The way of representing Earth has changed; two dimensional (2D) maps have turned into three Dimensional (3D) representations. There are many studies in order to create 3D city maps as well as areas where these are applied such as 3D cadastral, 3D visualization and flood simulation, etc. These can be created with the aid of different data sources using photogrammetric Digital Surface Model (DSM) derived from image matching and from Light Detection and Ranging (LiDAR) point clouds or both of them combining orthophotos and building footprints. Several software has been developed to ease and speed up this process. In this study, a current state-of-the art in the 3D city modeling with particular interest to commercial software was analyzed. DSMs from image matching (Satellite and Airborne) were used in order to create a 3D city model of Trento, Italy. The objectivewas to examine the degree of automation and the computation time of two available software: Feature Manipulation Engine (FME) and Building Reconstruction (BREC). Other problem such as the quality of the DSM needed would be discussed for each software and the results would be compared to those achieved using LiDAR data. Recommendations and possible problems would also be addressed. In order to create a 3D city model, the ALDPAT software (Airborne LiDAR Data Processing and Analysis Tool) has been used to separate the ground regions (Digital Terrain Model, DTM) from the man-made objects and trees (Normal Digital Surface Model, nDSM). FME and BREC software have been used to reconstruct the 3D city model. The output results from FME and BREC have been analyzed qualitatively and quantitatively. The comparison between the models generated from photogrammetric and LiDAR DSMs have been performed. The results show that buildings generated by satellite images have poorest quality compared with buildings from LiDAR and airborne data. In particular, the performed tests will be shown that among the Level of Details (LoD), a LoD1 and LoD2 3D city models can be generated using a DSM by image matching. A deeper study should be done in order to analyze the level of detail qualitatively.

The aim of this work is to develop research on 3D building modeling. In particular, the research in aerial-based 3D building reconstruction is a topic very developed since 1990. However, it is necessary to pursue the research since the actual approaches for 3D massive building reconstruction (although efficient) still encounter problems in generalization, coherency, accuracy. Besides, the recent developments of street acquisition systems such as Mobile Mapping Systems open new perspectives for improvements in building modeling in the sense that the terrestrial data (very dense and accurate) can be exploited with more performance (in comparison to the aerial investigation) to enrich the building models at facade level (e.g., geometry, texturing).Hence, aerial and terrestrial based building modeling approaches are individually proposed. At aerial level, we describe a direct and featureless approach for simple polyhedral building reconstruction from a set of calibrated aerial images. At terrestrial level, several approaches that essentially describe a 3D urban facade modeling pipeline are proposed, namely, the street point cloud segmentation and classification, the geometric modeling of urban facade and the occlusion-free facade texturing

L'objectif principal de ce travail est le développement de recherches en modélisation 3D du bâti. En particulier, la recherche en reconstruction 3D de bâtiment est un sujet très développé depuis les années 90. Malgré tout, il paraît nécessaire de poursuivre les recherches dans cet axe étant données que les approches actuelles consacrées à la reconstruction 3D de bâtiment (bien qu'efficaces) rencontrent encore des difficultés en terme de généralisation, de cohérence et de précision. Par ailleurs, les récents développements des systèmes d'acquisitions de rues tel que les systèmes de cartographie mobile ouvrent de nouvelles perspectives d'amélioration de la modélisation des bâtiments dans le sens ou les données terrestres (très précises et résolus) peuvent être exploitées avec davantage de cohérence (en comparaison à l'aérien) pour enrichir les modèles de bâtiments au niveau des façades (la géométrie, la texture).Ainsi, des approches de modélisation aériennes et terrestres sont individuellement proposées. Au niveau aérien, nous décrivons une approche directe et dépourvu d'extraction et d'assemblage de primitives géométriques en vue de la reconstruction 3D de modèles polyédriques simples de bâtiments à partir d'un jeu d'images aériennes calibrées. Au niveau terrestre, plusieurs approches qui décrivent essentiellement un pipeline pour la modélisation 3D des façades urbaines sont proposées; à savoir, la segmentation et classification de nuage de rues urbaines, la modélisation géométrique des façades urbaines et le texturage des façades urbaines comportant des occultations causées par d'autres objets du mobilier urbains / The aim of this work is to develop research on 3D building modeling. In particular, the research in aerial-based 3D building reconstruction is a topic very developed since 1990. However, it is necessary to pursue the research since the actual approaches for 3D massive building reconstruction (although efficient) still encounter problems in generalization, coherency, accuracy. Besides, the recent developments of street acquisition systems such as Mobile Mapping Systems open new perspectives for improvements in building modeling in the sense that the terrestrial data (very dense and accurate) can be exploited with more performance (in comparison to the aerial investigation) to enrich the building models at facade level (e.g., geometry, texturing).Hence, aerial and terrestrial based building modeling approaches are individually proposed. At aerial level, we describe a direct and featureless approach for simple polyhedral building reconstruction from a set of calibrated aerial images. At terrestrial level, several approaches that essentially describe a 3D urban facade modeling pipeline are proposed, namely, the street point cloud segmentation and classification, the geometric modeling of urban facade and the occlusion-free facade texturing

La modélisation automatique de villes à partir d’images satellites est l'un des principaux défis en lien avec la reconstruction urbaine. Son objectif est de représenter des villes en 3D de manière suffisamment compacte et précise. Elle trouve son application dans divers domaines, qui vont de la planification urbaine aux télécommunications, en passant par la gestion des catastrophes. L'imagerie satellite offre plusieurs avantages sur l'imagerie aérienne classique, tels qu'un faible coût d'acquisition, une couverture mondiale et une bonne fréquence de passage au-dessus des sites visités. Elle impose toutefois un certain nombre de contraintes techniques. Les méthodes existantes ne permettent que la synthèse de DSM (Digital Surface Models), dont la précision est parfois inégale. Cette dissertation décrit une méthode entièrement automatique pour la production de modèles 3D compacts, précis et répondant à une sémantique particulière, à partir de deux images satellites en stéréo. Cette méthode repose sur deux grands concepts. D'une part, la description géométrique des objets et leur assimilation à des catégories génériques sont effectuées simultanément, conférant ainsi une certaine robustesse face aux occlusions partielles ainsi qu'à la faible qualité des images. D'autre part, la méthode opère à une échelle géométrique très basse, ce qui permet la préservation de la forme des objets, avec finalement, une plus grande efficacité et un meilleur passage à l'échelle. Pour générer des régions élémentaires, un algorithme de partitionnement de l'image en polygones convexes est présenté. / Automatic city modeling from satellite imagery is one of the biggest challenges in urban reconstruction. The ultimate goal is to produce compact and accurate 3D city models that benefit many application fields such as urban planning, telecommunications and disaster management. Compared with aerial acquisition, satellite imagery provides appealing advantages such as low acquisition cost, worldwide coverage and high collection frequency. However, satellite context also imposes a set of technical constraints as a lower pixel resolution and a wider that challenge 3D city reconstruction. In this PhD thesis, we present a set of methodological tools for generating compact, semantically-aware and geometrically accurate 3D city models from stereo pairs of satellite images. The proposed pipeline relies on two key ingredients. First, geometry and semantics are retrieved simultaneously providing robust handling of occlusion areas and low image quality. Second, it operates at the scale of geometric atomic regions which allows the shape of urban objects to be well preserved, with a gain in scalability and efficiency. Images are first decomposed into convex polygons that capture geometric details via Voronoi diagram. Semantic classes, elevations, and 3D geometric shapes are then retrieved in a joint classification and reconstruction process operating on polygons. Experimental results on various cities around the world show the robustness, scalability and efficiency of the proposed approach.