Marta Román , BedeF.R. Davies , Simon Oiry , Philippe Rosa , Pierre Gernez , Celia Olabarria , Laurent Barillé
{"title":"岩岸无脊椎动物和大型藻类潮间带鹅藤壶的原位高光谱特征鉴别","authors":"Marta Román , BedeF.R. Davies , Simon Oiry , Philippe Rosa , Pierre Gernez , Celia Olabarria , Laurent Barillé","doi":"10.1016/j.rsase.2025.101697","DOIUrl":null,"url":null,"abstract":"<div><div>Using remote sensing techniques based on spectral reflectance for mapping intertidal species, offers advantages over traditional surveys. However, the effect of the spectral resolution of the sensors, hyper- or multi-spectral, for the detection of intertidal sessile goose barnacles has not been assessed yet. We described the reflectance spectra of the species <em>Pollicipes pollicipes</em> and tested if it could be discriminated from mussels (adults and spat) from the <em>Mytilus</em> genus, other barnacles of the genus <em>Chthamalus</em> and <em>Semibalanus</em> and red, brown and green macroalgae. We measured their hyperspectral signatures in 337 samples, at three sites along the French and Spanish NE Atlantic coast and in the laboratory. From these hyperspectral signatures, composed of 491 narrow bands, we tested the ability of a lower resolution multispectral sensor of 10 bands to capture key spectral features for classification. Dissimilarity between classification targets was assessed and Random Forest classifications were trained with hyper and multispectral resolutions. There was a higher accuracy with hyperspectral data, but classifications with multispectral resolution showed a satisfactory overall accuracy of 0.88. Barnacles, mussels and macroalgae, showed discernible dissimilarities. User accuracy of the goose barnacle class at a multispectral resolution was 0.89 showing only a small confusion with other barnacles. Spectral bands belonging to red edge and green wavelengths were the most important features for discrimination between the two classes of barnacles. This highlights the necessity of near infrared bands for goose barnacle identification and suggests a potential for mapping these populations with a visible near infra-red sensor mounted on a drone.</div></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"39 ","pages":"Article 101697"},"PeriodicalIF":4.5000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Discrimination of the intertidal goose barnacle Pollicipes pollicipes from rocky shore invertebrates and macroalgae using in situ hyperspectral signatures\",\"authors\":\"Marta Román , BedeF.R. Davies , Simon Oiry , Philippe Rosa , Pierre Gernez , Celia Olabarria , Laurent Barillé\",\"doi\":\"10.1016/j.rsase.2025.101697\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Using remote sensing techniques based on spectral reflectance for mapping intertidal species, offers advantages over traditional surveys. However, the effect of the spectral resolution of the sensors, hyper- or multi-spectral, for the detection of intertidal sessile goose barnacles has not been assessed yet. We described the reflectance spectra of the species <em>Pollicipes pollicipes</em> and tested if it could be discriminated from mussels (adults and spat) from the <em>Mytilus</em> genus, other barnacles of the genus <em>Chthamalus</em> and <em>Semibalanus</em> and red, brown and green macroalgae. We measured their hyperspectral signatures in 337 samples, at three sites along the French and Spanish NE Atlantic coast and in the laboratory. From these hyperspectral signatures, composed of 491 narrow bands, we tested the ability of a lower resolution multispectral sensor of 10 bands to capture key spectral features for classification. Dissimilarity between classification targets was assessed and Random Forest classifications were trained with hyper and multispectral resolutions. There was a higher accuracy with hyperspectral data, but classifications with multispectral resolution showed a satisfactory overall accuracy of 0.88. Barnacles, mussels and macroalgae, showed discernible dissimilarities. User accuracy of the goose barnacle class at a multispectral resolution was 0.89 showing only a small confusion with other barnacles. Spectral bands belonging to red edge and green wavelengths were the most important features for discrimination between the two classes of barnacles. This highlights the necessity of near infrared bands for goose barnacle identification and suggests a potential for mapping these populations with a visible near infra-red sensor mounted on a drone.</div></div>\",\"PeriodicalId\":53227,\"journal\":{\"name\":\"Remote Sensing Applications-Society and Environment\",\"volume\":\"39 \",\"pages\":\"Article 101697\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing Applications-Society and Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352938525002502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352938525002502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Discrimination of the intertidal goose barnacle Pollicipes pollicipes from rocky shore invertebrates and macroalgae using in situ hyperspectral signatures
Using remote sensing techniques based on spectral reflectance for mapping intertidal species, offers advantages over traditional surveys. However, the effect of the spectral resolution of the sensors, hyper- or multi-spectral, for the detection of intertidal sessile goose barnacles has not been assessed yet. We described the reflectance spectra of the species Pollicipes pollicipes and tested if it could be discriminated from mussels (adults and spat) from the Mytilus genus, other barnacles of the genus Chthamalus and Semibalanus and red, brown and green macroalgae. We measured their hyperspectral signatures in 337 samples, at three sites along the French and Spanish NE Atlantic coast and in the laboratory. From these hyperspectral signatures, composed of 491 narrow bands, we tested the ability of a lower resolution multispectral sensor of 10 bands to capture key spectral features for classification. Dissimilarity between classification targets was assessed and Random Forest classifications were trained with hyper and multispectral resolutions. There was a higher accuracy with hyperspectral data, but classifications with multispectral resolution showed a satisfactory overall accuracy of 0.88. Barnacles, mussels and macroalgae, showed discernible dissimilarities. User accuracy of the goose barnacle class at a multispectral resolution was 0.89 showing only a small confusion with other barnacles. Spectral bands belonging to red edge and green wavelengths were the most important features for discrimination between the two classes of barnacles. This highlights the necessity of near infrared bands for goose barnacle identification and suggests a potential for mapping these populations with a visible near infra-red sensor mounted on a drone.
期刊介绍:
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems