Détail de l'auteur
Auteur Pasi Korpelainen |
Documents disponibles écrits par cet auteur (3)
Affiner la rechercheComparing multispectral and hyperspectral UAV data for detecting peatland vegetation patterns / Yuwen Pang in International journal of applied earth observation and geoinformation, 132 (2024)
Titre : Comparing multispectral and hyperspectral UAV data for detecting peatland vegetation patterns Type de document : Numérique Auteurs : Yuwen Pang ; Aleksi Räsänen ; Franziska Wolff ; Teemu Tahvanainen ; Milja Männikkö ; Mika Aurela ; Pasi Korpelainen ; Timo Kumpula ; Tarmo Virtanen Année de publication : 2024 Article en page(s) : 12 p. Langues : Anglais (eng) Catégories : [CBNPMP-Thématique] Télédétection Résumé : Northern peatland vegetation exhibits fine-scale spatial and spectral heterogeneity that can potentially be captured with uncrewed aerial vehicle (UAV) data due to their ultra-high spatial resolution (<10 cm). From this perspective, the contribution of different spectral sensors in mapping various vegetation characteristics has not been thoroughly investigated. We delineated spatial patterns of plant community clusters, plant functional types (PFTs), and selected plant species with UAV hyperspectral (HS), UAV multispectral (MS), and airborne LiDAR (light detection and ranging) topography (TP) data in two northern peatlands. We conducted random forest (RF) regressions in a geographic object-based image analysis (GEOBIA) framework and compared the relative contributions of the different datasets. In the best regression models, the percentage of explained variance was 24–74 % (RMSE:0.24–0.31), 40–90 % (RMSE:0.12–0.41), and 18–90 % (RMSE:0.03–0.40) for plant community clusters, PFTs, and plant species, respectively. The MS-TP combination had, in many cases, the highest performance, while HS-based models had better performance for some plant community clusters, PFTs, and plant species. TP features were useful only in certain situations. Overall, our results suggest that UAV MS imagery combined with TP data outperformed or performed at least almost as well as the models using UAV HS data and while all data combinations are capable for fine-scale detection of vegetation in northern peatlands. A more comprehensive investigations of data processing and methodology selection is needed to conclude if there is an added value of UAV HS data for peatland vegetation monitoring Lien pérenne : DOI : 10.1016/j.jag.2024.104043 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=155067
in International journal of applied earth observation and geoinformation > 132 (2024) . - 12 p.Pang, Yuwen, Räsänen, Aleksi, Wolff, Franziska, Tahvanainen, Teemu, Männikkö, Milja, Aurela, Mika, Korpelainen, Pasi, Kumpula, Timo, Virtanen, Tarmo 2024 Comparing multispectral and hyperspectral UAV data for detecting peatland vegetation patterns. International journal of applied earth observation and geoinformation, 132: 12 p..Documents numériques
Consultable
article (2024)Adobe Acrobat PDF
Titre : Reindeer control over shrubification in subarctic wetlands: spatial analysis based on unoccupied aerial vehicle imagery Type de document : Imprimé Auteurs : Miguel Villoslada ; Henni Ylänne ; Tina H. M. Kolari ; Pasi Korpelainen ; Teemu Tahvanainen ; Franziska Wolff ; Timo Kumpula Année de publication : 2023 Article en page(s) : 687-706 Langues : Anglais (eng) Catégories : [CBNPMP-Thématique] Télédétection Résumé : Herbivores can exert a controlling effect on the reproduction and growth of shrubs, thereby counter-acting the climate-driven encroachment of shrubs in the Arctic and the potential consequences. This control is particularly evident in the case of abundant herbivores, such as reindeer (Rangifer tarandus tarandus), whose grazing patterns are affected by management. Here, we tested how different reindeer grazing practices on the border between Finland and Norway impact the occurrence of willow (Salix spp.) dominated patches, their above-ground biomass (AGB) and the ability of willows to form dense thickets. We used a combination
of multispectral and RGB imagery obtained from unoccupied aerial vehicles field data and an ensemble of machine-learning models, which allowed us to model the occurrence of plant community types (Overall accuracy = 0.80), AGB fractions (maximum R2 = 0.90) and topsoil moisture (maximum R2 = 0.89). With this combination of approaches, we show that willows are kept in a browsing-trap under spring and early summer grazing by reindeer, growing mostly small and scattered in the landscape. In contrast, willows under the winter grazing regime formed dense stands, particularly within riparian areas. We confirm this pattern using a random forest willow habitat distribution model based on topographical parameters. The model shows that willow biomass correlated with parameters of optimal habitat quality only in the winter grazing regime and did not respond to the same parameters under spring and summer grazing of reindeer.Lien pérenne : DOI : 10.1002/rse2.337 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=155071
in Remote Sensing in Ecology and Conservation > 9 (2023) . - 687-706Villoslada, Miguel, Ylänne, Henni, Kolari, Tina H. M., Korpelainen, Pasi, Tahvanainen, Teemu, Wolff, Franziska, Kumpula, Timo 2023 Reindeer control over shrubification in subarctic wetlands: spatial analysis based on unoccupied aerial vehicle imagery. Remote Sensing in Ecology and Conservation, 9: 687-706.Documents numériques
Consultable
article (2023)URL
Titre : UAV and field hyperspectral imaging for Sphagnum discrimination and vegetation modelling in Finnish aapa mires Type de document : Imprimé Auteurs : Franziska Wolff ; Sandra Lorenz ; Pasi Korpelainen ; Anette Etner ; Timo Kumpula Année de publication : 2024 Langues : Anglais (eng) Catégories : [CBNPMP-Thématique] Télédétection Mots-clés : Sphagnum Résumé : Detailed knowledge of vegetation patterns allows to evaluate mire ecosystems and their dynamics. The use of hyperspectral information has the benefits of exploring spectral characteristics of species and vegetation modelling. Our study employed multi-scale and multi-source hyperspectral imaging with a handheld camera in the field and an UAV (Unoccupied Aerial Vehicle) sensor covering the wavelengths of 400 – 1000 nm. Plot-level spectra acquired with a UAV and field spectra collected at 1 m height were combined to develop a spectral library for Sphagnum moss species. This library was then used to map dominant Sphagnum species in a Finnish Aapa mire complex using the Spectral Angle Mapper (SAM) classifier. Classification performance assessment was supported by calculating a water index from the UAV-information. Additionally, we examined the transferability of sitespecific spectral libraries to an aapa mire with similar vegetation. The results showed little spectral variation in the plot spectrum between the sensors. A fusion of species- and plot-level libraries yielded the highest accuracy of 62 %. For both mires, there was a great variation among the class accuracies. Floating mosses had an accuracy of 86 %, followed by lawn-forming Sphagnum balticum with 77 %. For the test site, the latter species was mapped with an accuracy of 59 %. Red moss species achieved low accuracies of 45 % and 38 %, likely due to effects from sub-pixel and mixed-pixel effects of neighbouring graminoid species and the presence of litter. This might have also enhanced the contrast of adjacent pixels contributing to spectral alterations. Water table depth measurements and the water index revealed a hydrological preference for most species, with classification performance notably improving with higher water index values. We recommend collecting on-site hyperspectral information at varying hydrological circumstances to build a comprehensive spectral library for mire vegetation and modelling. Lien pérenne : DOI : 10.1016/j.jag.2024.104201 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=155065
in International journal of applied earth observation and geoinformation > 134 (2024)Wolff, Franziska, Lorenz, Sandra, Korpelainen, Pasi, Etner, Anette, Kumpula, Timo 2024 UAV and field hyperspectral imaging for Sphagnum discrimination and vegetation modelling in Finnish aapa mires. International journal of applied earth observation and geoinformation, 134.Documents numériques
Consultable
article (2024)Adobe Acrobat PDF
