Ainong LI--INSTITUTE OF MOUNTAIN HAZAPDS AND ENVIRONMENT CHINESE ACADEMY OF SCIENCES

Name	Ainong LI
Professional Title	Professor
Address	No. 9, Block 4, Renminnanlu Road, Chengdu, 610041, People’s Republic of China
E-mail	ainongli@imde.ac.cn
Professional Expertise	MountainQuantitativeRemote Sensing
Education 2017 PH.D. Physical Geography, University of Chinese Academy of Sciences, China 2003 M.S. Cartography and Geographical Information System, University of Chinese Academy of Sciences, China 1997 B.S. Photogrammetry and Remote Sensing, Southwest Jiaotong University, China
Employment Record(including international working experience ) 07/2010 – present, Full Professor, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences 02/2008–04/2010, Visiting research scientist, Department of Geographical Sciences, University of Maryland at College Park, USA 01/2007–06/2010, Assistant Professor, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences 02/2005–08/2005, Visiting research scientist, Department of Geographical Sciences, University of Maryland at College Park, USA 07/1997–12/2006, Assistant Professor, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences
Running Projects [1]Stereoscopic observation and high-resolution product development of key parameters of global change in mountain ecosystems .The National Key Research and Development Program of China. ( No.2020YFA0608700). 2021-2025.PI. [2]Satellite-Aerial-Ground stereo observation and spatio-temporal scale extension for key parameters of global change in typical mountain ecosystems. The National Key Research and Development Program of China. (No.2020YFA0608702). 2021-2025.PI. [3]Land cover mapping over critical and hard-to-identify areas. The Key Project of Natural Science Foundation of China (No. 42090015). 2021-2025. PI. [4]Remote sensing monitoring and integrated assessment of the ecological environment in the economic corridors of the Belt and Road. The Strategic Priority Research Program of CAS (No. XDA19030303). 2018-2022.PI. [5] An integrated Satellite-Aerial-Ground monitoring platform for mountain surface processes and biodiversity. Scientific Research Equipment Project of The Special Fund for Improving Scientific Research Conditions of the Central Scientific Institutions. 2022-2023. [6]The integrated retrieving methodology for key ecological parameters in mountainous regions and its validation. The Key Project of Natural Science Foundation of China (No.41631180). 2017-2021. PI. [7]The satellite-aerial-ground integrated observation for the Essential Climate Variables (ECVs) in mountain areas and its application. The National Key Research and Development Program of China. (No. 2016YFA0600103). 2016-2020. PI. [8]The spatial-temporal pattern of key resource and environment parameters in South Asia and the spatial information services for the Road and Belt Initiative. The 135 key project of IMHE. 2016-2020. PI.
Academic Society Activities [1] Director of the Digital Mountain Committee, Chinese Committee of International Society of Digital Earth (CNISDE). [2] Vice director of the Resource information system Committee, China Society of Natural Resources. [3] Vice director of the Youth Working Committee, Geographical Society of China. [4] Board member of the Remote Sensing of Environment Brunch, Geographical Society of China. [5]Editorial board member or Peer-reviewer of over 30 SCI-indexed international journals.
Awards [1] Outstanding Mentor Award of Chinese Academy of Sciences, University of Chinese Academy of Sciences, 2021. [2] Academic and Technical Leader of Sichuan Province, 2021. [3] Elsevier Atlas Award, Elsevier, 2020. [4] National "WR Program" Technology Innovation Leading Talent, 2018. [5] Young and middle-aged scientific and technological innovation leading talents of the Ministry of Science and Technology, 2016. [6] Second Prize of Science and Technology Progress Award in Surveying and Mapping, China Society for Geodesy Photogrammetry and Cartography, 2016. [7] Youth Science and Technology Award, China Society for Natural Resources, 2013. [8] National Youth geographic science and Technology Award, The Geographical Society of China, 2013. [9] Sichuan Province's "QR Plan" to introduce overseas high-level talents，2012. [10] The Best Paper Award, International Society for Environmental Information Sciences, 2010. [11] Chinese Academy of Sciences "BR Program" (Class A) to introduce outstanding oversea talents，2010.
Publications [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. andLi, 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. andLi, 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. andLi, 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. andLi, 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.

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