學科專業：攝影測量與遙感 研究領域：激光雷達遙感、森林生态遙感、北極遙感、地球交互

[1] 基于背包式MLS與UAV遙感協同的單木-林分尺度森林地上生物量精細反演、國家自然科學基金面上項目、項目負責人、2015/01-2018/12

[2] 針對形态特征的激光掃描植物表型技術研究、北京市自然科學基金青年項目、項目負責人、2015/01-2016/12

[3] 基于背包式移動地基激光掃描的林下灌木層形态分布模式測量、博士學科點專項科研基金、項目負責人、2014/01-2016/12

[4] 面向多領域遙感應用的輕小型激光掃描技術研發、beat365985學科建設、項目負責人、2013/01-2015/12

[5] 基于地基激光掃描反演森林冠層結構參數、教育部留學回國人員科研啟動基金、項目負責人、2014/01-2016/12

[1] Lin Y*, Jiang M, Pellikka P, Heiskanen J, 2018. Recruiting conventional tree architecture models into state-of-the-art LiDAR mapping for investigating tree growth habits in structure. Frontiers in Plant Science, 9, 220.

[2] Jiang M, Lin Y*, 2018. Desertification in the south Junggar Basin, 2000-2009: Part I. Spatial analysis and indicator retrieval. Advances in Space Research, doi: 10.1016/j.asr.2017.11.038.

[3] Zhang L, Chen Y, Zhao Y, Henze D, Zhu L, Song Y, Paulot F, Liu X, Pan Y, Lin Y, Huang B, 2018. Agricultural ammonia emissions in China: reconciling bottom-up and top-down estimates, Atmospheric Chemistry and Physics, 18, 339–355.

[4] Luo S, Chen J, Wang C, Gonsamo A, Xi X, Lin Y, Qian M, Peng D, Nie S, Qin H, 2018. Comparative performance of airborne LiDAR height and intensity data for leaf area index estimation. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 11(1), 300-310.

[5] Zeng W, Fang X, Lin Y, Huang X, Yao Y, 2018. On the errors-in-variables model with inequality constraints of dependent variables for geodetic transformation. Survey Review, doi: 10.1080/00396265.2017.1396407.

[6] Zeng W, Fang X, Lin Y, Huang X, Zhou Y, 2018. On the total least-squares estimation for autoregressive model. Survey Review, doi: 10.1080/00396265.2017.1281096.

[7] Lin Y*, Jiang M, 2017. Maximum temperature drove snow cover expansion from the Arctic, 2000-2008. Scientific Reports, 10(7), 701-718.

[8] Lin Y*, Wei T, Yang B, Knyazikhin Y, Zhang Y, Sato H, Fang X, Liang X, Yan L, Sun S, 2017. TLS-bridged co-imputation of tree-level multifarious stem structure variables from WorldView-2 panchromatic imagery: A case study of boreal forest. International Journal of Digital Earth, 10(7), 701-718.

[9] Lin Y*, Jiang M, 2017. Towards extending terrestrial laser scanning applications in forestry: A case study of broad- and needle-leaf tree classification. Journal of Applied Remote Sensing, 11(1), 016037.

[10] Wang H, Lin Y*, Wang Z, Yao Y, Zhang Y, Wu L, 2017. Development of a low-cost 2D laser scanner based mobile terrestrial proximal sensing system for 3D plant structure phenotyping in indoor environments. Computers and Electronics in Agriculture, 140, 180-189.

[11] Jing X, Yan L, Hu X, He L, Zhao S, Hu X, Xu H, Lin Y*, Ma A, 2017. NPP/VIIRS solar reflectance bands radiation validation based on mid-infrared reference standard on sea surface sun glint sites. Journal of Infrared and Millimeter Waves, 36(6), 694-700.

[12] Yao Y, Liang S, Yu J, Chen J, Liu S, Lin Y, Fisher J, McVicar T, Cheng J, Jia K, Zhang X, Xie X, Jiang B, Sun L, 2017. A simple temperature domain two-source model for estimating agricultural field surface energy fluxes from Landsat imagery. Journal of Geophysical Research: Atmospheres, 122(10), 5211-5236.

[13] Qin H, Wang C, Pan F, Lin Y, Xi X, Luo S, 2017. Estimation of FPAR and FPAR profile for maize canopies using airborne LiDAR. Ecological Indicators, 83, 53-61.

[14] Yao Y, Liang S, Yu J, Zhao S, Lin Y, Jia K, Zhang X, Cheng J, Xie X, Sun L, Wang X, Zhang L, 2017. Difference in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms. International Journal of Applied Earth Observation and Geoinformation, 56, 1-12.

[15] Fan A, Chen W, Liang L, Sun W, Lin Y, Che H, Zhao X, 2017. Evaluation and comparison of long-term MODIS C5.1 and C6 products against AERONET observations over China. Remote Sensing, 9(12), 1269.

[16] Luo S, Wang C, Xi X, Pan F, Qian M, Peng D, Nie S, Qin H, Lin Y, 2017. Retrieving aboveground biomass of wetland Phragmites australis (common reed) using a combination of airborne discrete-return LiDAR and hyperspectral data. International Journal of Applied Earth Observation and Geoinformation, 58, 107-117.

[17] Rimal B, Zhang L, Keshtkar H, Wang N, Lin Y, 2017. Monitoring and modeling of spatiotemporal urban expansion and land-use/land-cover change using integrated Markov Chain cellular automata model. ISPRS International Journal of Geo-Information, 6(9), 288.

[18] Lin Y*, Herold M, 2016. Tree species classification based on explicit tree structure feature parameters derived from static terrestrial laser scanning data. Agriculture and Forest Meteorology, 216, 105-114.

[19] Lin Y*, Hyyppä J, 2016. A comprehensive but efficient framework of proposing and validating feature parameters from airborne LiDAR data for tree species classification. International Journal of Applied Earth Observation and Geoinformation, 46, 45-55.

[20] Lin Y*, West G, 2016. Reflecting conifer phenology using mobile terrestrial LiDAR: A case study of Pinus sylvestris growing under the Mediterranean climate in Perth, Australia. Ecological Indictors, 70, 1-9.

[21] Lin Y*, Zhang L, Wang C, 2016. Airborne LiDAR laser return intensity-based investigation into crown-inside? - a case study on Quercus robur trees. Journal of Applied Remote Sensing, 10(2), 026024.

[22] Lin Y*, West G, 2016. Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR. International Journal of Applied Earth Observation and Geoinformation, 50, 150-158.

[23] Wei T, Lin Y*, Yan L, Zhang L, 2016. Tree species classification based on stem-related feature parameters derived from static terrestrial laser scanning data. International Journal of Remote Sensing, 37(18), 4420-4440.

[24] Yang B, Knyazikhin Y, Lin Y, Yan K, Chen C, Park T, Choi S, Mottus M, Rautainen M, Myneni R, Yan L, 2016. Analysis of impact of needle surface properties on estimation of needle absorption spectrum: Case study with coniferous needle and shoot samples. Remote Sensing, 8(7), 563.

[25] Zhang Y, Yao Y, Lin Y, Xiang L, 2016. Satellite characterization of terrestrial drought over Xinjiang Uygur Autonomous Region of China over past three decades. Environmental Earth Sciences, 75, 6.

[26] Wang S, Huang C, Zhang L, Lin Y, Cen Y, Wu T, 2016. Monitoring and assessing the 2012 drought in the Great Plains: Analyzing satellite retrieved solar-induced chlorophyll fluorescence, drought indices, and flux measured gross primary production. Remote Sensing, 8, 61.

[27] Lin Y*, 2015. LiDAR: An important tool for next-generation phenotyping technology of high potential for plant phenomics? Computers and Electronics in Agriculture, 119, 61-73.

[28] Lin Y*, Jiang M, Yao Y, Zhang L, Lin J, 2015. Automatic detection of individual trees in UAV oblique images of residential environments. Urban Forestry and Urban Greening, 14(2), 404-412.

[29] Lin Y*, West G, Belton D, Helmholz P, 2015. MLS-assisted validation of VHR WorldView panchromatic imagery for estimating Pinus sylvestris crown height. Remote Sensing Letters, 6(2), 125-134.

[30] Lin Y*, Holopainen M, Kankare V, Hyyppä J, 2014. Validation of mobile laser scanning for understory tree mapping in urban forest. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 7(7), 167-3173.

[31] Lin Y*, Hyyppä J, 2014. Geometrically modeling of 2D scattered points: A review potential for methodically improving mobile laser scanning in data processing. International Journal of Digital Earth, 7(6), 432-449.

[32] Yao Y, Liang S, Cheng J, Lin Y, Jia K, Liu M, 2014. Impacts of deforestation and climate variability on terrestrial evapotranspiration in subarctic China. Forests, 5(10), 2542-2560.

[33] Lin Y*, Puttonen E, Hyyppä J, 2013. Investigation of tree spectral reflectance characteristics using mobile terrestrial line spectrometer and laser scanner. Sensors – Special Issue: Sensor-based Technologies and Processes in Agriculture and Forestry, 13(7), 9305-9320.

[34] Lin Y*, Hyyppä J, Rosnell T, Jaakkola A, Honkavaara E, 2013. Development of a UAV-MMS-collaborative aerial-to-ground remote sensing system – A preparatory field validation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(4), 1893-1898.

[35] Holopainen M, Kankare V, Vastaranta M, Liang X, Lin Y, Vaaja M, Yu X, Hyyppä J, Hyyppä H, Kaartinen H, Kukko A, Tanhuanpää T, Alho P, 2013. Tree mapping using airborne, terrestrial and mobile laser scanning – A case study in a heterogeneous urban forest. Urban Forest and Urban Greening, 12(4), 546-553.

[36] Lin Y*, Hyyppä J, Kukko A, 2013. Stop-and-go mode: Sensor manipulation as essential as sensor development in terrestrial laser scanning. Sensors, 13(7), 8140-8154.

[37] Lin Y*, Hyyppä J, Kaartinen H, Kukko A, 2013. Performance analysis of mobile laser scanning systems in target representation. Remote Sensing – Special Issue: Advances in Mobile Laser Scanning and Mobile Mapping, 5(7), 3140-3155.

[38] Jiang M, Lin Y*, 2013. Individual deciduous tree recognition in leaf-off aerial ultra high spatial resolution remotely sensed imagery. IEEE Geoscience and Remote Sensing Letters, 10(1), 38-42.

[39] Lin Y*, Hyyppä J, 2012. Multiecho-recording mobile laser scanning for enhancing individual tree crown reconstruction. IEEE Transactions on Geoscience and Remote Sensing, 50(11), 4323-4332.

[40] Lin Y*, Hyyppä J, Antero K, Anttoni J, Kaartinen H, 2012. Tree-level height growth investigation by integrating airborne, static terrestrial, and mobile LiDAR techniques. Sensors – Special Issue: Laser sensing and Imaging, 12(9), 12798-12813.

[41] Lin Y*, Hyyppä J, Jaakkola A, Yu X, 2012. Three-level frame and RD-schematic algorithm for automatic recognition of individual trees from MLS point clouds. International Journal of Remote Sensing, 33(6), 1701-1716.

[42] Lin Y*, Hyyppä J, Jaakkola A, Holopainen M, 2012. Characterization of mobile LiDAR data collected with multiple echoes per pulse from crowns during foliation. Scandinavian Journal of Forest Research, 8(3), 298-311.

[43] Lin Y*, Hyyppä J, 2012. Automatic extraction of parallel edges based on eigenvalue analysis and collateral expansion. International Journal of Remote Sensing, 33(2), 382-395.

[44] Lin Y*, Hyyppä J, Jaakkola A, 2011. Mini-UAV-borne Lidar for fine-scale mapping. IEEE Geoscience and Remote Sensing Letters, 8(3), 426-430.

[45] Lin Y*, Hyyppä J, Jaakkola A, 2011. Combining mobile and static terrestrial laser scanners for investigation of individual crown attributes during foliation. Canadian Journal of Remote Sensing, 37(4), 359-375.

[46] Lin Y*, Hyyppä J, 2011. k-segments-based geometric modeling of VLS scan lines. IEEE Geoscience and Remote Sensing Letters, 8(1), 93-97.

[47] Lin Y*, 2010. Hausdorff-based RC and IESIL combined positioning algorithm for underwater geomagnetic navigation. EURASIP Journal on Advances in Signal Processing, Article Number: 593238.

[48] Jaakkola A, Hyyppä J, Kukko A, Yu X, Kaartinen H, Lehtomäki M, Lin Y, 2010. A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements. ISPRS Journal of Photogrammetry and Remote Sensing, 65(6), 514-522.

[49] Lin Y*, Hyyppä J, 2010. Geometry and intensity based culvert detection in mobile laser scanning point clouds. Journal of Applied Remote Sensing, 4, Article No. 043553.

[50] Lin Y*, Jaakkola A, Hyyppä J, and Kaartinen H, 2010. From TLS to VLS: Biomass estimation at individual tree level. Remote Sensing, 2(8), 1864-1879.

2017 How did temperature extremes chase each other around the circumpolar Arctic during 1900-2013? DBAR2017

2017 偏振激光雷達對地觀測遙感，偏振遙感新方法應用探索高端論壇

2016 太平洋海溫異常對中高緯歐亞大陸高溫氣候因子的影響，高校GIS論壇

2016 高光譜激光雷達：三維生物物理化學生态測量學，測繪地理信息青年學者論壇

2016 LiDAR-based investigation of boreal island ecosystems，Digital Earth Summit 2016

2015 激光雷達遙感：從技術基礎的角度助推對森林生态的認知, 激光雷達森林生态應用培訓班

2015 森林生态：激光雷達與無人機的遙感切入, 無人機遙感遙測學術研讨會

[1] 2017 航海學會科學技術獎一等獎

[2] 2016 高校GIS創新人物獎

[3] 2015 科技部國家遙感中心遙感創新青年科技人才計劃

[4] 2014 德國DAAD Research Scholarship

[5] 2014 澳大利亞Endeavour Research Fellowship

[6] 2013 北京市科學技術獎三等獎

2017- 至今 北京市空間信息集成重點實驗室, 副主任

2016- 至今 中-芬北極遙感聯合研究中心，中方Coordinator

2015- 至今 桂林航天工業學院, 客座教授