徐林林，博士，副教授，博士生导师
出生年月：1984年10月
Email：xulinlin@cugb.edu.cn
地址：北京市海淀区学院路29号，中国地质大学（北京）土地科学技术学院，100083

研究方向为北极海冰遥感、海洋油污监测、冰冻圈卫星遥感、遥感大数据信息工程及应用、机器学习与深度学习、高光谱资源环境遥感等。在《RemoteSensingofEnvironment》、《IEEETransactionsonGeosciencesandRemoteSensing》等遥感地学领域国际著名SCI期刊上发表多篇论文。任IEEE地球科学与遥感协会、国际摄影测量与遥感学会会员，受邀任《RemoteSensingofEnvironment》、《IEEETransactionsonGeosciencesandRemoteSensing》、《IEEETransactionsonImageProcessing》、《IEEETransactionsonIntelligentTransportationSystems》、《IEEEJournalofSelectedTopicsonAppliedEarthObservationsandRemotesensing》、《IEEEG、eosciencesandRemoteSensingLetters》、《patternrecognitionletters》等国际SCI期刊审稿人。与加拿大滑铁卢大学地理系、系统设计工程系，以及德国耶拿大学地理系等进行联合硕士与博士培养，优秀者推荐攻读国外博士与联合培养博士。

教育与工作履历
2016.09—今副教授中国地质大学（北京）土地科学技术学院
2014.06—2016.09博士后加拿大滑铁卢大学系统设计工程系
2010.09—2014.07博士加拿大滑铁卢大学地理系
2007.09—2010.07硕士中国地质大学（北京）土地科学技术学院
2003.09—2007.07本科中国地质大学（北京）土地科学技术学院

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2017:

1. Linlin Xu, A. Wong and D. A. Clausi. 2017, "A Novel Bayesian Spatial-Temporal Random Field Model Applied to Cloud Detection from Remotely Sensed Imagery", IEEE Transactions on Geosciences and Remote Sensing, accepted.
2. F. Li, D. A. Clausi, Linlin Xu and A. Wong. 2017, "ST-IRGS: A Region-Based Self-Training Algorithm applied to Hyperspectral Image Classification and Segmentation", IEEE Transactions on Geosciences and Remote Sensing, accepted.
3. Y. Cao, Linlin Xu, D. A. Clausi, "Exploring the Potential of Active Learning for Automatic Identification of Marine Oil Spills Using 10-Year (2004–2013) RADASAT Data", Remote Sensing, accepted.
4. W. Tan, Linlin Xu, J. Li, 2017, "Mapping Sea Ice in Labrador Coast with Sentinel-1 SAR Imagery", IEEE Journal of Selected Topics on Applied Earth Observations and Remote Sensing, under revision.
5. Yuan Fang, Linlin xu, J. Peng, H. Yang, D. A. Clausi and A. Wong, 2017, "Unsupervised Bayesian Classification of Hyperspectral Image based on Spectral Mixture Model and Markov Random Field", IEEE Journal of Selected Topics on Applied Earth Observations and Remote Sensing, under revision.
6. Linlin Xu, J. Peng, D. A. Clausi and A. Wong, 2017, "The classification of sea ice and open water from Sentinel-1 imagery using a deep convolutional neural network approach", Remote Sensing of Environment, under revision.
7. Mohsen Ghanbari, Linlin Xu, Mingzhe Jiang, D. A. Clausi, "Compact Polarimetry Assessment: An Application of Sea-Ice Type Mapping", IEEE Transactions on Geoscience and Remote Sensing, under revision.


2016:

1. Linlin Xu, F. Li, D. A. Clausi and A. Wong, 2016. "Weakly supervised classification of remotely sensed imagery using edge penalty and label constraint", IEEE Transactions on Geosciences and Remote Sensing, 55(3):1424-1436.
2. Linlin Xu, D. A. Clausi and A. Wong, 2016. "An Enhanced Probabilistic Posterior Sampling Approach for Synthesizing SAR Imagery with Sea Ice and Oil Spills", IEEE Geosciences and Remote Sensing Letters, 14(2):188-192.
3. Linlin Xu, A. Wong, F. Li, and D. A. Clausi, 2016. "Intrinsic representation of hyperspectral imagery for unsupervised feature extraction", IEEE Transactions on Geosciences and Remote Sensing, 54(2):1118-1130.
4. Linlin Xu, A. Wong, F. Li, and D. A. Clausi, 2016. "Extraction of endmembers from hyperspectral images using a weighted fuzzy purified-means clustering model", IEEE Journal of Selected Topics on Applied Earth Observations and Remote Sensing, 9(2): 695-707.
5. Linlin Xu, J. S. Mohammad, A. Wong, and D. A. Clausi, 2016. “ Fully connected continuous conditional random field with stochastic cliques for dark-spot detection In SAR imagery", IEEE Journal of Selected Topics on Applied Earth Observations and Remote Sensing, 9(7):2882-2890.
6. Wang L., K. A. Scott, Linlin Xu, D. A. Clausi, 2016. "Sea Ice Concentration Estimation During Melt From Dual-Pol SAR Scenes Using Deep Convolutional Neural Networks: A Case Study", IEEE Transactions on Geosciences and Remote Sensing, 54(8): 4524-4533.
7. Yuan Fang, Linlin Xu, Xiao Sun, Longshan Yang, Yujia Chen, Junhuan Peng, 2016, “A novel unsupervised classification approach for hyperspectral imagery based on spectral mixture model and markov random field”，International Geosicence and Remote Sensing Symposium (IGARSS) , July 2016, Beijing.
8. Xiao Sun, Linlin Xu, Longshan Yang, Yujia Chen, Yuan Fang, Junhuan Peng, 2016, “Super-resolution reconstruction of hyperspectral imagery using an spectral unmixing based representational model”, International Geosicence and Remote Sensing Symposium (IGARSS) , July 2016, Beijing.
9. Longshan Yang, Linlin Xu, Xiao Sun, Yuan Fang, Yujia Chen, Junhuan Peng, 2016, "Denoising of hyperspectral imagery using an intrinsic spectral representation model with spatial smoothness constraint”, International Geosicence and Remote Sensing Symposium (IGARSS) , July 2016, Beijing.
10. Yongfeng Cao, Linlin Xu, David Clausi, 2016, “Active learning for identifying marine oil spills using 10-year radarsat data”, International Geosicence and Remote Sensing Symposium (IGARSS) , July 2016, Beijing.

2015:

1. Linlin Xu, F. Li, A. Wong, and D. A. Clausi, 2015. "Hyperspectral image denoising using a spatial-spectral Monte Carlo sampling approach", IEEE Journal of Selected Topics on Applied Earth Observations and Remote Sensing, 8(9): 3025-3038.
2. Li F., Linlin Xu, A. Wong, and D. A. Clausi, 2015, "Feature extraction for hyperspectral imagery via ensemble localized manifold learning", IEEE Geoscience and Remote Sensing Letters, 12(12): 2486-2490.
3. Li F., Linlin Xu, A. Wong, and D. A. Clausi, 2015, "QMCTLS: Quasi Monte Carlo texture likelihood sampling for despeckling of complex polarimetric SAR images", IEEE Geoscience and Remote Sensing Letters, 12(7): 1566-1570.
4. Li F., Linlin Xu, P. Siva, A. Wong, and D. A. Clausi, 2015. "Hyperspectral image classification with limited labeled training samples using enhanced ensemble learning and conditional random fields", IEEE Journal of Selected Topics in Applied Earth observations and Remote Sensing, 8(6): 2427- 2438.
5. Linlin Xu, J. S. Mohammad, A. Wong, F. Li, L. Wang, D. A. Clausi, 2015, “Oil spill candidate detection from SAR imagery using a thresholding-guided stochastic fully-connected conditional random field model,” The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, June 2015, Boston, IEEE Explore digital library, 79-86.
6. Li F., D. A. Clausi, L. Wang, and Linlin Xu, “A semi-supervised approach for ice-water classification using dual-polarization SAR satellite imagery”, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, June 2015, Boston, IEEE Explore digital library, 2015, 28-35.

2014:

1. Linlin Xu, J. Li and A. Brenning, 2014. “A comparative study of different classification techniques for marine oil spill identification using RADARSAT-1 images“, Remote Sensing of Environment, 141, 14-23.
2. Linlin Xu, and J. Li, 2014. “Bayesian classification of hyperspectral imagery based on probabilistic sparse representation and Markov random field“, IEEE Geoscience and Remote Sensing Letters, 11(4): 823-827.
3. Linlin Xu, J. Li, Y. Shu and J. Peng, 2014. “SAR image denoising via clustering-based principal component analysis“, IEEE Transactions on Geoscience and Remote Sensing, 52(11): 6858-6869.
4. Linlin Xu, J. Li, A. Wong and J. Peng, 2014. “K-P-Means: a clustering algorithm of K “purified” means for hyperspectral endmember estimation“, IEEE Geoscience and Remote Sensing Letters, 11(10): 1787-1791
5. Linlin Xu, J. Li, A. Wong, C. Wang, 2014. “A kernel PCA texture feature for efficient segmentation of RADARSAT-2 sea ice imagery“, International Journal of Remote Sensing, 35(14): 5053-5072.

books：

1. 徐林林，2010，“JAVA WEB编程从入门到实践”，ISBN 978-7-302-19747-8，清华大学出版社。
2. Linlin Xu, J. Li, "Mapping Sea Ice from Satellite SAR Imagery", Monitoring and Modeling of Global Changes: A Geomatics Perspective, Springer Netherlands, 2015, pp 113-135.

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国家自然基金青年基金项目：顾及异方差与空间约束的高光谱混合像元模糊聚类分解方法研究，** （主持）.
国家自然基金面上基金项目：耦合非平稳噪声的卡尔曼滤波方法研究及应用，**（参与）.
其他部委重点实验室开放基金：联合星间链路与地基观测数据的导航卫星融合定轨技术研究，（参与）。

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徐林林，2010，“JAVA WEB编程从入门到实践”，ISBN 978-7-302-19747-8，清华大学出版社。
Linlin Xu, J. Li, "Mapping Sea Ice from Satellite SAR Imagery", Monitoring and Modeling of Global Changes: A Geomatics Perspective, Springer Netherlands, 2015, pp 113-135.

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招收测绘工程、遥感信息工程、地理信息系统、计算机科技与技术专业的研究生。欢迎报考。