Civilian science: the potential of participatory environmental monitoring in areas affected by armed conflicts.

Civilian science: the potential of participatory environmental monitoring in areas affected by armed conflicts.

Weir, Doug;McQuillan, Dan;Francis, Robert A;
Environmental monitoring and assessment 2019 Vol. 191 pp. 618
311
weir2019civilianenvironmental

Abstract

Legal and policy initiatives to address the environmental dimensions of armed conflicts and their impact on people, ecosystems and sustainable development are highly dependent on the availability of environmental data from conflict-affected areas. Socio-political and security conditions in these areas often impede data collection, while traditional models of post-conflict environmental assessments are limited in scope. In response, an increasing range of actors is utilising remote sensing and open source data collection to identify and estimate health and ecological risks during and after conflicts. This paper considers the role of participatory citizen science methodologies in complementing both remote monitoring and post-conflict assessments. It examines existing models and mechanisms for environmental data collection and utilisation in conflict contexts, and the extent to which the core values and principles of citizen science are transferable. We find that 'civilian science' is feasible and could be well-suited to conflict conditions. In addition to addressing gaps in data collection, it may also empower communities affected by environmental degradation, enhance their environmental human rights, supplement the often limited monitoring capacity of governmental agencies and facilitate cooperation and peacebuilding. The paper concludes by proposing methodological approaches for three common forms of environmental degradation associated with armed conflicts.

Citation

ID: 42899
Ref Key: weir2019civilianenvironmental
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
42899
Unique Identifier:
10.1007/s10661-019-7773-9
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet