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首页> 外文期刊>Estuarine Coastal and Shelf Science >An error analysis of marine habitat mapping methods and prioritised work packages required to reduce errors and improve consistency
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An error analysis of marine habitat mapping methods and prioritised work packages required to reduce errors and improve consistency

机译:船舶栖息地映射方法的误差分析和减少误差所需的优先工作包,提高一致性

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摘要

Many technical issues influence the accuracy and repeatability of marine habitat mapping studies - identifying, quantifying and suggesting further work to reduce these issues was the objective of this investigation. Issues were identified by firstly defining the methods that are common used for marine habitat mapping and then by identifying the 'methodological variables' (i.e. decision points within a map production methodology) within each method that entrained error, and ultimately contribute to inaccuries in end products. Following the identification of issues, potential solutions for addressing the methodological variables that were subsequently ranked by efficacy and cost-effectiveness.A total of 56 marine habitat mapping methods for were constructed using combinations of 18 common mapping techniques and platforms (e.g. ship, UAV). A total of 39 significant methodological variables were identified for all of the methods with individual methods having between 6 and 18 methodological variables each. The error analysis requires that the potential of each methodological variable to influence the overall accuracy of a map be estimated. These estimates of influence were taken from published studies that have compared different approaches within a methodological variable, and subsequently compared the accuracy of the resulting maps (typically via cross-validation). Sometimes it was necessary to use expert judgement to estimate the contribution of a methodological variables to changes in map accuracy when other forms of information were not available.Recommended work packages to reduce the influence of each of the 39 methodological variables (termed error reduction solutions here) are listed and prioritised. Error reduction solutions relevant to: (i) classification analysis (also referred to as segmentation); (ii) matching sampling resolution to the habitat resolution (via a habitat resolution catalogue); (iii) improving the positional error of ground-truthing sampling; (iv) increasing the replication and improving distribution of ground-truthing; and (v) reducing reader error during the processing of benthic footage were particularly important for reducing error within the final mapped outputs across multiple methods.
机译:许多技术问题影响了海洋栖息地映射研究的准确性和可重复性 - 识别,量化和建议进一步努力减少这些问题是这一调查的目标。首先定义用于海洋栖息地映射的常见方法的方法,然后通过识别涉及错误的每种方法中识别“方法的方法变量”(即地图生产方法中的决策点),并最终为最终产品中的因不准确贡献。在识别问题之后,用于解决随后因疗效和成本效益排序的方法变量的潜在解决方案。使用18个常见映射技术和平台的组合(例如船舶,无人机)构建了56个海洋栖息地映射方法的总共56个海洋栖息地映射方法。 。对于每个方法,共鉴定了39种显着的方法论变量,其中各种方法各自在6至18个方法变量之间。误差分析要求估计每个方法的各种方法变量的潜力估计地图的整体精度。这些影响估计来自发表的研究,这些研究已经比较了方法变量的不同方法,随后比较了所得贴图的精度(通常通过交叉验证)。有时有必要使用专家判断来估算方法变量对地图精度的变化的贡献,当不可用。推荐的工作包以减少39种方法变量中的每一个的影响(这里被称为错误减少解决方案)列出并优先考虑。误差减少解决方案与:(i)分类分析(也称为分段); (ii)将抽样解决符合居署决议(通过栖息地分辨率目录); (iii)改善地面串拔采样的位置误差; (iv)增加复制和改善地面串联的分布; (v)减少了在Benthic镜头处理过程中的读取器误差对于在多种方法中降低最终映射输出中的误差尤为重要。

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