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View article: Flame Length and Geometry as Key Indicators for Real-Time Thermal Stress Monitoring in a Multi-Burner Combustion Chamber
Flame Length and Geometry as Key Indicators for Real-Time Thermal Stress Monitoring in a Multi-Burner Combustion Chamber Open
This study investigates the relationship between flame length measurements and the temperature of the refractory lining in combustion chambers with multiple burners interacting in terms of fluid dynamics. As this has not been done before, …
View article: From Temperature Observations to Targeted Action: Data-Driven Climate Adaptation Strategies in Hesse, Germany
From Temperature Observations to Targeted Action: Data-Driven Climate Adaptation Strategies in Hesse, Germany Open
Rising urban temperatures and the push for densification have intensified the need for robust climate adaptation measures. In partnership with the federal state of Hesse, we developed a participative, data-driven framework to identify and …
View article: High-Resolution Segmentation of Photovoltaic Systems: Leveraging Geoinformation and Deep Learning for Enhanced Renewable Energy Assessment
High-Resolution Segmentation of Photovoltaic Systems: Leveraging Geoinformation and Deep Learning for Enhanced Renewable Energy Assessment Open
Shifting to renewable energy sources is crucial for reducing greenhouse gas emissions and mitigating the effects of climate change. Photovoltaic (PV) systems are an essential technology for generating renewable energy. These systems show c…
View article: From temperature observations to mitigation measures: Data-driven approaches to multi-scale climate adaptation in Hesse, Germany
From temperature observations to mitigation measures: Data-driven approaches to multi-scale climate adaptation in Hesse, Germany Open
As urban temperatures rise and the demand for urban densification increases, climate adaptation has become a significant concern for policymakers. However, we face a challenge in today's data-rich environment: How can we effectively manage…
View article: Machine Learning Approaches for Vehicle Counting on Bridges Based on Global Ground-Based Radar Data
Machine Learning Approaches for Vehicle Counting on Bridges Based on Global Ground-Based Radar Data Open
This study introduces a novel data-driven approach for classifying and estimating the number of vehicles crossing a bridge solely on non-invasive ground-based radar time series data (GBR data). GBR is used to measure the bridge displacemen…
View article: Road Accessibility during Natural Hazards Based on Volunteered Geographic Information Data and Network Analysis
Road Accessibility during Natural Hazards Based on Volunteered Geographic Information Data and Network Analysis Open
Natural hazards can present a significant risk to road infrastructure. This infrastructure is a fundamental component of the transportation infrastructure, with significant importance. During emergencies, society heavily relies on the func…
View article: Machine Learning and Signal Processing for Bridge Traffic Classification with Radar Displacement Time-Series Data
Machine Learning and Signal Processing for Bridge Traffic Classification with Radar Displacement Time-Series Data Open
This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but…
View article: Utilizing Volunteered Geographic Information for Real-Time Analysis of Fire Hazards: Investigating the Potential of Twitter Data in Assessing the Impacted Areas
Utilizing Volunteered Geographic Information for Real-Time Analysis of Fire Hazards: Investigating the Potential of Twitter Data in Assessing the Impacted Areas Open
Natural hazards such as wildfires have proven to be more frequent in recent years, and to minimize losses and activate emergency response, it is necessary to estimate their impact quickly and consequently identify the most affected areas. …
View article: EVALUATION OF SELF-SUPERVISED LEARNING APPROACHES FOR SEMANTIC SEGMENTATION OF INDUSTRIAL BURNER FLAMES
EVALUATION OF SELF-SUPERVISED LEARNING APPROACHES FOR SEMANTIC SEGMENTATION OF INDUSTRIAL BURNER FLAMES Open
In recent years, self-supervised learning has made tremendous progress in closing the gap to supervised learning due to the rapid development of more sophisticated approaches like SimCLR, MoCo, and SwAV. However, these achievements are pri…
View article: Determining and Investigating the Variability of Bridges’ Natural Frequencies with Ground-Based Radar
Determining and Investigating the Variability of Bridges’ Natural Frequencies with Ground-Based Radar Open
Assessing the condition of bridge infrastructure requires estimating damage-sensitive features from reliable sensor data. This study proposes to estimate natural frequencies from displacement measurements of a ground-based interferometric …
View article: Glacier Monitoring Based on Multi-Spectral and Multi-Temporal Satellite Data: A Case Study for Classification with Respect to Different Snow and Ice Types
Glacier Monitoring Based on Multi-Spectral and Multi-Temporal Satellite Data: A Case Study for Classification with Respect to Different Snow and Ice Types Open
Remote sensing techniques are frequently applied for the surveying of remote areas, where the use of conventional surveying techniques remains difficult and impracticable. In this paper, we focus on one of the remote glacier areas, namely …
View article: Supervised Machine Learning Approaches on Multispectral Remote Sensing Data for a Combined Detection of Fire and Burned Area
Supervised Machine Learning Approaches on Multispectral Remote Sensing Data for a Combined Detection of Fire and Burned Area Open
Bushfires pose a severe risk, among others, to humans, wildlife, and infrastructures. Rapid detection of fires is crucial for fire-extinguishing activities and rescue missions. Besides, mapping burned areas also supports evacuation and acc…
View article: Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases
Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases Open
OpenStreetMap (OSM), with its global coverage and Open Database License, has recently gained popularity. Its quality is adequate for many applications, but since it is crowd-sourced, errors remain an issue. Errors in associated tags of the…
View article: CONVOLUTIONAL NEURAL NETWORKS FOR DETECTING BRIDGE CROSSING EVENTS WITH GROUND-BASED INTERFEROMETRIC RADAR DATA
CONVOLUTIONAL NEURAL NETWORKS FOR DETECTING BRIDGE CROSSING EVENTS WITH GROUND-BASED INTERFEROMETRIC RADAR DATA Open
This study focuses on detecting vehicle crossings (events) with ground-based interferometric radar (GBR) time series data recorded at bridges in the course of critical infrastructure monitoring. To address the challenging event detection a…
View article: Advanced Methods for Kiln-Shell Monitoring to Optimize the Waelz Process for Zinc Recycling
Advanced Methods for Kiln-Shell Monitoring to Optimize the Waelz Process for Zinc Recycling Open
The recycling of zinc in the Waelz process is an important part of the efficient use of resources in the steel processing cycle. The pyro-metallurgical processing of zinc-containing wastes takes place in a Waelz rotary kiln. Various measur…
View article: Advancing Ground-Based Radar Processing for Bridge Infrastructure Monitoring
Advancing Ground-Based Radar Processing for Bridge Infrastructure Monitoring Open
In this study, we further develop the processing of ground-based interferometric radar measurements for the application of bridge monitoring. Applying ground-based radar in such complex setups or long measurement durations requires advance…
View article: Deep Learning with WASI Simulation Data for Estimating Chlorophyll a Concentration of Inland Water Bodies
Deep Learning with WASI Simulation Data for Estimating Chlorophyll a Concentration of Inland Water Bodies Open
Information about the chlorophyll a concentration of inland water bodies is essential for water monitoring. This study focuses on estimating chlorophyll a with remote sensing data, and machine learning (ML) approaches on the real-world Spe…
View article: Integrated water management solutions in the Lurín Catchment, Lima, Peru : supporting United Nations' Sustainable Development Goal 6 : final report of the joint project TRUST
Integrated water management solutions in the Lurín Catchment, Lima, Peru : supporting United Nations' Sustainable Development Goal 6 : final report of the joint project TRUST Open
With the 2030 Agenda for Sustainable Development, the United Nations have established a catalog of 17 Sustainable Development Goals (SDGs) to achieve a better and more sustainable future for all by 2030. One important aspect, formulated as…
View article: Deep Learning for Land Cover Change Detection
Deep Learning for Land Cover Change Detection Open
Land cover and its change are crucial for many environmental applications. This study focuses on the land cover classification and change detection with multitemporal and multispectral Sentinel-2 satellite data. To address the challenging …
View article: oliversefrin/lstm-sentinel2-landcover: Code for Deep Learning for Land Cover Change Detection 1.0.1
oliversefrin/lstm-sentinel2-landcover: Code for Deep Learning for Land Cover Change Detection 1.0.1 Open
Add code citation with DOI
View article: Machine Learning Framework for the Estimation of Average Speed in Rural Road Networks with OpenStreetMap Data
Machine Learning Framework for the Estimation of Average Speed in Rural Road Networks with OpenStreetMap Data Open
Average speed information, which is essential for routing applications, is often missing in the freely available OpenStreetMap (OSM) road network. In this contribution, we propose an estimation framework, including different machine learni…
View article: Introducing a Non-Invasive Monitoring Approach for Bridge Infrastructure with Ground-Based Interferometric Radar
Introducing a Non-Invasive Monitoring Approach for Bridge Infrastructure with Ground-Based Interferometric Radar Open
In this paper, we introduce a non-invasive approach for monitoring bridge infrastructure with ground-based interferometric radar. This approach is called the mirror mode, since it utilises the flat surface of the bridge underside as a mirr…
View article: Machine Learning Framework for Speed Estimation of Roads With OpenStreetMap Data
Machine Learning Framework for Speed Estimation of Roads With OpenStreetMap Data Open
Machine learning framework and exemplary dataset for an estimation of average speed with OpenStreetMap road network data.
View article: SpecWa: Spectral remote sensing data and chlorophyll a values of inland waters
SpecWa: Spectral remote sensing data and chlorophyll a values of inland waters Open
This dataset contains data of measurements at several inland water bodies in the region around Karlsruhe, Germany, including spectral data and mainly chlorophyll a values. The measurements are motivated by the idea to link remote sensing d…
View article: DETECTION AND CLASSIFICATION OF BRIDGE CROSSING EVENTS WITH GROUND-BASED INTERFEROMETRIC RADAR DATA AND MACHINE LEARNING APPROACHES
DETECTION AND CLASSIFICATION OF BRIDGE CROSSING EVENTS WITH GROUND-BASED INTERFEROMETRIC RADAR DATA AND MACHINE LEARNING APPROACHES Open
In this paper, we investigate the potential of detecting and classifying vehicle crossings (events) on bridges with ground-based interferometric radar (GBR) data and machine learning (ML) approaches. The GBR data and image data recorded by…
View article: felixriese/sentinel2-pipeline-caos: CAOS Sentinel-2 Pipeline in Python
felixriese/sentinel2-pipeline-caos: CAOS Sentinel-2 Pipeline in Python Open
Initial release
View article: HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques
HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques Open
This dataset comprises data of an interdisciplinary pedon-scale irrigation experiment at a grassland site near Karlsruhe, Germany, including pedo-hydrological, geophysical, and remote sensing data. The objective of this experiment is to mo…
View article: Multi-Parameter Estimation of Average Speed in Road Networks Using Fuzzy Control
Multi-Parameter Estimation of Average Speed in Road Networks Using Fuzzy Control Open
Average speed is crucial for calculating link travel time to find the fastest path in a road network. However, readily available data sources like OpenStreetMap (OSM) often lack information about the average speed of a road. However, OSM c…
View article: The contribution of tsunami evacuation analysis to evacuation planning in Chile: Applying a multi-perspective research design
The contribution of tsunami evacuation analysis to evacuation planning in Chile: Applying a multi-perspective research design Open
Research on evacuation behavior in natural disasters provides a valuable contribution in the development of effective short- and long-term strategies in disaster risk management (DRM). Many studies address evacuation simulation utilizing m…