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A modeling-based approach for soil frost detection in the northern boreal forest region with C-Band SAR / Juval Cohen in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 2 (February 2019) . - pp 1069 - 1083 Titre : A modeling-based approach for soil frost detection in the northern boreal forest region with C-Band SAR Type de document : Article/Communication Auteurs : Juval Cohen, Auteur ; Kimmo Rautinainen, Auteur ; Jaakko Ikonen, Auteur Année de publication : 2019 Article en page(s) : pp 1069 - 1083 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] Betula (genre) [Termes IGN] état du sol [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] podzosol Résumé : (Auteur) This paper presents a new approach for monitoring soil frost in the northern boreal forest region using co-polarized C-band synthetic aperture radar (SAR) data. Due to the high sensitivity of the C-band signal to vegetation, estimating the soil freeze/thaw (F/T) state directly from the measured backscatter is not feasible over dense vegetation, such as boreal forests. The presented method is based on applying a simple zeroth-order model to estimate the contribution of the ground and the forest canopy on the observed total backscatter. The retrieved ground and canopy backscatter values were compared with in situ information on soil F/T state. By using a linear least sum of square errors classification algorithm, the retrieved ground and canopy backscatter values representing frozen and thawed ground were successfully separated. The method was tested for various soil types and incidence angles. For soil types with higher water holding capacities and lower infiltration rates such as fine Haplic Podzol and Umbric Gleysol, the estimation accuracy of the F/T state was over 97%, whereas for drier, well-drained soil types such as Haplic Arenosol and Coarse Haplic Podzol it was over 94%. Estimation accuracy slightly increased with higher incidence angle. The method is not feasible in rocky terrain due to very low water content, or in wet snow conditions due to lack of penetration of the C-band SAR signal through wet snow. With low ancillary data and computational requirements, the proposed method is applicable for continuous near real-time monitoring of soil F/T state. Numéro de notice : A2019-111 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2864635 Date de publication en ligne : 17/09/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2864635 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92450 [article]