ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-2/W7
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W7, 205–210, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W7-205-2019
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W7, 205–210, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W7-205-2019

  16 Sep 2019

16 Sep 2019

TREE DROUGHT STRESS DETECTION BASED ON 3D MODELLING

Y. Xia, J. Tian, P. d’Angelo, and P. Reinartz Y. Xia et al.
  • German Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, Germany

Keywords: Tree, 3D Modelling, Semi-Global Matching, Convolutional Neural Networks, Drought Detection, Deformation

Abstract. Precise and detailed reconstruction of 3D plant models is an important goal in computer vision. Based on these models, important parameters can be extracted, which would be very useful for monitoring the tree health situation. This paper has firstly constructed the 3D plant model based on MC-CNN using close-range photogrammetric imagery, and then applied a leaf index based segmentation to highlight the leaves region. In the end, the 3D model of each leaf can be represented and some geometric parameters of the leaf are designed and analyzed to predict the drought status. The experiments on real close-range stereo imagery justified the performance of the proposed approach to differentiate drought and healthy leaves.