Intelligent Evaluation Method of Grottoes Surface Weathering Based on Multispectral Imaging and Random Forest Algorithm

Chipeng Cao; Huiqin Wang; Ke Wang; Zhan Wang; Gang Zhang; Tao Ma

doi:10.3788/AOS202040.2230001

[1] Chai B L, Su B M, Zhang W Y et al. Standard multispectral image database for paint materials used in the Dunhuang murals[J]. Spectroscopy and Spectral Analysis, 37, 3289-3306(2017).

[2] Liu R Z, Zhang B J, Zhang H et al. Deterioration of Yungang grottoes: diagnosis and research[J]. Journal of Cultural Heritage, 12, 494-499(2011).

[3] Bruthans J, Filippi M, Schweigstillová J et al. Quantitative study of a rapidly weathering overhang developed in an artificially wetted sandstone cliff[J]. Earth Surface Processes and Landforms, 42, 711-723(2017).

[4] Qin Y, Wang Y H, Li L L et al. Experimental weathering of weak sandstone without direct water participation by using sandstone from the Yungang grottoes in Datong, China[J]. Rock Mechanics and Rock Engineering, 49, 4473-4478(2016).

[5] McAllister D, Warke P, McCabe S. Stone temperature and moisture variability under temperate environmental conditions: implications for sandstone weathering[J]. Geomorphology, 280, 137-152(2017).

[6] Chen W W, Liao R X, Wang N et al. Effects of experimental frost-thaw cycles on sandstones with different weathering degrees: a case from the Bingling Temple Grottoes, China[J]. Bulletin of Engineering Geology and the Environment, 78, 5311-5326(2019).

[7] Ling X, Wu M L, Liao Y et al. Nondestructive techniques in the research and preservation of cultural relics[J]. Spectroscopy and Spectral Analysis, 38, 2026-2031(2018).

[8] Liu S, Tan X, Liu C Y et al. Recognition of fusarium head blight wheat grain based on hyperspectral data processing algorithm[J]. Spectroscopy and Spectral Analysis, 39, 3540-3546(2019).

[9] Xi Z H, Hou C Y, Yuan K P et al. Super-resolution reconstruction of accelerated image based on deep residual network[J]. Acta Optica Sinica, 39, 0210003(2019).

[10] Ma H Q, Ma S P, Xu Y L et al. Low-light image enhancement based on deep convolutional neural network[J]. Acta Optica Sinica, 39, 0210004(2019).

[11] Wu Z H, Gao Y M, Li L et al. Fully convolutional network method of semantic segmentation of class imbalance remote sensing images[J]. Acta Optica Sinica, 39, 0428004(2019).

[12] Zhang H K, Li Y, Jiang Y N. Deep learning for hyperspectral imagery classification: the state of the art and prospects[J]. Acta Automatica Sinica, 44, 961-977(2018).

[13] Wu J F, Jiang Z G, Zhang H P et al. Hyperspectral remote sensing image classification based on semi-supervised conditional random field[J]. Journal of Remote Sensing, 21, 588-603(2017).

[14] Cao X H, Li R J, Ge Y M et al. Densely connected deep random forest for hyperspectral imagery classification[J]. International Journal of Remote Sensing, 40, 3606-3622(2019).

[15] Scott G J, England M R, Starms W A et al. Training deep convolutional neural networks for land-cover classification of high-resolution imagery[J]. IEEE Geoscience and Remote Sensing Letters, 14, 549-553(2017).

[16] Du P J, Xia J S, Xue Z H et al. Review of hyperspectral remote sensing image classification[J]. Journal of Remote Sensing, 20, 236-256(2016).

[17] Cen Y, Zhang G Z, Zhang L F et al. Spectral uncertainty of terrestrial objects and the applicability of spectral angle mapper algorithm[J]. Spectroscopy and Spectral Analysis, 35, 2841-2845(2015).

[18] Cai J X, Feng G C, Tang X et al. Human action recognition based on local image contour and random forest[J]. Acta Optica Sinica, 34, 1015006(2014).

[19] Fang X R, Wen Z F, Chen J L et al. Remote sensing estimation of suspended sediment concentration based on random forest regression model[J]. Journal of Remote Sensing, 23, 756-772(2019).

[20] Wang M, Zhang X C, Wang J Y et al. Forest resource classification based on random forest and object oriented method[J]. Acta Geodaetica et Cartographica Sinica, 49, 235-244(2020).

[21] Xu C B, Qiu J T, Zhong Q L et al. Reflectance spectroscopy applied in sandstone weathering and nitrogen excretion: a case study in Longhushan mountain, Jiangxi Province[J]. Spectroscopy and Spectral Analysis, 39, 3801-3808(2019).

[22] Jiang X D, Cao J J, Li Y A et al. Application of near-infrared spectrum technology to research of weathering of red sandstone relics[J]. Spectroscopy and Spectral Analysis, 31, 2102-2105(2011).

[23] Skurichina M. Duin R P W. Bagging, boosting and the random subspace method for linear classifiers[J]. Pattern Analysis & Applications, 5, 121-135(2002).

[24] Breiman L. Random forests[J]. Machine Learning, 45, 5-32(2001).

[25] Zhang Z Q, Zhang X C, Xin Q C et al. Combining the pixel-based and object-based methods for building change detection using high-resolution remote sensing images[J]. Acta Geodaetica et Cartographica Sinica, 47, 102-112(2018).

[26] Shannon C E. A mathematical theory of communication[J]. ACM SIGMOBILE Mobile Computing and Communications Review, 5, 3-55(2001).

[27] Yuan B, Hu B. Band selection algorithm for hyperspectral remote sensing with relative entropy and mutual information[J]. Remote Sensing Information, 34, 33-38(2019).