scholarly journals Combining Remote Sensing with Webdata and Machine Learning to Support Humanitarian Relief Work

2021 ◽  
Author(s):  
Jens Kersten ◽  
Malin Kopitzsch ◽  
Jan Bongard ◽  
Friederike Klan
Keyword(s):  
Social Media ◽  
Information Overload ◽  
Field Work ◽  
Relevant Information ◽  
Extraction Methods ◽  
Legal Aspects ◽  
Crisis Response ◽  
In Situ Data ◽  
Information Gaps

<p>Gathering, analyzing and disseminating up-to-date information related to incidents and disasters is key to disaster management and relief. Satellite imagery, geo-information, and in-situ data are the mainly used information sources to support decision making. However, limitations in data timeliness as well as in spatial and temporal resolution lead to systematic information gaps in current well-established satellite-based workflows. Citizen observations spread through social media channels, like Twitter, as well as freely available webdata, like WikiData or the GDELT database, are promising complementary sources of relevant information that might be utilized to fill these information gaps and to support in-situ data acquisition. Practical examples for this are impact assessments based on social media eyewitness reports, and the utilization of this information for the early tasking of satellite or drone-based image acquisitions.</p><p>The great potential, for instance of social media data analysis in crisis response, was investigated and demonstrated in various related research works. However, the barriers of utilizing webdata and appropriate information extraction methods for decision support in real-world scenarios are still high, for instance due to information overload, varying surrounding conditions, or issues related to limited field work infrastructures, trustworthiness, and legal aspects.</p><p>Within the current DLR research project "Data4Human", demand driven data services for humanitarian aid are developed. Among others, one project goal is to investigate the practical benefit of augmenting existing workflows of the involved partners (German Red Cross, World Food Programme, and Humanitarian Open Street Map) with social media (Twitter) and real-time global event database (GDELT) data. In this contribution, the general concepts, ideas and corresponding methods for webdata analysis are presented. State-of-the-art deep learning models are utilized to filter, classify and cluster the data to automatically identify potentially crisis-related data, to assess impacts, and to summarize and characterize the course of events, respectively. We present first practical findings and analysis results for the 2019 cyclones Idai and Kenneth.</p>

Supporting Policy-Makers with Social Media Analysis Tools to Get Aware of Citizens' Opinions

2014 ◽  
pp. 121-156
Author(s):  
Timo Wandhöfer ◽  
Steve Taylor ◽  
Miriam Fernandez ◽  
Beccy Allen ◽  
Harith Alani ◽  
...  
Keyword(s):  
Social Media ◽  
Information Overload ◽  
User Behavior ◽  
Relevant Information ◽  
Media Analysis ◽  
Control Group ◽  
Data Sets ◽  
Online Forums ◽  
Policy Makers ◽  
Facebook Pages

The role of social media in politics has increased considerably. A particular challenge is how to deal with the deluge of information generated on social media: it is impractical to read lots of messages with the hope of finding useful information. In this chapter, the authors suggest an alternative approach: utilizing analysis software to extract the most relevant information of the discussions taking place. This chapter discusses the WeGov Toolbox as one concept for policy-makers to deal with the information overload on Social Media, and how it may be applied. Two complementary, in depth case studies were carried out to validate the usefulness of the analysis results of the WeGov Toolbox components' within its target audience's everyday life. Firstly, the authors used the “HeadsUp” forum, operated by the Hansard Society. Here, they were able to compare the key themes and opinions extracted automatically by the Toolbox to a control group of manually pre-analyzed data sets. In parallel, results of analyses based on four weeks' intensive monitoring on policy area-specific Facebook pages selected by German policy makers, as well as topics on Twitter globally and local, were assessed by taking into account their existing experience with content discussed and user behavior in their respective public spheres. The cases show that there are interesting applications for policy-makers to use the Toolbox in combination with online forums (blogs) and social networks, if behavioral user patterns will be considered and the framework will be refined.

scholarly journals Crisis Coordination and the Role of Social Media in Response to COVID-19 in Wuhan, China

2020 ◽  
Vol 50 (6-7) ◽  
pp. 698-705
Author(s):  
Yiran Li ◽  
Yanto Chandra ◽  
Naim Kapucu
Keyword(s):  
Social Media ◽  
Nonprofit Organizations ◽  
Local Governments ◽  
Information Overload ◽  
Central Government ◽  
Crisis Response ◽  
Chinese Government ◽  
Media Platform ◽  
The Government ◽  
Use Of Social Media

The commentary addresses the government’s role in mitigating information asymmetry problems during pandemic crisis response. We use the outbreak of COVID-19 in Wuhan, China, as a case to show the use of social media as a key mechanism in shaping the actions of the central government in its coordination with the local governments during the pandemic response. The Chinese government effectively collaborated with a social media platform to not only create a dedicated channel to allow citizens to post information about the pandemic to accelerate the speed of relief but also mobilize citizens and nonprofit organizations to support government response and recovery efforts. This suggests that social media can provide a venue for the government to not only tackle the information overload but also mitigate the friction among levels of governments.

scholarly journals PRODUCTION OF ISO-INTENSITY MAP FOR THE ELAZIG EARTHQUAKE (JAN 24, 2020) USING CITIZEN COLLECTED GEODATA

2020 ◽  
Vol XLIII-B5-2020 ◽  
pp. 51-56
Author(s):  
I. Yalcin ◽  
S. Kocaman ◽  
C. Gokceoglu
Keyword(s):  
Mobile Devices ◽  
Mobile Application ◽  
Pilot Project ◽  
Field Work ◽  
Disaster Mitigation ◽  
Related Information ◽  
In Situ Data ◽  
Scientific Disciplines ◽  
Intensity Map

Abstract. Earthquake, depending on its intensity and location of epicentre, is one of the destructive hazards. Disaster mitigation after a severe earthquake are important to minimize its detrimental effects. Nowadays, several scientific disciplines, such as biodiversity, ecology, geosciences, natural hazards etc., utilize the Citizen Science (CitSci) approaches for various purposes, since the relevant attributes can easily be provided by non-experts with mobile devices. With the CitSci method, disaster related information can be identified and provided rapidly by locals during or after a disaster. Timely, in-situ data after an earthquake can also be collected with CitSci approaches via mobile devices, which can be even more important for all countries. In addition, scientific studies on earthquakes can be enriched and accelerated by using the information provided by volunteers. By collecting reliable data with the CitSci method, the disaster mitigation efforts can be improved, and losses may be decreased. This study aims at developing a CitSci pilot project by using the data collected by volunteers (citizens) to reduce the need for field work in creating earthquake iso-intensity maps and produce them promptly. The present study was based on the 6.8 Mw Elazig earthquake occurred at 20:55 UTC on January 24th, 2020. Through the mobile application “I felt the quake”, the observations of citizens regarding the earthquake were collected. The intensities were revised from the Modified Mercalli Intensity Scale. With the help of data, an iso-intensity map was created and compared to the map produced by The Disaster and Emergency Management Presidency (AFAD), Turkey.

Comparison of in situ DGT measurement with ex situ methods for predicting cadmium bioavailability in soils with combined pollution to biotas

2017 ◽  
Vol 75 (9) ◽  
pp. 2171-2178 ◽  
Author(s):  
Peifang Wang ◽  
Cui Liu ◽  
Yu Yao ◽  
Chao Wang ◽  
Teng Wang ◽  
...  
Keyword(s):  
Soil Solution ◽  
Contaminated Soils ◽  
Pearson Correlation ◽  
Solution Concentration ◽  
Extraction Methods ◽  
Single Step ◽  
Ex Situ ◽  
In Situ Data ◽  
Positive Correlations

To assess the capabilities of the different techniques in predicting Cadmium (Cd) bioavailability in Cd-contaminated soils with the addition of Zn, one in situ technique (diffusive gradients in thin films; DGT) was compared with soil solution concentration and four widely used single-step extraction methods (acetic acid, EDTA, sodium acetate and CaCl2). Wheat and maize were selected as tested species. The results demonstrated that single Cd-polluted soils inhibited the growth of wheat and maize significantly compared with control plants; the shoot and root biomasses of the plants both dropped significantly (P < 0.05). The addition of Zn exhibited a strong antagonism to the physiological toxicity induced by Cd. The Pearson correlation coefficient presented positive correlations (P < 0.01, R > 0.9) between Cd concentrations in two plants and Cd bioavailability indicated by each method in soils. Consequently, the results indicated that the DGT technique could be regarded as a good predictor of Cd bioavailability to plants, comparable to soil solution concentration and the four single-step extraction methods. Because the DGT technique can offer in situ data, it is expected to be widely used in more areas.

STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

2017 ◽  
Author(s):  
Alexander Myasoedov ◽  
Alexander Myasoedov ◽  
Sergey Azarov ◽  
Sergey Azarov ◽  
Ekaterina Balashova ◽  
...  
Keyword(s):  
Satellite Data ◽  
Wind Wave ◽  
Arctic Region ◽  
Web Gis ◽  
The Arctic ◽  
Flexible Tool ◽  
In Situ Data ◽  
Current State ◽  
Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

Measuring Relevant Information in Health Social Network Conversations and Clinical Diagnosis Cases (Preprint)

2018 ◽  
Author(s):  
Albert Moreira ◽  
Raul Alonso-Calvo ◽  
Alberto Muñoz ◽  
Jose Crespo
Keyword(s):  
Social Media ◽  
Social Network ◽  
Relevant Information ◽  
Online Discussions ◽  
Biomedical Knowledge ◽  
Expert Opinions ◽  
Health Related ◽  
Health Social Network ◽  
Discussion System ◽  
Clinical Cases

BACKGROUND Internet and Social media is an enormous source of information. Health Social Networks and online collaborative environments enable users to create shared content that afterwards can be discussed. While social media discussions for health related matters constitute a potential source of knowledge, characterizing the relevance of participations from different users is a challenging task. OBJECTIVE The aim of this paper is to present a methodology designed for quantifying relevant information provided by different participants in clinical online discussions. METHODS A set of key indicators for different aspects of clinical conversations and specific clinical contributions within a discussion have been defined. These indicators make use of biomedical knowledge extraction based on standard terminologies and ontologies. These indicators allow measuring the relevance of information of each participant of the clinical conversation. RESULTS Proposed indicators have been applied to two discussions extracted from PatientsLikeMe, as well as to two real clinical cases from the Sanar collaborative discussion system. Results obtained from indicators in the tested cases have been compared with clinical expert opinions to check indicators validity. CONCLUSIONS The methodology has been successfully used for describing participant interactions in real clinical cases belonging to a collaborative clinical case discussion tool and from a conversation from a Health Social Network.

scholarly journals COVID-19 information overload and generation Z's social media discontinuance intention during the pandemic lockdown

2021 ◽  
Vol 166 ◽  
pp. 120600
Author(s):  
Hongfei Liu ◽  
Wentong Liu ◽  
Vignesh Yoganathan ◽  
Victoria-Sophie Osburg
Keyword(s):  
Social Media ◽  
Information Overload

scholarly journals Critical Dynamics of Defects and Mechanisms of Damage-Failure Transitions in Fatigue

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2554
Author(s):  
Oleg Naimark ◽  
Vladimir Oborin ◽  
Mikhail Bannikov ◽  
Dmitry Ledon
Keyword(s):  
Fatigue Damage ◽  
Kinetic Equations ◽  
Experimental Methodology ◽  
Preliminary Deformation ◽  
Scaling Properties ◽  
In Situ Data ◽  
Number Of Cycles ◽  
Fish Eye ◽  
Very High

An experimental methodology was developed for estimating a very high cycle fatigue (VHCF) life of the aluminum alloy AMG-6 subjected to preliminary deformation. The analysis of fatigue damage staging is based on the measurement of elastic modulus decrement according to “in situ” data of nonlinear dynamics of free-end specimen vibrations at the VHCF test. The correlation of fatigue damage staging and fracture surface morphology was studied to establish the scaling properties and kinetic equations for damage localization, “fish-eye” nucleation, and transition to the Paris crack kinetics. These equations, based on empirical parameters related to the structure of the material, allows us to estimate the number of cycles for the nucleation and advance of fatigue crack.

scholarly journals Measuring and inferring the ice thickness distribution of four glaciers in the Tien Shan, Kyrgyzstan

2020 ◽  
pp. 1-18
Author(s):  
Lander Van Tricht ◽  
Philippe Huybrechts ◽  
Jonas Van Breedam ◽  
Johannes J. Fürst ◽  
Oleg Rybak ◽  
...  
Keyword(s):  
Cross Validation ◽  
Thickness Distribution ◽  
Tien Shan ◽  
Ice Thickness ◽  
Ice Volume ◽  
In Situ Data ◽  
Radio Echo Sounding ◽  
Thickness Measurements ◽  
Tien Shan Mountains

Abstract Glaciers in the Tien Shan mountains contribute considerably to the fresh water used for irrigation, households and energy supply in the dry lowland areas of Kyrgyzstan and its neighbouring countries. To date, reconstructions of the current ice volume and ice thickness distribution remain scarce, and accurate data are largely lacking at the local scale. Here, we present a detailed ice thickness distribution of Ashu-Tor, Bordu, Golubin and Kara-Batkak glaciers derived from radio-echo sounding measurements and modelling. All the ice thickness measurements are used to calibrate three individual models to estimate the ice thickness in inaccessible areas. A cross-validation between modelled and measured ice thickness for a subset of the data is performed to attribute a weight to every model and to assemble a final composite ice thickness distribution for every glacier. Results reveal the thickest ice on Ashu-Tor glacier with values up to 201 ± 12 m. The ice thickness measurements and distributions are also compared with estimates composed without the use of in situ data. These estimates approach the total ice volume well, but local ice thicknesses vary substantially.

The Value of Brand Fans during a Crisis: Exploring the Roles of Response Strategy, Source, and Brand Identification

2021 ◽  
pp. 232948842199969
Author(s):  
Hayoung Sally Lim ◽  
Natalie Brown-Devlin
Keyword(s):  
Social Media ◽  
Experimental Design ◽  
Crisis Communication ◽  
Word Of Mouth ◽  
Crisis Response ◽  
Response Strategy ◽  
Brand Identification ◽  
Communication Source ◽  
Practical Implications ◽  
Selection Of

Using a two (crisis response strategy: diminish vs. rebuild) × three (source: brand organization vs. brand executive vs. brand fan) experimental design, this study examines how brand fans (i.e., consumers who identify with a brand) can be prompted to protect a brand’s reputation during crises and how the selection of a crisis spokesperson can influence consumers’ evaluations of the crisis communication. Being buffers for their preferred brands, brand fans are more likely to accept their brand’s crisis response and engage in positive electronic word-of-mouth on social media. Brand fans are more likely to evaluate other brand fan’s social media accounts as a credible crisis communication source, whereas those who are not brand fans are more likely to evaluate brand and/or brand executives as credible. Findings provide theoretical applications in paracrisis literature pertaining to social media but also practical implications for brand managers to strategically utilize brand fans in crisis communication.

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