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TanDEM-X digital surface models in boreal forest above-ground biomass change detection / Kirsi Karila in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 148 (February 2019) . - pp 174 - 183 Titre : TanDEM-X digital surface models in boreal forest above-ground biomass change detection Type de document : Article/Communication Auteurs : Kirsi Karila, Auteur ; Xiaowei Yu, Auteur ; Mikko Vastaranta, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 174 - 183 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] biomasse aérienne [Termes IGN] biomasse forestière [Termes IGN] densité de la végétation [Termes IGN] détection de changement [Termes IGN] données localisées 3D [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] hauteur des arbres [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] MNS TerraSAR & TanDEM-X [Termes IGN] modèle numérique de surface Résumé : (Auteur) Satellite images provide spatially explicit information on forest change covering wide areas. In this study, bistatic TanDEM-X (TDX) synthetic aperture radar (SAR) satellite data were used to derive digital surface models (DSMs) of forest areas using SAR interferometry (InSAR). The capability of change features derived from bi-temporal InSAR DSMs to detect forest height (90th percentile of canopy height distribution, H90) and density variations was investigated. Moreover, changes in the forest above-ground biomass (AGB) were estimated from height changes between two InSAR DSMs. Bi-temporal airborne laser scanning (ALS) data, aerial orthoimages and an ALS-based AGB change map from a study area in Southern Finland were used as references. The results indicate that the InSAR height change of a forested area correlates more with vegetation density change than with height change. The correlation between the InSAR mean height change and the height change feature from ALS was 0.76 at stand level. Correspondingly, the correlation between the InSAR mean height change and the ALS penetration rate change was 0.89. The AGB changes predicted based on InSAR height change agreed well with the reference data; the root-mean-square error (RMSE) was 20.7 Mg/ha (18.5% of the mean biomass in 2012) at stand level and 27.4 Mg/ha (27.0%) for 16 × 16 m grid cells. The results show that TDX DSMs can be used to detect biomass changes of different orders of magnitude, e.g. due to logging and thinning. Numéro de notice : A2019-073 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.002 Date de publication en ligne : 11/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.002 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92160 [article]

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Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating / Leena Matikainen in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 128 (June 2017) . - pp 298 - 313 Titre : Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating Type de document : Article/Communication Auteurs : Leena Matikainen, Auteur ; Kirsi Karila, Auteur ; Juha Hyyppä, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 298 - 313 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse d'image orientée objet [Termes IGN] classification dirigée [Termes IGN] image 3D [Termes IGN] image multibande [Termes IGN] instrumentation Optech [Termes IGN] mise à jour cartographique [Termes IGN] occupation du sol [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté Résumé : (Auteur) During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are no shadows on intensity images produced from the data. These are significant advantages in developing automated classification and change detection procedures. Numéro de notice : A2017-336 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.04.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.04.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85499 [article]

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081-2017062	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt