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Remote sensing

Multispectral and hyperspectral satellite and aerial image processing and analysis

On the use of dorsiventral reflectance asymmetry of hornbeam (Carpinus betulus L.) leaves in air pollution estimation

M. Brackx, Verhelst, J., Scheunders, P., and Samson, R., “On the use of dorsiventral reflectance asymmetry of hornbeam (Carpinus betulus L.) leaves in air pollution estimation”, Environmental Monitoring and Assessment, vol. 189, no. 9, 2017.

Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation

E. K. Ghasrodashti, Karami, A., Heylen, R., and Scheunders, P., “Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation”, Remote Sensing, vol. 9, no. 6, 2017.

Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene

R. Luo, Liao, W., Zhang, H., Zhang, L., Pi, Y., Scheunders, P., and Philips, W., “Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 8, pp. 3768-3781, 2017.

Habitat mapping and quality assessment of NATURA 2000 Heatland using airborne imaging spectroscopy

B. Haest, Vanden Borre, J., Spanhove, T., Thoonen, G., Delalieux, S., Kooistra, L., Mücher, C. A., Paelinckx, D., Scheunders, P., and Kempeneers, P., “Habitat mapping and quality assessment of NATURA 2000 Heatland using airborne imaging spectroscopy”, Remote Sensing, vol. 9, no. 3, 2017.

Hyperspectral leaf reflectance of Carpines betulus L. saplings for urban air quality estimation

M. Brackx, Van Wittenberghe, S., Verhelst, J., Scheunders, P., and Samson, R., “Hyperspectral leaf reflectance of Carpines betulus L. saplings for urban air quality estimation”, Environmental Pollution, vol. 220, pp. 159-167, 2017.

Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon

R. Heylen, Parente, M., and Scheunders, P., “Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon”, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, pp. 2191-2200, 2017.

Close range hyperspectral imaging for plant phenotyping

P. Mishra, Asaari, M. Shahrimie, Mertens, S., Wuyts, N., Dhondt, S., and Scheunders, P., “Close range hyperspectral imaging for plant phenotyping”, in Hyperspectral Imaging and Applications Conference, Coventry, UK, 2016.

Modeling effects of illumination and plant geometry on leaf reflectance spectra in close-range hyperspectral imaging

M. Shahrimie Asaari, Mishra, P., Mertens, S., Dhondt, S., Wuyts, N., and Scheunders, P., “Modeling effects of illumination and plant geometry on leaf reflectance spectra in close-range hyperspectral imaging”, in 8th WHISPERS - Evolution in Remote Sensing, Los Angeles, USA, 2016.

Classification of hyperspectral images with very small training size using sparse unmixing

V. Andrejchenko, Heylen, R., Scheunders, P., Philips, W., and Liao, W., “Classification of hyperspectral images with very small training size using sparse unmixing”, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

Optical Solutions for Improving Spatial Resolution of Hyperspectral Sensors

A. Adibi, Karami, A., Heylen, R., and Scheunders, P., “Optical Solutions for Improving Spatial Resolution of Hyperspectral Sensors”, in 8th workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing, Los Angeles, USA, 2016.

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