资源环境遥感与信息技术

2007年、2010年、2013年在华中农业大学分别获得学士、硕士和博士学位。2013年进入浙江大学博士后流动站，期间荣获中国博士后科学基金会2015年度“博士后国际交流计划派出项目”赴澳大利亚 CSIRO 土水所合作开展为期两年的博士后研究。现主要从事资源环境遥感与信息技术应用研究。

1.Chen, S., Li, S., Ma, W., Xu, D., Shi, Z., and Zhang, G. Rapid determination of soil classes in soil profiles using vis–NIR spectroscopy and Multiple Objectives Mixed Support Vector Classification. European Journal of Soil Science. 2018, doi:101111/ejss.12715
2.Xu, D., Zhao, R., Li, S., Chen, S., Jiang, Q., Zhou, L., Shi, Z. Multi-sensor fusion for the determination of several soil properties in the Yangtze River Delta, China. European Journal of Soil Science. 2018, doi:10.1111/ejss.12729
3.Ji, W., Li, S., Chen, S., Shi, Z., Viscarra Rossel, R.A., Mouazen, A.M. Prediction of soil attributes using the Chinese soil spectral library and standardized spectra recorded at field conditions. Soil & Tillage Research, 2016, 155, 492–500.
4.Peng, J., Ji, W., Ma, Z., Li, S., Chen, S., Zhou, L., Shi, Z. Predicting total dissolved salts and soluble ion concentrations in agricultural soils using portable visible near-infrared and mid-infrared spectrometers. Biosystems Engineering. 2016, 152, 94–103.
5.Li, S., Shi, Z., Chen, S., Ji, W., Zhou, L., Yu, W., Webster, R. In situ measurements of organic carbon in soil profiles using vis-NIR spectroscopy on the Qinghai–Tibet Plateau. Environmental Science & Technology. 2015, 49, 4980–4987.
6.Li, S., Ji, W., Chen, S., Peng, J., Zhou, Y., Shi, Z. Potential of VIS-NIR-SWIR spectroscopy from the Chinese soil spectral library for assessment of nitrogen fertilization rates in the paddy-rice region, China. Remote Sensing, 2015, 7, 7029–7043.
7.Ji, W., Shi, Z., Huang, J., Li, S. In situ measurement of some soil properties in paddy soil using visible and near-infrared spectroscopy. PLoS ONE, 2014, 9, e105708.
8.李硕, 汪善勤, 史舟. 基于成像光谱技术预测氮素在土壤剖面中的垂直分布. 土壤学报, 2015, 52, 1014–1023.
9.陈颂超, 冯来磊, 李硕, 纪文君, 史舟. 基于局部加权回归的土壤全氮含量可见-近红外光谱反演. 土壤学报, 2015, 52, 312–320.
10.王乾龙, 李硕, 卢艳丽, 彭杰, 周炼清, 史舟. 基于大样本土壤光谱数据库的氮含量反演. 光学学报, 2014, 34, 308–314.
11.李硕, 汪善勤, 张美琴. 基于可见-近红外光谱比较主成分回归、偏最小二乘回归和反向传播神经网络对土壤氮的预测研究. 光学学报, 2012, 32, 289–293.

1.基于成像光谱技术的原状土壤剖面光学特性与氮素估算制图研究. 国家自然科学基金青年科学基金项目, 41601370, 2017–2019. (主持)
2.基于可见近红外成像光谱技术土壤剖面氮的预测研究. 中国博士后科学基金面上项目, 2014M561772, 2014–2017. (主持)
3.基于可见近红外成像光谱技术土壤剖面氮的预测研究. 浙江省博士后项目择优资助, BSH1402033, 2014–2017. (主持)
4.基于遥感–模型融合的高寒山区土壤有机碳时空演化与空间表征研究. 国家自然科学基金面上项目, 41571339, 2016–2019. (参与)