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Data Study Group Final Report: Smart monitoring for conservation areas

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The_Alan_Turing_Institute_Data_Study_Group_Final_Report_-_WWF.pdf

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Resource type
Research report
Creator (person)
Hosseini, Kasra
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Coll Ardanuy, Mariona
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Patterson, David
Garcia-Velez, Laura
Castro-Gonzalez, Leonardo
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Date published
2020
Abstract

WWF (World Wide Fund for Nature) monitors over 250,000 protected areas (e.g. national parks and nature reserves) and thousands of other sites and critical habitats. These sites are the foundation of global natural assets and are central to the preservation of biodiversity and human well-being. Unfortunately, they face increasing pressures from human development. In this challenge, we explore various data science techniques to automatically detect news articles that report emerging threats to key protected areas. We describe a system that identifies such news stories near real-time. This is vital to enable the wider machinery of WWF and the conservation community to engage with governments, companies, shareholders, insurers, and others to help halt the degradation or destruction of key habitats.

Contributor (organisation)
British Library
Collaborative Institution
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Living with Machines
Research Group
Project(s)
Living with Machines
Funder
Funder nameISNIAwards
Arts and Humanities Research Council
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AH/S01179X/1
Engineering and Physical Sciences Research Council
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EP/N510129/1
Pagination
34
Publisher
Zenodo
Official URL
http://doi.org/10.5281/zenodo.3878457
Related URL
https://www.turing.ac.uk/research/publications/data-study-group-final-report-wwf
Licence
CC BY-SA 4.0
DOI
10.5281/zenodo.3878457
Keywords
natural language processing
supervised learning
neural networks
WWF
conservation
Alan Turing Institute
habitats
Data Study Groups
Collection
Living with Machines
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