Extent, accuracy and repeatability of bare sand and vegetation cover in dunes mapped from aerial imagery is highly variable

IF 3.1 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Aeolian Research Pub Date : 2022-06-01 DOI:10.1016/j.aeolia.2022.100799
Thomas A.G. Smyth , Ryan Wilson , Paul Rooney , Katherine L. Yates
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引用次数: 9

Abstract

Vegetation cover on coastal sand dunes has been increasing worldwide since at least the 1940s. Analysis of aerial and satellite imagery has been the principal source used to measure this change, however no studies have systematically evaluated the accuracy of remotely sensed estimates. Using established land cover classification methods and in-situ field measurements, we show that both the extent and accuracy of remotely sensed areas of bare sand and vegetation in dunes varies with image resolution and classification method. We found that supervised methods of classification (semi-automatic), whilst mapping a greater extent of bare sand and being more accurate than manual digitisation, had poor repeatability, exhibiting a relatively large range of bare sand and vegetation extent between classifications replicated under the same conditions. In contrast, areas of bare sand and vegetation classified by manual digitisation had high repeatability but a relatively low percentage of observed agreement with data collected in the field. For all classification methods, observed agreement with field data generally increased with image resolution. Our results demonstrate that users of land classification data in dunes should be cautious when interpreting trends of bare sand and vegetation cover due to substantial repeatability error in supervised classification methods, and relatively poor observed agreement with field data of manual classification. We recommend that analysis of bare sand and vegetation cover in dunes should be based on multiple replicates using supervised classification, employing the highest resolution imagery available and that all results presented should also include the range measured by multiple replicates.

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从航空图像中绘制的沙丘上的裸沙和植被覆盖的范围、精度和可重复性变化很大
至少从20世纪40年代以来,全世界沿海沙丘上的植被覆盖一直在增加。对航空和卫星图像的分析是用来测量这一变化的主要来源,但是没有研究系统地评价遥感估计的准确性。利用已建立的土地覆盖分类方法和现场实测数据,我们发现不同的图像分辨率和分类方法对沙丘裸沙和植被遥感区域的范围和精度都有影响。我们发现,监督分类方法(半自动)虽然绘制了更大范围的裸沙,比人工数字化更准确,但可重复性差,在相同条件下复制的分类之间显示出相对较大的裸沙和植被范围。相比之下,通过人工数字化分类的裸沙和植被区域具有很高的可重复性,但观测到的数据与现场收集的数据的一致性相对较低。对于所有分类方法,观测结果与现场数据的一致性通常随着图像分辨率的增加而增加。研究结果表明,由于监督分类方法的重复性误差较大,且与人工分类的野外观测数据的一致性相对较差,沙丘土地分类数据的使用者在解释裸沙和植被覆盖趋势时应谨慎。我们建议对沙丘中的裸沙和植被覆盖的分析应基于使用监督分类的多个重复,使用可用的最高分辨率图像,并且所提供的所有结果还应包括多个重复测量的范围。
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来源期刊
Aeolian Research
Aeolian Research GEOGRAPHY, PHYSICAL-
CiteScore
7.10
自引率
6.10%
发文量
43
审稿时长
>12 weeks
期刊介绍: The scope of Aeolian Research includes the following topics: • Fundamental Aeolian processes, including sand and dust entrainment, transport and deposition of sediment • Modeling and field studies of Aeolian processes • Instrumentation/measurement in the field and lab • Practical applications including environmental impacts and erosion control • Aeolian landforms, geomorphology and paleoenvironments • Dust-atmosphere/cloud interactions.
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