[1]. Samat, A., Du, P., Liu, S., Li, J., & Cheng, L. (2014). E2LMs: Ensemble Extreme Learning Machines for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(4), 1060-1069.  

[2]. Samat, A., Gamba, P., Du, P., & Luo, J. (2015). Active extreme learning machines for quad-polarimetric SAR imagery classification. International Journal of Applied Earth Observation and Geoinformation, 35, 305-319.  

[3]. Samat, A., Li, J., Liu, S., Du, P., Miao, Z., & Luo, J. (2016). Improved hyperspectral image classification by active learning using pre-designed mixed pixels. Pattern Recognition, 51, 43-58.  

[4]. Samat, A., Gamba, P., Abuduwaili, J., Liu, S., & Miao, Z. (2016). Geodesic flow kernel support vector machine for hyperspectral image classification by unsupervised subspace feature transfer. Remote Sensing, 8(3), 234.  

[5]. Samat, A., Gamba, P., Liu, S., Du, P., & Abuduwaili, J. (2016). Jointly informative and manifold structure representative sampling based active learning for remote sensing image classification. IEEE Transactions on Geoscience and Remote Sensing, 54(11), 6803-6817.  

[6]. Samat, A., Persello, C., Gamba, P., Liu, S., Abuduwaili, J., & Li, E. (2017). Supervised and semi-supervised multi-view canonical correlation analysis ensemble for heterogeneous domain adaptation in remote sensing image classification. Remote sensing, 9(4), 337.  

[7]. Samat, A., Persello, C., Liu, S., Li, E., Miao, Z., & Abuduwaili, J. (2018). Classification of VHR multispectral images using extratrees and maximally stable extremal region-guided morphological profile. IEEE Journal of selected topics in applied earth observations and remote sensing, 11(9), 3179-3195.  

[8]. Samat, A., Gamba, P., Liu, S., Miao, Z., Li, E., & Abuduwaili, J. (2018). Quad-PolSAR data classification using modified random forest algorithms to map halophytic plants in arid areas. International journal of applied earth observation and geoinformation, 73, 503-521.  

[9]. Samat, A., Gamba, P., Liu, S., Li, E., Miao, Z., & Abuduwaili, J. (2018). Fuzzy multiclass active learning for hyperspectral image classification. IET Image Processing, 12(7), 1095-1101. 

[10]. Samat, A., Yokoya, N., Du, P., Liu, S., Ma, L., Ge, Y., ... & Lin, C. (2019). Direct, ECOC, ND and END Frameworks—Which One Is the Best? An Empirical Study of Sentinel-2A MSIL1C Image Classification for Arid-Land Vegetation Mapping in the Ili River Delta, Kazakhstan. Remote Sensing, 11(16), 1953.  

[11]. Samat, A., Li, J., Lin, C., Liu, S., & Li, E. (2019). Edge Gradient-Based Active Learning for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters.  

[12]. Samat, A., Liu, S., Persello, C., Li, E., Miao, Z., & Abuduwaili, J. (2019). Evaluation of ForestPA for VHR RS image classification using spectral and superpixel-guided morphological profiles. European journal of remote sensing, 52(1), 107-121. 

[13]. Samat, A., Li, J., Lin, C., Liu, S., & Li, E. (2019). Edge Gradient-Based Active Learning for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters. 

[14]. Du, P., Samat, A., Waske, B., Liu, S., & Li, Z. (2015). Random forest and rotation forest for fully polarized SAR image classification using polarimetric and spatial features. ISPRS Journal of Photogrammetry and Remote Sensing, 105, 38-53. 

[15]. Li, E., Xia, J., Du, P., Lin, C., & Samat, A. (2017). Integrating multilayer features of convolutional neural networks for remote sensing scene classification. IEEE Transactions on Geoscience and Remote Sensing, 55(10), 5653-5665. 

[16]. Luo, J., Du, P., Samat, A., Xia, J., Che, M., & Xue, Z. (2017). Spatiotemporal pattern of PM 2.5 concentrations in mainland China and analysis of its influencing factors using geographically weighted regression. Scientific reports, 7(1), 1-14. 

[17]. Du, P., Samat, A., Gamba, P., & Xie, X. (2014). Polarimetric SAR image classification by boosted multiple-kernel extreme learning machines with polarimetric and spatial features. International Journal of Remote Sensing, 35(23), 7978-7990. 

[18]. Li, E., Du, P., Samat, A., Xia, J., & Che, M. (2015). An automatic approach for urban land-cover classification from Landsat-8 OLI data. International Journal of Remote Sensing, 36(24), 5983-6007. 

[19]. Miao, Z., Shi, W., Samat, A., Lisini, G., & Gamba, P. (2015). Information fusion for urban road extraction from VHR optical satellite images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(5), 1817-1829. 

[20]. Liu, S., Du, Q., Tong, X., Samat, A., Bruzzone, L., & Bovolo, F. (2017). Multiscale morphological compressed change vector analysis for unsupervised multiple change detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(9), 4124-4137. 

[21]. Li, E., Du, P., Samat, A., Meng, Y., & Che, M. (2016). Mid-level feature representation via sparse autoencoder for remotely sensed scene classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(3), 1068-1081. 

[22]. Liu, S., Du, Q., Tong, X., Samat, A., Pan, H., & Ma, X. (2017). Band selection-based dimensionality reduction for change detection in multi-temporal hyperspectral images. Remote Sensing, 9(10), 1008. 

[23]. Liu, S., Chi, M., Zou, Y., Samat, A., Benediktsson, J. A., & Plaza, A. (2017). Oil spill detection via multitemporal optical remote sensing images: A change detection perspective. IEEE Geoscience and Remote Sensing Letters, 14(3), 324-328. 

[24]. Shen, H., Abuduwaili, J., Samat, A., & Ma, L. (2016). A review on the research of modern aeolian dust in Central Asia. Arabian Journal of Geosciences, 9(13), 625. 

[25]. Alifujiang, Y., Abuduwaili, J., Ma, L., Samat, A., & Groll, M. (2017). System Dynamics Modeling of Water Level Variations of Lake Issyk-Kul, Kyrgyzstan. Water, 9(12), 989. 

[26]. Yegemova, S., Kumar, R., Abuduwaili, J., Ma, L., Samat, A., Issanova, G., ... & Rodrigo-Comino, J. (2018). Identifying the key information and land management plans for water conservation under dry weather conditions in the Border areas of the Syr Darya River in Kazakhstan. Water, 10(12), 1754. 

[27]. Xie, X., Tian, S., Du, P., Zhan, W., Samat, A., & Chen, J. (2016). Quantitative estimation of carbonate rock fraction in karst regions using field spectra in 2.0–2.5 μm. Remote Sensing, 8(1), 68. 

[28]. Du, P., Li, E., Xia, J., Samat, A., & Bai, X. (2018). Feature and model level fusion of pretrained CNN for remote sensing scene classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(8), 2600-2611. 

[29]. Lin, C., Du, P., Samat, A., Li, E., Wang, X., & Xia, J. (2019). Automatic updating of land cover maps in rapidly urbanizing regions by relational knowledge transferring from GlobeLand30. Remote Sensing, 11(12), 1397. 

[30]. Li, E., Samat, A., Liu, W., Lin, C., & Bai, X. (2019). High-Resolution Imagery Classification Based on Different Levels of Information. Remote Sensing, 11(24), 2916. 

[31]. Liu, S., Du, Q., Tong, X., Samat, A., & Bruzzone, L. (2019). Unsupervised Change Detection in Multispectral Remote Sensing Images via Spectral-Spatial Band Expansion. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(9), 3578-3587. 

[32]. Liu, S., Hu, Q., Tong, X., Xia, J., Du, Q., Samat, A., & Ma, X. (2020). A Multi-Scale Superpixel-Guided Filter Feature Extraction and Selection Approach for Classification of Very-High-Resolution Remotely Sensed Imagery. Remote Sensing, 12(5), 862.