Department of Geography
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- Department of Geography
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- Cuizhen (Susan) Wang
Cuizhen (Susan) Wang
College of Arts and Sciences
|Office:||Callcott, Room 327-A|
|Resources:||Curriculum Vitae [pdf]
Department of Geography
Dr. Wang received her Ph.D. in Geography in 2004 from Michigan State University, and
a Ph.D. in Photogrammetry and Remote Sensing in 1999 from the Institute of Remote
Sensing and Digital Earth, Chinese Academy of Sciences. From 2004 to 2013, she was
an Assistant and Associate Professor in the Department of Geography at the University
of Missouri. She is a USGIF Subject Matter Expert (SME) in Remote Sensing & Image
Analysis, and the director the USGIF GEOINT Certificate Program at University of South Carolina. Dr. Wang is the founding director of the DBAR International Center of Excellence on Big Earth Data for Coasts (ICoE-Coasts).
GIScience; Remote Sensing; Environment Change; Big Earth Data
Dr. Wang’s primary research areas are bio-environmental remote sensing. Specific experiences include optical and radar remote sensing, satellite time series, image-based deep learning, small Unmanned Aircraft Systems (sUAS), and a wide spectrum of environmental applications such as fire/drought stress; marsh dieback; 3D landscape mapping. Dr. Wang’s research and education are embraced in Big Earth Data that harmonizes all kinds of Earth observations to promote environmental health and sustainability.
- GEOG 105: The Digital Earth (Caroline Core – ARP course)
- GEOG 345: Interpretation of Aerial Photographs
- GEOG 551: Principles of Remote Sensing
- GEOG 575: Digital Techniques and Applications in Remote Sensing
- GEOG 595: Internship in Geography (Coordinator)
- GEOG 755: Remote Sensing Modeling and Analysis
Wang, C., A. Wang, D. Guo, H. Li, and S. Zang, 2022. Off-peak NDVI correction to reconstruct Landsat time series for post-fire recovery in high-latitude forests. International Journal of Applied Earth observations and Geoinformation. 107,102704.
Li**, H., C. Wang, Q. Yu and E. Smith, 2022. Spatiotemporal assessment of potential drivers of salt marsh dieback in the North Inlet-Winyah Bay estuary, South Carolina (1990-2019). Journal of Environmental Management, 313, 114907.
Wang, C., 2021. At-sensor Radiometric correction of a multispectral camera (RedEdge) for sUAS vegetation mapping. Sensors, 21, 8224.
Morgan, G.R., C. Wang, Z. Li, S.R. Schill, and D.R. Morgan. 2022. Deep learning of high-resolution aerial imagery for coastal marsh change detection: a comparative study. International Journal of Geo-Information. 11, 100.
Li, H., C. Wang, Y. Cui, M. Hodgson, 2021. Mapping salt marsh along coastal South Carolina using U-Net. ISPRS Journal of Photogrammetry and Remote Sensing. 179:121-132.
Guo, D., C. Wang, S. Zang, J. Hua, Z. Lv, and Y. Lin, 2021. Gap-Filling of 8-day Terra MODIS Daytime Land Surface Temperature in high-latitude cold region with Generalized Additive Models (GAM). Remote Sensing, 13, 3667.
Wang, C., G. Morgan, and M. E. Hodgson, 2021. sUAS for 3D tree surveying: comparative experiments on a closed-canopy earthen dam. Forests, 12, 659.
Huang, X., C. Wang*, Z. Li, and H. Ning, 2020. A 100m population grid in the CONUS by disaggregating census data with open-source Microsoft building footprints. Big Earth Data, 1-22.
Huang, X., and C. Wang, 2020. Estimates of exposure to the 100-year floods in the conterminous United States using national building footprints. International Journal of Disaster Risk Reduction. 50:101731.
Li, H., Wang*, C., Ellis, J.T., C. Y., Miller, G. and Morris J.T., 2020. Identifying marsh dieback events from Landsat image series (1998-2018) with an Autoencoder in the NIWB estuary, South Carolina. International Journal of Digital Earth, 13(12), 1467-1483.
Davis, E., Wang, C., Dow, K., 2019. Comparing Sentinel-2 MSI and Landsat 8 OLI in Soil Salinity Detection: A Case Study of Agricultural Lands in Coastal North Carolina. International Journal of Remote Sensing, 40:6134-6153.
Huang, X., Wang, C. and Lu, J. 2019. Understanding the spatiotemporal development of human settlement in hurricane-prone areas on the US Atlantic and Gulf coasts using nighttime remote sensing. Natural Hazards and Earth System Sciences, 19:2141-2155.
Huang, X., C. Wang, and Z. Li, 2018. Reconstructing flood inundation probability by enhancing near real-time imagery with real-time gauges and tweets. IEEE Transactions on Geoscience and Remote Sensing, 56:4691-4701.
Li, Z., C. Wang, C. T. Emrich, D. Guo, 2017. A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina Floods. Cartography and Geographic Information Sciences. DOI: 10.1080/15230406.2016.1271356
Wang, C., Q. Fan, Q. Li, W. M. SooHoo, and L. Lu, 2017. Energy crop mapping with enhanced TM/MODIS time series in the BCAP agricultural lands. ISPRS Journal of Photogrammetry and Remote Sensing, 124: 133-143.