Image-based 3D corn reconstruction for retrieval of geometrical structural parameters

Abstract

Ground-based leaf area and leaf direction measurements are crucial for remote sensing validation of leaf area index (LAI) and leaf angle distribution (LAD) products. The existing methods, such as use of the expensive instruments and/or time-consuming and labour-intensive field operations, have led to scientists investigating advanced methods. For this reason an image-based method for measuring the leaf characteristics of corn is presented to avoid the limitations mentioned above. With application of photogrammetric techniques, a three-dimensional corn model is reconstructed from captured images, and accurate leaf areas and leaf directions are measured on the basis of the 3D model. The accuracy of the proposed method is assessed by comparing the results from the 3D model with that measured by tape in the field. The experimental results show that the proposed method is feasible and effective. The proposed method can save time and labour.

Acknowledgements

This work is supported by the National Natural Science Foundation of China Grant under numbers 40801131, 40701119 and J0630532. The work is also supported by the opening foundation of the State Key Laboratory of Remote Sensing Science, PR China.