Discrimination of the intertidal goose barnacle Pollicipes pollicipes from rocky shore invertebrates and macroalgae using in situ hyperspectral signatures

IF 4.5 Q2 ENVIRONMENTAL SCIENCES
Marta Román , BedeF.R. Davies , Simon Oiry , Philippe Rosa , Pierre Gernez , Celia Olabarria , Laurent Barillé
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引用次数: 0

Abstract

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.
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
利用基于光谱反射率的遥感技术对潮间带物种进行测绘,比传统调查具有优势。然而,目前对高光谱或多光谱传感器对潮间带鹅藤壶探测的光谱分辨率的影响尚未进行评估。我们描述了policipes policipes的反射光谱,并测试了它是否能与Mytilus属的贻贝(成体和贝)、Chthamalus和Semibalanus属的其他藤壶以及红色、棕色和绿色的大型藻类区分。我们在法国和西班牙东北大西洋沿岸和实验室的三个地点测量了337个样品的高光谱特征。从这些由491个窄带组成的高光谱特征中,我们测试了10个窄带的低分辨率多光谱传感器捕捉关键光谱特征用于分类的能力。评估分类目标之间的差异,并使用高光谱和多光谱分辨率训练随机森林分类。高光谱数据的分类精度较高,但多光谱分辨率的分类总体精度为0.88,令人满意。藤壶、贻贝和大型藻类表现出明显的差异。鹅藤壶类在多光谱分辨率下的用户精度为0.89,与其他藤壶类只有很小的混淆。光谱波段的红边和绿边是区分两类藤壶的最重要特征。这突出了近红外波段识别鹅藤壶的必要性,并提出了用安装在无人机上的可见近红外传感器绘制这些种群的潜力。
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来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
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
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