Voluntary consensus based geospatial data standards for the global illegal trade in wild fauna and flora.
Voluntary consensus based geospatial data standards for the global illegal trade in wild fauna and flora.
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DOI：
10.1038/s41597-022-01371-w
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发表时间：
2022-06-03
期刊：
影响因子：
9.8
通讯作者：
Naess, Leah Wanambwa
中科院分区：
文献类型：
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作者：
Gore, Meredith L.;Schwartz, Lee R.;Amponsah-Mensah, Kofi;Barbee, Emily;Canney, Susan;Carbo-Penche, Maria;Cronin, Drew;Hilend, Rowan;Laituri, Melinda;Luna, David;Maina, Faith;Mey, Christian;Mumford, Kathleena;Mugo, Robinson;Nduguta, Redempta;Nyce, Christopher;McEvoy, John;McShea, William;Mandimbihasina, Angelo;Salafsky, Nick;Smetana, David;Tait, Alexander;Wittig, Tim;Wright, Dawn;Naess, Leah Wanambwa
我们拥有比以往任何时候都多的关于野生动物贩运的数据，但这些数据在决策中仍然没有得到充分利用。有效的野生动物贩运干预措施的核心是收集、汇总和分析一系列来源地、过境地和目的地的数据。许多数据是地理空间数据，但如果没有适当的地理空间数据标准，就无法有效地获取或汇总这些数据。我们的目标是创建地理空间数据标准，以帮助推动打击野生动物贩运的努力。我们通过与来自三大洲的100多名参与者举办自愿、参与式和基于成果的研讨会、在线门户网站和电子通信，实现了我们的目标。这些标准支持该领域的数据决策工作，例如起诉野生动物贩运中的关键人物，并破坏其网络。地理空间数据标准有助于跨学科和部门更广泛地利用野生动物贩运数据，加快跨空间和时间的数据汇总和分析，推进循证决策，减少野生动物贩运。
We have more data about wildlife trafficking than ever before, but it remains underutilized for decision-making. Central to effective wildlife trafficking interventions is collection, aggregation, and analysis of data across a range of source, transit, and destination geographies. Many data are geospatial, but these data cannot be effectively accessed or aggregated without appropriate geospatial data standards. Our goal was to create geospatial data standards to help advance efforts to combat wildlife trafficking. We achieved our goal using voluntary, participatory, and engagement-based workshops with diverse and multisectoral stakeholders, online portals, and electronic communication with more than 100 participants on three continents. The standards support data-to-decision efforts in the field, for example indictments of key figures within wildlife trafficking, and disruption of their networks. Geospatial data standards help enable broader utilization of wildlife trafficking data across disciplines and sectors, accelerate aggregation and analysis of data across space and time, advance evidence-based decision making, and reduce wildlife trafficking.
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DOI：
10.1073/pnas.0403170101
发表时间：
2004-10-12
影响因子：
11.1
作者：
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影响因子：
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影响因子：
1.3
作者：
Forrester T;O'Brien T;Fegraus E;Jansen PA;Palmer J;Kays R;Ahumada J;Stern B;McShea W
通讯作者：
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DOI：
10.3390/s21010050
发表时间：
2020-12-24
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Liang SHL;Saeedi S;Ojagh S;Honarparvar S;Kiaei S;Mohammadi Jahromi M;Squires J
通讯作者：
Squires J