Based on deep learning, a desertification grassland classification (DGC) and three-dimensional convolution neural network (3D-CNN) model is established. The F-norm2 paradigm is used to reduce the data; the data volume was effectively reduced while ensuring the integrity of the spatial information. Through structure and parameter optimization, the accuracy of the model is further improved by 9.8%, with an overall recognition accuracy of the optimized model greater than 96.16%. Accordingly, high-precision classification of desert grassland features is achieved, informing continued grassland remote sensing research.
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Q. G. Zhao, G. Q. Huang, and Y. Q. Ma, Acta Ecol. Sin., 36, No. 19, 6328–6335 (2016).
Q. M. Pan, J. G. Xue, and T. Jin, Chin. Sci. Bull., 63, No. 17, 1642–1650 (2018).
Y. F. Bai, Q. M. Pan, and Q. Xing, Chin. Sci. Bull., 61, No. 2, 201–212 (2016).
Y. Yan, Y. F. Chen, and G. C. Zhao, Geol. Exploration., 55, No. 2, 630–640 (2019).
D. Han, H. Z. Wang, B. Y. Zheng, and F. Wang, Acta Ecol. Sin.,38, No. 18, 6655–6663 (2018).
Z. H. Gao, B. P. Sun, and G. D. Ding, J. Desert Res., 84, No. 1, 19–24 (2017).
X.-Q. Wei, X.-F. Gu, Q.-Y. Meng, T. Yu, K. Jia, Y.-L. Zhan, and Ch.-M. Wang, J. Appl. Spectrosc., No. 5, 829–836 (2017).
D. Tuia, C. Persello, and L. Bruzzone, IEEE Geosci. Rem. Sens. Magn., 4, 41–57 (2016).
R. R. Wan, P. Wang, and X. L. Wang, J. Appl. Rem. Sens., 12, No. 4, 046029 (2018).
Q. L. Niu, H. K. Feng, and G. J. Yang, Trans. Chin. Soc. Agric. Eng., 34, No. 5, 73–82 (2018).
C. Gevaert, J. Suomalainen, and J. Tang, IEEE J. Sel. Top. Appl. Earth Obs., 8, 3140–3146 (2015).
G. E. Hinton, N. Srivastava, and A. Krizhevsky, Neural Comput., 18, No. 3, 1527–1554 (2006).
L. M. Dang and S. Hassan, Expert Syst. Appl., 9, No. 1, 156–168 (2019).
H. Chen, Y. Sun, and X. L. Li, Neurocomputing, 9, No. 356, 83–96 (2019).
A. Krizhevsky, I. Sutskever, and G. E. Hinton, Commun. ACM, 60, No. 6, 84–90 (2017).
Q. Zou, L. H. Ni, and T. Zhang, IEEE Geosci. Rem. Sens. Lett., 12, No. 11, 2321–2325 (2015).
X. R. Ma, H. Y. Wang, and J. Geng, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 3282–3285 (2016).
Y. Li, H. K. Zhang, and X. Z. Xue, Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery, 8, No. 6 (2018).
L. Samaniego, A. Bardossy, and K. Schulz, IEEE Trans. Geosci. Rem. Sens., 46, No. 7, 2112–2125 (2008).
J. Li, J. M. Bioucas-Dias, and A. Plaza, IEEE Trans. Geosci. Rem. Sens., 48, No. 11, 4085–4098 (2010).
Y. Li, H. K. Zhang, and Q. Shen, Rem. Sens., 9, No. 1, 67 (2017).
J. Yue, S. J. Mao, and M. Li, Rem. Sens. Lett., 7, No. 9, 875–884 (2016).
Y. Chen, X. Zhao, and X. Jia, IEEE J. Sel. Top. Appl. Earth Observ. Rem. Sens., 8, No. 6, 2381–2392 (2015).
Y. S. Chen, Z. H. Lin, and X. Zhao, IEEE J. Sel. Top. Appl. Earth Observ. Rem. Sens., 7, No. 6, 2094–2107 (2014).
X. F. Liu, Q. Q. Sun, and Y. Meng, Rem. Sens., 10, No. 9, 1425 (2018).
Y. X. Jin, F, Liu, and J. Zhang, Chin. J. Plant Ecol., 42, No. 3, 361–371 (2018).
Z. B. Xie, P. Wu, and G. D. Han, J. Agric. Mech. Res., 35, No. 2, 189–191, 196 (2013).
S. W. Ji, W. Xu, and M. Yang, IEEE Trans. Pattern Anal. Mach. Intel.,35, 221–231 (2013).
W. Zhao and H. Zhang, Proc. 2012 Int. Conf. Computer Science and Electronics Engineering (ICCSEE 2012), 23–25 March 2012, 88–391 (2012).
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Published in Zhurnal Prikladnoi Spektroskopii, Vol. 87, No. 2, pp. 296–305, March–April, 2020.
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Pi, W., Du, J., Liu, H. et al. Desertification Glassland Classification and Three-Dimensional Convolution Neural Network Model for Identifying Desert Grassland Landforms with Unmanned Aerial Vehicle Hyperspectral Remote Sensing Images. J Appl Spectrosc 87, 309–318 (2020). https://doi.org/10.1007/s10812-020-01001-6
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DOI: https://doi.org/10.1007/s10812-020-01001-6