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研究队伍
姓   名
李爱农
性   别
职   务
数字山地与遥感应用中心主任
职   称
研究员
通讯地址
成都市人民南路四段九号,中国科学院成都山地灾害与环境研究所
邮政编码
610041
电子邮件
ainongli@imde.ac.cn

 简历:
 

 

李爱农,男(1974-),汉族,中共党员,理学博士,研究员(二级),博士生导师,国家重点研发计划项目首席科学家。数字山地与遥感应用中心主任、数字山地党支部书记、王朗山地遥感四川省野外观测研究站站长;兼任中国科学院无人机应用与管控研究中心副主任、《遥感学报》副主编、国际数字地球学会中国国家委员会(CNISDE)数字山地专业委员会主任、全国科技创新领军人才联盟理事等。曾任所团委书记(2007-2010)、山区发展与数字山地党支部书记(2015-2017)。

1997年毕业于西南交通大学摄影测量与遥感专业;2003年、2007年在中国科学院大学获得硕士和博士学位;2005年、2008-2010年先后赴美国马里兰大学地理系从事访问学习与博士后研究。先后承担国家重点研发计划项目、国家自然科学基金重点项目、中科院战略性先导科技专项、国际合作重点项目、环保部“生态十年”专项等科研任务20余项。在国内外主流学术期刊上发表论文238篇,其中SCI/TOP论文101/52篇,出版《山地遥感》、《山地土地利用/覆被遥感监测》、《Land cover change and its eco-environmental responses in Nepal》等专著5部、《中国数字山地图》等地图作品2套;获授权国家发明专利、软件著作权15项。

 

 研究领域:
 

  山地定量遥感理论、方法及其综合应用研究。

 社会任职:
 

 获奖及荣誉:
 

 

四川省学术和技术带头人(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)、中科院人才计划(A类)入选者(2010);获中国科学院优秀导师奖、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。

 

 代表论著:
 

 

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

[2] 李爱农, 雷光斌, 边金虎, .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, . 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, . 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, . 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, . 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, . 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, . 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, . 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, . 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.*, Ebrahimy, H., 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.*, Bian, J., 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.*, Lei, G., 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.*, Bian, J., 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.*, Xu, W., 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.*, Yin, G., 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.*, Deng, W., Zhao, W., 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.*, Huang, C., 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., Sánchez, N., Lu H. 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.

 

 承担科研项目情况:
 

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--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);

国家重点研发计划项目专题山地关键气候变量天--地一体化协同观测与应用示范2016-2021);

中国科学院成都山地所“一三五”重点培育方向项目“南亚地缘合作关键资源环境变化过程与空间信息服务”(2017-2020);

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