Article
Computer Science, Information Systems
Matthias Weigand, Simon Worbis, Marta Sapena, Hannes Taubenboeck
Summary: Over the past decade, the number of refugees and internally displaced people has doubled, leading to the construction of more refugee camps with diverse structures. However, there is currently no standardized inventory for these camp structures. In this study, a global database of settlement structures from 285 camps was created using satellite imagery and visual image interpretation. The findings highlight the importance of considering morphological differences in image analyses and provide a foundation for future humanitarian applications.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2023)
Article
Green & Sustainable Science & Technology
J. D. Nixon, K. Bhargava, A. Halford, E. Gaura
Summary: The paper presents evidence from the performance assessment of two solar energy interventions in refugee camps in Rwanda. It found low energy consumption levels and consumption gaps in the co-conceived interventions. To improve sustainability, design principles for future energy interventions were drawn.
ENERGY FOR SUSTAINABLE DEVELOPMENT
(2021)
Article
Computer Science, Information Systems
Zhouming Ma, Jusheng Mi, Yiting Lin, Jinjin Li
Summary: Variable precision rough set (VPRS) has been widely studied as an essential way of knowledge representation and acquisition in uncertainty theory. This paper investigates the corresponding CVPRS model based on a covering-based rough set model, and systematically studies its algebraic structures and properties. An attribute reduction approach is proposed for a covering-based decision information system using the CVPRS model, and the performances of different boundary operators and related indices in these reduction methods are compared. Necessity rules and possibility rules extraction methods corresponding to decision classes are established, and their validity and security are theoretically verified.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Meng Hu, Eric C. C. Tsang, Yanting Guo, Degang Chen, Weihua Xu
Summary: This study introduces a novel attribute reduction method based on weighted neighborhood relations, which fully mines the correlation between attributes and decisions, assigning higher weights to attributes with higher correlation, achieving good performance results.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Angelo Gaeta, Vincenzo Loia, Luigi Lomasto, Francesco Orciuoli
Summary: The paper presents and evaluates an approach based on Rough Set Theory to analyze Information Disorder phenomena. Rough Set Theory concepts and constructs are used to model and reason on social media user groups and sets of information. Information theoretic measures are used to evaluate Complexity and Milestone concepts in Information Disorder. The adoption of Rough Set Theory constructs and operators in this new field allows for modeling and reasoning on key elements of Information Disorder and interpreting its effects.
APPLIED INTELLIGENCE
(2023)
Article
Public, Environmental & Occupational Health
Manal Salem Omar Baaees, Jeremias D. Naiene, Ali Ahmed Al-Waleedi, Nasreen Salem Bin-Azoon, Muhammad Fawad Khan, Nuha Mahmoud, Altaf Musani
Summary: In Yemen, community-based surveillance was effective in detecting suspected outbreaks in IDP camps. However, in the early stages of the COVID-19 pandemic, the system failed to produce expected results in general communities in urban settings where little was known about the disease. Feasibility and acceptability studies should be conducted before expanding CBS in urban communities, while also expanding the project in IDP camps with dedicated reporting sites for COVID-19 and other outbreaks.
CONFLICT AND HEALTH
(2021)
Article
Engineering, Electrical & Electronic
Shihang Li, Zhiheng Zhang, Peng Liu, Jianfeng Cui
Summary: This paper proposes a new distributed lattice Kalman filter (DLKF) to deal with the high-dynamic and communication coupling in multiple micro-target tracking and positioning. The DLKF uses Cranley-Patterson shift and Korobov lattice rule for prediction, and weighted average consistency for update fusion. Simulation results show that DLKF achieves estimation accuracy with significantly fewer sampling points compared to other quasi-Monte Carlo (QMC) filters, and has significantly lower computational complexity for application to multiple micro-targets.
Article
Computer Science, Information Systems
Yangxue Li, Enrique Herrera-Viedma, Gang Kou, Juan Antonio Morente-Molinera
Summary: This paper proposes a Z-number-valued rule-based decision tree (ZRDT) and provides the learning algorithm. Compared with other classical decision trees, ZRDT performs better in terms of classification accuracy and decision tree size. ZRDT uses information gain to select features in each rule instead of fuzzy confidence, and generates a second fuzzy number with negative samples to improve the model's fit to the training data. Based on statistical tests, ZRDT achieves the highest classification performance with the smallest size for the produced decision tree.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Theory & Methods
Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski
Summary: This paper discusses the importance of granular representations of crisp and fuzzy sets in rule induction algorithms based on rough set theory. It demonstrates that the OWA-based fuzzy rough set model, which has been successfully applied in various machine learning tasks, allows for a granular representation. The practical implications of this result for rule induction from fuzzy rough approximations are highlighted.
FUZZY SETS AND SYSTEMS
(2022)
Article
Environmental Sciences
Yaqin Xie, Tianyuan Gu, Di Zheng, Yu Zhang, Hai Huan
Summary: With the advancement of positioning technology, the application and demand for location information have gained attention from various industries. In this paper, a novel 3D low-cost, high-precision target perception algorithm is introduced using an RFID mobile reader and double tags. The algorithm utilizes Received Signal Strength (RSS) and phase information measurements to estimate the target's position along the shelf. Simulations demonstrate the exceptional accuracy of the proposed method, achieving centimeter-level sensing accuracy.
Article
Mathematics, Applied
Ahmad N. Al-Kenani, Rukhshanda Anjum, Sahidul Islam
Summary: This article discusses the theory of intuitionistic fuzzy numbers and how to use priority degrees to establish operators in multicriteria decision-making problems. The study highlights the superiority of the provided work over other methods and thoroughly investigates the impact of priority degrees on the results.
JOURNAL OF FUNCTION SPACES
(2022)
Article
Computer Science, Artificial Intelligence
Xiaoping Zhang, Jinjin Li, Weikang Li
Summary: This paper discusses the problem of knowledge acquisition in granular computing theory and proposes a rule-based approach to address the measurement problem in information systems.
APPLIED INTELLIGENCE
(2022)
Article
Engineering, Environmental
Syed Imran Ali, Syed Saad Ali, Jean-Francois Fesselet
Summary: The study found that generating site-specific and evidence-based chlorination targets through modeling can improve household water safety, especially in hotter climates or poorer WASH conditions. However, in environments with smaller chlorine decay, the upper range of the current chlorination guideline still provides sufficient chlorine residual for ensuring household water safety.
Article
Computer Science, Artificial Intelligence
Zi-Xin Zhang, Liang Wang, Ying-Ming Wang, Luis Martinez
Summary: This study proposes a novel alpha level sets based fuzzy DEMATEL method to handle fuzzy information and considers experts' hesitation under uncertain and fuzzy environment. The proposed method improves the existing fuzzy DEMATEL studies and enriches the theoretical studies of fuzzy DEMATEL.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Long-Hao Yang, Jun Liu, Fei-Fei Ye, Ying-Ming Wang, Chris Nugent, Hui Wang, Luis Martinez
Summary: This study aims to design a novel rule-based system called Cumulative Belief Rule-Based System (CBRBS). By establishing efficient rule-base modeling and inference procedures, CBRBS achieves a balance of explainability, high-efficiency, and accuracy, overcoming the limitations of classical rule-based systems. Extensive experiments illustrate the features and advantages of CBRBS over other systems.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Environmental Sciences
Lorena Abad, Daniel Holbling, Raphael Spiekermann, Gunther Prasicek, Zahra Dabiri, Anne-Laure Argentin
Summary: Landslide-dammed lakes pose risks to communities and infrastructure, and it is essential to detect and monitor them for disaster management. This study utilized satellite remote sensing imagery and the computing capabilities of Google Earth Engine to automatically map and monitor landslide-dammed lakes caused by the 2016 Kaikoura earthquake.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Geosciences, Multidisciplinary
Lorena Abad, Daniel Holbling, Florian Albrecht, Helen Cristina Dias, Zahra Dabiri, Gerald Reischenbock, Dajana Tesic
Summary: The alpine infrastructure of trails and huts is crucial for summer tourism, but is prone to damage from mass movements caused by extreme rainfall events. This study utilized susceptibility mapping techniques to assess the mass movement susceptibility of alpine hut and trail infrastructure in Austria. Two statistical methods, logistic regression and informative value, were employed and compared, with both methods showing high prediction rates. Field validation demonstrated the reliability of the informative value method. Alpine associations recognize the potential of susceptibility mapping for strategic management of alpine infrastructure.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Environmental Sciences
Sabine Hennig, Lorena Abad, Daniel Holbling, Dirk Tiede
Summary: Contributory citizen science projects face challenges in data quantity and quality. To address this, the projects need to focus on citizen needs and preferences, provide instructions and support, and design specific elements to attract and engage citizens.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Jirathana Dittrich, Daniel Hoelbling, Dirk Tiede, Thornorsteinn Saemundsson
Summary: In this study, two-dimensional deformation estimates derived from Persistent Scatterer Interferometric (PSI) analysis of Synthetic Aperture Radar (SAR) data were examined for their improved characterization of spatially and temporally varying deformation processes of Earth's surface. By analyzing Sentinel-1 SAR image data from 2015 to 2018, the study obtained 2D vertical and horizontal surface deformation velocities, which showed good agreement with independent GPS measurements.
Article
Computer Science, Information Systems
Martin Sudmanns, Hannah Augustin, Brian Killough, Gregory Giuliani, Dirk Tiede, Alex Leith, Fang Yuan, Adam Lewis
Summary: This article explores the technology landscape for managing big Earth observation data and the importance and challenges of local EO data cubes. By analyzing examples of global and local EO data cubes, it is found that local EO data cubes can benefit various stakeholders but require technical developments such as establishing global and cloud-native EO data streaming mechanisms. The article argues that blurring the dichotomy between global and local aligns with the vision of the Digital Earth.
Article
Geography, Physical
Melanie Stammler, Thomas Stevens, Daniel Holbling
Summary: The current climate change in the Arctic has unprecedented impacts on the environment and landscape. In Arctic Sweden, aeolian sand dunes are affected by climate changes, and their type, location, and orientation can be used to understand past wind patterns and landscape destabilization. Geographic object-based image analysis is a suitable method to map these dunes. The study reveals that glaciofluvial and fluvial disturbances played a significant role in the formation of dune systems in Arctic Sweden.
PERMAFROST AND PERIGLACIAL PROCESSES
(2023)
Article
Computer Science, Information Systems
Andrea Baraldi, Luca D. Sapia, Dirk Tiede, Martin Sudmanns, Hannah Augustin, Stefan Lang
Summary: This paper focuses on the convergence between Earth observation Big Data and Artificial General Intelligence. It compares existing EO optical sensory image-derived Level 2/Analysis Ready Data (ARD) products and processes and proposes new requirements for harmonization and standardization. The paper presents original contributions in semantic-enriched ARD co-product pair requirements, ARD process requirements, ARD processing system design, and computer vision subsystem design.
Article
Geography, Physical
Wufan Zhao, Hu Ding, Jiaming Na, Mengmeng Li, Dirk Tiede
Summary: This study proposes a gradient-based self-supervised learning network to extract geometric information from non-labeled images, and uses novel local implicit constraint layers to refine high-resolution features in height estimation. Experimental evaluation shows that the proposed method outperforms other baseline networks in height map estimation.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2023)
Article
Environmental Sciences
Sean Jarrett, Daniel Hoelbling
Summary: This study proposes an evaluation method using C-band Sentinel-1 synthetic aperture radar (SAR) data to provide evidence of flood characteristic changes after the restoration of a floodplain. The evaluation framework replicates previous change detection research approaches and analyses the effects of Natural Flood Management (NFM) measures on flood risk mitigation. The study verifies the change detection methodology using flood records from drone footage and achieves an overall accuracy of 75% using the Change Detection and Thresholding (CDAT) technique. The use of SAR data maps the actual flood extent and evaluates the positive and negative outcomes of post-restoration floods.
Article
Environmental Sciences
Helen Cristina Dias, Daniel Holbling, Carlos Henrique Grohmann
Summary: The aim of this study is to develop a semi-automatic method for recognizing landslides and evaluate its applicability in different areas of Brazil. The results show that the method is suitable for recognizing this type of hazard in Brazil, but there are still some challenges.
Proceedings Paper
Environmental Sciences
Khishma Modoosoodun Nicolas, Lucas Drumetz, Sebastien Lefevre, Dirk Tiede, Touria Bajjouk, Jean-Christophe Burnel
Summary: Bathymetry studies are important for monitoring coastal topographies, updating navigation charts, and understanding the marine environment dynamics. This study explores the possibility of using deep learning with multispectral satellite data to predict bathymetry around Europa Island. The model shows good accuracy in predicting depth values and has the potential to be incorporated into electronic navigational charts.
EUROPEAN SPATIAL DATA FOR COASTAL AND MARINE REMOTE SENSING, EUCOMARE 2022
(2023)
Correction
Environmental Sciences
Lorena Abad, Daniel Hoelbling, Raphael Spiekermann, Guenther Prasicek, Zahra Dabiri, Anne-Laure Argentin
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Proceedings Paper
Geography, Physical
Barbara Riedler, Stefan Lang
Summary: More than half of the world's population lives in urban areas, with over 1 billion people lacking basic services and infrastructure. Spatially targeted, data-driven policies are crucial for sustainable urban planning to improve these situations and increase resilience. Earth observation can support the achievement of the Sustainable Development Goals, particularly SDG 11. The integration of heterogeneous datasets for humanitarian response requires adequate data assimilation strategies and a good understanding of data quality.
XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION IV
(2022)
Proceedings Paper
Geography, Physical
R. Lemmens, S. Lang, F. Albrecht, E. Augustijn, C. Granell, M. Olijslagers, C. Pathe, C. Dubois, M. Stelmaszczuk-Gorska
Summary: The EO4GEO Body of Knowledge (BoK) provides a conceptual framework for the Earth Observation and Geo-Information domain. This paper presents the integration of concepts related to Artificial Intelligence (AI) into the BoK, along with specific examples and training resources. AI plays a significant role in the EO/GI field.
XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION IV
(2022)
