IEEE Geoscience and Remote Sensing Magazine - September 2019 - 92

[174] Z. Wang, C. Gang, X. Li, Y. Chen, and J. Li, "Application of a
normalized difference impervious index (NDII) to extract urban impervious surface features based on Landsat TM images,"
Int. J. Remote Sens., vol. 36, no. 4, pp. 1055-1069, 2015.
[175] L. Gao, H. Zhao, M. Liu, and H. Zhang, "A damaged area assessment method for the post-earthquake urban regions based
on impervious surface estimating of remote sensing imagery,"
Remote Sens. Technol. Applicat., vol. 28, no. 4, pp. 582-587,
2013.
[176] Z. Sun, C. Wang, H. Guo, and R. Shang, "A modified normalized difference impervious surface index (MNDISI) for automatic urban mapping from Landsat imagery," Remote Sens., vol.
9, no. 9, pp. 942:1-942:18, 2017. doi: 10.3390/rs9090942.
[177] C. B. Deng and C. S. Wu, "BCI: A biophysical composition index for remote sensing of urban environments," Remote Sens.
Environ., vol. 127, pp. 247-259, Dec. 2012.
[178] R. C. Estoque and Y. Murayama, "Classification and change
detection of built-up lands from Landsat-7 ETM+ and Landsat-8 OLI/TIRS imageries: A comparative assessment of various spectral indices," Ecolog. Indicators, vol. 56, pp. 205-217,
Sept. 2015.
[179] L. V. Ying, H. P. Liu, and J. X. Liu, "Study on build-up index
based on MODIS data," Sci. Surveying Mapping, vol. 40, no. 5,
pp. 44-48, May 2015.
[180] Y. L. Chang, C. C. Han, and H. Ren, C.-T. Chen, K.-S.. Chen,
and K.-C. Fan, "Data fusion of hyperspectral and SAR images,"
Opt. Eng., vol. 43, no. 8, pp. 1787-1797, 2004.
[181] K. Irwin, D. Beaulne, A. Braun, and G. Fotopoulos, "Fusion of
SAR, optical imagery and airborne LiDAR for surface water detection," Remote Sens., vol. 9, no. 9, pp. 890:1-890:18, 2017. doi:
10.3390/rs9090890.
[182] H. Luo, L. Wang, C. Wu, and L. Zhang, "An improved method
for impervious surface mapping incorporating LiDAR data and
high-resolution imagery at different acquisition times," Remote
Sensing, vol. 10, no. 9, pp. 1349:1-1349:27, 2018. doi: 10.3390/
rs10091349.
[183] B. Chen, B. Huang, and B. Xu, "Multi-source remotely sensed
data fusion for improving land cover classification," ISPRS J.
Photogramm. Remote Sens., vol. 124, pp. 27-39, Feb. 2017.
[184] R. C. Luo and M. G. Kay, "Multisensor integration and fusion
for intelligent systems," IEEE Trans. Syst., Man, Cybern., vol. 19,
no. 5, pp. 901-931, 1989.
[185] Y. Zhang, H. Zhang, and H. Lin, "Improving the impervious
surface estimation with combined use of optical and SAR remote sensing images," Remote Sens. Environ., vol. 141, no. 2, pp.
155-167, 2014.
[186] Z. Shao, H. Fu, P. Fu, and L. Yin, "Mapping urban impervious surface by fusing optical and SAR data at the decision
level," Remote Sens., vol. 8, no. 11, pp. 945:1-945:21, 2016. doi:
10.3390/rs8110945.
[187] D. L. Hall and J. Llinas, "An introduction to multisensor data
fusion," Proc. IEEE, vol. 85, no. 1, pp. 6-23, 1997.
[188] S. Morchhale, V. P. Pauca, R. J. Plemmons, and T. C. Torgersen, "Classification of pixel-level fused hyperspectral and lidar data using deep convolutional neural networks," in Proc.
IEEE 8th Workshop Hyperspectral Image and Signal Processing:

92

Evolution Remote Sensing, 2016, pp. 1-5. doi: 10.1109/WHISPERS.2016.8071715.
[189] R. Fernandez-Beltran, J. M. Haut, M. E. Paoletti, J. Plaza, A.
Plaza, and F. Pla, "Remote sensing image fusion using hierarchical multimodal probabilistic latent semantic analysis," IEEE
J. Sel. Topics Appl. Earth Observ. in Remote Sens., vol. 11, no. 12,
pp. 4982-4993, 2018.
[190] N. B. Kolekar and R. P. Shelkikar, "Decision level based image
fusion using wavelet transform and support vector machine,"
Int. J. Scientific Eng. Res., vol. 4, no. 12, pp. 54-58, 2016.
[191] L. Wald, T. Ranchin, and M. Mangolini, "Fusion of satellite images of different spatial resolutions: Assessing the quality of
resulting images," Photogramm. Eng. Remote Sens., vol. 63, no. 6,
pp. 691-699, 2009.
[192] A. Mookambiga and V. Gomathi, "Comprehensive review on
fusion techniques for spatial information enhancement in hyperspectral imagery," Multidimensional Syst. Signal Process., vol.
27, no. 4, pp. 863-889, 2016.
[193] K. A. Germaine and M. C. Hung, "Delineation of impervious
surface from multispectral imagery and lidar incorporating
knowledge based expert system rules," Photogramm. Eng. Remote Sens., vol. 77, no. 1, pp. 75-85, 2011.
[194] Z. Shao, Y. Zhang, L. Zhang, et al. "Combining spectral and
texture features using random forest algorithm: Extracting
impervious surface area in Wuhan," Int. Archives Photogramm.,
Remote Sens. Spatial Inform. Sci., vol. XLI-B7, pp. 351-358, June
2016.
[195] B. Bigdeli and P. Pahlavani, "High resolution multisensor fusion of SAR, optical and LiDAR data based on crisp vs. fuzzy
and feature vs. decision ensemble systems," Int. J. Appl. Earth
Observ. Geoinform., vol. 52, pp. 126-136, Oct. 2016.
[196] M. Dalla Mura, S. Prasad, F. Pacifici, P. Gamba, J. Chanussot,
and J. A. Benediktsson, "Challenges and opportunities of multimodality and data fusion in remote sensing," Proc. IEEE, vol.
103, no. 9, pp. 1585-1601, 2015.
[197] R. Zurita-Milla, J. G. P. W. Clevers, and M. E. Schaepman, "Unmixing based Landsat TM and MERIS FR data fusion," IEEE
Geosci. Remote Sens. Lett., vol. 5, no. 3, pp. 453-457, July 2008.
[198] T. Hilker et al., "A new data fusion model for high spatial- and
temporal resolution mapping of forest disturbance based on
Landsat and Modis," Remote Sens. Environ., vol. 113, no. 8, pp.
1613-1627, 2009.
[199] H. Song and B. Huang, "Spatiotemporal satellite image fusion
through one-pair image learning," IEEE Trans. Geosci. Remote
Sens., vol. 51, no. 4, pp. 1883-1896, 2013.
[200] H. Song, Q. Liu, G. Wang, R. Hang, and B. Huang, "Spatiotemporal satellite image fusion using deep convolutional neural
networks," IEEE J. Sel. Topics Appl. Earth Observ. in Remote Sens.,
vol. 11, no. 3, pp. 821-829, 2018.
[201] Q. Ma, C. Y. He, J. G. Wu, Z. F. Liu, Q. F. Zhang, and Z. X. Sun,
"Quantifying spatio-temporal patterns of urban impervious surfaces in China: An improved assessment using nighttime light
data," Landscape Urban Planning, vol. 130, pp. 36-49, Oct. 2014.
[202] Y. Xie and Q. Weng, "Updating urban extents with nighttime
light imagery by using an object-based thresholding method,"
Remote Sens. Environ., vol. 187, pp. 1-13, Dec. 2016.
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

SEPTEMBER 2019
IEEE Geoscience and Remote Sensing Magazine - September 2019

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - September 2019
