bluuebunny/crossref_metadata_2025 huggingface dataset:
O PAPEL DO ADVOGADO: UM OLHAR ACERCA DA ESTRATÉGIA DO MARKETING JURÍDICO
Authors: Machado Junior Miguel livramento , Souza Guilherme Yuri Queiroz de , Werneck Marcus Nunes da Silva
Published: June 2022

Essa pesquisa buscou debater os meios disponíveis que o jovem advogado possui para encontrar seu espaço profissional atualmente. Considerando-se que todos os setores usam cada vez mais as mídias sociais como parte essencial de sua estratégia de marketing, entretanto, entre os escritórios de advocacia, a competição pelos clientes é particularmente acirrada. Como objeto, o tema Marketing Jurídico e o papel do advogado no cenário atual, em que foram considerados, para fins de desenvolvimento do estudo o trabalho do advogado na sociedade, as suas dificuldades e incertezas e a forma como ele poderá proceder na busca da clientela bem como seu marketing jurídico. Este trabalho foi desenvolvido a partir de um estudo de revisão sistemática com abordagem qualitativa através da revisão de literatura, acerca do tema aqui proposto bem como pesquisa de campo. Para a realização da pesquisa utilizaram-se artigos científicos ligados ao tema foi realizada uma busca em fontes científicas como livros, artigos, monografias, visando identificar as concepções de diversos autores sobre o tema investigado, procurando referências teóricas publicadas com o objetivo de recolher informações ou conhecimentos prévios sobre o problema investigado.
On the development of a new prototype PTR-ToF-MS instrument and its application to the detection of atmospheric amines
Authors: Håland Alexander , Mikoviny Tomáš , Syse Elisabeth Emilie , Wisthaler Armin
Published: June 2022

Abstract. We herein report on the development of a new prototype PTR-ToF-MS instrument that combines a hollow cathode glow discharge (HCGD) ion source with a focusing ion-molecule reactor (FIMR), which consists of a resistive glass drift tube surrounded by quadrupole rods. The new instrument configuration hybridizes the two main current commercial PTR-ToF-MS instrument designs. We provide a detailed technical description of the new analyzer and its optimized operational settings for detecting volatile amines via proton transfer reactions from hydronium (H3O+) or ammonium (NH4+) ions. We show that the new prototype PTR-ToF-MS instrument is capable of monitoring rapid changes of sticky amines on the timescale of a few seconds and detects atmospheric variations of amines down to single digit pptV levels. Application examples given include the real-time monitoring of i) methylamine emitted from a Chenopodium vulvaria L. plant, ii) small alkylamines in ambient air on site of an agricultural research center (Senter for husdyrforsøk, Ås, Norway), and iii) an industrial amine (2-amino-2-methylpropan-1-ol, AMP) on site and downwind of a carbon dioxide (CO2) capture test center (Technology Centre Mongstad – TCM, Mongstad, Norway).
Analysis of the evolution of parametric drivers of high-end sea-level hazards
Authors: Hough Alana , Wong Tony E.
Published: June 2022

Abstract. Climate models are critical tools for developing strategies to manage the risks posed by sea-level rise to coastal communities. While these models are necessary for understanding climate risks, there is a level of uncertainty inherent in each parameter in the models. This model parametric uncertainty leads to uncertainty in future climate risks. Consequently, there is a need to understand how those parameter uncertainties impact our assessment of future climate risks and the efficacy of strategies to manage them. Here, we use random forests to examine the parametric drivers of future climate risk and how the relative importances of those drivers change over time. In this work, we use the Building blocks for Relevant Ice and Climate Knowledge (BRICK) semi-empirical model for sea-level rise. We selected this model because of its balance of computational efficiency and representation of the many different processes that contribute to sea-level rise. We find that the equilibrium climate sensitivity and a factor that scales the effect of aerosols on radiative forcing are consistently the most important climate model parametric uncertainties throughout the 2020 to 2150 interval for both low and high radiative forcing scenarios. The near-term hazards of high-end sea-level rise are driven primarily by thermal expansion, while the longer-term hazards are associated with mass loss from the Antarctic and Greenland ice sheets. Our results highlight the practical importance of considering time-evolving parametric uncertainties when developing strategies to manage future climate risks.
Stability of alkalinity in Ocean Alkalinity Enhancement (OAE) approaches – consequences for durability of CO2 storage
Authors: Hartmann Jens , Suitner Niels , Lim Carl , Schneider Julieta , Marín-Samper Laura , Arístegui Javier , Renforth Phil , Taucher Jan , Riebesell Ulf
Published: June 2022

Abstract. According to modelling studies, ocean alkalinity enhancement (OAE) is one of the proposed carbon dioxide removal (CDR) approaches with large potential, and the beneficial side effect of counteracting ocean acidification. The real-world application of OAE, however, remains unclear as most basic assumptions are untested. Before large-scale deployment can be considered, safe and sustainable procedures for the addition of alkalinity to seawater must be identified and governance established. One of the concerns is the stability of alkalinity when added to seawater. Seawater is already supersaturated with respect to calcium carbonate minerals, and an increase in total alkalinity together with a corresponding shift in carbonate chemistry towards higher carbonate ion concentrations would result in further increase in supersaturation, and potentially to solid carbonate precipitation. Precipitation of carbonate minerals consumes alkalinity and increases dissolved CO2 in seawater, thereby reducing the efficiency of OAE for CO2 removal. In order to address the application of alkaline solution as well as fine particulate alkaline solids, a set of six experiments was performed using natural seawater with alkalinity of around 2,400 μmol/kgw. The application of CO2-equilibrated alkaline solution bears the lowest risk of losing alkalinity due to carbonate formation if added total alkalinity (ΔTA) is less than 2,400 μmol/kgw. The addition of reactive alkaline solids can cause a net loss of alkalinity if ΔTA > 600 μmol/kgw (e.g., for Mg(OH)2). Commercially available Ca(OH)2 causes in general a net loss in TA for the tested amounts of TA addition, which has consequences for suggested use of slurries supplied from ships. The application of excessive amounts of Ca(OH)2, exceeding a threshold for alkalinity loss, resulted in a massive increase in TA (> 20,000 μmol/kgw) at the cost of lower efficiency and resultant high pH values > 9.5. Our results indicate that using an alkaline solution instead of reactive alkaline particles can avoid carbonate formation, unless alkalinity addition shifts the system beyond critical supersaturation levels. To avoid the loss of alkalinity and dissolved inorganic carbon (DIC) from seawater, the application of reactor techniques can be considered. These techniques produce an equilibrated solution from alkaline solids and CO2 prior to application. Differing behaviours of tested materials suggest that standardized engineered materials for OAE need to be developed to achieve safe and sustainable OAE with solids, if reactors technologies should be avoided.
Non-Redfield carbon model for the Baltic Sea (ERGOM version 1.2) – Implementation and Budget estimates
Authors: Neumann Thomas , Radtke Hagen , Cahill Bronwyn , Schmidt Martin
Published: June 2022

Abstract. Redfield stoichiometry based marine biogeochemical models suffer from underestimating carbon fixation by primary production. Most pronounced indication of this is the overestimation of the dissolved inorganic carbon concentration and, consequently, the partial pressure of carbon dioxide in surface waters. The reduced production of organic carbon will impact most biogeochemical processes. We propose a marine biogeochemical model allowing for a non-Redfield carbon fixation. The updated model is able to reproduce observed partial pressure of carbon dioxide and other variables of the ecosystem, like nutrients and oxygen, reasonably well. The additional carbon uptake is realized in the model by an extracellular release of dissolved organic matter from phytoplankton. Dissolved organic matter is subject to flocculation and the sinking particles remove carbon from surface waters. This approach is mechanistically different from existing non-Redfield models, which allow for flexible element ratios for the living cells of the phytoplankton itself. The performance of the model is demonstrated as an example for the Baltic Sea. Budget estimates for carbon illustrate that the Baltic Sea acts as a carbon sink. For alkalinity, the Baltic Sea is a source due to internal alkalinity generation by denitrification. Owing to the underestimated model alkalinity, there exists still an unknown alkalinity source or underestimated land based fluxes.
CAPABILITIES AND LIMITATIONS OF URBAN NEAR-SURFACE PARTICULATE MATTER MONITORING NETWORKS – EVIDENCE FROM WUHAN
Authors: Fan Y. , Zhan Q. , Zhang H. , Xue W.
Published: June 2022

Abstract. Recent years have seen the emergence of local air pollutant monitoring networks that feature close proximity to urban activities, higher requirement for temporal granularity, and improvisions in equipment hardware and installation conditions. These networks are intended for the pertinent monitoring and improvement of urban air quality, but potential technical issues may undermine their ability to serve such purposes. This study utilizes a minute-granularity network in a university campus, and designs and conducts a series of experiments on how it performs under practical scenarios, including response to sudden environment change, reflection of multi-scale influencing factors, usability of different baseline stations, and ability to detect local emission events. Statistical and signal-processing technics are applied for understanding these experiments. The results indicate the source of complexity in such networks, the preferred temporal granularity for capturing different temporal patterns, the necessary reserved time for mobile stations, and the sensor location requirement for monitoring local emission events etc. In practical terms, these results provide a large amount of information on the specific capabilities and limitations of a near-surface, high-granularity monitoring network in the urban environment, and what to consider and to expect as a designer or user of such a network. In scientific terms, it is a strong reminder of the significance of numerous uncertainty issues in similar empirical studies.
DETECTION OF CHANGES IN GROUPS OF MOVING OBJECTS
Authors: Feuerhake U.
Published: June 2022

Abstract. The analysis of moving objects is a rather challenging but also informative task. It provides important knowledge which is required in a large variety of research fields and applications. The same holds for the analysis of group movements, which, for instance, is able to provide knowledge that can support or contribute to social behavior studies of human beings or animals. In this work, we present an approach to identify changes in the group structure over time, which can support studies regarding an object’s role or standing within the group. The presented methodology is based on the transformation to relative movements and a consecutive change detection algorithm. In order to evaluate our approach, we further conduct experiments by applying it to real data from different scenarios. The results obtained in these experiments demonstrate the functionality and its portability to different uses cases.
A REVIEW OF URBAN HUMAN MOBILITY RESEARCH BASED ON CROWD-SOURCED DATA AND SPACE-TIME AND SEMANTIC ANALYSIS
Authors: Kamel Basmenj S. , Li S.
Published: June 2022

Abstract. Detecting urban human mobility patterns helps contributes to many urbanization issues, such as urban planning and traffic management. With the growing volume of crowd-sourced data, many studies have benefited from this data type to explore people’s daily movements and track their activities. There are several published review papers examing these studies on urban human mobility, with the focus on defining models and applications. However, the absence of a review of studies on urban human mobility that considered spatial, temporal, and semantic properties as well as crowd-sourced data together has limited the proliferation of semantic content in addressing mobility issues. In response, this paper provides a review on urban human mobility, including the data, models, and applications used in the selected articles. We defined particular inclusion and exclusion criteria to select the most relevant articles. We also included metadata analysis to overview the existing relevant literature. Finally, several research challenges and open issues are discussed.
A CONCEPTUAL MODEL FOR CONVERTING OPENSTREETMAP CONTRIBUTION TO GEOSPATIAL MACHINE LEARNING TRAINING DATA
Authors: Li H. , Zipf A.
Published: June 2022

Abstract. In the recent decade, Volunteered Geographical Information (VGI), in particular the OpenStreetMap (OSM), has helped to fill substantial data gaps in base maps, especially in Global South, thus has become a promising source of massive, free training data together with rich and detailed semantic information for geospatial artificial intelligence (GeoAI) applications. Although intensive works have explored the potential of generating training data from OSM, a systematic approach of harvesting OSM contribution as quality-aware training data for different GeoAI tasks is still missing. To fill this research gap, we proposed a conceptual model consisting of three major components: historical OSM and external datasets, quality indicators, and GeoAI models. As a proof of concept, we validated our conceptual model with an example task of detecting OSM missing buildings in Mozambique, where the impact of different error sources (e.g., completeness, alignment, rotation) in training data were compared and investigated in a quantitative manner. The lessons learned in this paper shed important lights on cooperating OSM data quality aspects with the development of more explainable GeoAI models.
MAINTENANCE AND UPDATE NATIONAL TOPOGRAPHIC DATA BASE IN HIGH FREQENCY USING MODERN PROCEDURES AND TECHNIQUES
Authors: Keinan E. , Haj Yehia B. , Brody D. , Siman Tov O. , Shannan A. , Ronen H.
Published: June 2022

Abstract. The state of Israel is a small country, in terms of area, with one the higher population growth rate among all the OECD countries. Hence, each year more than 50,000 housing units built and more than 1,500 km roads constructed in average, each year along the last decade.The Survey of Israel )SOI( is a National Mapping and Cadastral agency (NMCA) that holds the responsibility to update, maintain and disseminate the National Topographic Data Base (NTDB) to all of the governmental offices and municipalities, to utilize, plan and promote the construction of the public needs.Today, the reality is dynamic and the changes occurs every day, therefore, the users expect that the existing database will portray the current reality as possible. In order to address the user's requirements for rapid updating rate, the Survey of Israel promote a new and modern initiatives, including:Promote the cooperation and working relationship with the municipalities to rapidly update the streets, address and POI’s.Data Fusion from different governmental and municipalities data sources.Developing change detection techniques to update the buildings and roads layers.Developing new frameworks for the manual inspection and QA/QC procedures.Developing automatic tools to update the height component via high resolution DSM and DTM (50cm GSD).Disseminate quarterly the NTDB products to the users.Develop a modern processes management system for the update and QA workflowIn this article, we will demonstrate the initiatives and techniques that improved our NTDB updating rate to less than a year and a half in a national average.
APPLICATION AND PLATFORM DESIGN OF SPATIOTEMPORAL DATA OPENING AND SHARING
Authors: Li H. , Huang W. , Zheng X. , Ding L.
Published: June 2022

Abstract. Spatiotemporal data is data that has both temporal attributes and spatial distribution. The core of the opening and sharing of spatiotemporal data is to exchange, share and collaborate with various data, including spatiotemporal data, based on a unified spatiotemporal benchmark. The research methods of domestic and foreign scholars on the opening and sharing of spatiotemporal data mainly focus on spatiotemporal data model, database research, big data mining analysis and visual expression. This paper introduces the connotation and current situation of open sharing of spatiotemporal data. The typical applications of spatiotemporal data open sharing are listed and summarized. This paper proposes to build an open sharing platform for spatiotemporal data, and gives the basic requirements of four parts: spatiotemporal benchmark, spatiotemporal modeling big data, cloud computing-based spatiotemporal big data system and supporting environment. Taking the National Platform for Common Geospatial Information Services (TIANDITU) as an example, the main indicators of the spatiotemporal data open sharing platform are given. Finally, the article concludes and points out the opportunities and challenges faced by the open sharing of spatiotemporal data. In order to play a greater role in social public application services and administrative decision-making.
THE ROLE OF TOPOLOGY IN HIGH-DEFINITION MAPS FOR AUTONOMOUS DRIVING
Authors: Lógó J. M. , Barsi A.
Published: June 2022

Abstract. Autonomous and highly automated driving has become one of the key research topics – even in mapping sciences. Today, it has been clearly proven that the desired autonomy can be reached solely by progressive development, where maps and requirements against environmental models shall be modified. The research of the past decades resulted in the specifications for building high-definition (HD) maps, which contain all necessary field objects with their relevant features in a sophistically designed database. Maps have also become indispensable tools in reliable automotive development processes as simulations request accurate and detailed environment descriptions. The most accepted simulator map format is ASAM’s OpenDRIVE, having a complete ecosystem nowadays with ultra-fine resolution pavement surface model, traffic flow description, and essential modules to produce those components by mainly automatic data collection and processing. Simulations enable efficient analysis of vehicle behavior as well as testing workflow for (onboard) vehicular and infrastructure sensors. With respect to the requirements of HD maps, not only their geometric fidelity but also the correct topology is expected. The available technology already serves OpenDRIVE models for various scenarios, where the topologic correctness is hard to test. The current research puts the emphasis on the topology analysis: with parsing the existing models, topology descriptors are derived, then a test suit containing rules of acceptable cases is applied. The rule set is built of items for detecting errors and warnings considering topology parameter tolerances; the result is quality documentation after a comprehensive testing approach. The actual topology testing environment forms an excellent base for (semi)automatic error fixing platforms involving artificial intelligence.
RESEARCH ON ESTABLISHING A MORE OPEN AND SYSTEMATIC NATIONAL GEO-INFORMATION STANDARD SYSTEM – TAKING CHINA’S GEO-INFORMATION STANDARD SYSTEM AS AN EXAMPLE
Authors: Wang W.
Published: June 2022

Abstract. Geo-information can be found, collected, released, shared, stored, combined and applied through geo-information standards. Building geo-information standard system is the basis for a country or organization to carry out the construction of geo-information standards. The excellent geo-information standard system can maximize the effectiveness of all geo-information standards in the system, so as to ensure that new geo-information sources and technical tools can be fully used. According to the analysis on the challenges of the construction of geo-information standards and standard systems in various countries by the author, most countries (including China) need to establish a more open and systematic national geo-information standard system and implement more flexible policies and measures for standards management. In this paper, the specific implementation measures proposed to improve China's geo-information standard system include 1) using policies to encourage the formulation, transformation and utilization of international standards 2) accelerating the top-level design of the construction of relevant information technology standard systems with geo-information as the core element, 3) filling the gap of standards construction by relevant group or enterprise according to the development requirements of geo-information industry, 4) evaluating and monitoring the important and concerned geo-information standards, etc. We think that the above measures will effectively improve overall openness and build better connection with the international standards, and ensure the scientific and forward-looking features during the construction and design of the standard system.
IFCALIGNMENT FOR RASTER-TO-VECTOR GIS RAILWAY CENTRELINE: A CASE STUDY IN THE SOUTH OF ITALY
Authors: Garramone M. , Scaioni M.
Published: June 2022

Abstract. Built environment Asset Management (AM) is evolving and renewing itself through the development of new technologies. Building Information Modelling (BIM) is the main methodology for the digitisation process of existing data and information. Although BIM was originally intended for buildings, in the last few years Infrastructure Building Information Modelling (I-BIM) and Civil Information Modelling (CIM) are emerging to manage civil infrastructure. The interaction of infrastructure with the surrounding environment is a fundamental aspect and it requires data-sharing between different sources and systems. Geographic Information Systems (GIS) is used to store and elaborate Earth’s surface information, and it is, therefore, necessary to achieve a complete BIM/GIS interoperability. This paper aims to test the popular BIM open-standard Industry Foundation Classes (IFC) capabilities and potentialities in storing GIS data. A case study of a disused railway in the south of Italy was used to test the methodology presented: rail-centreline (alignment) extraction from GIS raster data, and a conversion of the alignment to an IFCAlignment element. The possibility to export a rail alignment in IFC was confirmed.
INTEGRATING CONCEPTS OF ARTIFICIAL INTELLIGENCE IN THE EO4GEO BODY OF KNOWLEDGE
Authors: Lemmens R. , Lang S. , Albrecht F. , Augustijn E. , Granell C. , Olijslagers M. , Pathe C. , Dubois C. , Stelmaszczuk-Górska M.
Published: June 2022

Abstract. The EO4GEO Body of Knowledge (BoK) forms a structure of concepts and relationships between them, describing the domain of Earth Observation and Geo-Information (EO/GI). Each concept carries a short description, a list of key literature references and a set of associated skills which are used for job profiling and curriculum building. As the EO/GI domain is evolving continuously, the BoK needs regular updates with new concepts embodying new trends, and deprecating concepts which are not relevant anymore. This paper presents the inclusion of BoK concepts related to Artificial Intelligence. This broad field of knowledge has links to several applications in EO/GI. Its connection to concepts, already existing in the BoK, needs special attention. To perform a clean and structural integration of the cross-cutting domain of AI, first a separate cluster of AI concepts was created, which was then merged with the existing BoK. The paper provides examples of this integration with specific concepts and examples of training resources in which AI-related concepts are used. Although the presented structure already provides a good starting point, the positioning of AI within the EO/GI-focussed BoK needs to be further enhanced with the help of expert calls as part of the BoK update cycle.
A METHOD FOR REGIONAL ANALYSIS USING DEEP LEARNING BASED ON BIG DATA OF OMNIDIRECTIONAL IMAGES OF STREETS
Authors: Oki T. , Ogawa Y.
Published: June 2022

Abstract. In this paper, we propose a method for regional analysis using image recognition technology based on deep learning and big data of street images captured by omnidirectional cameras on vehicles. Specifically, we first construct a classification method of regions based on street images using a pretrained deep learning model (VGG16) for image recognition as a feature extractor. Next, we develop a method to evaluate the landscape and safety of streets based on the ratio of street components (such as buildings, roads, fences, vegetations, sky, street lights) at each shooting point, which is calculated by semantic segmentation.
3D GIS BASED LONG-DISTANCE PROJECT CONSTRUCTION PROGRESS VISUALIZATION
Authors: Xu Z. , Wen S. , Ding T. , Li S. , Zhang L. , Ma R.
Published: June 2022

Abstract. The construction progress of a long-distance project can generally be reflected by the percentage of the total length of the segmented project on the main line to the total length of the line. However, the way to express the construction progress based on the percentage is not intuitive enough and it is difficult to reflect the segmented project. Insufficient progress differences. This paper proposes a 3DGIS-based visualization method of long-distance project construction progress. Through regular project construction progress report, the completed line can be automatically generated. At the same time, the overall and local construction progress can be visually expressed through the superimposed display with the main line of the project and the three-dimensional terrain. The experiment combined with the engineering example of the Kunming section of Central Yunnan Water Diversion Project shows the visualization effect of the excavation progress of the water conveyance tunnel, and verifies the effectiveness of the method in this paper.
COMPUTER VISION SYSTEM FOR DETECTING ORCHARD TREES FROM UAV IMAGES
Authors: Jemaa H. , Bouachir W. , Leblon B. , Bouguila N.
Published: June 2022

Abstract. Orchard tree inventory plays an important role in acquiring up-to-date information on planted trees for effective treatments and crop insurance purposes. Determining tree damage could help assess orchards’ health faster and cheaper. Having accurate information on the tree’s status could also help managers to plan necessary fieldwork and predict productivity. Traditional orchard inventory is often performed manually, and thus is time-consuming, costly, and subject to error. An alternative is computer vision algorithms that could automatically detect orchard trees based on UAV imagery. The objective of this study is to develop a method using advanced computer vision algorithms to automatically detect apple trees on UAV multispectral images. This task is challenging since apple trees are overlapping over the UAV images, and hence distinguishing different crowns could be difficult. Motivated by the latest advances in UAV imagery and deep-learning models, addressed the tree detection problem by exploring the two CNN models YOLO (You Only Look Once) and DeepForest for detecting apple trees on UAV images. We first constructed a labelled dataset by dividing the study area into equally sized patches. Then we manually annotated all apple trees seen in RGB images. The annotated dataset was then randomly divided into three subsets (training, validation, and testing), for training and testing machine learning models. The performed experiments demonstrate the efficiency and validity of the proposed approach for orchard tree inventory. In particular, the proposed framework achieved a precision of 91% and an F1-score of 87% by adopting the DeepForest model for tree detection.
COLLABORATIVE EDUCATION MODEL ON GIS MAJOR UNDER THE PROFESSIONAL CERTIFICATION OF ENGINEERING EDUCATION
Authors: Jing C. , Zhang X. , Chen Q.
Published: June 2022

Abstract. Engineering education professional certification is a training model for engineering professionals based on international models. This paper discusses the inspiration of domestic and foreign engineering education practice to talent training in China. Based on the core elements of engineering education professional certification, we propose a closed-loop collaborative education model for study and research with "four integrations-two innovations-one education reform" as the core elements. This may be helpful to train the technological ability of students of GIS major. The exploration and practice of talent training in our school have achieved good results in talent cultivation, providing ideas and cases for exploring student-centered talent training.
FORGING AHEAD AND ADAPTING TO CHANGE: A REVIEW OF THE INITIATIVES OF THE ISPRS STUDENT CONSORTIUM
Authors: Reyes S. R. C. , Cruz C. A.
Published: June 2022

Abstract. The International Society for Photogrammetry and Remote Sensing Student Consortium (ISPRS SC) is an international organization that represents a constituency of the students and the young professionals with common interests and goals within ISPRS in the areas of photogrammetry, remote sensing and spatial information science. The ISPRS SC Board of Directors strengthened the organization’s foundations and increased its engagement in the Society from 2016 to 2022. Given the current global health crisis, selected members of the Board of Directors continued to serve in the ISPRS SC for a two-year extension and developed creative strategies in navigating the new normal. Building on the strengths of the organization and motivated by the incredible ideas of connecting and engaging the scientific community that emerged during the pandemic, we were able to transform challenges into opportunities through collaborations and sustained participation of our members. In this paper, we summarize all the activities of the Consortium from 2016 to 2022 and provide insights on the impacts and values of these initiatives to the organization and its members. We also elaborated on hosting the GeoMixers as virtual networking events with our partner organizations as well as organizing the virtual Google Earth Engine meetup in the Singapore Geospatial Festival, which was given the short title, EarthEngine@SG. Outcomes of the Leadership and Service Mentoring Programme, the Consortium’s first mentorship and training programme for potential nominees for the incoming Board of Directors, demonstrated the remarkable potential of the youth in leading and engaging in relevant social and global issues and contributing to the scientific community. Sustaining our relevance to ISPRS, experiencing growth during the pandemic and understanding our roles as an international organization, the Consortium will continue to forge ahead and adapt to change to support the youth and contribute to building resilience and adaptability in our scientific community.
ISPRS-SHY – OPEN DATA COLLECTOR FOR SUPPORTING GROUND TRUTH REMOTE SENSING ANALYSIS
Authors: Pirotti F. , Piragnolo M. , Yoshimura M. , Hernandez J. P. , Brovelli M. A. , Leblon B. , Yamashita M.
Published: June 2022

Abstract. The 2021 Scientific Initiatives in ISPRS funded this project called ISRS-SHY from “SHare mY ground truth”. It was intended as a collector of geographic data to support image analysis by sharing the necessary ground truth data needed for rigorous analysis. Regression and classification tasks that use remote sensing imagery necessarily require some control on the ground. The rationale behind this project is that often data on the ground is collected during projects, but is not valued by sharing across projects and teams globally. Internet has improved the way that data are shared, but there are still limitations related to discoverability of the data and its integrity. In other words, data are usually kept in local storage or, if in an accessible server, they are not documented and therefore they will not be picked up during search. In this initiative we created a portal using the Geonode environment to provide a hub for sharing data between research groups and openly to the community. The portal was then tested within the framework of three projects, with several participants each. The data that was uploaded and shared covered all types of geographic data formats and sizes. Further sharing was done in the context of teaching activities in higher education.The results show the importance of creating easy means to find data and share it across stakeholders. Qualitative results are discussed, and future steps will focus on quantitative assessment of the portal’s usage, e.g. number of registered users in time, number of visits, and other key performance indicators. The results of this project are to be considered also in light of the effort in the scientific community to make research data available, i.e. FAIR - Findability, Accessibility, Interoperability, and Reuse of digital assets.
DEVELOPMENT OF A SMART CITY CONCEPT IN VIRTUAL REALITY ENVIRONMENT
Authors: Buyukdemircioglu M. , Kocaman S.
Published: June 2022

Abstract. There is an increasing interest in smart city concept as a technology-based alternative to conventional urban planning approaches. The design and implementation of smart cities require multidisciplinary efforts. As one of the first examples, a smart city concept was developed in Turkey in the year 2018 in collaboration with researchers and experts from various disciplines, such as geomatics and civil engineers, architects, computer scientists and urban planners. The developed concept aimed at designing a city district that targets sustainability, human-centricity, smartness, and safety, along with a sense of place and reflects local expectations in an unconstructed sub-urban area. In the project, the collaborative design process and the usability issues of the presentation environments have been of importance for geomatics professionals. Within the study, the existing settlement areas were modelled by using aerial photogrammetric data and combined with elements designed in various Computer-aided design (CAD) software. In this paper, the smart city design elements, which originate from the design principles such as ensuring nature conservation, green, cultural, safe and smart living spaces, and social responsibility, are explained briefly. The city was presented to the stakeholders via Unity game engine for a realistic experience prior to construction. The potential of Virtual Reality (VR) environments for the design, modelling, and visualization of very high detailed smart city concept is presented and various issues are discussed. The model experiment videos with VR, web-based model and project video can be accessed via the web page www.bizimsehir.org.
MULTI-CRITERIA ANALYSIS IN THE MANAGEMENT OF TEMPORARY REUSE OF SPACES
Authors: D’Urso M. G. , Rasera S.
Published: June 2022

Abstract. Urban change has always marked the way of rethinking cities, bringing continuous studies aimed at urban regeneration. In contrast to traditional approaches, centered on the duality of demolition and construction, the temporary reuse of spaces addresses the issue of urban transformation with a multi-criteria approach involving the participation of community representatives.Analytic-hierarchical methods are support systems based on multiple criteria able to process a large number of different factors. Analytic-Hierarchy Process (AHP) is a specific instance of the general methods by means of which weights and quantities of an element, respect to the category taken into consideration, are assigned.The multi-criteria fuzzy criterion, applied in a study-case to three different alternatives (hypotheses) of reusing industrial ex-spaces abandoned in a municipality of the Milan province (Italy,) allows one to select the best alternatives in all cases in which many selection choices (spaces typology, required functions, benefits, timing) are possible and the optimal choice can be achieved by analyzing the different scopes of each criterion and sub-criterion as well as the relevant weights. Criteria are mutually compared in terms of the global objective while the alternatives are compared as function of the criterion. As outcome of this operative sequence the most sustainable solution, among the three different alternatives of the temporary re-use of the urban spaces addressed in the study-case, measures the relative priority of the alternatives existing at the lower level with respect to the achievement of the main objective and it is implemented according to the lowest economic cost.
FROM BIM TO POINTCLOUD: AUTOMATIC GENERATION OF LABELED INDOOR POINTCLOUD
Authors: Huang H. S. , Tang S. J. , Wang W. X. , Li X. M. , Guo R. Z.
Published: June 2022

Abstract. With the development of deep learning technology, a large number of indoor spatial applications, such as robotics and indoor navigation, have raised higher data requirements for indoor semantic model. However, creating deep learning classifiers requires a large number of labeled datasets, and the collection of such datasets requires a lot of manually labeling proces, which is labor-intensive and time-consuming. In this paper, we propose a method to automatically create 3D point clouds datasets with indoor semantic labels based on parametric BIM model. First, a automatic BIM generation method is proposed through simulating the structure of interior space Secondly, we use a viewpoint-guided labeled point cloud generation method to generate synthetic 3D point clouds with different labels, color information. Especially, noise are also simulated with a gaussian model. As shown in the experiments, the point cloud data with labels can be quickly obtained from existing BIM models, which will largely reduce the complexity of data labeling and improve efficiency. These simulated data can be used in the deep learning training process and improve the semantic segmentation accuracy.
Idealized simulations of Mei-yu rainfall in Taiwan under uniform southwesterly flow using a cloud-resolving model
Authors: Wang Chung-Chieh , Chuang Pi-Yu , Chen Shi-Ting , Lee Dong-In , Tsuboki Kazuhisa
Published: June 2022

Abstract. In this study, idealized cloud-resolving simulations are performed for horizontally uniform and steady southwesterly flow at fixed direction–speed
combinations to investigate rainfall characteristics and the role of the complex topography in Taiwan during the Mei-yu season without the
influence of a front or other disturbances. Eight directions (180 to 285∘, every 15∘) and eight speeds (5 to 22.5 m s−1,
every 2.5 m s−1) are considered, and near-surface relative humidity is also altered (from 55 %–100 %) in a subset of these
tests to further examine the effects of moisture content, yielding a total 109 experiments each having a integration length of 50 h. Three
rainfall regimes that correspond to different ranges of the wet Froude number (Frw) are identified from the idealized
simulations (with a grid size of 2 km). The low-Frw regime (Frw ≤ ∼ 0.3) is where the island circulation
from thermodynamic effects is the main driver of rainfall in local afternoon. The lower the wind speed and Frw are, the more widespread the rainfall is, as well as its
amount. On the other hand, the high-Frw regime (Frw ≥ ∼ 0.4) occurs when the flow of at least
12.5 m s−1 impinges on Taiwan terrain at a large angle (not parallel). This favors the flow-over scenario, and topographic rainfall
production becomes dominant through mechanical uplift of unstable air. In this scenario, the faster and wetter the flow is, the heavier the rainfall on
the windward slopes is, and maximum amounts typically occur at wind directions from 240–255∘. Between the two regimes above, a third, mixed
regime also exists. The idealized results are discussed for their applicability to the real atmosphere.
More than heavy rain turning into fast-flowing water – a landscape perspective on the 2021 Eifel floods
Authors: Dietze Michael , Bell Rainer , Ozturk Ugur , Cook Kristen L. , Andermann Christoff , Beer Alexander R. , Damm Bodo , Lucia Ana , Fauer Felix S. , Nissen Katrin M. , Sieg Tobias , Thieken Annegret H.
Published: June 2022

Abstract. Rapidly evolving floods are rare but powerful drivers of landscape reorganisation that have severe and long-lasting impacts on both the functions of a landscape’s subsystems and the affected society. The July 2021 flood that particularly hit several river catchments of the Eifel region in western Germany and Belgium was a drastic example. While media and scientists highlighted the meteorological and hydrological aspects of this flood, it was not just the rising water levels in the main valleys that posed a hazard, caused damage, and drove environmental reorganisation. Instead, the concurrent coupling of landscape elements and the wood, sediment, and debris carried by the fast-flowing water made this flood so devastating and difficult to predict. Because more intense floods are able to interact with more landscape components, they at times reveal rare non-linear feedbacks, which may be hidden during smaller events due to their high thresholds of initiation. Here, we briefly review the boundary conditions of the 14–15 July 2021 flood and discuss the emerging features that made this event different from previous floods. We identify hillslope processes, aspects of debris mobilisation, the legacy of sustained human land use, and emerging process connections and feedbacks as critical non-hydrological dimensions of the flood. With this landscape scale perspective, we develop requirements for improved future event anticipation, mitigation, and fundamental system understanding.
Reconstruction of Arctic sea ice thickness and its impact on sea ice forecasting in the melting season
Authors: Yang Lu , Fu Hongli , Luo Xiaofan , Zhang Shaoqing , Zhang Xuefeng
Published: June 2022

Abstract. Generally, the sea ice prediction skills can be improved via assimilating available observations of the sea ice concentration (SIC) and the sea ice thickness (SIT) into a numerical forecast model to update the initial fields of the model. However, due to the lack of SIT satellite observations in the melting season, only SIC fields in the forecast model can be directly updated, which will bring about the dynamical mismatch between SIC and SIT to affect the model prediction accuracy. In order to solve this problem, a statistically based bivariate regression model of SIT, named as BRMT, is tentatively established based on the grid reanalysis data of SIC and SIT, to reconstruct the daily Arctic sea ice thickness data. Both BRMT-constructed SIT and several popular reanalysis datasets are compared to each other and validated based on available SIT observations in situ. Results show that BRMT can effectively reproduce the spatial and temporal changes of ice thickness in the melting season, and BRMT-constructed SIT is more accurate in capturing the change trend of ice thickness over a period of time, also the reconstructed SIT of one-year ice and multi-year ice types in the central Arctic and E Greenland Sea are closer to the observations. Further, as SIT from BRMT and SIC from satellite remote sensing are jointly assimilated into the ice-sea coupled numerical model, the prediction accuracy of SIC and SIT in the Arctic melting season is significantly improved, especially the SIC in the marginal ice zone and SIT in the central Arctic.
Predicting power ramps from joint distributions of future wind speeds
Authors: Muschinski Thomas , Lang Moritz N. , Mayr Georg J. , Messner Jakob W. , Zeileis Achim , Simon Thorsten
Published: June 2022

Abstract. Power ramps are sudden changes in turbine power and must be accurately predicted to minimize costly imbalances in the electrical grid. Doing so requires reliable wind speed forecasts, which can be obtained from ensembles of physical numerical weather prediction (NWP) models through statistical postprocessing. Since the probability of a ramp event depends jointly on the wind speed distributions forecasted at multiple future times, these postprocessing methods must not only correct each individual forecast but also estimate the temporal dependencies among them. Typically though, crucial dependencies are adopted directly from the raw ensemble and the postprocessed forecast is limited to the tens of members computationally feasible for an NWP model. We extend statistical postprocessing to include temporal dependencies using novel multivariate Gaussian regression models that forecast 24-dimensional distributions of next-day hourly wind speeds at three offshore wind farms. The continuous joint distribution forecast is postprocessed from an NWP ensemble using flexible generalized additive models for the components of its mean vector μ and for parameters defining the forecast error covariance matrix Σ. Modeling these parameters on predictors which characterize the empirical joint distribution of the NWP ensemble allows forecasts for each hour and their temporal dependencies to be adjusted in one step. Wind speed ensembles of any size can be simulated from the postprocessed joint distribution and transformed into power for computing high-resolution ramp predictions that outperform state-of-the-art reference methods.
Gago Gómez, Laura, Léxico disponible árabe marroquí de Tánger-Arcila. Estudio y diccionario, en Libros de las islas 6, Cádiz - Córdoba, Editorial Uca - UcoPress, 2021, 96 pp. + 330 pp.
Authors: Moscoso García Francisco
Published: June 2022

Reseña de la obra de Gago Gómez, Laura, Léxico disponible árabe marroquí de Tánger-Arcila. Estudio y diccionario, en Libros de las islas 6, Cádiz - Córdoba, Editorial Uca - UcoPress, 2021, 96 pp. + 330 pp.
Necrológica Mahmud Sobh (Safad, 1936-Madrid, 2022)
Authors: Martos Quesada Juan
Published: June 2022

Obituario del poeta y arabista Mahmud Sobh (Safad, 1936-Madrid, 2022)
Length of hospital stay in laparoscopic transabdominal preperitoneal repair compared to open Mesh repair in patients with inguinal hernia: a randomized controlled trial
Authors: Abid Haider , Khan Salma
Published: June 2022

Introduction: One of the challenges faced by surgeons during repair of inguinal hernias is to adopt an approach with minimum complications of infection, chronic pain, and recurrence of hernia. Along with traditional techniques, modern methods of Laparoscopic Repair and Open Mesh Repair have been introduced and need further evaluation.

Objective: To compare the mean length of hospital stay in laparoscopic trans abdominal preperitoneal repair versus open Mesh repair in patients undergoing inguinal hernia repair with Mesh.

Methods:  A total of 334 patients of male gender with Inguinal hernias of any side and ASA score I and II were included in the study. History of Immunosuppression, concomitant other types of abdominal hernias, and recurrent hernias, were excluded. 167 patients were in Group A or laparoscopic trans abdominal preperitoneal repair group while 167 patients were in Group B or open Mesh repair. Data regarding length of hospital stay from both groups was recorded on especially designed proforma. Data were analyzed by SPSS 22 for descriptive and comparative statistics, keeping p≤0.05 as significant.

Results: Age range in this study was from 18 to 50 years. In group A, the mean age was 40.173 ± 6.19 years and mean duration of procedure was 37.658 ± 6.36 minutes; in group B, the mean age was 38.443 ± 5.10 years and mean duration of procedure was 61.748 ± 11.65 minutes. Majority of patients belonged to ASA-I in both groups. Moreover, majority of patients had right sided hernia in both groups. Mean length of hospital stay was 31.760 ± 11.25 hours in group A and 58.922 ± 11.98 hours in group B (p<0.001).

Conclusion: Laparoscopic approach for hernia repair had better outcome than open Mesh repair in terms of shorter duration of hospital stay.

Keywords: Inguinal hernia, Laparoscopic trans abdominal preperitoneal repair, Open Mesh repair, Length of hospital stay.