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宋英强

发布时间:2017-01-01 作者: 浏览次数:916

宋英强,男,19908月出生,汉族,博士,讲师,硕士生导师。研究方向为土地信息技术,主要从事数字土壤制图、土地遥感动态监测等相关领域的研究。2019年毕业于华南农业大学并获得农学博士学位。

项目:

山东省自然科学基金,高自然价值农田快速识别及其景观结构演变机制,ZR2020QD0132020/01-2023/12,在研,主持;

山东理工大学博士科研启动基金,典型农田关键土壤属性空间预测及制图,2020/09-2025/08, 420061,在研,主持;

国家重点研发计划“基于大数据挖掘的农产品安全评价模型与污染防控体系”(2016YFD0800307),2016/01-2020/12,参与,已结题;

横向课题,黄河三角洲盐碱地样本采样与预测化验分析,2022/06-2023/06,在研,主持。

代表性论著:

[1] Song Y, Kang L, Lin F, et al. Estimating the spatial distribution of soil heavy metals in oil mining area using air quality data[J]. Atmospheric Environment, 2022: 119274.

[2] Song Y, Sun N, Zhang L, et al. Using multispectral variables to estimate heavy metals content in agricultural soils: A case of suburban area in Tianjin, China[J]. Geoderma Regional, 2022: e00540.

[3] Song Y, Zhu A, Cui X, et al. Spatial variability of selected metals using auxiliary variables in agricultural soils[J]. Catena, 2019, 174: 499-513.

[4] Song Y, Zhao X, Su H, et al. Predicting spatial variations in soil nutrients with hyperspectral remote sensing at regional scale[J]. Sensors, 2018, 18(9): 3086.

[5] Bai X, Song Y, Yu R, et al. Hyperspectral Estimation of Apple Canopy Chlorophyll Content Using an Ensemble Learning Approach[J]. Applied Engineering in Agriculture, 2021, 37(3): 505-511.

[6] Song Y, Pan Z, Liu Y, et al. Monitoring of Inefficient Land Use with High Resolution Remote Sensing Image in a Chinese Mega-City [C]. IEEE International Conference on Computational Science & Engineering. IEEE, 2017, 2: 242-249. (EI)

[7] Zhou W, Song Y, Pan Z, et al. Classification of Urban Construction Land with Worldview-2 Remote Sensing Image Based on Classification and Regression Tree Algorithm[C]. IEEE International Conference on Computational Science & Engineering. IEEE, 2017, 2: 277-283. (EI)

[8] 宋英强, 杨联安, 冯武焕等. 基于多源辅助变量和极限学习机的蔬菜地土壤有机质预测研究[J]. 土壤通报, 2017, 48(01): 118-126.

[9] 杨颢, 宋英强, 胡月明等. 基于序贯指示模拟的农田土壤重金属风险区域识别[J]. 应用生态学报, 2018, 29(05): 1695-1704.

联系方式:yingqiang_song@163.com

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