Supervision : Matthieu CORD

Detection and Characterisation of Vegetation in Urban Areas from High Resolution Aerial Imagery

Automatic 3D reconstruction of urban areas is an active research topic in distinct application areas and an issue of primary importance in fields such as urban planning, disaster management, or telecommunications planning. Significant progress has been made in recent years concerning the automatic reconstruction of man-made objects or environments from multiple aerial images. Yet, a lot of challenge concerning the modelling of other objects present on the terrain surface, such as trees, shrubs, hedges, or lawns still exists. An accurate reconstruction of such types of vegetation areas is a challenge due to their complex nature and to their intricate distribution between man-made objects in dense urban areas. This thesis presents an image analysis system for vegetation detection and characterization from high resolution colour infrared aerial imagery for 3D city modelling. The aim of the system’s first module is to extract vegetation areas. The approach developed is based on a Support Vector Machines (SVM) classifier and its performances are compared to traditional remote sensing methods for vegetation detection. The system’s following modules aim at characterising vegetation areas thus identified, according to their morphology. Separation into high- (tree) and low- (lawn) height vegetation areas is based on texture characteristics computed on the digital surface model (DSM). Individual tree crown delineation is performed by using a region-growing algorithm based on geometrical characteristics of trees. 3D morphological characteristics (height, crown diameter, tree trunk position) are estimated for each tree crown. A supervised classification to characterise each tree by its species is performed on each tree crown. The set of parameters extracted by each of the modules are used to enrich 3D city models by virtual realistic tree models.

2007-2014 Publications

• 2014
  • C. Iovan, P.‑H. Cournède, Th. Guyard, B. Bayol, D. Boldo, M. Cord : “Model-Based Analysis-Synthesis for Realistic Tree Reconstruction and Growth Simulation”, IEEE Transactions on Geoscience and Remote Sensing, vol. 52 (2), pp. 1438-1450, (Institute of Electrical and Electronics Engineers) (2014)
• 2012
  • C. Iovan, D. Picard, N. Thome, M. Cord : “Classification of Urban Scenes from Geo-referenced Images in Urban Street-View Context”, Machine Learning and Applications (ICMLA), 2012 11^th International Conference on, vol. 2, Boca Raton, Florida, United States, pp. 339-344 (2012)
• 2009
  • C. Iovan : “Détection et caractérisation de la végétation en milieu urbain à partir d’images aériennes haute résolution”, thesis, phd defence 11/30/2009, supervision Cord, Matthieu (2009)
• 2008
  • C. Iovan, D. Boldo, M. Cord : “Detection, Characterization and Modeling Vegetation in Urban Areas from High Resolution Aerial Imagery”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 1 (3), pp. 206-213, (IEEE) (2008)
  • C. Iovan, D. Boldo, M. Cord : “Detection, segmentation and characterisation of vegetation in high-resolution aerial images for 3d city modelling”, XXI ISPRS Congress, Beijin, China, pp. 247-252 (2008)
• 2007
  • C. Iovan, D. Boldo, M. Cord, M. Erikson : “Automatic Extraction and Classication of Vegetation Areas from High Resolution Images in Urban Areas”, Scandinavian Conference on Artificial Intelligence, vol. 4522, Lecture Notes in Computer Science, Aalborg, Denmark, pp. 858-867, (Springer) (2007)
  • C. Iovan, D. Boldo, M. Cord : “Automatic Extraction of urban vegetation structures from High Resolution Imagery and digital elevation models”, Urban Remote Sensing Joint Event, Paris, France, pp. 1-5, (IEEE) (2007)