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海外发展研究所-数字测绘和人道主义应急工作的纳入(英)-2021.10

# 数字测绘 # 人道主义应急工作 大小:2.74M | 页数:50 | 上架时间:2021-10-21 | 语言:英文

海外发展研究所-数字测绘和人道主义应急工作的纳入(英)-2021.10.pdf

海外发展研究所-数字测绘和人道主义应急工作的纳入(英)-2021.10.pdf

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类型: 专题

上传者: FF

撰写机构: 海外发展研究所

出版日期: 2021-10-17

摘要:

Digital mapping is a critical activity in contemporary humanitarian responses. It is often the first step to improving situational awareness and coordination, facilitating access to affected populations and understanding pressing humanitarian needs. Through the collation and verification of geolocated data, the location and condition of key services can be monitored, the likely impact of hazards can be predicted, and reports of violence can aid the protection of those affected by conflict.

Though digital mapping tools and the global network of humanitarians who contribute to them are recent developments, issues of who is represented and who contributes to a shared understanding of a place or crisis are not new. Ensuring inclusivity – here referring to actions taken to ensure the right to assistance, information and protection for all people affected by crisis – is a challenge for the humanitarian system. The sector shares with the field of cartography a history of exclusivity that has led to extractive relationships with those they seek to assist and depict. Much of this has continued with digitalisation, usually to the detriment of the most marginalised people in crises. Yet participatory processes, open-source platforms and advocacy groups are also helping to break the exclusive dynamics in mapping, with much of this work made possible through new digital tools.

The impact that digital mapping has had on inclusivity in practice cannot be known for certain: as 

just one tool for understanding context and needs, it is applied within a far wider world of different priorities and incentives. But the value of visibility as the first step to greater inclusivity should not be underestimated. With millions of people simply invisible on many digital maps, recording their presence is often the first step towards improved public services and humanitarian responses, and greater accountability for those who provide them, as examples from informal settlements in Kenya, refugee camps in Uganda and urban Manila in the Philippines indicate. 

However, humanitarian responders face difficult trade-offs with inclusion and mapping. Inequities in access to and use of digital technologies mean the most marginalised can remain so even when free-to-access online platforms invite affected people to submit reports to inform crisis maps. Remote map creation can present local realities to a wider audience, but can also facilitate a ‘distancing’ and a remote management of responses, which help to preserve exclusive dynamics. Though maps and the data collection processes they show can achieve more granularity and accuracy than ever before, to the benefit of service providers, the means by which those mapped can access their own data have not improved at the same pace. Mapping may not perhaps present as obvious a data management risk as other technologies, but geolocated data can easily be layered together to identify particular groups for the purposes of further exclusion and harm. The scale of digital mapping now means more people than ever are being represented, but such drawbacks mean this does not necessarily equal greater inclusion.

The growth of crowdsourcing, where volunteers build maps from satellite imaging and on-the-ground data, also presents both new opportunities and barriers for inclusivity in responses. On the one hand, the creation of such ‘global public goods’, through a network of volunteers, is a positive and necessary step towards an alternative, networked means of humanitarian responses, with benefits beyond the strict scope of the aid system, its metrics and projects. On the other, such initiatives need to work deliberately to improve the diversity of their volunteer mapmakers, who are still dominated by those from Western Europe and North America. An approach based on volunteering also has limitations for ensuring maps remain updated as well as improving inclusion in low-income contexts. Open-source platforms come with their own risks, biases and potentially exclusive dynamics that also mean inclusive mapmaking is not guaranteed. 

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