IEEE Geoscience and Remote Sensing Magazine - December 2021 - 62

[11] L. Tusa et al., " Mineral mapping and vein detection in hyperspectral
drill-core scans: Application to porphyry-type mineralization, "
Minerals, vol. 9, no. 2, p. 122, 2019. doi: 10.3390/
min9020122.
[12] U. Bradter, J. O'Connell, W. E. Kunin, C. W. Boffey, R. J. Ellis,
and T. G. Benton, " Classifying grass-dominated habitats
from remotely sensed data: The influence of spectral
resolution, acquisition time and the vegetation classification
system on accuracy and thematic resolution, " Sci. Total Environ.,
vol. 711, p. 134,584, Apr. 2020. doi: 10.1016/j.scitotenv.2019.134584.
[13]
H. Zhang, J. Kang, X. Xu, and L. Zhang, " Accessing the temporal
and spectral features in crop type mapping using multi-temporal
Sentinel-2 imagery: A case study of Yi'an County, Heilongjiang
province, China, " Comput. Electron. Agricul., vol. 176,
p. 105,618, Sept. 2020. doi: 10.1016/j.compag.2020.105618.
[14] R. Darvishzadeh, C. Atzberger, A. Skidmore, and M. Schlerf,
" Mapping grassland leaf area index with airborne hyperspectral
imagery: A comparison study of statistical approaches and inversion
of radiative transfer models, " ISPRS J. Photogram. Remote
Sens., vol. 66, no. 6, pp. 894-906, 2011. doi: 10.1016/j.isprsjprs
.2011.09.013.
[15] B. Kong, H. Yu, R. Du, and Q. Wang, " Quantitative estimation
of biomass of alpine grasslands using hyperspectral remote
sensing, " Rangeland Ecol. Manage, vol. 72, no. 2, pp. 336-346,
2019. doi: 10.1016/j.rama.2018.10.005.
[16] K. C. Tiwari, M. K. Arora, and D. Singh, " An assessment of independent
component analysis for detection of military targets
from hyperspectral images, " Int. J. Appl. Earth Observ. Geoinf.,
vol. 13, no. 5, pp. 730-740, 2011. doi: 10.1016/j.jag.2011.03.007.
[17] M. Shimoni, R. Haelterman, and C. Perneel, " Hypersectral
imaging for military and security applications: Combining
myriad processing and sensing techniques, " IEEE Geosci. Remote
Sens. Mag., vol. 7, no. 2, pp. 101-117, 2019. doi: 10.1109/
MGRS.2019.2902525.
[18] A. Plaza, P. Martínez, J. Plaza, and R. Pérez, " Dimensionality
reduction and classification of hyperspectral image data using
sequences of extended morphological transformations, " IEEE
Trans. Geosci. Remote Sens., vol. 43, no. 3, pp. 466-479, 2005.
doi: 10.1109/TGRS.2004.841417.
[19] W. Li, S. Prasadand, J. E. Fowler, and L. M. Bruce, " Locality-preserving
dimensionality reduction and classification for hyperspectral
image analysis, " IEEE Trans. Geosci. Remote Sens., vol. 50,
no. 4, pp. 1185-1198, 2012. doi: 10.1109/TGRS.2011.2165957.
[20] W. Li, F. Feng, H. Li, and Q. Du, " Discriminant analysis-based dimension
reduction for hyperspectral image classification: A survey
of the most recent advances and an experimental comparison
of different techniques, " IEEE Geosci. Remote Sens. Mag., vol. 6,
no. 1, pp. 15-34, 2018. doi: 10.1109/MGRS.2018.2793873.
[21] H. Zhai, H. Zhang, L. Zhang, and P. Li, " Total variation regularized
collaborative representation clustering with a locally adaptive
dictionary for hyperspectral imagery, " IEEE Trans. Geosci.
Remote Sens., vol. 57, no. 1, pp. 166-180, 2019. doi: 10.1109/
TGRS.2018.2852708.
[22] L. Zhang, L. Zhang, B. Du, J. You, and D. Tao, " Hyperspectral
image unsupervised classification by robust manifold matrix
62
factorization, " Inf. Sci., vol. 485, pp. 154-169, June 2019. doi:
10.1016/j.ins.2019.02.008.
[23] Y. Kong, Y. Cheng, C. P. Chen, and X. Wang, " Hyperspectral
image clustering based on unsupervised broad learning, " IEEE
Geosci. Remote Sens. Lett., vol. 16, no. 11, pp. 1741-1745, 2019.
doi: 10.1109/LGRS.2019.2907598.
[24] H. Zhai, H. Zhang, L. Zhang, and P. Li, " Nonlocal means regularized
sketched reweighted sparse and low-rank subspace clustering
for large hyperspectral images, " IEEE Trans. Geosci. Remote
Sens., early access, 2020. doi: 10.1109/TGRS.2020.3023418.
[25] H. Zhai, H. Zhang, L. Zhang, and P. Li, " Sparsity-based clustering
for large hyperspectral remote sensing images, " IEEE
Trans. Geosci. Remote Sens., early access, 2020. doi: 10.1109/
TGRS.2020.3032427.
[26] H. Kashima, J. Hu, B. Ray, and M. Singh, " K-means clustering
of proportional data using L1 distance, " in Proc. IEEE
Int. Conf. Pattern Recognit., Dec. 2008, pp. 1-4. doi: 10.1109/
ICPR.2008.4760982.
[27] J. Mao and A. K. Jain, " A self-organizing network for hyperellipsoidal
clustering (HEC), " IEEE Trans. Neural Netw., vol. 7, no.
1, pp. 16-29, 1996. doi: 10.1109/72.478389.
[28] Y. Ma, S. Lao, E. Takikawa, and M. Kawade, " Discriminant analysis
in correlation similarity measure space, " in Proc. Int. Conf. Mach.
Learn., June 2007, pp. 577-584. doi: 10.1145/1273496.1273569.
[29] J. Chen, X. Jia, W. Yang, and B. Matsushita, " Generalization
of subpixel analysis for hyperspectral data with flexibility
in spectral similarity measures, " IEEE Trans. Geosci. Remote
Sens., vol. 47, no. 7, pp. 2165-2171, 2009. doi: 10.1109/
TGRS.2008.2011432.
[30] C. Rohkohl and K. Engel, " Efficient image segmentation using
pairwise pixel similarities, " in Proc. Joint Pattern Recognit. Symp.
(JPRS), Berlin: Springer-Verlag, Sept. 2007, pp. 254-263. doi:
10.1007/978-3-540-74936-3_26.
[31] U. Maulik and I. Saha, " Automatic fuzzy clustering using modified
differential evolution for image classification, " IEEE Trans.
Geosci. Remote Sens., vol. 48, no. 9, pp. 3503-3510, 2010. doi:
10.1109/TGRS.2010.2047020.
[32] Y. Zhong, S. Zhang, and L. Zhang, " Automatic fuzzy clustering
based on adaptive multi-objective differential evolution for
remote sensing imagery, " IEEE J. Sel. Topics Appl. Earth Observ.
Remote Sens., vol. 6, no. 5, pp. 2290-2301, 2013. doi: 10.1109/
JSTARS.2013.2240655.
[33] S. Ghaffarian and S. Ghaffarian, " Automatic histogram-based
fuzzy C-means clustering for remote sensing imagery, " ISPRS
J. Photogram. Remote Sens., vol. 97, pp. 46-57, Nov. 2014. doi:
10.1016/j.isprsjprs.2014.08.006.
[34] J. C. Bezdek, Pattern Recognition With Fuzzy Objective Function
Algorithms. New York: Plenum, 1981.
[35] T. N. Tran, R. Wehrens, and L. M. Buydens, " KNN-kernel density-based
clustering for high-dimensional multivariate data, "
Comput. Statist. Data Anal., vol. 51, no. 2, pp. 513-525, 2006.
doi: 10.1016/j.csda.2005.10.001.
[36] C. Cariou and K. Chehdi, " Nearest neighbor-density-based
clustering methods for large hyperspectral images, " in Proc. Image
Signal Process. Remote Sens. XXIII. Int. Soc. Opt. Photon., Oct.
2017, vol. 10427, p. 1,042,70I. doi: 10.1117/12.2278221.
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE DECEMBER 2021
IEEE Geoscience and Remote Sensing Magazine - December 2021

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - December 2021
