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A comparison of three ways to assemble wall-to-wall maps from distribution models of vegetation types
GIScience & Remote Sensing ( IF 6.7 ) Pub Date : 2021-12-01 , DOI: 10.1080/15481603.2021.1996313
Peter Horvath 1, 2 , Rune Halvorsen 1 , Trond Simensen 3 , Anders Bryn 1, 2, 4
Affiliation  

ABSTRACT

Distribution modeling methods are used to provide occurrence probability surfaces for modeled targets. While most often used for modeling species, distribution modeling methods can also be applied to vegetation types. However, surfaces provided by distribution modeling need to be transformed into classified wall-to-wall maps of vegetation types to be useful for practical purposes, such as nature management and environmental planning. The paper compares the performance of three methods for assembling predictions for multiple vegetation types, modeled individually, into a wall-to-wall map. The authors used grid-cell based probability surfaces from distribution models of 31 vegetation types to test the three assembly methods. The first, a probability-based method, selected for each grid cell the vegetation type with the highest predicted probability of occurrence in that cell. The second, a performance-based method, assigned the vegetation types, ordered from high to low model performance, to a fraction of the grid cells given by the vegetation type’s prevalence in the study area. The third, a prevalence-based method, differed from the performance-based method by assigning vegetation types in the order from low to high prevalence. Thus the assembly methods worked in two principally different ways: the probability-based method assigned vegetation types to grid cells in a cell-by-cell manner, and both the performance-based method and prevalence-based method assigned them in a type-by-type manner. All methods were evaluated by use of reference data collected in the field, more or less independently of the data used to parameterize the vegetation-type models. Quantity, allocation, and total disagreement, as well as proportional dissimilarity metrics, were used for evaluation of assembly methods. Overlay analysis showed 38.1% agreement between all three assembly methods. The probability-based method had the lowest total disagreement with, and proportional dissimilarity from, the reference datasets, but the differences between the three methods were small. The three assembly methods differed strongly with respect to the distribution of the total disagreement on its quantity and allocation components: the cell-by-cell assignment method strongly favored allocation disagreement and the type-by-type methods strongly favored quantity disagreement. The probability-based method best reproduced the general pattern of variation across the study area, but at the cost of many rare vegetation types, which were left out of the assembled map. By contrast, the prevalence-based and performance-based methods represented vegetation types in accordance with nationwide area statistics. The results show that maps of vegetation types with wall-to-wall coverage can be assembled from individual distribution models with a quality acceptable for indicative purposes, but all the three tested methods currently also have shortcomings. The results also indicate specific points in the methodology for map assembly that may be improved.



中文翻译:

从植被类型分布模型中组合墙到墙图的三种方法的比较

摘要

分布建模方法用于为建模目标提供发生概率面。虽然最常用于对物种进行建模,但分布建模方法也可应用于植被类型。然而,分布建模提供的表面需要转换为植被类型的分类墙到墙图,以用于实际目的,例如自然管理和环境规划。该论文比较了三种将单独建模的多种植被类型的预测组合到墙到墙地图中的性能。作者使用来自 31 种植被类型的分布模型的基于网格单元的概率面来测试三种组装方法。一、一种基于概率的方法,为每个网格单元选择在该单元中预测概率最高的植被类型。第二种是基于性能的方法,将植被类型从模型性能从高到低的顺序分配给研究区域中植被类型普遍性给出的网格单元的一小部分。三、基于流行度的方法,与基于性能的方法不同,它按照从低到高的顺序分配植被类型。因此,组装方法以两种主要不同的方式工作:基于概率的方法以逐个单元格的方式将植被类型分配给网格单元格,以及基于性能的方法和基于流行率的方法以逐个类型的方式将植被类型分配给网格单元格。 -类型方式。所有方法都通过使用在现场收集的参考数据进行评估,或多或少独立于用于参数化植被类型模型的数据。数量、分配和总差异以及比例差异度量用于评估组装方法。叠加分析显示所有三种组装方法之间的一致性为 38.1%。基于概率的方法具有最低的总分歧,和参考数据集的比例差异,但三种方法之间的差异很小。三种组装方法在其数量和分配组件的总分歧分布方面存在很大差异:逐单元分配方法强烈支持分配分歧,而逐类型方法强烈支持数量分歧。基于概率的方法最好地再现了整个研究区域的一般变化模式,但代价是许多稀有植被类型被排除在组装地图之外。相比之下,基于流行性和基于性能的方法根据全国面积统计来表示植被类型。结果表明,具有墙到墙覆盖的植被类型地图可以从具有指示性目的的质量可接受的单个分布模型组装,但所有三种测试方法目前也存在缺点。结果还表明地图组装方法中可以改进的特定点。

更新日期:2021-12-14
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