Tree crown detection in high resolution optical and LiDAR images of tropical forest - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2010

Tree crown detection in high resolution optical and LiDAR images of tropical forest

Abstract

Tropical forests are complex ecosystems where the potential of remote sensing has not yet been fully realized. The increasing availability of satellite metric imagery along with canopy altimetry from airborne LiDAR open new prospects to detect individual trees. For this objective, we optimized, calibrated and applied a model based on marked point processes to detect trees in high biomass mangroves of French Guiana by considering a set of 1m pixel images including 1) panchromatic images from the IKONOS sensor 2) LiDAR-derived canopy 2D altimetry and 3) reflectance panchromatic images simulated by the DART-model. The relevance of detection is then discussed considering: (i) the agreement in space of detected crown centers locations with known true locations for the DART images and also the detection agreement for each pair of IKONOS and LiDAR images, and (ii) the comparison between the frequency distributions of the diameters of the detected crowns and of the tree trunks measured in the field. Both distributions are expected to be related due to the allometry relationships between trunk and crown.
Fichier principal
Vignette du fichier
Tree_crown_detection_in_high_resolution_optical_and_LIDAR_images_of_tropical_forest.pdf (1.16 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00534791 , version 1 (10-11-2010)

Identifiers

Cite

Jia Zhou, Christophe Proisy, Xavier Descombes, Ihssen Hedhli, Nicolas Barbier, et al.. Tree crown detection in high resolution optical and LiDAR images of tropical forest. Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, Sep 2010, Toulouse, France. ⟨10.1117/12.865068⟩. ⟨inria-00534791⟩
770 View
474 Download

Altmetric

Share

Gmail Facebook X LinkedIn More