Corn 3D Reconstruction for Remote Sensing Validation

Wuming Zhang 1, 2, 3 +, Haoxing Wang 1, 2, 3, Guoqing Zhou 1, 2, 3 and Guangjian Yan 1, 2, 3 
1 School of Geography, Beijing Normal University
2 State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and  Institute of Remote Sensing Applications of Chinese Academy of Sciences, Beijing, China
Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing, China

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 have some drawbacks, for example the instrument is expensive, or the operation is time consuming and labour intensive. Towards the features of corn, an image-based method is proposed to avoid these limitations. On the basis of photogrammetry, a 3D corn model is reconstructed from captured images. Then accurate leaf areas and leaf directions can be measured on this 3D model. The topics about expanding individual measurement to group measurement and its application in remote sensing LAI inversion and validation are also discussed.

Keywords: corn, leaf area, three-dimensional reconstruction, remote sensing validation

In: Wan, Y. et al. (eds) Proceeding of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, World Academic Union (Press).

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