1. Linjing Zhang, Zhenfeng Shao*, Jianchen Liu, and Qimin Cheng. Deep Learning Based Retrieval of Forest Aboveground Biomass from Combined LiDAR and Landsat 8 Data. Remote Sens,11(12): 1459, 2019. (SCI)2. Zhenfeng Shao, Linjing Zhang*, and Lei Wang. Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-ground Biomass. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(12):5569-5582, 2017.(SCI)3. Zhen Zhang, Tao Jiang, Chenxi Liu, Linjing Zhang*. An Effective Classification Method for Hyperspectral Image With Very High Resolution Based on Encoder-Decoder Architecture. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 1509-1519, 2021.(SCI)4. Zhenfeng Shao and Linjing Zhang*. Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China. Sensors, 16(6):834, 2016.(SCI)5. Linjing Zhang, Zhenfeng Shao*, and Chunyuan Diao. Synergistic retrieval model of forest biomass using the integration of optical and microwave remote sensing. Journal of Applied Remote Sensing, 9: 096069, 2015.(SCI)6. Linjing Zhang, Qimin Cheng*, and Congmin Li. Improved model for estimating the biomass of Populus euphratica forest using the integration of spectral and textural features from the Chinese high-resolution remote sensing satellite GaoFen-1. Journal of Applied Remote Sensing , 9: 096010, 2015.(SCI)7. Xinliang Pan, Tao Jiang, Zhen Zhang, Baikai Sui, Chenxi Liu and Linjing Zhang*. A New Method for Extracting Laver Culture Carriers Based on Inaccurate Supervised Classification with FCN-CRF. Journal of Marine Science and Engineering, 8(4):274, 2020.(SCI)8. Linjing Zhang, Zhenfeng Shao*, and Zhiguo Wang. Estimation of forest aboveground biomass using the integration of spectral and textural features from GF-1 satellite image. 2016 Fourth International Workshop on Earth Observation and Remote Sensing Applications, pp. 353-357, 2016.(国际会议)
