{"title":"Highlighting broad-scale morphometric diversity of the seabed using geomorphons","authors":"Margaret Dolan, Lilja Rún Bjarnadóttir","doi":"10.34194/geusb.v52.8337","DOIUrl":null,"url":null,"abstract":"Morphometric diversity is an important component of overall seabed geodiversity. Automated methods for classification of morphometric features (ridges, peaks, valleys etc.) provide a convenient way of classifying large volumes of data in a consistent and repeatable way and a basis for assessing morphometric diversity. Here, we apply ‘geomorphons’, a pattern recognition approach to morphometric feature classification, to 100 m resolution multibeam bathymetry data in the Barents and Norwegian Seas, Norway. The study area spans depths from a few metres to nearly 6000 m across several geological settings. Ten unique morphometric features are delineated by the geomorphon analysis. From these results, we compute the variety of features per 10 km2. This simple ‘geomorphon richness’ measure highlights broad-scale morphometric diversity across the study area. We compare the richness results with terrain attributes and across physiographic regions. Our results provide new regional insights, which together with more detailed information will help guide follow-up surveys as well as identifying diversity hotspots, which may require special management.","PeriodicalId":48475,"journal":{"name":"Geus Bulletin","volume":"36 1","pages":"0"},"PeriodicalIF":2.0000,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geus Bulletin","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34194/geusb.v52.8337","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Morphometric diversity is an important component of overall seabed geodiversity. Automated methods for classification of morphometric features (ridges, peaks, valleys etc.) provide a convenient way of classifying large volumes of data in a consistent and repeatable way and a basis for assessing morphometric diversity. Here, we apply ‘geomorphons’, a pattern recognition approach to morphometric feature classification, to 100 m resolution multibeam bathymetry data in the Barents and Norwegian Seas, Norway. The study area spans depths from a few metres to nearly 6000 m across several geological settings. Ten unique morphometric features are delineated by the geomorphon analysis. From these results, we compute the variety of features per 10 km2. This simple ‘geomorphon richness’ measure highlights broad-scale morphometric diversity across the study area. We compare the richness results with terrain attributes and across physiographic regions. Our results provide new regional insights, which together with more detailed information will help guide follow-up surveys as well as identifying diversity hotspots, which may require special management.