王永吉，男，1992年生，郑州大学直聘副教授，硕士生导师。2020年博士毕业于中国科学院大学（中国科学院地理科学与资源研究所）地图学与地理信息系统专业，2020年至今就职于郑州大学地球科学与技术学院。主要研究方向为遥感与GIS（遥感智能解译，数字土壤制图等），主讲课程为《多元地理时空统计与分析》。联系方式：wangyongji@zzu.edu.cn。

主持有河南省高等学校重点科研项目1项，并参与科技基础性工作专项、国家自然科学基金、中国科学院科技服务网络计划（STS计划）等多项科研项目，在International Journal of Applied Earth Observation and Geoinformation，Precision Agriculture，IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing等国内外重要学术期刊上发表多篇学术论文。

主持和参与的主要科研项目：

1. 河南省高等学校重点科研项目基础研究计划：基于局部空间异质性的土壤样本潜在异常值识别方法研究，22A170021，主持

2. 科技基础性工作专项项目：新世纪版《中华人民共和国国家大地图集》编研，2013FY112800，参与

3. 国家自然科学基金项目：城市人群的PM2.5暴露-反应时空机理研究，41471414，参与

4. 中国科学院科技服务网络计划（STS计划）项目：智慧农业核心技术突破与集成示范，参与

5. 中国科学院科技服务网络计划（STS计划）项目子课题：县域现代农业信息服务平台研发与建设，参与

发表的学术论文和专利：

[1] Wang Yongji, Qi Qingwen, Bao Zhengyi*, Wu Lili, Geng Qingling, and Wang Jun, "A novel sampling design considering the local heterogeneity of soil for farm field-level mapping with multiple soil properties," , Precision Agriculture, 2022.

[2] Wang Yongji, Wu Lili*, Qi Qingwen, and Wang Jun, "Local Scale-Guided Hierarchical Region Merging and Further Over- and Under-Segmentation Processing for Hybrid Remote Sensing Image Segmentation," , IEEE Access, vol. 10, pp. 81492-81505, 2022.

[3] Tian Zhihui, Liu Yi, Wang Yongji*, and Wu Lili, "A Tourist Behavior Analysis Framework Guided by Geo-Information Tupu Theory and Its Application in Dengfeng City, China," ISPRS International Journal of Geo-Information, vol. 11, no. 4, 2022.

[4] Wang Yongji*, Tian Zhihui, Qi Qingwen, and Wang Jun, "Double-Variance Measures: A Potential Approach to Parameter Optimization of Remote Sensing Image Segmentation," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 2314-2326, 2021.

[5] Wang Yongji, Qi Qingwen, Jiang Lili, Ying Liu. Hybrid Remote Sensing Image Segmentation Considering Intrasegment Homogeneity and Intersegment Heterogeneity [J], IEEE Geoscience and Remote Sensing Letters, 2020, 17(1):22-26.

[6] Wang yongji, Jiang lili*, Qi Qingwen, Liu Ying, Jun Wang. Remote Sensing-Guided Sampling Design with Both Good Spatial Coverage and Feature Space Coverage for Accurate Farm Field-Level Soil Mapping [J], Remote Sensing, 2019, 11(16): 1946.

[7] Wang Yongji, Qi Qingwen, Liu Ying, Jiang Lili, Wang Jun. Unsupervised segmentation parameter selection using the local spatial statistics for remote sensing image segmentation [J], International Journal of Applied Earth Observation and Geoinformation, 2019, 81:98-109.

[8] Wang Yongji, Meng Qingyan, Qi Qingwen, Yang Jian, Liu Ying. Region Merging Considering Within- and Between-Segment Heterogeneity: An Improved Hybrid Remote-Sensing Image Segmentation Method [J], Remote Sensing, 2018, 10(5): 781.

[9] Wang Yongji, Qi Qingwen, Liu Ying. Unsupervised Segmentation Evaluation Using Area-Weighted Variance and Jeffries-Matusita Distance for Remote Sensing Images [J], Remote Sensing, 2018, 10(8): 1193.

[10] 王永吉,孟庆岩,杨健,孙云晓,李鹏,邢武杰.一种基于特征选择的面向对象遥感影像分类方法[J].科学技术与工程,2016,16(32):107-113.

[11] Wang Jun, Jiang Lili, Qi Qingwen, and Wang Yongji, "Exploration of Semantic Geo-Object Recognition Based on the Scale Parameter Optimization Method for Remote Sensing Images,", ISPRS International Journal of Geo-Information, vol. 10, no. 6, Jun 2021.

[12] Jun Wang, Lili Jiang*, Qingwen Qi,Yongji Wang. An Improved Hybrid Segmentation Method for Remote Sensing Images. International Journal of Geo-Information.2019.11.28

[13] 刘莹,孟庆岩,王永吉,杨健,刘洪杰,孙震辉.基于特征优选与支持向量机的不透水面覆盖度估算方法[J].地理与地理信息科学,2018,34(01):24-31+3.

[14] 孟庆岩，王永吉，杨健，孙震辉。一种结合改进快速合并算法的分水岭分割方法，2021（发明专利）