• 姓名: 阿里木·赛买提
  • 性别: 男
  • 职称: 研究员
  • 职务: 
  • 学历: 博士
  • 电话: 0991-7827371
  • 传真: 
  • 电子邮件: alim_smt@ms.xjb.ac.cn
  • 所属部门: 
  • 通讯地址: 新疆乌鲁木齐北京南路818号

    简  历:

  •   1984年10月生,中共党员,博士,硕士研究生导师;2015年9月参加工作,六届青科协基础科学专业委员会成员、 新疆维吾尔自治区青年科技工作者联谊会会员,新疆自然资源协会理事;入选自治区高层次人才引进工程(2015)、中国科学院青年创新促进会(2018)、自治区“天山英才”计划青年拔尖人才(2022)等人才计划;IEEE 地球科学与遥感协会J-STARS期刊2022年度最佳审稿人,J-STARS、Land等期刊专刊客座编辑;在国内学术刊物上发表论文70多篇,其中SCI检索论文60多篇。

    教育经历: 

      2012-2015 南京大学地理与海洋科学学院    地图学与地理信息系统专业   理学博士

      2009-2012 中国矿业大学环境与测绘学院    摄影测量与遥感专业         工学硕士

      2005-2009 南京大学地理与海洋科学学院    地理信息科学专业           理学学士

    工作经历: 

      2015.9-2018.11  中国科学院新疆生态与地理研究所  助理研究员

      2018.12-2022.11中国科学院新疆生态与地理研究所  副研究员

      2022.12-至今   中国科学院新疆生态与地理研究所  研究员

    社会任职:

  •  

    研究方向:

  •   遥感图像智能处理与地学分析,干旱区环境与生态遥感,城市遥感

    承担科研项目情况:

  • (1)自治区“天山英才”计划青年拔尖人才项目:巴音布鲁克草原甘肃马先蒿种群时空格局、动态与入侵态势预警,执行期:2023.1-2025.12,经费:150万。

    (2)中国科学院“西部青年学者”项目:面向干旱区植被覆盖遥感分类的弱监督学习方法研究与应用,执行期:2023.1-2026.12,经费:95万。

    (3)科技部第三次新疆综合科学考察项目子课题:额河下段湿地结构与演变过程调查,执行期:2022.10-2025.12,经费:60万。

    (4)国家自然科学基金面上项目:样本与特征迁移的中亚典型城市覆被精细分类方法研究,执行期:2021.1-2024.12,经费:55万元。

    (5)中国科学院青年创新促进会会项目,执行期间:2018.1-2021.12,经费:80万元。

    代表论著:

  • 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.

    33) 王伟,阿里木 赛买提,马龙,葛拥晓,吉力力 阿不都外力.1986—2019年新疆湖泊变化时空特征及趋势分析.生态学报,2022,42(4):1300~1314

    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.

    专利申请:

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    获奖及荣誉:

  • (一)第九届新疆青年科技奖,排名1,2019年;

    (二)中国测绘学会测绘科技进步一等奖,排名2, 2019年;

    (三)江苏省测绘地理信息学会科技进步一等奖,排名5,2018年;

    (四)湖南省科学技术进步二等奖,排名7,2020年。