1. 1.    基本信息

1. 2.    个人简介

车涛，博士，中国科学院西北生态环境资源研究院研究员，博导，杰青，遥感与地理信息科学研究室主任，中国科学院黑河遥感试验研究站站长。已主持完成国家自然科学基金面上项目3项，目前正在主持中国科学院A类先导专项和国家科技部基础调查专项两个国家级研究课题。长期从事积雪遥感研究，主要学术成果包括：（1）在我国青藏高原、西北和东北三大积雪区开展长期积雪野外观测，在祁连山建立了我国第一个综合积雪观测站，带领积雪团队开展积雪地面调查，获取了我国的积雪特性及分布；（2）发展了适合于我国积雪特性的微波遥感算法，率先提出了以积雪特性作为先验信息的动态遥感算法，并针对山区和林区等复杂环境下积雪遥感精度低的问题开展了创新性研究；（3）研发了我国长时间序列的雪深遥感产品，被国内外学者下载超过1300余次，并广泛应用在气候变化、水文水资源和灾害等研究领域。发表学术论文100余篇，参编专著10部，制定国家标准（草案）2项，国家发明专利4项，并分别获得2016年甘肃省自然科学一等奖和2018年测绘科技进步一等奖。

1. 3.    研究方向

冰冻圈遥感；积雪参数遥感反演；积雪观测试验；积雪数据同化

1. 4.    工作履历

2016-07~现在, 中国科学院西北生态环境资源研究院, 研究员

2014-01~2016-06, 中国科学院寒区旱区环境与工程研究所, 研究员

2009-01~2013-12, 中国科学院寒区旱区环境与工程研究所, 副研究员

2004-05~2008-12,寒区旱区环境与工程研究所, 助理研究员

1. 5.    教育经历

2000-09--2006-07 中国科学院寒区旱区环境与工程研究所 研究生/博士

1996-09--2000-07 西北大学 学士

1. 6.    科研项目

（1）国家自然科学基金杰出青年项目（42125604）：积雪遥感

（2）中国科学院A类先导专项课题（XDA19070100）：三极大数据共享与集成

（3）国家科技部基础调查专项课题（2017FY100501）：中国典型积雪区积雪特性地面调查

（4）国家自然科学基金面上项目（41271356）：积雪面积与雪水当量时空关系及其在寒区水文中的同化应用

（5）国家自然科学基金面上项目（40971188）：非均匀条件下积雪微波辐射特性观测、理解与模拟

（6）国家自然科学基金青年科学基金（40601065）：被动微波遥感反演雪水当量的数据同化方法研究

1. 7.    学术兼职

冰冻圈科学学会积雪专业委员会主任

国际数字地球学会中国国家委员会微波遥感专业委员会副主任

青藏高原研究会理事

全国遥感技术标准化技术委员会委员

国家遥感应用协会理事

甘肃省遥感学会秘书长

《地理科学》编委

《遥感学报》编委

《冰川冻土》编委

《遥感技术与应用》编委

1. 8.    奖励荣誉

2018年测绘科技进步一等奖

2016年甘肃省自然科学一等奖

1. 9.    学术成果（论文、专著、专利等）

[1] 车涛，李新，李新武，等. 冰冻圈遥感：助力“三极”大科学计划[J]. 中国科学院院刊. 2020, 35(04): 484-493.

[2] 车涛，李弘毅，晋锐，等. 遥感综合观测与模型集成研究为黑河流域生态环境保护与可持续发展提供科技支撑[J]. 中国科学院院刊. 2020, 35(11): 1417-1423.

[3] 车涛，郝晓华，戴礼云，等. 青藏高原积雪变化及其影响[J]. 中国科学院院刊. 2019, 34(11): 1247-1253.

 [4] Sun S, Che T, Gentine P, et al. Shallow groundwater inhibits soil respiration and favors carbon uptake in a wet alpine meadow ecosystem[J]. AGRICULTURAL AND FOREST METEOROLOGY. 2021, 297(108254).

 [5] Hu Y, Che T, Dai L, et al. Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere[J]. Remote Sensing. 2021, 13.

 [6] Su L, Che T, Dai L. Variation in Ice Phenology of Large Lakes over the Northern Hemisphere Based on Passive Microwave Remote Sensing Data[J]. Remote Sensing. 2021, 13.

 [7] Deng J, Che T, Jiang T, et al. Suitability projection for Chinese ski areas under future natural and socioeconomic scenarios[J]. Advances in Climate Change Research. 2021.

 [8] Dai L, Che T, Xiao L, et al. Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations[J]. IEEE Transactions on Geoscience and Remote Sensing. 2021, PP(99): 1-17.

 [9] Tan J, Che T, Wang J. Reconstruction of the Daily MODIS Land Surface Temperature Product Using the Two-Step Improved Similar Pixels Method[J]. Remote Sensing. 2021.

[10] Zhang J, Liu L, Su L, et al. Three in one: GPS-IR measurements of ground surface elevation changes, soil moisture, and snow depth at a permafrost site in the northeastern Qinghai--Tibet Plateau[J]. The Cryosphere. 2021, 15(6): 3021-3033.

[11] Xiao X, Zhang F, Li X, et al. Using stable isotopes to identify major flow pathways in a permafrost influenced alpine meadow hillslope during summer rainfall period[J]. Hydrological Processes. 2020, 34(5): 1104-1116.

[12] Chen T, Pan J, Chang S, et al. Validation of the SNTHERM Model Applied for Snow Depth, Grain Size, and Brightness Temperature Simulation at Meteorological Stations in China[J]. Remote Sensing. 2020, 12.

[13] Zhang H, Zhang F, Che T, et al. Comparative evaluation of VIIRS daily snow cover product with MODIS for snow detection in China based on ground observations[J]. Science of The Total Environment. 2020: 138156.

[14] Xiao X, Zhang F, Che T, et al. Changes in plot-scale runoff generation processes from the spring–summer transition period to the summer months in a permafrost-dominated catchment[J]. Journal of Hydrology. 2020, 587: 124966.

[15] Xiao L, Che T, Dai L. Evaluation of Remote Sensing and Reanalysis Snow Depth Datasets over the Northern Hemisphere during 1980-2016[J]. REMOTE SENSING. 2020, 12(325319).

[16] Wang W, Yang K, Zhao L, et al. Characterizing Surface Albedo of Shallow Fresh Snow and Its Importance for Snow Ablation on the Interior of the Tibetan Plateau[J]. JOURNAL OF HYDROMETEOROLOGY. 2020, 21(4): 815-827.

[17] Li X, Che T, Li X, et al. CASEarth Poles Big Data for the Three Poles[J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY. 2020, 101(9): E1475-E1491.

[18] Yu L, Shang J, Cheng Z, et al. Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network[J]. REMOTE SENSING. 2020, 12(330420).

[19] Geng L Y, Che T, Wang X F, et al. Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000-2017[J]. REMOTE SENSING. 2019, 11(2).

[20] Hao X, Luo S, Che T, et al. Accuracy assessment of four cloud-free snow cover products over the Qinghai-Tibetan Plateau[J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH. 2019, 12(4): 375-393.

[21] Sun S, Che T, Li H, et al. 9Water and carbon dioxide exchange of an alpine meadow ecosystem in the northeastern Tibetan Plateau is energy-limited[J]. AGRICULTURAL AND FOREST METEOROLOGY. 2019, 275: 283-295.

[22] Deng J, Che T, Xiao C, et al. Suitability analysis of ski areas in China: an integrated study based on natural and socioeconomic conditions[J]. CRYOSPHERE. 2019, 13(8): 2149-2167.

[23] Li G, Li X, Yao T, et al. Heterogeneous sea-level rises along coastal zones and small islands[J]. SCIENCE BULLETIN. 2019, 64(11): 748-755.

[24] Zhang H, Zhang F, Zhang G, et al. Ground-based evaluation of MODIS snow cover product V6 across China: Implications for the selection of NDSI threshold[J]. Science of The Total Environment. 2019, 651(2): 2712-2726.

[25] Che T, Li X, Liu S, et al. Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China[J]. Earth System Science Data. 2019, 11(3): 1483-1499.

[26] Wang X, Wang J, Che T, et al. Snow Cover Mapping for Complex Mountainous Forested Environments Based on a Multi-Index Technique[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2018, 11(5): 1433-1441.

[27] Zhang H, Zhang F, Zhang G, et al. How Accurately Can the Air Temperature Lapse Rate Over the Tibetan Plateau Be Estimated From MODIS LSTs?[J]. Journal of Geophysical Research: Atmospheres. 2018, 0(0).

[28] Wu X, Che T, Li X, et al. Slower Snowmelt in Spring Along With Climate Warming Across the Northern Hemisphere[J]. Geophysical Research Letters. 2018, 45(22): 12, 312-331, 339.

[29] Dai L, Che T, Xie H, et al. Estimation of Snow Depth over the Qinghai-Tibetan Plateau Based on AMSR-E and MODIS Data[J]. Remote Sensing. 2018, 10(12},

ARTICLE-NUMBER = {1989).

[30] Liu S, Li X, Xu Z, et al. The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China[J]. Vadose Zone Journal. 2018, 17(1800721).

[31] Sun S, Song Z, Wu X, et al. Spatio-temporal variations in water use efficiency and its drivers in China over the last three decades[J]. ECOLOGICAL INDICATORS. 2018, 94(1): 292-304.

[32] Shi Y, Niu F, Yang C, et al. Permafrost Presence/Absence Mapping of the Qinghai-Tibet Plateau Based on Multi-Source Remote Sensing Data[J]. REMOTE SENSING. 2018, 10(3092).

[33] Dai L, Che T, Ding Y, et al. Evaluation of snow cover and snow depth on the Qinghai--Tibetan Plateau derived from passive microwave remote sensing[J]. The Cryosphere. 2017, 11(4): 1933-1948.

[34] Xiao L, Che T, Chen L, et al. Quantifying Snow Albedo Radiative Forcing and Its Feedback during 2003-2016[J]. REMOTE SENSING. 2017, 9(8839): 1-10.

[35] Gou P, Ye Q, Che T, et al. Lake ice phenology of Nam Co, Central Tibetan Plateau, China, derived from multiple MODIS data products[J]. Journal of Great Lakes Research. 2017, 43(6): 989-998.

[36] Wang X, Xiao J, Li X, et al. No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau[J]. Journal of Geophysical Research-Biogeosciences. 2017, 122(12): 3288-3305.

[37] Li X, Liu S, Xiao Q, et al. A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system[J]. SCIENTIFIC DATA. 2017, 4(UNSP 170083).

[38] Che T, Dai L Y, Zheng X M, et al. Estimation of snow depth from passive microwave brightness temperature data in forest regions of northeast China[J]. Remote Sensing of Environment. 2016, 183: 334-349.

[39] Wang Z, Che T, Liou Y A. Global Sensitivity Analysis of the L-MEB Model for Retrieving Soil Moisture[J]. Geoscience and Remote Sensing, IEEE Transactions on. 2016, 54(5): 2949-2962.

[40] Sun S, Chen B, Ge M, et al. Improving soil organic carbon parameterization of land surface model for cold regions in the Northeastern Tibetan Plateau, China[J]. Ecological Modelling. 2016, 330: 1-15.

[41] Mo H M, Dai L Y, Fan F, et al. Extreme snow hazard and ground snow load for China[J]. Natural Hazards. 2016: 1-26.

[42] Zhang H, Zhang F, Ye M, et al. Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data[J]. Journal of Geophysical Research: Atmospheres. 2016, 121(19): 11, 411-425, 441.

[43] Mashtayeva S, Dai L, Che T, et al. Spatial and Temporal Variability of Snow Depth Derived from Passive Microwave Remote Sensing Data in Kazakhstan [J]. Journal of Meteorological Research. 2016, 30(6): 1033-1043.

[44] Sun S B, Che T, Wang J, et al. Estimation and Analysis of Snow Water Equivalents Based on C-band SAR Data and Field Measurements[J]. Arctic, Antarctic, and Alpine Research. 2015, 2(47): 313-326.

[45] Zhao T, Shi J C, Bindlish R, et al. Refinement of SMOS Multiangular Brightness Temperature Toward Soil Moisture Retrieval and Its Analysis Over Reference Targets[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2015, 2(8): 589-603.

[46] Dai L, Che T, Ding Y. Inter-Calibrating SMMR, SSM/I and SSMI/S Data to Improve the Consistency of Snow-Depth Products in China[J]. Remote Sensing. 2015, 7(6): 7212-7230.

[47] Ma M G, Che T, Li X, et al. A Prototype Network for Remote Sensing Validation in China[J]. Remote Sensing. 2015, 7: 5187-5202.

[48] Li H Y, He Y Q, Hao X H, et al. Downscaling Snow Cover Fraction Data in Mountainous Regions Based on Simulated Inhomogeneous Snow Ablation[J]. Remote Sensing. 2015, 7(7): 8995-9019.

[49] Che T, Xiao L, Liou Y. Changes in glaciers and glacial lakes and the identification of dangerous glacial lakes in the Pumqu river basin, Xizang (Tibet)[J]. Advances in Meteorology. 2014, 2014: 8.

[50] Che T, Li X, Jin R, et al. Assimilating passive microwave remote sensing data into a land surface model to improve the estimation of snow depth[J]. Remote Sensing of Environment. 2014, 143: 54-63.

[51] Li H Y, Tang Z G, Wang J, et al. Synthesis method for simulating snow distribution utilizing remotely sensed data for the Tibetan Plateau[J]. Journal of Applied Remote Sensing. 2014, 8: 84696.

[52] Dai L, Che T. Spatiotemporal variability in snow cover from 1987 to 2011 in northern China[J]. Journal of Applied Remote Sensing. 2014, 8(084693).

[53] Wang J, Li H X, Hao X H, et al. Remote sensing for snow hydrology in China: challenges and perspectives[J]. Journal of Applied Remote Sensing. 2014, 8(084687).

[54] Li X, Cheng G D, Liu S M, et al. Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific Objectives and Experimental Design[J]. Bulletin of the American Meteorological Society. 2013, 94(8): 1145-1160.

[55] Che T, Dai L Y, Wang J, et al. Estimation of snow depth and snow water equivalent distribution using airborne microwave radiometry in the Binggou Watershed, the upper reaches of the Heihe River basin[J]. International Journal of Applied Earth Observation and Geoinformation. 2012, 17(SI): 23-32.

[56] Dai L Y, Che T, Wang J, et al. Snow depth and snow water equivalent estimation from AMSR-E data based on a priori snow characteristics in Xinjiang, China[J]. Remote Sensing of Environment. 2012, 127: 14-29.

[57] Che T, Li X, Jin R. Monitoring the frozen duration of Qinghai Lake using satellite passive microwave remote sensing low frequency data[J]. Chinese Science Bulletin. 2009, 54(13): 2294-2299.

[58] Jin R, Li X, Che T. A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature[J]. Remote Sensing of Environment. 2009, 113(12): 2651-2660.

[59] Li X, Li X W, Li Z Y, et al. Watershed Allied Telemetry Experimental Research[J]. Journal of Geophysical Research-Atmospheres. 2009, 114.

[60] Li X, Cheng G D, Jin H J, et al. Cryospheric change in China[J]. Global and Planetary Change. 2008, 62(3-4): 210-218.

[61] Yue Z Y, Cao Z X, Li X, et al. Two-dimensional coupled mathematical modeling of fluvial processes with intense sediment transport and rapid bed evolution[J]. Science in China Series G-Physics Mechanics & Astronomy. 2008, 51(9): 1427-1438.

[62] Che T, Li X, Jin R, et al. Snow depth derived from passive microwave remote-sensing data in China[J]. Annals of Glaciology. 2008, 49: 145-154.

[63] Li X, Huang C L, Che T, et al. Development of a Chinese land data assimilation system: its progress and prospects[J]. Progress in Natural Science. 2007, 17(8): 881-892.

[64] Jin R, Li X, Che T, et al. Glacier area changes in the Pumqu river basin, Tibetan Plateau, between the 1970s and 2001[J]. Journal of Glaciology. 2005, 51(175): 607-610.

[65] Lu L, Li X, Huang C L, et al. Investigating the relationship between ground-measured LAI and vegetation indices in an alpine meadow, north-west China[J]. International Journal of Remote Sensing. 2005, 26(20): 4471-4484.