James V. Marcaccio, Jesse Gardner Costa, Scott Parker, Jonathan D. Midwood
{"title":"高分辨率的卫星数据和图像分割在五大湖的清澈水域中产生准确的底栖生物底物图","authors":"James V. Marcaccio, Jesse Gardner Costa, Scott Parker, Jonathan D. Midwood","doi":"10.1007/s12518-025-00607-9","DOIUrl":null,"url":null,"abstract":"<div><p>Benthic substrates are an important component of fish habitat and preferred substrates vary with species and life history traits. Understanding the location and areal extent of these substrates helps inform protection and management of fish and other aquatic species. Traditional methods of substrate mapping can require substantial effort and necessitate specialized equipment and personnel to work at and travel to sites. Satellite mapping of bottom types has been conducted in the past, though most of this work has been done in ocean systems and relatively little in freshwater. Using several permutations of input data and processing methods, we accurately map benthic substrates in the clear freshwater ecosystem of Fathom Five National Marine Park, Lake Huron, Canada. Using a novel approach, we were able to map substrate with relatively limited inputs to the model, making the method easily transferable among systems. An object-based approach to classification proved beneficial for accuracy, as was using higher resolution (< 2 m) satellite data to achieve our target accuracies. We also grouped accuracies by depth bins within the site to show that accuracy does not decrease linearly out to the maximum observable depth. Using a more limited depth range for classification results in higher overall and depth-specific accuracies, which may be beneficial when only a shallower portion of the site is necessary to map. With this model and information, accurate substrate maps for an area of interest could be developed to assist with the identification and management of aquatic habitat.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"17 2","pages":"343 - 356"},"PeriodicalIF":2.3000,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-025-00607-9.pdf","citationCount":"0","resultStr":"{\"title\":\"High resolution satellite data and image segmentation produce accurate benthic substrate maps in clear waters of the great lakes\",\"authors\":\"James V. Marcaccio, Jesse Gardner Costa, Scott Parker, Jonathan D. Midwood\",\"doi\":\"10.1007/s12518-025-00607-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Benthic substrates are an important component of fish habitat and preferred substrates vary with species and life history traits. Understanding the location and areal extent of these substrates helps inform protection and management of fish and other aquatic species. Traditional methods of substrate mapping can require substantial effort and necessitate specialized equipment and personnel to work at and travel to sites. Satellite mapping of bottom types has been conducted in the past, though most of this work has been done in ocean systems and relatively little in freshwater. Using several permutations of input data and processing methods, we accurately map benthic substrates in the clear freshwater ecosystem of Fathom Five National Marine Park, Lake Huron, Canada. Using a novel approach, we were able to map substrate with relatively limited inputs to the model, making the method easily transferable among systems. An object-based approach to classification proved beneficial for accuracy, as was using higher resolution (< 2 m) satellite data to achieve our target accuracies. We also grouped accuracies by depth bins within the site to show that accuracy does not decrease linearly out to the maximum observable depth. Using a more limited depth range for classification results in higher overall and depth-specific accuracies, which may be beneficial when only a shallower portion of the site is necessary to map. With this model and information, accurate substrate maps for an area of interest could be developed to assist with the identification and management of aquatic habitat.</p></div>\",\"PeriodicalId\":46286,\"journal\":{\"name\":\"Applied Geomatics\",\"volume\":\"17 2\",\"pages\":\"343 - 356\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s12518-025-00607-9.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12518-025-00607-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-025-00607-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
High resolution satellite data and image segmentation produce accurate benthic substrate maps in clear waters of the great lakes
Benthic substrates are an important component of fish habitat and preferred substrates vary with species and life history traits. Understanding the location and areal extent of these substrates helps inform protection and management of fish and other aquatic species. Traditional methods of substrate mapping can require substantial effort and necessitate specialized equipment and personnel to work at and travel to sites. Satellite mapping of bottom types has been conducted in the past, though most of this work has been done in ocean systems and relatively little in freshwater. Using several permutations of input data and processing methods, we accurately map benthic substrates in the clear freshwater ecosystem of Fathom Five National Marine Park, Lake Huron, Canada. Using a novel approach, we were able to map substrate with relatively limited inputs to the model, making the method easily transferable among systems. An object-based approach to classification proved beneficial for accuracy, as was using higher resolution (< 2 m) satellite data to achieve our target accuracies. We also grouped accuracies by depth bins within the site to show that accuracy does not decrease linearly out to the maximum observable depth. Using a more limited depth range for classification results in higher overall and depth-specific accuracies, which may be beneficial when only a shallower portion of the site is necessary to map. With this model and information, accurate substrate maps for an area of interest could be developed to assist with the identification and management of aquatic habitat.
期刊介绍:
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements