1)samat, a., li, e., wang, w., liu, s., & liu, x. (2022). holp-df: holp based screening ultrahigh dimensional subfeatures in deep forest for remote sensing image classification. ieee journal of selected topics in applied earth observations and remote sensing, 15, 8287-8298.

2)liu, x., samat, a.*, li, e., wang, w., & abuduwaili, j. (2022). self-trained deep forest with limited samples for urban impervious surface area extraction in arid area using multispectral and polsar imageries. sensors, 22(18), 6844.

3)wang, w., samat, a.*, abuduwaili, j.*, wang, c., de maeyer, p., & van de voorde, t. (2022). automatic identification of sand and dust storm sources based on wind vector and google earth engine. ieee geoscience and remote sensing letters.

4)wang, w., samat, a.*, abuduwaili, j.*, ge, y., de maeyer, p., & van de voorde, t. (2022). a novel hybrid sand and dust storm detection method using modis data on gee platform. european journal of remote sensing, 55(1), 420-428.

5)wang, w., samat, a.*, abuduwaili, j., ge, y., de maeyer, p., & van de voorde, t. (2022). temporal characterization of sand and dust storm activity and its climatic and terrestrial drivers in the aral sea region. atmospheric research, 275, 106242.

6)samat, a., gamba, p., wang, w., luo, j., li, e., liu, s., ... & abuduwaili, j. (2022). mapping blue and red color-coated steel sheet roof buildings over china using sentinel-2a/b msil2a images. remote sensing, 14(1), 230.

7)xu, t., li, e., samat, a., li, z., liu, w., & zhang, l. (2022). estimating large-scale interannual dynamic impervious surface percentages based on regional divisions. remote sensing, 14(15), 3786.

8)li, z., li, e., samat, a., xu, t., liu, w., & zhu, y. (2022). an object-oriented cnn model based on improved superpixel segmentation for high-resolution remote sensing image classification. ieee journal of selected topics in applied earth observations and remote sensing, 15, 4782 - 4796.

9)liu, s., zheng, y., du, q., bruzzone, l., samat, a., tong, x., ... & wang, c. (2022). a shallow-to-deep feature fusion network for vhr remote sensing image classification. ieee transactions on geoscience and remote sensing.

10)samat, a., li, e., du, p., liu, s., & miao, z. (2021). improving deep forest via patch-based pooling, morphological profiling, and pseudo labeling for remote sensing image classification. ieee journal of selected topics in applied earth observations and remote sensing, 14, 9334-9349.

11)samat, a., li, e., du, p., liu, s., & xia, j. (2021). gpu-accelerated catboost-forest for hyperspectral image classification via parallelized mrmr ensemble subspace feature selection. ieee journal of selected topics in applied earth observations and remote sensing, 14, 3200-3214.

12)li, e., samat, a., zhang, c., du, p., & liu, w. (2021). first and second-order information fusion networks for remote sensing scene classification. ieee geoscience and remote sensing letters, 19, 1-5.

13)li, e., samat, a., du, p., liu, w., & hu, j. (2020). improved bilinear cnn model for remote sensing scene classification. ieee geoscience and remote sensing letters.

14)liu, s., zheng, y., du, q., samat, a., tong, x., & dalponte, m. (2020). a novel feature fusion approach for vhr remote sensing image classification. ieee journal of selected topics in applied earth observations and remote sensing, 14, 464-473.

15)wang, w., samat, a., abuduwaili, j., & ge, y. (2021). quantifying the influences of land surface parameters on lst variations based on geodetector model in syr darya basin, central asia. journal of arid environments, 186, 104415.

16)samat, a., li, e., du, p., liu, s., miao, z., & zhang, w. (2020). catboost for rs image classification with pseudo label support from neighbor patches-based clustering. ieee geoscience and remote sensing letters.

17)wang, w., samat, a., ge, y., ma, l., tuheti, a., zou, s., & abuduwaili, j. (2020). quantitative soil wind erosion potential mapping for central asia using the google earth engine platform. remote sensing, 12(20), 3430.

18)samat, a., li, e., wang, w., liu, s., lin, c., & abuduwaili, j. (2020). meta-xgboost for hyperspectral image classification using extended mser-guided morphological profiles. remote sensing, 12(12), 1973.

19)wang, w., samat, a., abuduwaili, j., & ge, y. (2020). spatio-temporal variations of satellite-based pm2. 5 concentrations and its determinants in xinjiang, northwest of china. international journal of environmental research and public health, 17(6), 2157.

20)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, 17(9), 1588-1592.

21)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.

22)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.

23)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.

24)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.

25)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.

26)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.

27)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.

28)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.

29)luo, j., du, p., samat, a., xia, j., che, m., & xue, z. (2017). spatiotemporal pattern of pm2. 5 concentrations in mainland china and analysis of its influencing factors using geographically weighted regression. scientific reports, 7(1), 1-14.

30)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.

31)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.

32)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.

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34)盖一铭，阿里木·赛买提, 王伟, 吉力力·阿不都外力. 基于样本迁移的干旱区地表覆盖快速更新. 遥感技术与应用. 2022,37(02), 333-341.

35)王伟，阿里木·赛买提, 吉力力·阿不都外力. 基于地理探测器模型的中亚ndvi时空变化特征及其驱动因子分析[j]. 国土资源遥感, 2019, 31(4): 32-40.