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Urban Tree Species Mapping Using Airborne LiDAR and Hyperspectral Data

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Abstract

In this study the high-spatial resolution (0.5 m) hyperspectral imagery with LiDAR data were fused at tree crown object level to classify 8 common tree species in Anyang, Henan, China. First, vertical forest features were extracted from LiDAR point clouds resulting in a canopy height model (CHM), followed by the acquisition of tree crown object (TCO) information from the CHM using a mean shift algorithm. Then, the CHM was combined with a minimum noise fraction transformation (MNF) and enhanced vegetation index (EVI), which were extracted from hyperspectral images. These combined features were used as the input to the SVM to produce a rough classification scheme for different tree species. Finally, a majority voting method was applied to the TCO to produce the final tree species map. The experiment showed that a combination of CHM-spatial-spectral features to classify tree species led to higher accuracy when compared to using only MNF features in the pixel-wise classification. However, the CHM and EVI features had their own limitations, largely depending on different characteristics of the different tree species.

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Acknowledgments

The authors would like to thank Luxia Liu for providing detailed information about the tree species in the research area. This research was supported by National Natural Science Foundation of China (grant No. 41501365).; the Fundamental Research Funds for the Central Universities under grant number 2014QC018; and Key Laboratory for National Geographic Census and Monitoring, National Administration of Surveying, Mapping and Geoinformation under grant number 2013NGCM05.

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Authors and Affiliations

  1. College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, China

    Yuanyong Dian

  2. Institute of Forest Resources Information Techniques, Chinese Academy of forest Sciences, Beijing, 100091, China

    Yuanyong Dian, Yong Pang & Zengyuan Li

  3. Institute of Earthquake Science, China Earthquake Administration, Beijing, 100036, China

    Yanfang Dong

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  1. Yuanyong Dian
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  2. Yong Pang
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  4. Zengyuan Li
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Correspondence to Yuanyong Dian.

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Dian, Y., Pang, Y., Dong, Y. et al. Urban Tree Species Mapping Using Airborne LiDAR and Hyperspectral Data. J Indian Soc Remote Sens 44, 595–603 (2016). https://doi.org/10.1007/s12524-015-0543-4

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  • DOI: https://doi.org/10.1007/s12524-015-0543-4

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