Chen Zhang
Ph.D. Candidate in Earth Systems and Geoinformation Sciences
M.S. and B.S. in Computer Science
Hi, I am Chen Zhang, a Ph.D. candidate in the Department of Geography and Geoinformation Science and graduate research assistant of the Center for Spatial Information Science and Systems at George Mason University. My research interests include:
Specifically, I am an active advocate of applying state-of-the-art methods, technologies, and tools in multidisciplinary fields to discover, understand, and share agro-geoinformation. My Ph.D. dissertation focuses on in-season mapping and prediction of crop cover using AI/machine learning and geospatial cyberinfrastructure. I am also a full-stack developer and in charge of developing, maintaining, and enhancing multiple operational geospatial data service systems including CropScape, VegScape, Crop-CASMA, and GEOSS Information Exchange DataHub.
News:
George Mason University
Fairfax, VA, USA
2021 (expected)
China University of Mining and Technology, Beijing
Beijing, China
Jul. 2014
China University of Mining and Technology, Beijing
Beijing, China
Jul. 2011
* Here is a list of my ongoing researches. Please see R&D Page for all research and development projects.
Food and Agriculture Cyberinformatics Tools (FACT): Machine-learning-based In-season Crop Mapping and Associated Cloud-based Bigdata Cyberinfrastructure to Support USDA NASS Decision Making
Research project funded by USDA NIFA (Grant #2021-67021-34151, PI: Dr. Liping Di)
Lead Developer, Research Scientist
Feb. 2021 - present
Crop-CASMA: A Web-based Geospatial Application for Crop Condition and Soil Moisture Analytics
Operational system in collaboration with USDA NASS and NASA
Lead Developer, Research Scientist
Jun. 2019 - present
USDA NASS Online Geospatial Applications CropScape and VegScape Systems Maintaining, Hosting and Enhancement of NASS Operation
Operational system funded by U.S. Department of Agriculture
Senior Developer, Research Scientist
Sep. 2018 - present
WaterSmart: A Cyberinfrastructure-Based Integrated Agro-Geoinformatic Decision-Support Web Service System to Facilitate Informed Irrigation Decision-Making
Research project funded by National Science Foundation (Grant #CNS-1739705, PI: Dr. Liping Di)
Research Scientist
Apr. 2018 - present
GEOSS Components and Services Registry
Operational system in collaboration with Federal Geographic Data Committee and U.S. Geological Survey
Senior Developer
Apr. 2018 - present
* Here is a list of my latest publications as the first author. Please see Publication Page for abstract and full-text access.
* Full publication list and citations can be found on my Google Scholar Profile.
Zhang, C., Di, L., Hao, P., Yang, Z., Lin, L., Zhao, H., and Guo, L., 2021. Rapid in-season mapping of corn and soybeans using machine-learned trusted pixels from Cropland Data Layer. International Journal of Applied Earth Observation and Geoinformation, 102, 102374. doi: 10.1016/j.jag.2021.102374.
Zhang, C., and Lin, L., 2021. Image Processing Methods in Agricultural Observation Systems. In: Di L., Üstündağ B. (eds) Agro-geoinformatics: Theory and Practice, Springer Remote Sensing/Photogrammetry. Springer, Cham. doi: 10.1007/978-3-030-66387-2_6.
Zhang, C., Di, L., Yang, Z., Lin, L., and Hao, P., 2020. AgKit4EE: A toolkit for agricultural land use modeling of the conterminous United States based on Google Earth Engine. Environmental Modelling & Software, 129, 104694. doi: 10.1016/j.envsoft.2020.104694.
Zhang, C., Yang, Z., Di, L., Lin, L., and Hao, P., 2020. Refinement of Cropland Data Layer Using Machine Learning. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, pp. 161-164. doi: 10.5194/isprs-archives-XLII-3-W11-161-2020.
Zhang, C., Di, L., Lin, L., and Guo, L., 2019. Machine-learned prediction of annual crop planting in the U.S. Corn Belt based on historical crop planting maps. Computers and Electronics in Agriculture, 166, 104989. doi: 10.1016/j.compag.2019.104989.
Zhang, C., Di, L., Yang, Z., Lin, L., Eugene, G.Y., Yu, Z., Rahman, M.S. and Zhao, H., 2019. Cloud Environment for Disseminating NASS Cropland Data Layer. The 8th International Conference on Agro-Geoinformatics. doi: 10.1109/Agro-Geoinformatics.2019.8820465.
Zhang, C., Di, L., Lin, L. and Guo, L., 2019. Extracting Trusted Pixels from Historical Cropland Data Layer Using Crop Rotation Patterns: A Case Study in Nebraska, USA. The 8th International Conference on Agro-Geoinformatics. doi: 10.1109/Agro-Geoinformatics.2019.8820236.
Zhang, C., Di, L., Sun, Z., Lin, L., Eugene, G.Y. and Gaigalas, J., 2019. Exploring cloud-based Web Processing Service: A case study on the implementation of CMAQ as a Service. Environmental Modelling & Software, 113, pp. 29-41. doi: 10.1016/j.envsoft.2018.11.019.
Graduate Research Assistant, Center for Spatial Information Science and Systems
2015 - present
Ph.D. Student, Department of Geography and Geoinformation Science
2015 - present
Research Assistant, Institute of Remote Sensing and Geographical Information Systems
2012 - 2014
Research Assistant, Department of Computer Science and Technology
2011 - 2014
Member, IEEE GRSS (Geoscience and Remote Sensing Society)
2020 - present
Student Member, AGU (American Geophysical Union)
2020 - present
Student Member, AAG (American Association of Geographers)
2018 - present
Student Member, IEEE (Institute of Electrical and Electronics Engineers)
2017 - present
Student Member, ESIP (Earth Science Information Partners)
2016 - present
Member, OGC (Open Geospatial Consortium)
2016 - present
* Please see all verified reviews on Publon.
Alexandria Engineering Journal, Elsevier
2021
Applied Sciences, MDPI
2020, 2021
Climate, MDPI
2020
Computers and Electronics in Agriculture, Elsevier
2020, 2021
Environmental Challenges, Elsevier
2021
European Journal of Remote Sensing, Taylor & Francis
2021
Forests, MDPI
2020
International Conference on Agro-Geoinformatics
2016, 2017, 2018, 2019, 2021
International Journal of Remote Sensing, Taylor & Francis
2020
Journal of King Saud University - Computer and Information Sciences, Elsevier
2019, 2020
Journal of Computational Science, Elsevier
2021
PeerJ, PeerJ
2021
Remote Sensing, MDPI
2020, 2021
Remote Sensing Letters, Taylor & Francis
2021
Remote Sensing of Environment, Elsevier
2021
Science of the Total Environment, Elsevier
2020
Sustainability, MDPI
2020, 2021