Member of the Board of Directors of the National Industrial Statistics Teaching and Research Association;

Member of the Board of the ninth Directors of the Fujian Provincial Society of Surveying, Mapping and Geographic Information;

Deputy Director of Fujian Provincial Statistical Information Research Center (School Research Platform).

Research areas of interest: Mathematical earth science, geographic information science, 

computer science and other multi-disciplinary interdisciplinary learning and research backgrounds. 

Specific research directions include: spatiotemporal weighted regression and its applications, 

GIS spatiotemporal data modeling and analysis, spatiotemporal data mining, MPI parallel computing, and knowledge graphs

ORCID: 0000-0002-5687-8627

1. Guest associate editor of the special issue of Earth Science Informatics (SCI, IF: 2.705),

Progress of Geoinformatics in Earth and Environmental Sciences,

Submissions are welcome:

https://www.springer.com/journal/12145/updates/24595120

2. Guest associate editor of the special issue Sustainability (SCI, IF: 3.889),

Special Issue Sustainability in Geospatial Analysis and Geographic Information Science Application,

Submissions are welcome:

https://www.mdpi.com/journal/sustainability/special_issues/0B7755R16E

Statistics, Spatial Statistics, Data Mining and Its Application Technology, Statistical Professional Practice, Statistical Comprehensive Practice

Multi-scale space-time weighted regression and its parallel calibration algorithm research, National Natural Science Foundation of China Youth Fund, approval number: 42202333, ¥300,000, 2023-01-2025-12, PI.

Mathematical model development of infectious disease monitoring and early warning and emergency response technology research platform based on geographic information technology, Fuzhou Center for Disease Control and Prevention, ¥100,000, 2022.02-2022.9, PI.

 Spatio-temporal heterogeneity modeling and early warning research of regional rainfall-type landslide hazard risk—taking Yongtai County as an example, Yongtai County Meteorological Bureau of Fujian Province, ¥55,000, 2022.3-2023.5, PI.

Monitoring and early warning analysis of infectious diseases based on geographic information technology, Fujian Jingwei Surveying and Mapping Information Co., Ltd., 2022350004000482, 2022.3-2022.9, ¥50,000, PI.

  Construction of Land and Resources Monitoring and Supervision System Based on Spatial Big Data, Fuzhou Science and Technology Plan Project 2021-P-056 (Rong Ke [2021] No. 266), ¥30,000 (total funding ¥300,000), 2021.06.01-2023.05.31. Co-PI.

Research on Multi-scale Geographically Weighted Regression Method Considering Time-varying Value Difference Rate, Fujian Provincial Natural Science Foundation (2021J05030), 40,000, 2021-2024, PI.

 Research on key technologies of 3D spatio-temporal data visualization and distributed storage in land space (2021L3003), 2021 central government-guided local development special project, ¥225,000 (total funding ¥900,000), 2021.9-2024.8, Co-PI.

R&D and application of key technologies for dynamic evaluation of wetland carbon pool ecological security, 2021 Fujian Provincial Key Project of Science and Technology Innovation (2021G02007), ¥ 600,000, Co-PI.

Research on key technologies of spatiotemporal dynamic monitoring and intelligent computing of carbon storage in coastal wetlands in Fujian Province, Department of Natural Resources of Fujian Province (Ministry of Natural Resources' Southeast Ecological Fragile Area Monitoring and Restoration Engineering Technology Innovation Center), Southeast Ecological Restoration [2021] No. 4, ¥100,000, 2021.4 -2023.4, Co-PI.

Green Smart Wetland Ecological Protection Information Service Team, Fujian Agriculture and Forestry University Rural Revitalization Service Team Support Program (11899170152), ¥300,000, Co-PI.

Land and Resources Monitoring and Supervision System Construction—Ecological Dynamic Monitoring and Supervision System, Telihui Technology Information Co., Ltd., 2021350104001014, 2021.4-2023.4, ¥100,000, PI.

[1] Que, X., Huang, J., Ralph, J., Zhang, J., Prabhu, A., Morrison, S., Hazen, R. and Ma, X., 2024. Using adjacency matrix to explore remarkable associations in big and small mineral data. Geoscience Frontiers (中科院一区top, SCI, IF= 8.9), 15(5), p.101823. https://doi.org/10.1016/j.gsf.2024.101823

[2] Hong, Y., Que, X*., Wang, Z., Ma, X., Wang, H., Salati, S. and Liu, J., 2024. Mangrove extraction from super-resolution images generated by deep learning models. Ecological Indicators (中科院一区top, SCI, IF= 7.4), 159, p.111714.https://doi.org/10.1016/j.ecolind.2024.111714

[3] Que, X., Zhang, J., Chen, W., Ralph, J., and Ma, X., 2025. The OpenMindat v1.0.0 R package: a machine interface to Mindat open data to facilitate data-intensive geoscience discoveries, Geoscientific Model Development (中科院二区, SCI),18,4455-4467,2025. https://doi.org/10.5194/gmd-18-4455-2025 

[4] Wang, Z., Que, X*., Li, M., Liu, Z., Shi, X., Ma, X., Fan, C. and Lin, Y., 2024. Spatiotemporally weighted regression (STWR) for assessing Lyme disease and landscape fragmentation dynamics in Connecticut towns. Ecological Informatics (中科院二区, SCI, IF=7.3), 84, p.102870. https://doi.org/10.1016/j.ecoinf.2024.102870

[5] Que, X., Ma, C., Ma, X. and Chen, Q., 2021. Parallel computing for fast spatiotemporal weighted regression. Computers & Geosciences (中科院二区, SCI, IF2021= 5.168), 150, p.104723. https://doi.org/10.1016/j.cageo.2021.104723

[6] Que, X., Ma, X., Ma, C., and Chen, Q.: A spatiotemporal weighted regression model (STWR v1.0) for analyzing local nonstationarity in space and time, Geoscientific Model Development (中科院一区,SCI, IF2020 = 6.135), 13, 6149–6164, 2020.https://doi.org/10.5194/gmd-13-6149-2020    

[7] Fan, C., Que, X.*, Wang, Z. and Ma, X., 2023. Land cover impacts on surface temperatures: evaluation and application of a novel spatiotemporal weighted regression approach. ISPRS International Journal of Geo-Information (SCI, IF2023 = 2.8), 12(4), p.151.https://doi.org/10.3390/ijgi12040151

[8] Que, X., Zhuang, X., Ma, X., Lai, Y., Xie, J., Fei, T., Wang, H. and Yuming, W.U., 2024. Modeling the spatiotemporal heterogeneity and changes of slope stability in rainfall-induced landslide areas. Earth Science Informatics (SCI,IF =3), 17(1), pp.51-61.https://doi.org/10.1007/s12145-023-01165-7

[9] Deng, S.Y. and Que, X*., 2019. Research on the teaching assessment of students of science and engineering teachers in a university. Computer Applications in Engineering Education (SCI, IF =1.435), 27(1), pp.5-12.https://doi.org/10.1002/cae.22051   

[10] Chen, L., Wang, Z., Ma, X., Zhao, J., Que, X.*, Liu, J., Chen, R. and Li, Y., 2024. Empirical analysis of a Super-SBM-based framework for wetland carbon stock safety assessment. Remote Sensing (中科院二区, SCI, IF=4.2), 16(10), p.1678.https://doi.org/10.3390/rs16101678

[11] Lai, Y., Fei, T., Wang, C., Xu, X., Zhuang, X., Que, X*., Zhang, Y., Yuan, W., Yang, H. and Hong, Y., 2025. Energy Carbon Emission Reduction Based on Spatiotemporal Heterogeneity: A County-Level Empirical Analysis in Guangdong, Fujian, and Zhejiang. Sustainability (SCI/SSCI, IF = 3.3), 17(7), p.3218.https://doi.org/10.3390/su17073218

[12] Weilin Chen, Jiyin Zhang, Wenjia Li, Xiang Que, Chenhao Li, Xiaogang Ma, 2025, Integrating Neuro-Symbolic AI and Knowledge Graph for Enhanced Geochemical Prediction in Copper Deposits, Applied Computing and Geosciences (ESCI, IF =3.2) , 100259.https://doi.org/10.1016/j.acags.2025.100259 

[13] Hong, Y., Zhou, R., Liu, J., Que, X., Chen, B., Chen, K., He, Z. and Huang, G., 2025. Monitoring Mangrove Phenology Based on Gap Filling and Spatiotemporal Fusion: An Optimized Mangrove Phenology Extraction Approach (OMPEA). Remote Sensing (中科院二区, SCI, IF=4.1 ), 17(3), p.549.https://doi.org/10.3390/rs17030549

[14] Zhang, J., Que, X., Madhikarmi, B., Hazen, R.M., Ralph, J., Prabhu, A., Morrison, S.M. and Ma, X., 2024. Using a 3D heat map to explore the diverse correlations among elements and mineral species. Applied Computing and Geosciences (ESCI/EI, IF= 3.2), 21, p.100154.https://doi.org/10.1016/j.acags.2024.100154

[15] Zhang, J., Clairmont, C., Que, X., Li, W., Chen, W., Li, C. and Ma, X., 2025. Streamlining geoscience data analysis with an LLM-driven workflow. Applied Computing and Geosciences (ESCI/EI, IF=3.2), 25, p.100218.https://doi.org/10.1016/j.acags.2024.100218

[16] Ma, X., Ralph, J., Zhang, J., Que, X., Prabhu, A., Morrison, S.M., Hazen, R.M., Wyborn, L. and Lehnert, K., 2024. OpenMindat: Open and FAIR mineralogy data from the Mindat database. Geoscience Data Journal (SCI, IF = 3.3), 11(1), pp.94-104.https://doi.org/10.1002/gdj3.204

[17] Chen, R., Wang, C., Que, X.*, Liao, F.H., Ma, X., Wang, Z., Li, Z., Wen, K., Lai, Y. and Xu, X., 2024. Exploring Urban Heat Distribution and Thermal Comfort Exposure Using Spatiotemporal Weighted Regression (STWR). Buildings (SCI, IF = 3.1), 14(6), p.1883.https://doi.org/10.3390/buildings14061883

[18] Zou, X., Wang, C., Que, X*., Ma, X., Wang, Z., Fu, Q., Lai, Y. and Zhuang, X., 2024. Spatiotemporal Heterogeneous Responses of Ecosystem Services to Landscape Patterns in Urban–Suburban Areas. Sustainability (SCI/SSCI, IF = 3.3), 16(8), p.3260.https://doi.org/10.3390/su16083260

[19] Cui, Z., Chen, Q., Liu, G., Ma, X. and Que, X., 2021. Multiple-point geostatistical simulation based on conditional conduction probability. Stochastic Environmental Research and Risk Assessment (中科院二区,SCI, IF=3.821), 35(7), pp.1355-1368.https://doi.org/10.1007/s00477-020-01944-4

[20] Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S.M., Li, W., Chen, W. and Ma, X., 2024. Mindat. org–the open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist (SCI, IF = 2.7).https://doi.org/10.2138/am-2024-9486

[21] Wang, Z., Fan, C., Que, X., Liao, F.H., Ma, X. and Wang, H., 2024. Multi-scale analysis of urban forests and socioeconomic patterns in a desert city, Phoenix, Arizona. Scientific Reports (SCI, 中科院二区,IF = 3.9), 14(1), p.23864. https://doi.org/10.1038/s41598-024-74208-8

[22] Chen, Q., Zheng, X., Xu, B., Sun, M., Zhou, Q., Lin, J., Que, X., Zhang, X. and Xu, Y., 2024. Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model. Scientific Reports (SCI, 中科院二区, IF = 3.9 ), 14(1), p.4116. https://doi.org/10.1038/s41598-024-54630-8

[23] Ralph, J., Martynov, P., Ma, X., Von Bargen, D., Li, W., Huang, J., Golden, J., Profeta, L., Prabhu, A., Morrison, S. and Que, X., 2024. Identifier Service in the Mindat Database: Persistent and Structured Access to Massive Records of Minerals and Other Natural Materials.Data Intelligence (ESCI/EI,中科院二区，IF = 1.9), https://doi.org/10.3724/2096-7004.di.2024.0021

[24] Que X*., Su S. (2021) Geographically Weighted Regression. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_141-1

[25] Que X*., Ma X., Ma C., Liu F., Chen Q. (2021) Spatiotemporal Weighted Regression. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_307-1

[26] Chen, W., Ma, X., Wang, Z., Li, W., Fan, C., Zhang, J., Que, X. and Li, C., 2024. Exploring neuro-symbolic AI applications in geoscience: implications and future directions for mineral prediction. Earth Science Informatics (SCI, IF = 2.8), 17(3), pp.1819-1835. https://doi.org/10.1007/s12145-024-01278-7

[27] Wang, H., Chen, M., Wang, Z., Huang, L., Caudill, C.C., Qu, S. and Que, X., 2024. How does extreme point sampling affect non-extreme simulation in geographical random forest?. Earth Science Informatics (SCI, IF= 2.8), 17(3), pp.1983-1991.https://doi.org/10.1007/s12145-024-01268-9

[28] Li, C., Zhang, J., Kale, A., Que, X., Salati, S. and Ma, X., 2022. Toward trust-based recommender systems for open data: A literature review. Information, 13(7), p.334.https://doi.org/10.3390/info13070334

[29] Chen Q., Liu G., Ma X., Que X. (2021) Spatial Analysis. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_300-1

[30] Hummer D, Ma X, Que X, Zhang S, Liu C, Hazen R, Golden J & Downs R, Towards Quantitative Scales of Lithophilicity, Chalcophilicity and Hydrophilicity Using Statistical Correlations Among the Mineral-Forming Elements, Goldschmidt2020, https://doi.org/10.46427/gold2020.1113

[31] Tian, Shanjun, Wu, Chonglong, Liu, G, Que, X., Chen, Qiyu. (2016). Spatiotemporal Data Model for Managing 3D Geological Solid Models in Coal Digging Simulation. Int. J. Earth Sci. Eng (SCI), 12, 2472-2479.

[32] G Liu, X Que, X Hu, S Tian, J Zhu. Spatiotemporal Data Model forMulti-Factor Geological Process Analysis with Case Study, Mathematics of PlanetEarth, Springer Berlin Heidelberg,2014:319-323. https://doi.org/10.1007/978-3-642-32408-6_71

[33] Que, X., Wu, C., Chen, R., Liu, J. and Lu, C., 2016, July. Spatiotemporal data model for geographical process analysis with case study. In 2016 15th International Symposium on Parallel and Distributed Computing (ISPDC) (pp. 390-394). IEEE.https://doi.org/10.1109/ISPDC.2016.66

[34] Que, X., Liu, G., He, Z. and Qi, G., 2014. Realistic 3D terrain roaming and real-time flight simulation. 3D Research (EI), 5, pp.1-11. https://doi.org/10.1007/s13319-014-0027-2

[35] 费婷婷,丁晓婷,阙翔*,等.基于SBM-DEA与STWR模型的中国能源碳排放效率时空异质性分析[J].环境工程 (CSCD), 2024, 42(10):188-200.  

[36] 朱映辰,谭芳林,阙翔*, 洪宇,潘爱芳,刘金福. 多时间尺度下森林公园负离子变化特征及与温湿度关系研究[J].西北林学院学报(CSCD),2023,38(06):211-218+227. doi:10.3969/j.issn.1001-7461.2023.06.28 

[37] 龚声燕,连海峰, 阙翔*, 刘金福,谭芳林.基于APEI的2013—2018年福建省大气污染评价[J].环境工程(CSCD),2023,41(02):73-81.

[38] 苏少强, 阙翔* , 严宣辉，何中声，刘金福，李梦航，黄朝法，刘海,基于STWR模型的森林病虫影响因素研究[J].西北农林科技大学学报（自然科学版）(CSCD),2022, 50(11).

[39] 阙翔,陈日清,刘必雄,罗超,李梦航,苏少强.福建省农业技术推广信息化展示平台设计与实现[J].农业工程,2021,11(03):43-49.

[40] 林津, 洪宇, 林志玮, 阙翔, 刘金福, 连海峰. 福建泉州湾河口湿地时空动态及其驱动机理[J]. 北京林业大学学报(CSCD).2021,43(6):75-82.

[41] 温康民,任国玉,阙翔,孙秀宝.福州城市热岛精细化时空结构特征研究[J].环境监测管理与技术(CSCD) , 2023,35(01):14-19.

[42] 张志庭，彭帅，阙翔，陈麒玉. 基于提示和度量学习的小样本地质关系抽取[J].地学前缘(CSCD / EI),2025, https://doi.org/10.13745/j.esf.sf.2025.4.65 

Patent

Xiang Que*; Ma Chao; Fan Liu; Wang Kun; Spatiotemporal Weighted Regression Method Based on Geographically Weighted Regression Framework, 2019-8-1, United States, application number: 16528845, ranking first.

A method for realizing the corresponding relationship sequence between options and test questions in 3D question bank, 2016-9-19, China, CN201610828677.3, ranking third.

Computer software copyright registration

Wetland waterbird online sample annotation platform V1.0 (registration number 2023SR0971735), ranked 1.

Bird positioning and observation applet V0.2 (registration number 2023SR0977259), ranked 1.

The spatiotemporal weighted regression operation software is referred to as STWRV1.0 (registration number: 2020SR1667551), 

ranking first.

Smart Wetland Monitoring and Display System V1.0 (Registration Number: 2017SR657981), ranked first.

Agricultural technology extension display system ATEDS V1.0 (registration number: 2016SR361801), ranked first.

Agricultural technology extension collection system V1.0 (registration number: 2017SR075858), ranked first.

Geological spatiotemporal data management system GeoSTDMS V1.0 (registration number: 2015SR015605), ranked third.

Award

2023 Fujian Provincial Surveying, Mapping and Geographic Information Science and Technology Award - Outstanding Academic Paper 

Award, Second Prize, Ranked 1st

Candidates for training in Fujian Agriculture and Forestry University’s “Hundred Climbing Plan” in 2023

2021 Fujian Provincial Surveying, Mapping and Geographic Information Science and Technology Award - Outstanding Academic Paper 

Award, First Prize, Ranked 1st

2021 School May 4th Youth Individual Medal

2018-2020 School Major Basic Research Key Core Technology Achievement Award, Second Prize, Ranked 2nd.