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167 results for “Disaster”
The result of research and analysis of disaster knowledge
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SMDRM - Social Media for Disaster Risk Management
<p><strong>SMDRM - Social Media for Disaster Risk Management</strong></p> <p>Social media has been described as a form of distributed cognition, a mechanism for understanding a situation using information spread across many minds. The interactions among people in social media are a form of collective intelligence, as they allow people to make sense of a developing event collectively. Social media users can contribute to creating a "sensor" for citizen-generated data that modelling or monitoring systems can assimilate during a crisis. Gaining situational awareness in a disaster is critical and time-sensitive. Social media presents the possibilities of a growing data source to help improve response in the early hours and days of a crisis. However, social media platforms may not provide the functionality of summarising the information that is useful for crisis responders.SMDRM is a software platform that streamlines the processing of text and images extracted from Twitter in near real-time during a specific event. The data is collected using a combination of keywords and locations based on daily forecasts from the early warnings systems of the Copernicus Emergency Management Service such as EFAS, GloFAS and EFFIS (emergency.copernicus.eu) or triggered manually in case of earthquakes or not-forecasted events. Text is automatically "annotated" using a binary multilingual classifier trained on 12 languages and extended with multilingual embeddings. Simultaneously, a multi-class convolutional neural network labels relevant images for floods, storms, earthquakes and fires. The information that doesn't embed coordinates is geolocated in a two-step algorithm where location candidates are first selected using a multilingual named-entity recognition tool and then searched on available gazetteers. The last step of the SMDRM data processing is the aggregation of relevant information in spatial (administrative areas) and temporal (daily) units. Social media activity about an event can finally be distributed as a data map and visualised on a map server and made available to users.SMDRM could offer timely information useful for reducing the hazard models' uncertainty and providing added-value information such as reports or descriptions of the situation on the ground or in the vicinity. Other stakeholders, such as research groups could access new data to complement the ones extracted from traditional sensors or earth observation. The platform can adapt to cope with the varying workload as it uses scalable software containers. If the number of tweets is higher during an impactful event, the platform can use more containers to annotate them. SMDR code, together with the tens of thousands of annotated social media messages used for training its models, will be released as an open-source platform whose modules can be adapted to serve other research projects. We describe the platform's architecture and implementation details, and two use cases where images and text were used as a use-case to test the system's modules.</p> <p>Source https://ui.adsabs.harvard.edu/abs/2021EGUGA..2315012L/abstract</p>
FIGURE 8 in Two new species of small minnow mayfly (Ephemeroptera: Baetidae) from a mine-tailing dam disaster area in Minas Gerais, Brazil
FIGURE 8. Rivudiva watu sp. nov., (INPA). A, dorsal habitus of immature nymph (holotype); B, dorsal habitus of mature nymph (paratype); C, posterior margin of tergum IV; D, paraproct; E, paracercus; F, cercus.
FIGURE 2 in Calamities causing loss of museum collections: a historical and global perspective on museum disasters
FIGURE 2. View of the collection of animals preserved in alcohol in the Instituto Butantan, Sao Paulo, Brazil before (upper) and after (lower) the fire in 2010. Courtesy of Marcelo Ribeiro Duarte (Instituto Butantan).
Geocoded Disasters (GDIS) Dataset
The Geocoded Disasters (GDIS) Dataset is a geocoded extension of a selection of natural disasters from the Centre for Research on the Epidemiology of Disasters' (CRED) Emergency Events Database (EM-DAT). The data set encompasses 39,953 locations for 9,924 disasters that occurred worldwide in the years 1960 to 2018. All floods, storms (typhoons, monsoons etc.), earthquakes, landslides, droughts, volcanic activity and extreme temperatures that were recorded in EM-DAT during these 58 years and could be geocoded are included in the data set. The highest spatial resolution in the data set corresponds to administrative level 3 (usually district/commune/village) in the Global Administrative Areas database (GADM, 2018). The vast majority of the locations are administrative level 1 (typically state/province/region).
Video S2 Five-year monitoring of a desert burrow-dwelling spider fol-lowing an environmental disaster indicates long-term impacts.
<p>A supplementary video S2</p> <p><em>Sahastata aravaensis</em> sp. nov. feeding in captivity with ants, Efrat Gavish-Regev. The spiders usually bite the ant’s leg before feeding.</p> <p>Five-year monitoring of a desert burrow-dwelling spider fol-lowing an environmental disaster indicates long-term impacts.</p> <p>Submitted to the Journal: Insects</p> <p> </p>
Business grant following natural disasters and its different impact on the performance of female and male-owned microenterprises: Evidence from Sri Lanka
<p><strong><em>Objective</em></strong></p> <p>This paper investigates gender differences in the treatment effects of business grants on firm performance following natural disasters, and seeks to identify the mechanisms underlying the unequal effects.</p> <p><strong><em>Method</em></strong></p> <p>A panel dataset from an experiment in Sri Lanka is used to measure the difference in the treatment effects of a business grant on the performance of female and male-owned firms following the 2004 Indian Ocean tsunami. The sample of 608 microenterprises includes 297 female-owned firms and 311 male-owned firms. There are 338 firms (male = 176, female = 162) in the treatment group that received the grant and 270 firms (male = 135, female = 135) in the control group that did not receive the grant. Data on firm performance, firm characteristics and owner characteristics were collected in 13 survey waves from April 2005 to December 2010. Firm performance, which is measured by firm profit, is assessed by employing linear regression with fixed effects in an intention-to-treat analysis.</p> <p><strong><em>Findings</em></strong></p> <p>The results suggest that the business grant has a positive impact on the performance of male-owned firms, but zero effect on that of female-owned firms. Several potential mechanisms drive the results, including gender differences in business investment, household expenditures and initial business closures. The results also show a positive treatment effect of the business grant on the psychological recovery of recipients, but there is no evidence supporting gender differences in this dimension.</p> <p><strong><em>Contribution</em></strong></p> <p>This paper provides new evidence on gender differences in the treatment effects of business grants on firm performance in the context of post-disasters, and has implications for business recovery programs aimed at supporting female microentrepreneurs in the aftermath of large-scale catastrophes.</p>
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