个人简介：

李爱农（1974-），男，汉族，安徽庐江人，中共党员，理学博士，研究员（二级），博士生导师。

招生专业：

自然地理学（山地遥感方向）（博士）、地图学与地理信息系统（硕士）

学习与工作经历：

学习经历：

1993.9-1997.7  西南交通大学（学士）；

2001.9-2003.12  中国科学院大学（硕士）；

2004.9-2007.7  中国科学院大学（博士）；

2008.2-2010.5  美国马里兰大学（博士后）。

工作经历：

1997.7-2006.12 中国科学院水利部成都山地灾害与环境研究所，研究实习员、助理研究员；

2005.2-2005.8  美国马里兰大学地理系，访问学者；

2007.1-2010.7  中国科学院水利部成都山地灾害与环境研究所，副研究员；

2008.2-2010.5  美国马里兰大学地理系，访问研究员；

2010.7-至今  中国科学院水利部成都山地灾害与环境研究所，研究员。

研究方向及科研工作：

山地定量遥感理论、方法及其综合应用研究。

在研主持项目：

国家重点研发计划项目“山地生态系统全球变化关键参数立体观测与高分辨率产品研制”（2021-2025）；

国家重大研发计划项目课题“典型山地生态系统全球变化关键参数星-空-地立体观测与时空尺度扩展”（2021-2025）；

国家自然科学基金重大项目“陆表智慧化定量遥感的理论与方法研究”专题“重难点地表覆盖制图”（2021-2025）；

中国科学院任务/战略性先导科技专项（A类）子课题“一带一路重要经济廊道生态环境遥感监测与综合评估”（2018-2022）；

中央级科学事业单位改善科研条件专项资金科研装备项目“山地地表过程和生物多样性天空地一体化监测平台”（2022-2023）；

国家自然科学基金重点项目“山地典型生态参量遥感反演建模及其时空表征能力研究”（2017-2021）。

社会任职、荣誉称号：

四川省学术和技术带头人（2021）、获中国科学院优秀导师奖（2021）、国家高层次人才计划入选者（2018）、科技部中青年科技创新领军人才（2016）、四川省引进海外高层次人才（2012年）、中科院人才计划（A类）入选者（2010年）；《遥感学报》副主编、国际数字地球学会(CNISDE)数字山地专业委员会主任；获爱思唯尔国际“擎天神”奖、国际环境信息协会“最佳论文”奖、全国青年地理科技奖、中国自然资源学会青年科技奖、中国测绘地理信息学会科学技术奖、四川省青年科技奖等奖项。

代表性论文论著：

[1]  李爱农, 边金虎, 靳华安, 等. 山地遥感[M]. 北京: 科学出版社, 2016.

[2] 李爱农, 雷光斌, 边金虎, 等.山地土地利用/覆被遥感监测[M]. 北京:科学出版社, 2021.

[3]  Li Ainong, Deng Wei, Zhao Wei. Land Cover Change and Its Eco-Environmental Response in Nepal[M]. Singapore, Springer-Nature, 2017.

[4] 邓伟, 李爱农(副主编), 南希, 陈昱, 廖克. 中国数字山地图[M]. 北京: 中国地图出版社, 2015.

[5] 邓伟, 李爱农(副主编). 南亚地理—资源与环境[M].成都:四川科技出版社,2017.

[6] 李爱农^*, 边金虎, 张正健, 等. 山地遥感主要研究进展、发展机遇与挑战[J]. 遥感学报, 2016, 20(5): 1199-1215.

[7] 李爱农^*, 边金虎, 张正健, 等. 若尔盖高原区域碳收支参量多尺度遥感综合观测试验：科学目标与试验设计[J]. 遥感技术与应用, 2016, 31(3): 405-416.

[8] 李爱农^*, 尹高飞, 靳华安, 等. 山地地表生态参量遥感反演的理论、方法与问题[J]. 遥感技术与应用, 2016, 31(1): 1-11.

[9] 李爱农^*, 边金虎, 尹高飞, 等. 山地典型生态参量遥感反演建模及其时空表征能力研究[J]. 地球科学进展, 2018, 33(2): 141-151.

[10] 李爱农^*,尹高飞,张正健,等. 基于站点的生物多样性星空地一体化遥感监测[J]. 生物多样性, 2018,26(08): 819-827.

[11] 李爱农^*, 张正健, 雷光斌, 等. 四川芦山“4·20”强烈地震核心区灾损遥感快速调查与评估[J]. 自然灾害学报, 2013, 22(6): 8-18.

[12] 李爱农^*, 南希, 张正健, 等. 茂县“6.24”特大高位远程崩滑灾害遥感回溯与应急调查[J]. 自然灾害学报, 2018, 27(2):1-9.

[13] 李爱农^*, 南希, 张正健,等. 特大山地灾害遥感应急响应调查方法与案例[J]. 中国减灾, 2018,(19): 42-45.

[14] Hu, G. and Li, A.^*. SGOT: A Simplified Geometric-Optical Model for Crown Scene Components Modeling over Rugged Terrain [J]. Remote Sensing , 2022, 14(8): 1821.

[15] Naboureh, A., Li, A.^*, H. Ebrahimy, et al. Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine [J]. International Journal of Applied Earth Observation and Geoinformation, 2021, 105: 102607.

[16] Jin, Y., Li, A.^*, J. Bian, et al. Spatiotemporal analysis of ecological vulnerability along Bangladesh-China-India-Myanmar economic corridor through a grid level prototype model [J]. Ecological Indicators, 2021, 120: 106933.

[17] Xie, X. and Li, A.^*. An Adjusted Two-Leaf Light Use Efficiency Model for Improving GPP Simulations Over Mountainous Areas [J]. Journal of Geophysical Research: Atmospheres, 2021, 125(13): e2019JD031702.

[18] Xie, X. and Li, A.^*. Development of a topographic-corrected temperature and greenness model (TG) for improving GPP estimation over mountainous areas [J]. Agricultural and Forest Meteorology, 2020, 295: 108193.

[19]  Bian, J., Li, A.^*, G. Lei, et al. Global high-resolution mountain green cover index mapping based on Landsat images and Google Earth Engine [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 162: 63-76.

[20] Lei, G., Li, A.^*, J. Bian, et al. OIC-MCE: A Practical Land Cover Mapping Approach for Limited Samples Based on Multiple Classifier Ensemble and Iterative Classification [J]. Remote Sensing, 2020, 12(6): 987.

[21] Jin, H., Li, A.^*, W. Xu, et al. Evaluation of topographic effects on multiscale leaf area index estimation using remotely sensed observations from multiple sensors [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 154: 176-188.

[22] Jin, H., Li, A.^*, G. Yin, et al. A Multiscale Assimilation Approach to Improve Fine-Resolution Leaf Area Index Dynamics [J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(10): 8153-8168.

[23] Tan, J.,  Li, A.^*, Lei, G., et al. A novel and direct ecological risk assessment index for environmental degradation based on response curve approach and remotely sensed data [J]. Ecological Indicators, 2019, 98:783-793.

[24] Tan, J.,  Li, A.^*, Lei, G., et al. A SD-MaxEnt-CA model for simulating the landscape dynamic of natural ecosystem by considering socio-economic and natural impacts [J]. Ecological Modelling, 2019, 410: 108783.

[25] Li, A.^*, W. Deng, W. Zhao, et al. A geo-spatial database about the eco-environment and its key issues in South Asia [J]. Big Earth Data, 2018, 2(3): 298-319.

[26] Xie, X., Li, A.^*, Yin, G., et al. Derivation of temporally continuous leaf maximum carboxylation rate (Vcmax) from the sunlit leaf gross photosynthesis productivity through combining BEPS model with light response curve at tower flux sites [J]. Agricultural and Forest Meteorology, 2018, 259:82-94,

[27] Bian, J., Li, A.^*, C. Huang, et al. A self-adaptive approach for producing clear-sky composites from VIIRS surface reflectance datasets [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2018, 144: 189-201.

[28] Zhao, W., N. Sánchez, H. Lu and Li, A.^*. A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression [J]. Journal of Hydrology, 2018, 563: 1009-1024.

[29] Yin, G., LI, A.^*, Wu, S., et al. PLC: A simple and semi-physical topographic correction method for vegetation canopies based on path length correction [J]. Remote Sensing of Environment, 2018, 215:184-198.

[30] Bian, J., Li, A.^*, Zhang, Z., et al. Monitoring fractional green vegetation cover dynamics over a seasonally inundated alpine wetland using dense time series HJ-1 A/B constellation images and an adaptive endmember selection LSMM model [J]. Remote Sensing of Environment, 2017, 197: 98-114.

[31] Yin, G., LI, A.^*, Zhao, W., et al. Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction [J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(8): 4597 - 4609.

[32] Yin, G., Li, A.^*, Jin, H., et al. Derivation of temporally continuous LAI reference maps through combining the LAINet observation system with CACAO [J]. Agricultural and Forest Meteorology, 2017, 233(2017): 209-221.

[33] Zhao, W., Li, A.^*, Zhao, T. Potential of Estimating Surface Soil Moisture With the Triangle-Based Empirical Relationship Model [J]. IEEE Transactions on Geoscience & Remote Sensing, 2017, 55(11): 6494-6504.

[34] Zhao, W., Li, A.^*, Jin, H., et al. Performance Evaluation of the Triangle-Based Empirical Soil Moisture Relationship Models Based on Landsat-5 TM Data and In Situ Measurements [J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(5): 2632-2645.

[35] Tan, J., Li, A.^*, Lei, G., et al. Preliminary assessment of ecosystem risk based on IUCN criteria in a hierarchy of spatial domains: A case study in Southwestern China [J]. Biological Conservation, 2017, 215(2017): 152-161.

[36] Lei, G., Li, A.^*, Bian, J., et al. Land Cover Mapping in Southwestern China Using the HC-MMK Approach [J]. Remote Sensing, 2016, 8(4): 305.

[37] Wang, J., Li, A.^*, Bian, J. Simulation of the Grazing Effects on Grassland Aboveground Net Primary Production Using DNDC Model Combined with Time-Series Remote Sensing Data—A Case Study in Zoige Plateau, China [J]. Remote Sensing, 2016, 8(3): 168.

[38] Bian, J., Li, A.^*, Wang, Q., et al. Development of Dense Time Series 30-m Image Products from the Chinese HJ-1A/B Constellation: A Case Study in Zoige Plateau, China [J]. Remote Sensing, 2016, 7(12): 16647-16671.

[39] Jin, H., Li, A.^*, Wang, J., et al. Improvement of spatially and temporally continuous crop leaf area index by integration of CERES-Maize model and MODIS data [J]. European Journal of Agronomy, 2016, 78(2016): 1-12.

[40] Yin, G., Li, A.^*, Zeng, Y., et al. A cost-constrained sampling strategy in support of lai product validation in mountainous areas [J]. Remote Sensing, 2016, 8, 704.

[41] Li, A.^*, Wang, Q., Bian, J., et al. An Improved Physics-Based Model for Topographic Correction of Landsat TM Images [J]. Remote Sensing, 2015, 7(5): 6296-6319.

[42] Li, A.^*, Zhao, W., Deng, W. A Quantitative Inspection on Spatio-Temporal Variation of Remote Sensing-Based Estimates of Land Surface Evapotranspiration in South Asia [J]. Remote Sensing, 2015, 7(4): 4726-4752.

[43] Li, A.^*, Zhang, W., Lei, G., et al. Comparative Analysis on Two Schemes for Synthesizing the High Temporal Landsat-like NDVI Dataset Based on the STARFM Algorithm [J]. ISPRS International Journal of Geo-Information, 2015, 4(3): 1423-1441.

[44] Li, A.^*, Deng, W., Kong, B., et al. A study on wetland landscape pattern and its change process in Huang-Huai-Hai (3H) area, China [J]. Journal of Environmental Informatics, 2013, 21(1): 23-34.

[45] Li, A.^*, Liang, S., Wang, A., et al. Investgating the impacts of the North Atlantic Oscillation on global vegetation changes by a remotely sensed vegetation index. International Journal of Remote Sensing [J], 2012, 33(22): 7222-7239.

[46] Li, A.^*, Jiang, J., Bian, J., et al. Combining the matter element model with the associated function of probability transformation for multi-source remote sensing data classification in mountainous regions [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 67(1): 80-92.

[47] Li, A.^*, Bian, J., Lei, G., et al. Estimating the maximal light use efficiency for different vegetation through the CASA model combined with time-series remote sensing data and ground measurements [J]. Remote Sensing, 2012, 4(12): 3857-3876.

[48] Li, A., Huang, C., Sun, G., et al. Modeling the height of young forests regenerating from recent disturbances in Mississippi using Landsat and ICESat data [J]. Remote sensing of Environment, 2011, 115(8): 1837-1849.

[49] Li, A.^*, Deng, W., Liang, S., et al. Investigation on the patterns of global vegetation change using a satellite-sensed vegetation index [J]. Remote Sensing, 2010, 2(6): 1530-1548.

[50] Li, A.^*, Liang, S., Wang, A., et al. Estimating crop yield from multi-temporal satellite data using multivariate regression and neural network techniques [J]. Photogrammetric Engineering and Remote Sensing, 2007, 73(10): 1149-1157.

[51] Li, A.^*, Wang, A., Liang, S., et al. Eco-environmental vulnerability evaluation in mountainous region using remote sensing and GIS - A case study in the upper reaches of Minjiang River, China [J]. Ecological Modelling, 2006, 192(1-2): 175-187.

　　通讯方式：610041，成都市人民南路四段9号，中国科学院水利部成都山地灾害与环境研究所 

　　电话：028-85224131 

　　传真：028-85222258 

　　Email：ainongli@imde.ac.cn