WANG Kun
Professional Title：Associate Professor
Email：wangk@aircas.ac.cn
WANG Kun, Ph.D., an Associate Researcher at State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences（AIR-CAS）. Her research program focuses on advancing precision agriculture through innovative coupling of mechanistic crop growth models with high-throughput phenotyping platforms, biodiversity monitoring (particularly endangered species and invasive organisms) and remote sensing-based assessment of ecological service functions. As Principal Investigator (PI), she has secured competitive funding for 10+ national-level research projects, including flagship grants from the National Key R&D Program of China (NKPs) and the National Natural Science Foundation of China (NSFC). Her scholarly output includes 20+ SCI-indexed publications in top-tier journals (e.g., Agricultural and Forest Meteorology, Chemical Engineering Journal), with first/corresponding authorship on key methodological breakthroughs.
Ecological Monitoring; Ecological Model; Data Assimilation
[1] Huang, T., Yang, T., Wang, K.*, & Huang, W. (2024). Assessing the Current and Future Potential Distribution of Solanum rostratum Dunal in China Using Multisource Remote Sensing Data and Principal Component Analysis. Remote Sensing, 16, 271
[2] Guo, A., Huang, W., Wang, K. *, Qian, B., & Cheng, X. (2024). Early Monitoring of Maize Northern Leaf Blight Using Vegetation Indices and Plant Traits from Multiangle Hyperspectral Data. Agriculture, 14
[3] Zhang, Y., Yu, H., Huang, W., Huang, T., Fan, M., & Wang, K. * (2024). Integrating Real-Time Meteorological Conditions into a Novel Fire Spread Model for Grasslands. Fire, 7
[4] Wang, Y., Zhang, Y., Zhao, C., Dong, D., & Wang, K. * (2023a). CO and CH4 atmospheric trends from dense multi-point forest fires around the city of Chongqing using spaceborne spectrometer data. Atmospheric Pollution Research, 14, 101807
[5] Wang, Y., Zhao, C., Dong, D., & Wang, K. * (2023b). Real-time monitoring of insects based on laser remote sensing. Ecological Indicators, 151, 110302
[6] Liu X., Li X., Gao L., Zhang J., Qin D., Wang K., Li Z. (2023). Early-Season and refined mapping of winter wheat based on phenology algorithms - A case of Shandong, China. Front. Artif. Intell. 6.
[7] Chen, Q., Jia, L., Menenti, M., Hu, G., Wang, K., Yi, Z., Zhou, J., Peng, F., Ma, S., You, Q., Chen, X., & Xue, X. (2023). A data-driven high spatial resolution model of biomass accumulation and crop yield: Application to a fragmented desert-oasis agroecosystem. Ecological Modelling, 475, 110182.
[8] Guo J, Lu L, Dong Y, Huang W, Zhang B, Du B, Ding C, Ye H, Wang K, Huang Y, Hao Z, Zhao M, Wang N. (2023). Spatiotemporal Distribution and Main Influencing Factors of Grasshopper Potential Habitats in Two Steppe Types of Inner Mongolia, China. Remote Sensing. 15(3):866.
[9] Tian, H., Jiao, L., Wang, K., Zhao, X., Cao, F., & Dong, D. (2022). Exploring smartphone-based environmental sensors through applying perovskite quantum dots. Chemical Engineering Journal, 448, 137583.
[10] Jiao, F., Wang, K., Shuang, F., Dong, D., & Jiao, L. (2022). A Smartphone-Based Sensor With an Uncooled Infrared Thermal Camera for Accurate Temperature Measurement of Pig Groups. Frontiers in Physics, 10. [11] Huang T, Huang W, Wang K*, Li Y, Li Z, Yang Y. (2022). Ecosystem Service Value Estimation of Paddy Field Ecosystems Based on Multi-Source Remote Sensing Data. Sustainability. 14(15):9466.
[12] Xiao, Y., Dong, Y., Huang, W., Liu, L., Ma, H., Ye, H., & Wang, K. (2020). Dynamic Remote Sensing Prediction for Wheat Fusarium Head Blight by Combining Host and Habitat Conditions. Remote Sensing, 12, 3046.
[13] Jiang, D., Wang, K. (2019). The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review. Water, 11, 1615.
[14] Chen Qiting; Jia Li,; Menenti Massimo; Hutjes Ronald; Hu Guangcheng, Zheng Chaolei, Wang K. (2019).A numerical analysis of aggregation error in evapotranspiration estimates due to heterogeneity of soil moisture and leaf area index, Agricultural and Forest Meteorology, , 269-270: 335-350.
