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Auteur Fabian E. Fassnacht |
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Synergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status / Johannes Schmidt in Remote sensing in ecology and conservation, vol 4 n° 3 (September 2018)
[article]
Titre : Synergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status Type de document : Article/Communication Auteurs : Johannes Schmidt, Auteur ; Fabian E. Fassnacht, Auteur ; Michael Förster, Auteur ; Sebastian Schmidtlein, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Calluna vulgaris
[Termes IGN] directive européenne
[Termes IGN] état de conservation
[Termes IGN] habitat (nature)
[Termes IGN] image Sentinel-SAR
[Termes IGN] site Natura 2000Résumé : (auteur) Habitat quality assessments often demand wall-to-wall information about the state of vegetation. Remote sensing can provide this information by capturing optical and structural attributes of plant communities. Although active and passive remote sensing approaches are considered as complementary techniques, they have been rarely combined for conservation mapping. Here, we combined spaceborne multispectral Sentinel-2 and Sentinel-1 SAR data for a remote sensing-based habitat quality assessment of dwarf shrub heathland, which was inspired by nature conservation field guidelines. Therefore, three earlier proposed quality layers representing (1) the coverage of the key dwarf shrub species, (2) stand structural diversity and (3) an index reflecting co-occurring vegetation were mapped via linking in situ data and remote sensing imagery. These layers were combined in an RGB-representation depicting varying stand attributes, which afterwards allowed for a rule-based derivation of pixel-wise habitat quality classes. The links between field observations and remote sensing data reached correlations between 0.70 and 0.94 for modeling the single quality layers. The spatial patterns shown in the quality layers and the map of discrete quality classes were in line with the field observations. The remote sensing-based mapping of heathland conservation status showed an overall agreement of 76% with field data. Transferring the approach in time (applying a second set of Sentinel-1 and -2 data) caused a decrease in accuracy to 73%. Our findings suggest that Sentinel-1 SAR contains information about vegetation structure that is complimentary to optical data and therefore relevant for nature conservation. While we think that rule-based approaches for quality assessments offer the possibility for gaining acceptance in both communities applied conservation and remote sensing, there is still need for developing more robust and transferable methods. Numéro de notice : A2018-005 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1002/rse2.68 En ligne : https://doi.org/10.1002/rse2.68 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88738
in Remote sensing in ecology and conservation > vol 4 n° 3 (September 2018)[article]Documents numériques
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Synergetic use of Sentinel-1 and Sentinel-2 - pdf éditeurAdobe Acrobat PDF Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? / Fabian E. Fassnacht in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
[article]
Titre : Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? Type de document : Article/Communication Auteurs : Fabian E. Fassnacht, Auteur ; Daniel Mangold, Auteur ; Jannika Schäfer, Auteur ; Markus Immitzer, Auteur Année de publication : 2017 Article en page(s) : pp 613 - 631 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] biomasse forestière
[Termes IGN] densité de la végétation
[Termes IGN] données lidar
[Termes IGN] espèce végétale
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The estimation of various forest inventory attributes from high spatial resolution airborne remote sensing data has been widely examined and proved to be successful at the experimental level. Nevertheless, the operational use of these data in automated procedures to support forest inventories and forest management is still limited to a small number of cases. The reasons for this are high data costs, limited availability of remote sensing data over large areas and resistance from practitioners. In this review the main aim is to stimulate debate about spaceborne very high resolution stereo-imagery (VHRSI) as an alternative to airborne remote sensing data by presenting: (1) a case study on the retrieval of stand density, aboveground biomass and tree species using a set of easy-to-calculate variables obtained from VHRSI data combined with image processing and nonparametric classification and modelling approaches; and (2) the results of an expert opinion survey on the potential of VHRSI as compared with Light Detection and Ranging (LiDAR), hyperspectral and airborne digital imagery to derive a range of forest inventory attributes. In the case study, stand density was estimated with r² = 0.71 and RMSE = 156 trees (rel./norm. RMSE = 24.9 per cent/12.4 per cent), biomass with r² = 0.64 and RMSE of 36.7 t/ha (rel./norm. RMSE = 20.0 per cent/12.8 per cent) while tree species classifications with five species reached overall accuracies of 84.2 per cent (kappa = 0.81). These results were comparable to earlier studies in the same test site, obtained with more expensive airborne acquisitions. Expert opinions were more diverse for VHRSI and aerial photographs (Shannon index values of 0.94 and 0.97) than for LiDAR and hyperspectral data (Shannon index values 0.69 and 0.88). In our opinion, this reflects the current state-of-the-art in the application of VHRSI for automatically retrieving forest inventory attributes. The number of studies using these data is still limited, and the full potential of these datasets is not yet completely explored. Compared with LiDAR and hyperspectral data, which both mostly received high scores for forest inventory products matching the sensor systems’ strengths, VHRSI and aerial photographs received more homogeneous scores indicating their potential as multi-purpose instruments to collect forest inventory information. In summary, considering the simpler acquisition, reasonable price and the comparably easy data format and handling of VHRSI compared with other sensor types, we recommend further research on the application of these data for supporting operational forest inventories. Numéro de notice : A2017-902 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx014 En ligne : https://doi.org/10.1093/forestry/cpx014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93196
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 613 - 631[article]