人物經歷
2009年於中國地質大學(北京)獲學士學位,2012年於中國科學院地理科學與資源研究獲碩士學位,2017年於加州大學默塞德分校獲博士學位,並於同年進入中國科學院植物研究所數字生態研究組工作。曾獲得美國攝影測量學會“William A. Fischer Memorial Scholarship”、國家優秀自費留學生等獎項。
研究方向
利用雷射雷達(LiDAR)為主的遙感技術探討人類活動以及全球氣候變化對陸地生態系統的影響。
科研項目
[1] 基於雷射雷達與光學影像的作物表型採集與翻譯,中科院先導子任務,2019.01-2024.12,主持
[2] 基於雷射雷達技術的樹木三維構型空間格局及驅動力分析:以蒙古櫟為例,國家自然科學基金面上項目,2019.01.01-2021.12.31,主持
[3] 基於雷射雷達與深度學習技術的作物三維表型特徵提取研究,國家自然科學基金應急項目,2018.01.01-2018.12.31,主持
[4] 新一代中國植被圖繪製,中科院先導子課題,2018.01.01-2022.12.31,骨幹成員
發表論文
2021
1.Jin SC, Sun XL, Wu FF, Su YJ, Li YM, Song SL, Xu KX, Ma Q, Baret F, Jiang D, Ding YF, Guo QH. 2021. Lidar Sheds New Light on Plant Phenomics for Plant Breeding and Management: Recent Advances And Future Prospects. ISPRS Journal of Photogrammetry and Remote Sensing. 171: 202-223.
2020
2.Hu TY, Sun XL, Su YJ, Guan HC, Sun QH, Kelly M, Guo QH. 2020. Development and Performance Evaluation of A Very Low-Cost UAV-Lidar System for Forestry Applications. Remote Sensing. 13(1):77
3.Wu SB, Wang J, Yan ZB, Ssong GQ, Chen Y, Ma Q, Deng MF, Wu YT, Zhao YY, Guo ZF, Yuan ZQ, Dai GH, Xu XT, Yang X, Su YJ, Liu LL, Wu J. 2020. Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations. ISPRS Journal of Photogrammetry and Remote Sensing. 171: 36-48.
4.Jin SC, Su YJ, Zhao XQ, Hu TY, Guo QH. 2020. A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13: 3958-3974.
5.Guan HC, Su YJ*, Sun XL, Xu GC, Ma Q, Wu XY Wu J, Liu LL, Guo QH. 2020. A Marker-Free Method for Registering Multi-Scan Terrestrial Laser Scanning Data in Forest Environments. ISPRS Journal of Photogrammetry and Remote Sensing. 166(8): 82-94.
6.Hu TY, Zhang YY, Su YJ, Zheng Y, Lin GH, Guo QH. 2020. Mapping the Global Mangrove Forest Aboveground Biomass Using Multisource Remote Sensing Data. Remote Sensing. 12: 1690.
7.Jin SC, Su YJ, Song SL, Xu KX, Hu TY, Yang QL, Wu FF, Xu GC, Ma Q, Guan HC, Pang SX, Li YM, Guo QH. 2020. Non-Destructive Estimation of Field Maize Biomass Using Terrestrial Lidar: An Evaluation from Plot Level to Individual Leaf Level. Plant Methods. 16(69): 1-19.
8.Su YJ, Guo QH, Hu TY, Guan HC, Jin SC, An SZ, Chen XL, Guo K, Hao ZQ, Hu YM, Huang YM, Jiang MX, Li JX, Li ZJ, Li XK, Li XW, Liang CZ, Liu RL, Liu Q, Ni HW, Peng SL, Shen ZH, Tang ZY, Tian XJ, Wang XH, Wang RQ, Xie ZQ, Xie YZ, Xu XN, Yang XB, Yang YC, Yu LF, Yue M, Zhang F, Ma KP. 2020. An Updated Vegetation Map of China (1: 1000000). Science Bulletin. 65(13): 1125-1136.
9.Su YJ, Hu TY, Wang YC, Li YM, Dai JY, Liu HY, Jin SC, Ma Q, Wu J, Liu LL, Fang JY, Guo QH. 2020. Large-Scale Geographical Variations and Climatic Controls on Crown Architecture Traits. Journal of Geophysical Research – Biogeosciences. 125(2): e2019JG005306.
10. Guo QH, Jin SC, Li M, Yang QL, Xu KX, Ju YZ, Zhang J, Xuan J, Liu J, Su YJ, Xu Q, Liu Y. 2020. Application of Deep Learning In Ecological Resource Research: Theories, Methods, And Challenges. Science China Earth Science. 63: 1457–1474.
11. Li YM, Su YJ, Zhao XX, Yang MH, Hu TY, Zhang J, Liu J, Liu M, Guo QH. 2020. Retrieval of Tree Branch Architecture Attributes from Terrestria Laser Scan Data Using A Laplacian Algorithm. Agricultural and Forest Meteorology. 284: 107874.
12. Wang DZ, Wan B, Liu J, Su YJ*, Guo QH, Qiu PH, Wu XC. 2020. Estimating Aboveground Biomass of The Mangrove Forests on Northeast Hainan Island in China Using An Upscaling Method From Field Plots, UAV-LiDAR Data and Sentinel-2 Imagery. International Journal of Applied Earth Observation and Geoinformation. 85: 101986.
13. Xu KX, Su YJ, Liu J, Hu TY, Jin SC, Ma Q, Zhai QP, Wang R, Zhang J, Li YM, Liu HY, Guo QH. 2020. Estimation of Degraded Grassland Aboveground Biomass Using Machine Learning Methods from Terrestrial Laser Scanning Data. Ecological Indicators. 108: 105747.
14. Guan HC, Su YJ*, Hu TY, Wang R, Ma Q, Yang QL, Sun XL, Li YM, Jin SC, Zhang J, Ma Q, Liu M, Wu FY, Guo QH. 2020. A Novel Framework to Automatically Fuse Multi-platform Lidar Data in Forest Environments Based on Tree Locations. IEEE Transactions on Geoscience and Remote Sensing. 58(3): 2165-2177.
15. 郭慶華,胡天宇,馬勤,徐可心,楊秋麗,孫千惠,李玉美,蘇艷軍, 2020. 新一代遙感技術助力生態系統生態學研究(生態技術與方法專輯)”. 植物生態學報. 44(4): 418-435.
2019
16. Jin SC, Su YJ*, Gao S, Wu FF, Ma Q, Xu KX, Ma Q, Hu TY, Liu J, Pang SX, Guan HC, Zhang J, Guo QH*. 2019. Separating The Structural Components of Maize for Field Phenotyping Using Terrestrial Lidar Data and Deep Convolutional Neural Networks.IEEE Transactions on Geoscience and Remote Sensing. 58(4): 2644 - 2658. (Cover Paper) (ESI Highly cited paper).
17. Guan HC, Su YJ, Hu TY, Chen J, Guo QH. 2019. An Object-Based Strategy for Improving The Accuracy of Spatiotemporal Satellite Imagery Fusion for Vegetation Mapping Applications. Remote Sensing. 11(24): 2927.
18. Yang QL, Su YJ, Kelly M, Hu TY, Ma Q, Li YM, Song SL, Zhang J, Xu GC, Wei JX, Guo QH. 2019. The Influences of Vegetation Characteristics on Individual Tree Segmentation Methods with Airborne Lidar Data. Remote Sensing. 11: 2880.
19. Hu TY, Ma Q, Su YJ*, Battles JJ, Collins BM., Stephens SL, Kelly M, Guo QH. 2019. A Simple and Integrated Approach for Fire Severity Assessment Using Bi-Temporal Airborne Lidar Data. International Journal of Applied Earth Observation and Geoinformation. 78: 25-38.
20. Su YJ, Wu FF, Ao Zr, Jin SC, Qin F, Liu BX, Pang SX, Liu LL, Guo QH. 2019. Evaluating Maize Phenotype Dynamics Under Drought Stress Using Terrestrial Lidar. Plant Methods. 15: 11.
21. Sun F, Wang R, Wan B, Su YJ, Guo QH, Huang YX, Wu XC. 2019. Efficiency of Extreme Gradient Boosting for Imbalanced Land Cover Classification Using an Extended Margin and Disagreement Performance. ISPRS International Journal of Geo-Information. 8(7): 315.
22. Zheng ZS, Ma Q, Jin SC, Su YJ, Guo QH, Bales RC. 2019. Canopy and Terrain Interactions Affecting Snowpack Spatial Patterns in the Sierra Nevada of California. Water Resources Research. 55: 8721–8739.
23. Jin SC, Su YJ, Wu FF, Pang SX, Gao S, Hu TY, Liu J, Guo QH. 2019. Stem-Leaf Segmentation and Phenotypic Trait Extraction of Individual Maize Using Terrestrial LiDAR Data. IEEE Transactions on Geoscience and Remote Sensing. 57(3): 1336-1346.
2018
24. Jin SC, Su YJ*, Gao S, Wu FF, Hu TY, Liu J, Li WK, Wang DC, Chen SJ, Jiang YX, Pang SX, Guo QH*. 2018. Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms.Front Plant Sci. 9: 866-875.
25. Jin SC Su YJ, Gao S, Hu TY, Liu J, Guo QH. 2018. The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data. Remote Sensing. 10(8): 1183.
26. Li WK, Guo QH, Tao SL, Su YJ. 2018. VBRT: A Novel Voxel-Based Radiative Transfer Model for Heterogeneous Three-Dimensional Forest Scenes. Remote Sensing of Environment. 206: 318-335.
27. Li YM, Su YJ*, Hu TY, Xu GC, Guo QH*. 2018. Retrieving 2-D Leaf Angle Distributions for Deciduous Trees From Terrestrial Laser Scanner Data. IEEE Transactions on Geoscience and Remote Sensing. 56(8): 4945-4955.
28. Luo LP, Zhai QP, Su YJ*, Ma Q, Kelly M, Guo QH*. 2018. Simple Method for Direct Crown Base Height Estimation of Individual Conifer Trees Using Airborne Lidar Data. Opt Express. 26(10): A562-A578.
29. Ma Q, Su YJ*, Luo LP, Li Le, Kelly M, Guo QH. 2018. Evaluating The Uncertainty of Landsat-Derived Vegetation Indices in Quantifying Forest Fuel Treatments Using Bi-Temporal Lidar Data. Ecological Indicators. 95: 298-310.
30. Wang DZ, Wan B, Qiu PH, Su YJ, Guo QH, Wang R, Sun F, Wu XC. 2018. Evaluating the Performance of Sentinel-2, Landsat 8 and Pleiades-1 in Mapping Mangrove Extent and Species. Remote Sensing. 10(9): 27.
31. Wang DZ, Wan B, Qiu PH, Su YJ, Guo QH, Wu XC. 2018. Artificial Mangrove Species Mapping Using Pléiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms. Remote Sensing. 10(2): 294.
32. Zhao XQ, Su YJ, Li WK, Hu TY, Liu J, Guo QH. 2018. A Comparison of LiDAR Filtering Algorithms in Vegetated Mountain Areas. Canadian Journal of Remote Sensing. 1-12.
33. Zhao XQ, Su YJ, Hu TY, Chen LH, Gao S, Wang R, Jin SC, Guo QH. 2018. A Global Corrected SRTM DEM Product for Vegetated Areas. Remote Sensing Letters. 9(4): 393-402.
34. 周中一,劉冉,時書納,蘇艷軍,李文楷,郭慶華, 2018. 基於雷射雷達數據的物種分布模擬: 以美國加州 內華達山脈南部區域食魚貂分布模擬為例. 生物多樣性, 26, 878-891.
35. 郭慶華, 胡天宇, 姜媛茜, 金時超, 王瑞, 關宏燦, 楊秋麗, 李玉美, 吳芳芳, 翟秋萍, 劉瑾, 蘇艷軍. 2018. 遙感在生物多樣性研究中的套用進展. 生物多樣性, 26, 789-806.
2017
36. Ao ZR, Su YJ, Li WK, Guo QH, Zhang J. 2017. One-Class Classification of Airborne LiDAR Data in Urban Areas Using a Presence and Background Learning Algorithm. Remote Sensing. 9(10): 1001.
37. Guo QH, Su YJ, Hu TY, Zhao XQ, Wu FF, Li YM, Liu J, Chen LH, Xu GC, Lin GH, Zheng Y, Lin YQ, Mi XC, Fei L, Wang XG. 2017. An Integrated UAV-Borne Lidar System for 3D Habitat Mapping in Three Forest Ecosystems Across China. International Journal of Remote Sensing.38(8-10): 2954-2972.
38. Kelly M, Su YJ, Di T S, Fry D, Collins B, Stephens S, Guo QH. 2017. Impact of Error in Lidar-Derived Canopy Height and Canopy Base Height on Modeled Wildfire Behavior in the Sierra Nevada, California, USA.Remote Sensing. 10(2): 10.
39. Li YM, Guo QH, Su YJ, Tao SL, Zhao KG, Xu GC. 2017. Retrieving The Gap Fraction, Element Clumping Index, And Leaf Area Index of Individual Trees Using Single-Scan Data From A Terrestrial Laser Scanner. ISPRS Journal of Photogrammetry and Remote Sensing. 130: 308-316.
40. Ma Q, Su YJ, Guo QH. 2017. Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 10(9): 4225-4236.
41. Ma Q, Su YJ, Tao SL, Guo QH. 2017. Quantifying Individual Tree Growth and Tree Competition Using Bi-Temporal Airborne Laser Scanning Data: A Case Study in The Sierra Nevada Mountains, California.International Journal of Digital Earth. 11(5): 485-503.
42. Su YJ, Bales RC., Ma Q, Nydick K, Ray RL., Li WK, Guo QH. 2017. Emerging Stress and Relative Resiliency of Giant Sequoia Groves Experiencing Multiyear Dry Periods in a Warming Climate. Journal of Geophysical Research: Biogeosciences. 122(11): 3063-3075.
43. Su YJ, Ma Q, Guo QH. 2017. Fine-Resolution Forest Tree Height Estimation Across The Sierra Nevada Through The Integration of Spaceborne Lidar, Airborne Lidar, and Optical Imagery.International Journal of Digital Earth. 10(3): 307-323.
44. Xue BL, Guo QH, Hu TY, Wang GQ, Wang YC, Tao SL, Su YJ, Liu J, Zhao XQ. 2017. Evaluation of Modeled Global Vegetation Carbon Dynamics: Analysis Based on Global Carbon Flux and Above-Ground Biomass Data. Ecological Modelling. 355: 84-96.
45. Xue BL, Guo QH, Hu TY, Xiao JF, Yang YH, Wang GQ, Tao SL, Su YJ, Liu J, Zhao XQ. 2017. Global Patterns of Woody Residence Time and Its Influence on Model Simulation of Aboveground Biomass. Global Biogeochemical Cycles. 31(5): 821-835.
46. Zhu JX, Su YJ, Guo QH, Harmon TC. 2017. Unsupervised Object-Based Differencing for Land-Cover Change Detection. Photogrammetric Engineering & Remote Sensing. 83(3): 225-236.
2016
47. Hu TY, Su YJ, Xue BL, Liu J, Zhao XQ, Fang JY, Guo QH. 2016. Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data.Remote Sensing. 8(7): 1-27.
48. Li YM, Guo QH, Tao SL, Zheng G, Zhao KG, Xue BL, Su YJ. 2016. Derivation, Validation, and Sensitivity Analysis of Terrestrial Laser Scanning-Based Leaf Area Index. Canadian Journal of Remote Sensing. 42(6): 719-729.
49. Su YJ, Guo QH, Collins BM., Fry DL., Hu TY, Kelly M. 2016. Forest Fuel Treatment Detection Using Multi-Temporal Airborne Lidar Data and High-Resolution Aerial Imagery: A Case Study in the Sierra Nevada Mountains, California. International Journal of Remote Sensing. 37(14): 3322-3345. (Cover Paper)
50. Su YJ, Guo QH, Fry DL., Collins BM., Kelly M, Flanagan JP., Battles JJ. 2016. A Vegetation Mapping Strategy for Conifer Forests by Combining Airborne LiDAR Data and Aerial Imagery. Canadian Journal of Remote Sensing. 42(1): 1-15.
51. Su YJ, Guo QH, Xue BL, Hu TY, Alvarez O, Tao SL, Fang JY. 2016. Spatial Distribution of Forest Aboveground Biomass in China: Estimation Through Combination of Spaceborne Lidar, Optical Imagery, And Forest Inventory Data. Remote Sensing of Environment. 173: 187-199.
52. Zhao XQ, Guo QH, Su YJ, Xue BL. 2016. Improved Progressive Tin Densification Filtering Algorithm for Airborne Lidar Data in Forested Areas. ISPRS Journal of Photogrammetry and Remote Sensing. 117: 79-91.
2015及以前
53. Su YJ, Guo QH, Ma Q, Li WK. 2015. SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery.Remote Sensing. 7(9): 11202-11225.
54. Tao SL, Guo QH, Xu SW, Su YJ, Li YM, Wu FF. 2015. A Geometric Method for Wood-Leaf Separation Using Terrestrial and Simulated Lidar Data. Photogrammetric Engineering & Remote Sensing. 81(10): 767-776.
55. Tempel DJ., Gutiérrez RJ., Battles JJ., Fry DL., Su YJ, Guo QH, Reetz MJ., Whitmore SA., Jones GM., Collins BM., Stephens SL., Kelly M, Berigan WJ., Peery MZ. 2015. Evaluating Short- and Long-Term Impacts of Fuels Treatments and Simulated Wildfire on An Old-Forest Species. Ecosphere. 6(12): 1-19.
56. Wan B, Guo QH, Fang F, Su YJ, Wang R. 2015. Mapping US Urban Extents from MODIS Data Using One-Class Classification Method.Remote Sensing. 7(8): 10143-10163.
57. Su YJ, Guo QH. 2014. A Practical Method for SRTM DEM Correction Over Vegetated Mountain Areas. ISPRS Journal of Photogrammetry and Remote Sensing. 87: 216-228.
58. Tao SL, Guo QH, Li L, Xue BL, Kelly M, Li WK, Xu GC, Su YJ. 2014. Airborne Lidar-Derived Volume Metrics for Aboveground Biomass Estimation: A Comparative Assessment for Conifer Stands.Agricultural and Forest Meteorology. 198-199: 24-32.
59. Wang YJ, Su YJ*, 2013. Influence of solar activity on breaching, overflowing and course shifting events of the lower yellow river in the late Holocene. Holocene, 23, 656-666.
60. Wang YJ, Su YJ*, 2011. The geo-pattern of course shifts of the Lower Yellow River. Journal of Geographical Sciences, 21, 1019-1036.
61. 蘇艷軍, 王英傑, 羅斌, & 余卓淵, 2009. 新型網路地圖符號概念模型及其描述體系. 地球信息科學, 11, 839-844.