Cuizhen Wang
Biographic Data
| ID | 5232237 |
|---|---|
| NAME | Cuizhen Wang |
| GIVEN NAMES | Cuizhen |
| FAMILY NAME | Wang |
| SIGNATURE | WANG C |
| AFFILIATIONS | University of South Carolina |
| ORCID | 0000-0002-0306-9535 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 10 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 1 |
Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection
Deep learning techniques are increasingly being recognized as effective image classifiers. Aside from their successful performance in past studies, the accuracies have varied in complex environments, in comparison with the popularly of applied machine learning classifiers. This study seeks to explore the feasibility of using a U-Net deep learning architecture to classify bi-temporal, high-resolution, county-scale aerial images to determine the sp…
Converting street view images to land cover maps for metric mapping
Prototyping a Social Media Flooding Photo Screening System Based on Deep Learning
This article aims to implement a prototype screening system to identify flooding-related photos from social media. These photos, associated with their geographic locations, can provide free, timely, and reliable visual information about flood events to the decision-makers. This screening system, designed for application to social media images, includes several key modules: tweet/image downloading, flooding photo detection, and a WebGIS applicatio…
Estimates of exposure to the 100-year floods in the conterminous United States using national building footprints
A novel approach to leveraging social media for rapid flood mapping
Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the st…
Phenology-Based Assessment of Perennial Energy Crops in North American Tallgrass Prairie
Biomass is the largest source of renewable energy in the United States, and corn ethanol currently constitutes the vast majority of the country's biofuel. Extended plantation of annual crops for biofuel production, however, has raised concerns about long-term environmental, ecological, and socioeconomic consequences. Switchgrass (Panicum virgatum L.), along with other warm-season grasses, is native to the precolonial tallgrass prairie in North Am…
A novel approach to leveraging social media for rapid flood mapping
Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the st…
Phenology-Based Assessment of Perennial Energy Crops in North American Tallgrass Prairie
Biomass is the largest source of renewable energy in the United States, and corn ethanol currently constitutes the vast majority of the country's biofuel. Extended plantation of annual crops for biofuel production, however, has raised concerns about long-term environmental, ecological, and socioeconomic consequences. Switchgrass (Panicum virgatum L.), along with other warm-season grasses, is native to the precolonial tallgrass prairie in North Am…
Phenology-Based Assessment of Perennial Energy Crops in North American Tallgrass Prairie
Biomass is the largest source of renewable energy in the United States, and corn ethanol currently constitutes the vast majority of the country's biofuel. Extended plantation of annual crops for biofuel production, however, has raised concerns about long-term environmental, ecological, and socioeconomic consequences. Switchgrass (Panicum virgatum L.), along with other warm-season grasses, is native to the precolonial tallgrass prairie in North Am…
A novel approach to leveraging social media for rapid flood mapping
Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the st…
Prototyping a Social Media Flooding Photo Screening System Based on Deep Learning
This article aims to implement a prototype screening system to identify flooding-related photos from social media. These photos, associated with their geographic locations, can provide free, timely, and reliable visual information about flood events to the decision-makers. This screening system, designed for application to social media images, includes several key modules: tweet/image downloading, flooding photo detection, and a WebGIS applicatio…
Estimates of exposure to the 100-year floods in the conterminous United States using national building footprints
Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection
Deep learning techniques are increasingly being recognized as effective image classifiers. Aside from their successful performance in past studies, the accuracies have varied in complex environments, in comparison with the popularly of applied machine learning classifiers. This study seeks to explore the feasibility of using a U-Net deep learning architecture to classify bi-temporal, high-resolution, county-scale aerial images to determine the sp…
Converting street view images to land cover maps for metric mapping
Geography (6 works) · Computer Science (5 works) · Cartography (4 works) · Artificial Intelligence (3 works) · Flood myth (3 works) · Flood Risk Assessment and Management (3 works) · Computer security (2 works) · Ecology (2 works) · Engineering (2 works) · Environmental Science (2 works)