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Fusing interferometric radar and Laser altimeter data to estimate surface topography and vegetation heights / K.C. Slatton in IEEE Transactions on geoscience and remote sensing, vol 39 n° 11 (November 2001)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 39 n° 11 (November 2001) . - pp 2470 - 2482 Titre : Fusing interferometric radar and Laser altimeter data to estimate surface topography and vegetation heights Type de document : Article/Communication Auteurs : K.C. Slatton, Auteur ; Melba M. Crawford, Auteur ; B.L. Evans, Auteur Année de publication : 2001 Article en page(s) : pp 2470 - 2482 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] couvert végétal [Termes IGN] données lidar [Termes IGN] données multiéchelles [Termes IGN] filtre de Kalman [Termes IGN] fusion de données [Termes IGN] hauteur des arbres [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] lasergrammétrie [Termes IGN] modèle de diffusion du rayonnement [Termes IGN] modèle numérique de sursol [Termes IGN] problème inverse [Termes IGN] télémétrie laser aéroporté Résumé : (Auteur) Interferometric synthetic aperture radar (INSAR) and laser altimeter (LIDAR) systems are both widely used for mapping topography. INSAR can map extended areas but accuracies are limited over vegetated regions, primarily because the observations are not measurements of true surface topography. The measurements correspond to a height above the true surface that depends on both the sensor and the vegetation. Conversely, topography from LIDAR is very accurate, but coverage is limited to smaller regions. We demonstrate how these technologies can be used synergistically. First, we determine surface elevations and vegetation heights from dual-baseline INSAR data by inverting an INSAR scattering model. We then combine sparse LIDAR observations with the INSAR inversion results to improve the estimates of ground elevations and vegetation heights. This is accomplished via a multiresolution Kalman Filter that provides both the estimates and a measure of their uncertainty at each location. Combining data from the two sensors provides estimates that are more accurate than those obtained from INSAR alone yet have dense, extensive coverage, which is difficult to obtain with LIDAR. Contributions of this work include 1) combining physical modeling with multiscale estimation to accommodate non-linear measurement-state relationships and 2) improving estimates of ground elevations and vegetation heights for remote sensing applications. Numéro de notice : A2001-132 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/36.964984 En ligne : https://doi.org/10.1109/36.964984 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21828 [article]

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