22 October 2010 Tree crown detection in high resolution optical and lidar images of tropical forest
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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. Results are encouraging provided that crown sizes sufficiently large compared to 1m pixels.
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Jia Zhou, Jia Zhou, Christophe Proisy, Christophe Proisy, Xavier Descombes, Xavier Descombes, Ihssen Hedhli, Ihssen Hedhli, Nicolas Barbier, Nicolas Barbier, Josiane Zerubia, Josiane Zerubia, J. P. Gastellu-Etchegorry, J. P. Gastellu-Etchegorry, Pierre Couteron, Pierre Couteron, "Tree crown detection in high resolution optical and lidar images of tropical forest", Proc. SPIE 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 78240Q (22 October 2010); doi: 10.1117/12.865068; https://doi.org/10.1117/12.865068

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