电子邮件: longtf@aircas.ac.cn
通信地址: 北京市海淀区邓庄南路9号
邮政编码: 100094
研究领域
遥感图像处理与应用、智能遥感信息挖掘、国产卫星数据定量化、森林-火烧迹地遥感制图、夜光遥感等
教育背景
工作经历
工作简历
社会兼职
2020-12-28-2021-12-27,《Remote Sensing》, Topic Editor, Guest Editor
专利与奖励
奖励信息
专利成果
出版信息
第一/通讯作者代表性论文如下:
1. C. Gong, T. Long, R. Yin, W. Jiao, and G. Wang, “A hybrid algorithm with swin transformer and convolution for cloud detection,” Remote Sens., vol. 15, no. 21, Art. no. 21, Jan. 2023, doi: 10.3390/rs15215264.
2. Y. Du et al., “Improving unsupervised object-based change detection via hierarchical multi-scale binary partition tree segmentation: a case study in the yellow river source region,” Remote Sens., vol. 16, no. 4, p. 629, Feb. 2024, doi: 10.3390/rs16040629.
3. Liu, Y.; Long, T.; Jiao, W.; Chen, B.; Cheng, B.; Du, Y.; He, G.; Huang, P. Leveraging “Night-Day” Calibration Data to Correct Stripe Noise and Vignetting in SDGSAT-1 Nighttime-Light Images. IEEE Trans. Geosci. Remote Sens. 2023, 1–1, doi:10.1109/TGRS.2023.3300257.
4. Liu, Y.; Long, T.; Jiao, W.; Du, Y.; He, G.; Chen, B.; Huang, P. Automatic Segment-Wise Restoration for Wide Irregular Stripe Noise in SDGSAT-1 Multispectral Data Using Side-Slither Data. Egypt. J. Remote Sens. Space. Sci. 2023, 26, 747–757, doi:10.1016/j.ejrs.2023.07.012.
5. 温春晖; 龙腾飞; 焦伟利; 林子镕; 刘永坤; 刘慧婵; 刘鸣; 何国金 北京市典型居住区道路照明公众感知评价及模拟优化. 照明工程学报 2023, 34, 114–125.
6. 龙腾飞; 焦伟利; 何国金; 王桂周; 张兆明 国产光学卫星正射影像产品及自动生成算法. 遥感学报 2023, 27, 635–650, doi:10.11834/jrs.20232041.
7. Long, T.; Xu, Y.; Zou, H.; Lu, L.; Yuan, T.; Dong, Z.; Dong, J.; Ke, X.; Ling, S.; Ma, Y. A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction. Sensors 2022, 22, 8565, doi:10.3390/s22218565.
8. Liu, Y.; Long, T.; Jiao, W.; He, G.; Chen, B.; Huang, P. A General Relative Radiometric Correction Method for Vignetting and Chromatic Aberration of Multiple CCDs: Take the Chinese Series of Gaofen Satellite Level-0 Images for Example. IEEE Trans. Geosci. Remote Sens. 2022, 60, 1–25, doi:10.1109/TGRS.2022.3141223.
9. Wei, M.; Zhang, Z.; Long, T.; He, G.; Wang, G. Monitoring Landsat Based Burned Area as an Indicator of Sustainable Development Goals. Earth’s Future 2021, 9, doi:10.1029/2020EF001960.
10. Zhang, Z.; Long, T.; He, G.; Wei, M.; Tang, C.; Wang, W.; Wang, G.; She, W.; Zhang, X. Study on Global Burned Forest Areas Based on Landsat Data. Photogramm. Eng. Remote Sens. 2020, 86, 503–508, doi:10.14358/PERS.86.8.503.
11. Long, T.; Jiao, W.; He, G.; Yin, R.; Wang, G.; Zhang, Z. Block Adjustment With Relaxed Constraints From Reference Images of Coarse Resolution. IEEE Trans. Geosci. Remote Sens. 2020, 58, 7815–7828, doi:10.1109/TGRS.2020.2984533.
12. Long, T.; Zhang, Z.; He, G.; Jiao, W.; Tang, C.; Wu, B.; Zhang, X.; Wang, G.; Yin, R. 30 m Resolution Global Annual Burned Area Mapping Based on Landsat Images and Google Earth Engine. Remote Sensing 2019, 11, 489, doi:10.3390/rs11050489.
13. Dong, Y.; Jiao, W.; Long, T.; Liu, L.; He, G.; Gong, C.; Guo, Y. Local Deep Descriptor for Remote Sensing Image Feature Matching. Remote Sensing 2019, 11, 430, doi:10.3390/rs11040430.
14. Dong, Y.; Jiao, W.; Long, T.; Liu, L.; He, G. Eliminating the Effect of Image Border with Image Periodic Decomposition for Phase Correlation Based Remote Sensing Image Registration. Sens. 2019, 19, 2329, doi:10.3390/s19102329.
15. Jiang, W.; He, G.; Long, T.; Guo, H.; Yin, R.; Leng, W.; Liu, H.; Wang, G. Potentiality of Using Luojia 1-01 Nighttime Light Imagery to Investigate Artificial Light Pollution. Sens. 2018, 18, 2900, doi:10.3390/s18092900.
16. Jiang, W.; He, G.; Long, T.; Ni, Y.; Liu, H.; Peng, Y.; Lv, K.; Wang, G. Multilayer Perceptron Neural Network for Surface Water Extraction in Landsat 8 OLI Satellite Images. Remote Sensing 2018, 10, 755, doi:10.3390/rs10050755.
17. Jiang, W.; He, G.; Leng, W.; Long, T.; Wang, G.; Liu, H.; Peng, Y.; Yin, R.; Guo, H. Characterizing Light Pollution Trends across Protected Areas in China Using Nighttime Light Remote Sensing Data. ISPRS International Journal of Geo-Information 2018, 7, 243, doi:10.3390/ijgi7070243.
18. Dong, Y.; Long, T.; Jiao, W.; He, G.; Zhang, Z. A Novel Image Registration Method Based on Phase Correlation Using Low-Rank Matrix Factorization With Mixture of Gaussian. IEEE Trans. Geosci. Remote Sens. 2018, 56, 446–460, doi:10.1109/TGRS.2017.2749436.
19. Dong, Y.; Jiao, W.; Long, T.; He, G.; Gong, C. An Extension of Phase Correlation-Based Image Registration to Estimate Similarity Transform Using Multiple Polar Fourier Transform. Remote Sensing 2018, 10, 1719, doi:10.3390/rs10111719.
20. Jiang, W.; He, G.; Long, T.; Liu, H. Ongoing Conflict Makes Yemen Dark: From the Perspective of Nighttime Light. Remote Sensing 2017, 9, 798, doi:10.3390/rs9080798.
21. Long, T.; Jiao, W.; He, G.; Zhang, Z. A Fast and Reliable Matching Method for Automated Georeferencing of Remotely-Sensed Imagery. Remote Sensing 2016, 8, 56, doi:10.3390/rs8010056.
22. Long, T.; Jiao, W.; He, G. RPC Estimation via $\ell_1$-Norm-Regularized Least Squares (L1LS). IEEE Trans. Geosci. Remote Sens. 2015, 53, 4554–4567, doi:10.1109/TGRS.2015.2401602.
23. Long, T.; Jiao, W.; He, G.; Zhang, Z.; Cheng, B.; Wang, W. A Generic Framework for Image Rectification Using Multiple Types of Feature. Isprs J. Photogramm. Remote Sens. 2015, 102, 161–171, doi:10.1016/j.isprsjprs.2015.01.015.
24. Long, T.; Jiao, W.; He, G. Nested Regression Based Optimal Selection (NRBOS) of Rational Polynomial Coefficients. Photogramm. Eng. Remote Sens. 2014, 80, 261–269, doi:10.14358/PERS.80.3.261.
25. Long, T.; Jiao, W.; He, G.; Wang, W. Automatic Line Segment Registration Using Gaussian Mixture Model and Expectation-Maximization Algorithm. IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. 2014, 7, 1688–1699, doi:10.1109/JSTARS.2013.2273871.
26. 龙腾飞; 焦伟利; 王威 基于面特征的遥感图像几何校正模型. 测绘学报 2013, 42, 540–545.
发表著作
科研项目
( 2 ) 基于新型泛化模型的超大幅宽卫星影像快速高精度几何处理技术研究, 负责人, 研究所科学与颠覆性技术研究先导基金, 2023-06--2025-05
( 3 ) 青年创新促进会, 负责人, 中国科学院人才项目, 2019-01--2022-12
( 4 ) 基于松弛约束的卫星影像序列多特征地面无控协同定位, 负责人, 自然科学基金青年项目, 2018-01--2020-12
( 5 ) 30m分辨率全球多源卫星数据定量化处理, 负责人, 国家重点研发计划子课题, 2016-01--2021-12
( 6 ) 基于认知计算的遥感卫星下行数据即时服务的理论与方法研究, 几何技术负责人, 自然科学基金重点项目, 2018-01--2022-12
( 7 ) 地球大数据科学工程——CASEarth DataBank 系统建设, 主任设计师, A类先导专项, 2018-01--2022-12
( 8 ) 第二次青藏高原综合科学考察研究-生态系统特征参数遥感反演, 副组长, 国家任务, 2019-01--2024-12
( 9 ) 全时序地表反射率地理格网RTU产品研制, 负责人, 中国科学院计划, 2021-01--2021-12
全球火烧迹地制图
提出基于Landsat系列卫星数据的全球火烧迹地自动制图方法,结合长时间序列的多源卫星遥感数据,通过利用全球火烧迹地和非火烧迹地样本库和基于生态系统分区的机器学习方法,实现了全球30米分辨率火烧迹地产品的快速高精度生产。研发了国际首套长时序全球30米分辨率火烧迹地产品(GABAM,2000-2021),是目前最高空间分辨率的全球火烧迹地产品,比现有国际同类产品空间分辨率高出一个数量级,实现全球火灾的精准监测。
GABAM 2015
与Fire_cci产品(其它最高分辨率全球火烧迹地产品)对比
产品链接:https://vapd.gitlab.io/post/gabam/
Long, T.; Zhang, Z.; He, G.; Jiao, W.; Tang, C.; Wu, B.; Zhang, X.; Wang, G.; Yin, R. 30 m Resolution Global Annual Burned Area Mapping Based on Landsat Images and Google Earth Engine. Remote Sens. 2019, 11, 489.
指导学生
现指导学生
温春晖 硕士研究生 085700-资源与环境
王龙飞 硕士研究生 070503-地图学与地理信息系统