPING SYSTEM IN DIFFERENT OUTDOOR SCENARIOS
Authors: Maset E. , Cucchiaro S. , Cazorzi F. , Crosilla F. , Fusiello A. , Beinat A.
Published: June 2021

Abstract. In recent years, portable Mobile Mapping Systems (MMSs) are emerging as valuable survey instruments for fast and efficient mapping of both internal and external environments. The aim of this work is to assess the performance of a commercial handheld MMS, Gexcel HERON Lite, in two different outdoor applications. The first is the mapping of a large building, which represents a standard use-case scenario of this technology. Through the second case study, that consists in the survey of a torrent reach, we investigate instead the applicability of the handheld MMS for natural environment monitoring, a field in which portable systems are not yet widely employed. Quantitative and qualitative assessment is presented, comparing the point clouds obtained from the HERON Lite system against reference models provided by traditional techniques (i.e., Terrestrial Laser Scanning and Photogrammetry).
OPEN URBAN AND FOREST DATASETS FROM A HIGH-PERFORMANCE MOBILE MAPPING BACKPACK – A CONTRIBUTION FOR ADVANCING THE CREATION OF DIGITAL CITY TWINS
Authors: Blaser S. , Meyer J. , Nebiker S.
Published: June 2021

Abstract. With this contribution, we describe and publish two high-quality street-level datasets, captured with a portable high-performance Mobile Mapping System (MMS). The datasets will be freely available for scientific use. Both datasets, from a city centre and a forest represent area-wide street-level reality captures which can be used e.g. for establishing cloud-based frameworks for infrastructure management as well as for smart city and forestry applications. The quality of these data sets has been thoroughly evaluated and demonstrated. For example, georeferencing accuracies in the centimetre range using these datasets in combination with image-based georeferencing have been achieved. Both high-quality multi sensor system street-level datasets are suitable for evaluating and improving methods for multiple tasks related to high-precision 3D reality capture and the creation of digital twins. Potential applications range from localization and georeferencing, dense image matching and 3D reconstruction to combined methods such as simultaneous localization and mapping and structure-from-motion as well as classification and scene interpretation. Our dataset is available online at: https://www.fhnw.ch/habg/bimage-datasets
AUTOMATED REFLECTANCE TARGET DETECTION FOR AUTOMATED VICARIOUS RADIOMETRIC CORRECTION OF UAV IMAGES
Authors: Ban S. , Kim T.
Published: June 2021

Abstract. Recently, with increasing use of unmanned aerial vehicle (UAV), radiometric calibration of UAV images has become an important pre-processing step for application such as vegetation mapping, crop field monitoring, etc. In order to obtain accurate spectral reflectance, some UAVs measure irradiance at the time of image acquisition. However, most of UAV systems do not have such irradiance sensors. In these cases, vicarious radiometric correction method has to be used. Digital numbers (DNs) of imaged ground reflectance targets are measured and spectral reflectance is acquired from with known reflectance values of the targets. For automated vicarious calibration, a technique for automatically detecting image location of ground reflectance targets has been developed. In this study, we report an improved version of automated reflectance target detection and a new semi-automatic reflectance target detection developed. Test results showed that among the 14 reflectance targets, 13 targets were detected with the automatic target detection method. The undetected target was extracted by the proposed semi-automatic target detect method. Additional test was conducted on the remaining targets to confirm the applicability of our semi-automatic target detection method. As a result, other targets were also detected. The proposed automated and semi-automated target detection method can be used for automated vicarious calibration of UAV images.
TOWARDS MORE EFFICIENT UAS DATA ACQUISITION: CAMERA AUTO MOUNT PIVOTING OBLIQUE SURVEY
Authors: Campos I. S. G.
Published: June 2021

Abstract. In this paper I present a new MAVLink command, enabling oblique aerial surveys, along with its implementation on the major open source flight stacks (PX4 and ArduPilot) and ground control station (QGroundControl). A key advantage of this approach is that it enables vehicles with a typical gimbaled camera to capture oblique photos in the same pass as nadir photos, without the need for heavier and more expensive alternatives that feature multiple cameras, at fixed angles in a rigid mount, thus are unsuitable for lightweight platforms. It also allows for flexibility in the configuration of the camera angles. The principle is quite simple, the command combines camera triggering with mount actuation in a synchronized cycle along the flight traverses through the region of interest. Oblique photos have also been shown to increase the accuracy of data and help filling holes in point clouds and related outputs of surveys with vertical components. To provide evidence of its benefits, I compare the results of several missions, in simulated and field experiments, flown with nadir only surveys versus oblique surveys, and different camera configurations. In both cases, ground control and check points were used to evaluate the accuracy of the surveys. The field experiments show the vehicle had to fly 44% less with the oblique survey to cover the same area as the nadir survey, which could translate in a 80% gain in efficiency in coverage area per flight. Furthermore, this new command is capable of enhancing functionality of Unmanned Aerial Systems (UASs) without any additional hardware, therefore its adoption should be straightforward.
ANALYSIS OF POSITIONING DEVIATION BETWEEN BEIDOU AND GPS BASED ON NATIONAL REFERENCE STATIONS IN CHINA
Authors: Chen M. , Zhang Q.
Published: June 2021

Abstract. In order to probe into the characteristics of positioning deviation between Beidou Navigation Satellite System (Beidou) and global positioning system (GPS), and investigate possible contribution of Beidou data to refinement of global coordinate system, refined calculation is made on observation data of 240 national reference stations that are distributed uniformly across China on the whole in this study. These stations support satellite signals of four global navigation satellite systems, including Beidou, GPS, GLONASS and Galileo, and a 5-year time span from 2016 to 2020 is adopted. In this study, PPP is calculated based on GPS data and Beidou single system data in no-difference resolution network mode, and accurate coordinates of national reference stations in two processing modes are obtained. Analysis of difference between the calculations based on Beidou data and on GPS data shows that the consistency between Beidou and GPS positioning results reaches about 5 mm in the east and in the north, and about 1.3 cm in the height direction.
FEASIBILITY VERIFICATION OF VIRTUAL REFERENCE STATION TECHNOLOGY IN GEOLOGICAL HAZARD MONITORING
Authors: Zhang Q. , Chen M. , Wu J. , Xu C. , Wang F.
Published: June 2021

Abstract. The surveying and mapping administrative competent departments in 31 provinces (autonomous regions and municipalities) have built provincial-level satellite navigation and positioning reference stations and data centers, and provided CORS services. This provides a good condition for exploring the application of geological hazard monitoring and early warning using Virtual Reference Station (VRS) service based on CORS. At present, the layout mode of "one point one reference station" is usually adopted, when GNSS is used for geological disaster monitoring and early warning. However, the high deployment cost of this plan limits its largescale promotion and application. Using the existing CORS service resources of natural resource system, this paper carried out the application experiment of virtual reference station in geological hazard monitoring application at Huanglongya geological hazard monitoring site in Shaanxi Province, and assessed the virtual reference station data quality, comparative analyzed the precision of static baseline processing results and GNSS real-time deformation monitoring results. The experimental results show that the overall quality of virtual reference station data is better than that of the monitoring station, and the accuracy of the static baseline calculation results is better than 1.0cm in the X direction, and better than 2.0cm in the Y direction and Z direction, which is similar to the static baseline calculation results formed by the physical reference station. The accuracy of the baseline results of real-time observation data calculation is better than 5mm in horizontal RMS and 15mm in vertical RMS. Therefore, it can be seen that the virtual reference station is feasible to be used as the reference station for geological disaster monitoring. In addition, the application experiment of network RTK real-time dynamic single epoch positioning mode is also carried out in geological hazard monitoring. The experimental results show that the RMS values of all three directions are ±3.7mm, ±9.2mm and ±5.0mm respectively, which meet the precision requirements of GNSS disaster monitoring. Therefore, it is also a feasible scheme for geological disaster monitoring and early warning.
AN EFFICIENT DEEP LEARNING APPROACH FOR GROUND POINT FILTERING IN AERIAL LASER SCANNING POINT CLOUDS
Authors: Nurunnabi A. , Teferle F. N. , Li J. , Lindenbergh R. C. , Hunegnaw A.
Published: June 2021

Abstract. Ground surface extraction is one of the classic tasks in airborne laser scanning (ALS) point cloud processing that is used for three-dimensional (3D) city modelling, infrastructure health monitoring, and disaster management. Many methods have been developed over the last three decades. Recently, Deep Learning (DL) has become the most dominant technique for 3D point cloud classification. DL methods used for classification can be categorized into end-to-end and non end-to-end approaches. One of the main challenges of using supervised DL approaches is getting a sufficient amount of training data. The main advantage of using a supervised non end-to-end approach is that it requires less training data. This paper introduces a novel local feature-based non end-to-end DL algorithm that generates a binary classifier for ground point filtering. It studies feature relevance, and investigates three models that are different combinations of features. This method is free from the limitations of point clouds’ irregular data structure and varying data density, which is the biggest challenge for using the elegant convolutional neural network. The new algorithm does not require transforming data into regular 3D voxel grids or any rasterization. The performance of the new method has been demonstrated through two ALS datasets covering urban environments. The method successfully labels ground and non-ground points in the presence of steep slopes and height discontinuity in the terrain. Experiments in this paper show that the algorithm achieves around 97% in both F1-score and model accuracy for ground point labelling.
SETUP OF A CORONA CAMERA AND IMAGE CO-REGISTRATION / CALIBRATION
Authors: Kunz N. , Bochmann P. , Kemper G.
Published: June 2021

Abstract. Power lines are an important infrastructure and need special attention. Their functionality is of high importance for our life. Their monitoring is important to guarantee their sustainable operation. It is done mostly by aerial survey using different technologies. In addition to standard setups, e.g. LiDAR and high resolution RGB cameras, often UV cameras, so called Corona Cameras, are used to detect unwanted discharges. In many cases this UV cameras are combined along with RGB cameras with a similar field of view in order to superimpose the detected UV signals onto a visual image of the inspected objects. Discharges at power lines indicate findings that should be monitored with such additional sensors like thermal or high resolution mapping cameras then.The use of Corona-Cameras for such inspection work needs several steps of calibration, co registering and direct referencing methods in order to get them in a good georeference to the other sensors.
RANDOM FOREST-BASED RIVER PLASTIC DETECTION WITH A HANDHELD MULTISPECTRAL CAMERA
Authors: Cortesi I. , Masiero A. , De Giglio M. , Tucci G. , Dubbini M.
Published: June 2021

Abstract. Plastic pollution has become one of the main global environmental emergencies. A considerable part of used plastics materials is dispersed or accumulated in the environment with a significant damaging impact on many terrestrial and aquatic ecosystems.Artificial Intelligence has proven a fundamental approach in last years for the detection of plastics waste in the aquatic habitats: several groups have recently tried to tackle such problem by developing some machine learning-based methods and multispectral or RGB imagery. This study compares the results obtained by two machine learning classifiers, namely Random Forests and Support Vector Machine, to detect macroplastic in the fluvial habitat through multispectral imagery. The acquisition of images has been made with a hand-held multispectral camera called MAIA-WV2. Despite the obtained results are quite good in terms of accuracy in a random validation dataset, some issues, mostly related to the presence of white rocks and glares on water have still to be properly solved.
UAV UWB POSITIONING CLOSE TO BUILDING FACADES: A CASE STUDY
Authors: Bouloukou M. P. , Masiero A. , Vettore A. , Gikas V.
Published: June 2021

Abstract. Nowadays, Unmanned Aerial Vehicles represent a very popular tool used in dramatically wide range of applications: indeed, their high flexibility, ease of use, and in certain cases quite affordable price make them a very attractive solutions in a number of applications, including surveying and mapping. Despite such a wide range of uses, their usage in automatic/autonomous mode is still restricted by the requirement of the availability of a reliable positioning and navigation system, which in practically all the commercial solutions is represented by the Global Navigation Satellite System (GNSS). Unfortunately, the availability and reliability of GNSS cannot be ensured in all the working conditions of interest. In particular, such condition may not hold downtown, close to high buildings. Since this can also be an operative condition of wide interest, this paper aims at investigating the use of an alternative positioning method that can be integrated with GNSS in order to compensate its unavailability. To be more specific, this paper investigates the positioning performance of an Ultra Wide-Band (UWB) system when an UWB rover is attached to a drone flying close to a building facade, whereas a set of UWB anchors are on the ground, close to the facade. The results obtained in the case study of a building of the University of Padua show that the UWB system positioning performance is quite good (quite less than 1 meter error for most of the time) up to approximately 15–20 meters of distance from the anchors. Close to the top of the building the error significantly increases when using an Extended Kalman filter (EKF) positioning approach, probably mostly due to the low UWB measurement success rate at such heights and to the poor geometric configuration of the UWB network. Nevertheless, a Gauss-Newton-based positioning strategy outperforms the EKF in such critical case, still ensuring errors at 1 meter level.
STATE OF THE ART IN DENSE IMAGE MATCHING COST COMPUTATION FOR HIGH-RESOLUTION SATELLITE STEREO
Authors: Wang Y. , Gong D. , Hu H. , Wang S. , Han Y. , Wang Y. , Ma X.
Published: June 2021

Abstract. Large-scale Digital Surface Model (DSM) generated with high-resolution satellite images (HRSI) are comparable, cheaper, and more accessible when comparing to Light Detection and Ranging (LiDAR) data and aerial remotely sensed images. Several photogrammetric commercial/open-source software packages are being developed for satellite image-based 3D reconstruction, in which, most of them adopt a modified version of Semi-Global Matching (SGM) algorithm for dense image matching. With the continuous development of matching cost computation methods, the existing methods can be divided into classical (low-level) and learning-based algorithms (non-end-to-end learning and end-to-end learning methods). On Middlebury and KITTI datasets, learning-based algorithms has shown their superiority compared to SGM derived methods. In this context, we assume that matching cost is the key factor of DIM. This paper reviews and evaluates Census Transform, and MC-CNN on a WorldView-3 typical city scene satellite stereo images on the premise that the overall SGM framework remains unchanged, providing a preliminary comparison for academic and industrial. We first compute the cost valume of these two methods, obtains the final DSM after semi-global optimization, and compares their gemetric accuracy with the corresponding LiDAR derived ground truth. We presented our comparison and findings in the experimental section.
INTERACTIVE EXTRACTION OF LINEAR STRUCTURES FROM LIDAR RAWDATA FOR ARCHAEOMORPHOLOGICAL STRUCTURE PROSPECTION
Authors: Even P. , Grzesznik A. , Gebhardt A. , Chenal T. , Even P. , Ngo P.
Published: June 2021

Abstract. A new detection and visualization tool to inspect raw LiDAR data for archaeological prospection is introduced in this paper. It allows the supervised extraction of linear structures (ridge or hollow) from the 3D ground points, for on-line detailed analysis of their cross and longitudinal profiles. Using raw data provides a richer information than an interpolated digital terrain model. In particular, the extraction process is made aware of point repartition irregularities caused by dense canopies in forested environments. The tool is based on a recent curvilinear structure extraction framework with fast execution time, that ensures a good interaction. Additional performance is achieved through the detection of the local terrain trend around the structure, that allows finer characterizations of the extracted structure. The suitability to several application purposes has been evaluated by archaeologists through real context experiments. The tool was first applied to the survey of a well-known medieval wall and to the identification of its less preserved parts, that are still undisclosed in the forested landscape. Then it was used in the scope of a prospective work about man impacts on its environment to detect and analyze old holloways and to get a better understanding of their local sunkness or the cause of their local deviations. Potential and limits of the tools are discussed. Open source and executable codes are left available for more extensive exploitation and possible integration into GIS softwares.
EVALUATION OF INTERIOR ORIENTATION MODELLING FOR CAMERAS WITH ASPHERIC LENSES AND IMAGE PRE-PROCESSING WITH SPECIAL EMPHASIS TO SFM RECONSTRUCTION
Authors: Hastedt H. , Luhmann T. , Przybilla H.-J. , Rofallski R.
Published: June 2021

Abstract. For optical 3D measurements in close-range and UAV applications, the modelling of interior orientation is of superior importance in order to subsequently allow for high precision and accuracy in geometric 3D reconstruction. Nowadays, modern camera systems are often used for optical 3D measurements due to UAV payloads and economic purposes. They are constructed of aspheric and spherical lens combinations and include image pre-processing like low-pass filtering or internal distortion corrections that may lead to effects in image space not being considered with the standard interior orientation models. With a variety of structure-from-motion (SfM) data sets, four typical systematic patterns of residuals could be observed. These investigations focus on the evaluation of interior orientation modelling with respect to minimising systematics given in image space after bundle adjustment. The influences are evaluated with respect to interior and exterior orientation parameter changes and their correlations as well as the impact in object space. With the variety of data sets, camera/lens/platform configurations and pre-processing influences, these investigations indicate a number of different behaviours. Some specific advices in the usage of extended interior orientation models, like Fourier series, could be derived for a selection of the data sets. Significant reductions of image space systematics are achieved. Even though increasing standard deviations and correlations for the interior orientation parameters are a consequence, improvements in object space precision and image space reliability could be reached.
SEMANTIC SEGMENTATION OF TERRESTRIAL LIDAR DATA USING CO-REGISTERED RGB DATA
Authors: Sanchez Castillo E. , Griffiths D. , Boehm J.
Published: June 2021

Abstract. This paper proposes a semantic segmentation pipeline for terrestrial laser scanning data. We achieve this by combining co-registered RGB and 3D point cloud information. Semantic segmentation is performed by applying a pre-trained off-the-shelf 2D convolutional neural network over a set of projected images extracted from a panoramic photograph. This allows the network to exploit the visual image features that are learnt in a state-of-the-art segmentation models trained on very large datasets. The study focuses on the adoption of the spherical information from the laser capture and assessing the results using image classification metrics. The obtained results demonstrate that the approach is a promising alternative for asset identification in laser scanning data. We demonstrate comparable performance with spherical machine learning frameworks, however, avoid both the labelling and training efforts required with such approaches.
EVALUATION OF TUNNEL EXCAVATION COMBINING TERRESTRIAL LASER SCANNING POINT CLOUDS AND DESIGN MODELS
Authors: Zhou Y. , Dong Z. , Tong P. , Yang B.
Published: June 2021

Abstract. The quality of tunnel excavation is evaluated by comparing the excavated tunnel and the design model. Terrestrial laser scanning (TLS) provides surveyors with dense and accurate three-dimensional (3D) point clouds for excavation model reconstruction. However, sufficient attention has not been paid to incorporating design models for tunnel point cloud processing. In this paper, a technical framework that combines TLS point clouds and the design model for tunnel excavation evaluation is proposed. Firstly, the point clouds are sliced into cross-sections and the feature points are accordingly extracted. Then, considering the structure of the design model, feature point deficiencies are repaired by topological and parametric model interpolation. Finally, the excavation quality is evaluated in terms of the deviation of centerlines and 3D models. This method is validated in the case study. Experiments show that the deviation of centerline azimuth is acceptable but there remain considerable overbreak and underbreak, which respectively account for 20.6% and 11.2% of the design excavation volume.
REGISTRATION OPTIMIZATION OF MOBILE HANDHELD SCANNER POINT CLOUDS WITH STATIC SCANS
Authors: Alteirac V. , Macher H. , Landes T.
Published: June 2021

Abstract. In recent years, 3D acquisition methods involving different types of scanners have undergone a phenomenal technological growth. Nowadays, mobile acquisition devices are popular because of their ease of use and their fairly competitive cost. Static scanners provide higher accuracy and more detail, but the acquisition time required with these systems is higher than with mobile systems. Mobile scanners are known for their high acquisition speed but lower point density and accuracy. Until now, the choice of the type of system to use was dependent on the geometry of the study area and the required accuracy. This research aims to find a way to optimize the survey by finding a compromise between the two types of devices, in order to take advantage of both systems for the same acquisition campaign. The first objective is to study the minimum number of static positions required for respecting the required accuracy. A solution is also proposed for compensating the drift of the mobile device. Secondly, the pertinence to use static stations for the principal loop and mobile system for adjoining rooms is investigated. The datasets chosen allow, on the one side, to quantify the limits of the mobile system for the acquisition of indoor buildings and, on the other side, to give recommendations regarding the configuration of static stations as a reference for mobile point clouds. Based on these experiments, a methodology is proposed for indoor environments to combine the use of the two acquisition systems and thus to save time in the field while still providing a good registration quality.
AUTOMATIC DETECTION AND VECTORIZATION OF LINEAR AND POINT OBJECTS IN 3D POINT CLOUD AND PANORAMIC IMAGES FROM MOBILE MAPPING SYSTEM
Authors: Barçon E. , Picard A.
Published: June 2021

Abstract. Surveys of roadways with Mobile Laser Scanning (MLS) are nowadays the faster and more secured way to collect topographic data compared with conventional techniques. To deliver topographic plans, the voluminous data collected by the MLS device need to be processed. If the acquisition step is quite fast, the second part of interpretation and vectorization of the LiDAR data and the panoramic images is laborious and time consuming. This paper proposes two approaches that have been developed in order to reduce the time required to process roadway MLS data. The first one is about automatic detection of pole like objects, and the second one is about the detection of linear objects. The presented workflow try to automatically extract a 3D position for each object from MLS Data.
REAL-TIME DENSE 3D RECONSTRUCTION FROM MONOCULAR VIDEO DATA CAPTURED BY LOW-COST UAVS
Authors: Hermann M. , Ruf B. , Weinmann M.
Published: June 2021

Abstract. Real-time 3D reconstruction enables fast dense mapping of the environment which benefits numerous applications, such as navigation or live evaluation of an emergency. In contrast to most real-time capable approaches, our method does not need an explicit depth sensor. Instead, we only rely on a video stream from a camera and its intrinsic calibration. By exploiting the self-motion of the unmanned aerial vehicle (UAV) flying with oblique view around buildings, we estimate both camera trajectory and depth for selected images with enough novel content. To create a 3D model of the scene, we rely on a three-stage processing chain. First, we estimate the rough camera trajectory using a simultaneous localization and mapping (SLAM) algorithm. Once a suitable constellation is found, we estimate depth for local bundles of images using a Multi-View Stereo (MVS) approach and then fuse this depth into a global surfel-based model. For our evaluation, we use 55 video sequences with diverse settings, consisting of both synthetic and real scenes. We evaluate not only the generated reconstruction but also the intermediate products and achieve competitive results both qualitatively and quantitatively. At the same time, our method can keep up with a 30 fps video for a resolution of 768 × 448 pixels.
AMBIGUITY CONCEPT IN STEREO MATCHING PIPELINE
Authors: Sarrazin E. , Cournet M. , Dumas L. , Defonte V. , Fardet Q. , Steux Y. , Jimenez Diaz N. , Dubois E. , Youssefi D. , Buffe F.
Published: June 2021

Abstract. In a 3D reconstruction pipeline, stereo matching step aims at computing a disparity map representing the depth between image pair. The evaluation of the disparity map can be done through the estimation of a confidence metric. In this article, we propose a new confidence metric, named ambiguity integral metric, to assess the quality of the produced disparity map. This metric is derived from the concept of ambiguity, which characterizes the property of the cost curve profile. It aims to quantify the difficulty in identifying the correct disparity to select. The quality of ambiguity integral metric is evaluated through the ROC curve methodology and compared with other confidence measures. In regards to other measures, the ambiguity integral measure shows a good potential. We also integrate this measure through various steps of the stereo matching pipeline in order to improve the performance estimation of the disparity map. First, we include ambiguity integral measure during the Semi Global Matching optimization step. The objective is to weight, by ambiguity integral measure, the influence of points in the SGM regularization to reduce the impact of ambiguous points. Secondly, we use ambiguity as an input of a disparity refinement deep learning architecture in order to easily locate noisy area and preserve details.