High resolution radargrammetry with COSMO-SkyMed, TerraSAR-X and RADARSAT-2 imagery: development and implementation of an image orientation model for Digital Surface Model generation
Notice bibliographique
Résumé
Digital Surface and Terrain Models (DSM/DTM) have large relevance in several territorial applications, such as topographic mapping, monitoring engineering, geology, security, land planning and management of Earth's resources. The satellite remote sensing data offer the opportunity to have continuous observation of Earth's surface for territorial application, with short acquisition and revisit times. Meeting these requirements, the SAR (Synthetic Aperture Radar) high resolution satellite imagery could offer night-and-day and all-weather functionality (clouds, haze and rain penetration). Two different methods may be used in order to generate DSMs from SAR data: the interferometric and the radargrammetric approaches. The radargrammetry uses only the intensity information of the SAR images and reconstructs the 3D information starting from a couple of images similarly to photogrammetry. Radargrammetric DSM extraction procedure consists of two basic steps: the stereo pair orientation and the image matching for the automatic detection of homologous points. The goal of this work is the definition and the implementation of a geometric model in order to orientate SAR imagery in zero Doppler geometry. The radargrammetric model implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione - developed at the Geodesy and Geomatic Division - University of Rome "La Sapienza") is based on the equation of radar target acquisition and zero Doppler focalization Moreover a tool for the SAR Rational Polynomial Coefficients (RPCs) generation has been implemented in SISAR software, similarly to the one already developed for the optical sensors. The possibility to generate SAR RPCs starting from a radargrammetric model sounds of particular interest since, at present, the most part of SAR imagery is not supplied with RPCs, although the RPFs model is available in several commercial software. Only RADARSAT-2 data are supplied with vendors RPCs. To test the effectiveness of the implemented RPCs generation tool and the SISAR radargrammetric orientation model the reference results were computed: the stereo pairs were orientated with the two model. The tests were carried out on several test site using COSMO-SkyMed, TerraSAR-X and RADARSAT-2 data. Moreover, to evaluate the advantages and the different accuracy between the orientation models computed without GCPs and the orientation model with GCPs a Monte Carlo test was computed. At last, to define the real effectiveness of radargrammetric technique for DSM extraction and to compare the radrgrammetric tool implemented in a commercial software PCI-Geomatica v. 2012 and SISAR software, the images acquired on Beauport test site were used for DSM extraction. It is important underline that several test were computed. Part of this tests were carried out under the supervision of Prof. Thierry Toutin at CCRS (Canada Centre of Remote Sensing) where the PCI-Geomatica orientation model was developed, in order to check the better parameters solution to extract radargrammetric DSMs. In conclusion, the results obtained are representative of the geometric potentialities of SAR stereo pairs as regards 3D surface reconstruction.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».