论文：
[1] Xin Tian*, Zengyuan Li, Christiaan van der Tol, Zhongbo Su, Xin Li, Qisheng He, Yingfei Bao, Erxue Chen. Estimating Zero-Plane Displacement Height and Aerodynamic Roughness Length using Synthesis of LiDAR and SPOT-5 data. Remote Sensing of Environment. 2011, 115(9):2330-2341.
[2] Xin Tian, Zhongbo Su, Erxue Chen, Zengyuan Li*, Christiaan van der Tol, Jianping Guo, Qisheng He. Estimation of forest above-ground biomass using multi-parameter remote sensing data over a cold and arid area. International Journal of Applied Earth Observation and Geoinformation, 2012, 14(1):160-168.
[3] Xin Tian, Zengyuan Li*, Zhongbo Su, Erxue Chen, Christiaan van der Tol, Xin Li, Yun Guo, Longhui Li, Feilong Ling. Estimating montane forest above-ground biomass in the upper reaches of the Heihe River Basin using Landsat-TM data. International Journal of Remote Sensing. 2014, 35(21):7339-7362. DOI: 10.1080/01431161.2014.967888.
[4] Xin Tian, Christiaan van der Tol, Zhongbo Su, Zengyuan Li *, Erxue Chen *, Xin Li , Min Yan, Xuelong Chen, Xufeng Wang, Xiaoduo Pan, Feilong Ling, Chunmei Li, Wenwu Fan, Longhui Li. Simulation of Forest Evapotranspiration Using Time-Series Parameterization of the Surface Energy Balance System (SEBS) over the Qilian Mountains. Remote Sensing. 2015, 7(12):15822–15843. DOI:10.3390/rs71215806.
[5] Xin Tian, Zengyuan Li*, Erxue Chen*, et al. The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE). PLoS ONE. 2015, 10(9):e0137545. DOI:10.1371/journal.
[6] Xin Tian, Min Yan, Christiaan van der Tol, et al. Modeling forest above-ground biomass dynamics using multi-source data and incorporated models: A case study over the qilian mountains. Agricultural and Forest Meteorology, 2017, 246, 1-14.
[7] Min Yan, Xin Tian*, Zengyuan Li, et al. A long-term simulation of forest carbon fluxes over the Qilian Mountains. International Journal of Applied Earth Observation and Geoinformation. 2016, 52: 515-526.
[8] Min Yan, Xin Tian*, Zengyuan Li, et al. Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation. Remote Sensing. 2016, 8(7), 567. DOI: 10.3390/rs8070567.
[9] Min Yan, Mei Xue, Li Zhang 1 , Xin Tian*, et al. A decade’s change in vegetation productivity and its response to climate change over Northeast China. 2021, Plants, 10, 821.
[10] Yong Su, Wangfei Zhang, Bingjie Liu, Xin Tian*, Shuxin Chen, Haiyi Wang and Yingwu Mao. Forest Carbon Flux Simulation Using Multi-Source Data and Incorporation of Remotely Sensed Model with Process-Based Model. Remote Sensing. 2022. 14 (19): 4766. DOI:10.3390/rs14194766.
[11]Bingjie Liu, Shuxin Chen, Huaguo Huan and Xin Tian*. Tree Species Classification of Backpack Laser Scanning Data Using the PointNet++ Point Cloud Deep Learning Method. Remote Sensing. 2022. 14 (15): 3809. DOI:10.3390/rs14153809.
[12] Bingjie Liu, Huaguo Huang, Yong Su, Shuxin Chen, Zengyuan Li, Erxue Chen and Xin Tian*. Tree Species Classification Using Ground-Based LiDAR Data by Various Point Cloud Deep Learning Methods. Remote Sensing . 2022. 14 (22): 5733. DOI:10.3390/rs14225733.
[13] Bingjie Liu, Yuanshuo Hao, Huaguo Huang, Shuxin Chen, Zengyuan Li, Erxue Chen, Xin Tian* and Min Ren. TSCMDL: Multimodal Deep Learning Framework for Classifying Tree Species Using Fusion of 2-D and 3-D Features . IEEE Transactions on Geoscience and Remote Sensing. 2023. 61: 1–11. DOI:10.1109/TGRS.2023.3266057.
[14] Xin Luo, Lili Jin, Xin Tian*, et al. A High Spatiotemporal Enhancement Method of Forest Vegetation Leaf Area Index Based on Landsat8 OLI and GF-1 WFV Data. Remote Sensing .2023.15 (11): 2812. DOI:10.3390/rs15112812.
[15]韩宗涛, 江洪, 王威, 李增元, 陈尔学, 闫敏, 田昕*. 基于多源遥感的森林地上生物量KNN-FIFS估测,林业科学, 2018, 54(9): 70-79, EI, 通讯作者.
专著：
复杂地表定量遥感模型与反演，合著，2019，科学出版社。
合成孔径雷达森林参数反演技术与方法，合著，2019，科学出版社。
林业定量遥感：框架、模型与应用，合著，2020，科学出版社。
中国科技之路-林草卷，合著，2021，中国林业出版社。
专利：
田昕，韩宗涛，李增元，陈尔学。一种特征选择的森林参数遥感估测方法，ZL201710190338.1
