Personal Information
Chengye ZHANG
Associate Professor
Email：czhang@cumtb.edu.cn
Research Interests
(1) Monitoring of Ecological Environment Utilizing Remote Sensing and Development of Informatization System.
(2) Monitoring and Evaluation of Natural Resources and Intelligent Decision-making Utilizing Remote Sensing.
Education/Work Background
2009.09-2013.07, Beijing University of Aeronautics and Astronautics, Major in Remote Sensing, Bachelor;
2016.09-2017.07, Purdue University (USA), Major in Computer Science, Joint Ph.D. student；
2013.09-2018.07, Peking University, Major in Remote Sensing & GIS, Ph.D.；
2018.07-2021.06, College of Geosciences and Surveying Engineering, China University of Mining and Technology, Beijing, China, Assistant Professor;
2021.07-Now, College of Geosciences and Surveying Engineering, China University of Mining and Technology, Beijing, China, Associate Professor.
Teaching Courses
Undergraduates: Processing of Remotely Sensed Digital Image
Postgraduates: High-resolution remote sensing
Key Research Funding
[1]. Extraction method for vegetation disturbance process in open-pit coal mining areas utilizing remote sensing and discovering of the spatio-temporal patterns in different areas nationwide. National Natural Science Foundation of China (No. 42371347), 2024.01-2027.12, PI
[2]. Construction of spectral radiative transfer model for wheat leaves under copper stress based on PROSPECT-D. National Natural Science Foundation of China (No. 41901291), 2020.01-2022.12, PI
[3]. Monitoring and evaluation of ecological disturbance in mining areas based on quantitative remote sensing big data. Fundamental Research Funds for the Central Universities of China (No. 2022YQDC08), 2022.01-2022.11, PI
[4]. Estimation of watershed parameters and primary productivity using remote sensing. National Science and Technology Platform Sub-Project, 2019.01-2021.12, PI
Honors
2023, the first prize of the National Geographic Information Science and Technology Progress Award.
2022, the first prize of the National Coal Industry Science and Technology Award.
2022, the first prize in the second Teacher Innovation in Teaching Competition.
2022, the Beijing Challenge Cup Entrepreneurship Program Competition for Capital University Students.
2020, the first prize of National Coal Industry Education Teaching Achievements.
2020, the first prize of China University of Mining and Technology (Beijing) Excellent Teaching Quality Award.
2013-2018, I was awarded the National Scholarship, the Presidential Scholarship of Peking University, the Outstanding Doctoral Dissertation of Peking University, and the Outstanding Graduate of Beijing.
2018, the second prize of the Ministry of Education's Science and Technology Progress Award.
2016, the first prize of the National Geographic Information Science and Technology Progress Award.
Selected Publications
[1] Chengye Zhang, Jianghe Xing, Jun Li, et al. A new method for the extraction of tailing ponds from very high-resolution remotely sensed images: PSVED. International Journal of Digital Earth, 2023, 16(1), 2681-2703.
[2] Chengye Zhang, Feiyue Li, Jun Li, et al. Assessing the effect, attribution, and potential of vegetation restoration in open-pit coal mines’ dumping sites during 2003-2020 utilizing remote sensing. Ecological Indicators, 2023, 155.
[3] Jun Li, Yaling Xu, Chengye Zhang*, et al. Unmixing the coupling influence from driving factors on vegetation changes considering spatio-temporal heterogeneity in mining areas: a case study in Xilinhot, Inner Mongolia, China. Environmental Monitoring and Assessment. 2023, 195(1).
[4] Chengye Zhang, Huiyu Zheng, Jun Li*, et al. A method for identifying the spatial range of mining disturbance based on contribution quantification and significance test. International Journal of Environmental Research and Public Health. 2022, 19(9): 5176.
[5] Yaling Xu, Li Guo, Jun Li*, Chengye Zhang, et al. Automatically identifying the vegetation destruction and restoration of various open-pit mines utilizing remotely sensed images: Auto-VDR. Journal of Cleaner Production. 2023, 137490.
[6] Jun Li, Tingting Qin, Chengye Zhang*, et al. A new method for quantitative analysis of driving factors for vegetation coverage change in mining areas: GWDF-ANN. Remote Sensing. 2022, 14(7): 1579.
[7] Chengye Zhang, Huiyu Zheng, Jun Li*, et al. A Method for Identifying the Spatial Range of Mining Disturbance Based on Contribution Quantification and Significance Test. International Journal of Environmental Research and Public Health, 2022, 19(9): 5176.
[8] Jun Li, Yan Zhu, Juqing Liu, Chengye Zhang*, et al. Parcel-level evaluation of urban land use efficiency based on multisource spatiotemporal data: A case study of Ningbo City, China. Transactions in GIS, 2021, 25(6), 2766-2790.
[9] Chengye Zhang, Jun Yue, Qiming Qin. Deep quadruplet network for hyperspectral image classification with a small number of samples. Remote Sensing. 2020, 12: 647.
[10] Chengye Zhang, Yanqiu Pei et al. Application of Luojia 1-01 nighttime images for detecting the light changes for the 2019 Spring Festival in western cities, China. Remote Sensing. 2020, 12: 1416.
[11] Chengye Zhang, Jun Yue, Qiming Qin. Global prototypical network for Few-Shot hyperspectral image classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020, 13: 4748-4759.
[12] Chengye Zhang, Qiming Qin*, Li Chen, et al. Rapid determination of coalbed methane exploration target region utilizing hyperspectral remote sensing. International Journal of Coal Geology. 2015, 150: 19-34.
[13] Chengye Zhang*, Huazhong Ren, Xiujuan Dai, et al. Spectral characteristics of copper-stressed vegetation leaves and further understanding of the copper stress vegetation index, International Journal of Remote Sensing. 2019, 40(12): 4473–4488.
[14] Chengye Zhang*, Huazhong Ren, Ziyi Huang, et al. Assessment of the application of copper stress vegetation index on Hyperion image in Dexing Copper Mine, China. Journal of Applied Remote Sensing. 2019, 13(1): 014511.
[15] Chengye Zhang, Qiming Qin*, Tianyuan Zhang, et al. Endmember extraction from hyperspectral image based on discrete firefly algorithm (EE-DFA). ISPRS Journal of Photogrammetry and Remote Sensing. 2017, 126: 108-119.
[16] Chengye Zhang, Huazhong Ren, et al. Advancing the PROSPECT-5 model to simulate the spectral reflectance of copper-stressed leaves. Remote Sensing. 2017, 9(11): 1191.
[17] Chengye Zhang, Huazhong Ren, Qiming Qin*, Okan K. Ersoy. A new narrow band vegetation index for characterizing the degree of vegetation stress due to copper: the copper stress vegetation index (CSVI). Remote Sensing Letters. 2017, 8:6, 576-585.
[18] Qiming Qin, Zili Zhang, Li Chen, Nan Wang, Chengye Zhang*. Oil and gas reservoir exploration based on hyperspectral remote sensing and super low frequency electromagnetic detection. Journal of Applied Remote Sensing. 2016，10(1): 016017.