Thomas A.G. Smyth , Ryan Wilson , Paul Rooney , Katherine L. Yates
{"title":"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","authors":"Thomas A.G. Smyth , Ryan Wilson , Paul Rooney , Katherine L. Yates","doi":"10.1016/j.aeolia.2022.100799","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":49246,"journal":{"name":"Aeolian Research","volume":"56 ","pages":"Article 100799"},"PeriodicalIF":3.1000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1875963722000295/pdfft?md5=82c56ebe3285e357539f2f82d1c42f61&pid=1-s2.0-S1875963722000295-main.pdf","citationCount":"9","resultStr":"{\"title\":\"Extent, accuracy and repeatability of bare sand and vegetation cover in dunes mapped from aerial imagery is highly variable\",\"authors\":\"Thomas A.G. Smyth , Ryan Wilson , Paul Rooney , Katherine L. Yates\",\"doi\":\"10.1016/j.aeolia.2022.100799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":49246,\"journal\":{\"name\":\"Aeolian Research\",\"volume\":\"56 \",\"pages\":\"Article 100799\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1875963722000295/pdfft?md5=82c56ebe3285e357539f2f82d1c42f61&pid=1-s2.0-S1875963722000295-main.pdf\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aeolian Research\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1875963722000295\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aeolian Research","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1875963722000295","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
Extent, accuracy and repeatability of bare sand and vegetation cover in dunes mapped from aerial imagery is highly variable
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.
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.