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- Luo R., Zhang M.* and Ma G. (2023): Regional Representativeness Analysis of Ground-Monitoring PM2.5 Concentration Based on Satellite Remote Sensing Imagery and Machine Learning Techniques. Remote Sensing, 2023, 15, 3040, [doi: 10.3390/rs15123040]
- Li, S. and Zhang, M.* (2023): Improving the MODIS leaf area index product for a cropland with the nonlinear autoregressive neural network with eXogenous input model. Front. Earth Sci. 10:962498, 1-13, [doi: 10.3389/feart.2022.962498]
- Wang, Z. and Zhang, M.* (2022): Evaluation and Comparison of Different Machine Learning Models for NSAT Retrieval from Various Multispectral Satellite Images. Atmosphere 2022, 13, 1429, 1-17, [doi: 10.3390/atmos13091429]
- Li, S., Li, X. and Zhang, M.* (2022): Spatial-Temporal Pattern Evolution of Xi’an Metropolitan Area Using DMSP/OLS and NPP/VIIRS Nighttime Light Data. Sustainability 2022, 14, 9747, 1-20, [doi: 10.3390/su14159747]
- Yang X., Zhang M.* and Zhang B. (2021): A Generic Model to Estimate Ozone Concentration From Landsat 8 Satellite Data Based on Machine Learning Technique, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 7938-7947, 2021, [doi: 10.1109/JSTARS.2021.3101206]
- Pan D., Zhang M.* and Zhang B. (2021): A Generic FCN-Based Approach for the Road-Network Extraction From VHR Remote Sensing Images – Using OpenStreetMap as Benchmarks, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 2662-2673, 2021, [doi: 10.1109/JSTARS.2021.3058347]
- Zhang B., Zhang M.*, Hong D. (2019): Land surface temperature retrieval from Landsat 8 OLI/TIRS images based on back-propagation neural network, Indoor and Built Environment, 2019; [doi: 10.1177/1420326X19882079]
- Zhang B., Zhang M.*, Kang J., Hong D., Xv J. and Zhu X. (2019): Estimation of PMx Concentrations from Landsat 8 OLI Images Based on a Multilayer Perceptron Neural Network, Remote Sensing, 2019, 11(6): 646; [doi: 10.3390/rs11060646]
- Zhang, M., Zhang, B., Fan, H. (2018): An automatic data-integration approach to enrich ATKIS with the VGI of outdoor-sports data, Arabian Journal of Geosciences, 11:486. Springer; [doi: 10.1007/s12517-018-3849-z]
- Gong, H., Zhang, M.*, Wang, J., Meng, L. (2018): A Generic Method to Organize Boundaries of Complex Polygons for Embedded Devices, Arabian Journal of Geosciences, 11:238. Springer; [doi: 10.1007/s12517-018-3575-6]
- Qian, H., Zhang, M.* & Wu, F. (2016): A New Simplification Approach Based on the Oblique-Dividing-Curve Method for Contour Lines, ISPRS Int. J. Geo-Inf. 2016, 5:153; [doi:10.3390/ijgi5090153]
- Zhang, M., Yao, W. & Meng, L. (2016): Automatic and Accurate Conflation of Different Road-Network Vector Data towards Multi-Modal Navigation, ISPRS Int. J. Geo-Inf. 2016, 5(5), 68; [doi:10.3390/ijgi5050068]
- Zhang, M., Yao, W. & Meng, L. (2014): Enrichment of topographic road database for the purpose of routing and navigation, International Journal of Digital Earth, 7(5): 411–431 [doi:10.1080/17538947.2012.717110]
- Yao, W., Zhang, M. & Stilla, A. (2012): Areas using LiDAR Data - Theory and Experiments, International Journal of Remote Sensing, 33 (12) : 3930-3945 ,Taylor & Francis, [doi:10.1080/01431161.2011.637528]
- Zhang, M., Meng, L. & Bobrich, J. (2010): A road-network matching approach guided by 'structure'. In: Annals of GIS, 16(3):165-176, 2010, Taylor & Francis [doi:10.1080/19475683.2010.513154]
- Mustafa, M., Zhang, M. & Meng, L. (2008): Congestion Visualization Based on Probe Vehicle Data. In: Location Based Services and TeleCartography II - From Sensor Fusion to Context Models, Lecture Notes in Geoinformation and Cartography, Springer book, pp. 47-61, 2008 [doi: 10.1007/978-3-540-87393-8_4]
- Zhang, M. & Meng, L. (2008): Delimited Stroke Oriented Algorithm- Working Principle and Implementation for the Matching of Road Networks. In: Journal of Geographic Information Sciences, volume 14/1, pp. 44-53, June 2008 [doi: 10.1080/10824000809480638]
- Zhang, M. & Meng, L. (2007): An iterative road-matching approach for the integration of postal data. In: Computers, Environment and Urban Systems, volume 31/5 pp. 597~ 615; Elsevier Journal, ScienceDirect [doi: 10.1080/10824000809480638]
