112 citations · 133 across the 14 of their papers we have counts for
14 papers
Data-Driven Vision-Language Models for Remote Sensing: A Survey
Yue Zhou, Shujun Zhao, Xue Yang +7
During the deep learning era, innovations in remote sensing (RS) vision models primarily focused on optimizing network architectures for specific tasks and conducting end-to-end tr…
Real-Scale Island Area and Coastline Estimation using Only its Place Name or Coordinates
Quanyun Wu, Kyle Gao, Wentao Sun +4
Accurate measurement of island area and coastline length is crucial for coastal zone monitoring and oceanographic analysis. However, traditional measurement and mapping methods usu…
Trustworthy Data-Driven Wildfire Risk Prediction and Understanding in Western Canada
Zhengsen Xu, Lanying Wang, Sibo Cheng +12
In recent decades, the intensification of wildfire activity in western Canada has resulted in substantial socio-economic and environmental losses. Accurate wildfire risk prediction…
BCWildfire: A Long-term Multi-factor Dataset and Deep Learning Benchmark for Boreal Wildfire Risk Prediction
Zhengsen Xu, Sibo Cheng, Lanying Wang +4
Wildfire risk prediction remains a critical yet challenging task due to the complex interactions among fuel conditions, meteorology, topography, and human activity. Despite growing…
Instructor-Worker Large Language Model System for Policy Recommendation: a Case Study on Air Quality Analysis of the January 2025 Los Angeles Wildfires
Kyle Gao, Dening Lu, Liangzhi Li +4
The Los Angeles wildfires of January 2025 caused more than 250 billion dollars in damage and lasted for nearly an entire month before containment. Following our previous work, the…
Digital Twin Buildings: 3D Modeling, GIS Integration, and Visual Descriptions Using Gaussian Splatting, ChatGPT/Deepseek, and Google Maps Platform
Kyle Gao, Dening Lu, Liangzhi Li +4
Urban digital twins are virtual replicas of cities that use multi-source data and data analytics to optimize urban planning, infrastructure management, and decision-making. Towards…
Gaussian Building Mesh (GBM): Extract a Building's 3D Mesh with Google Earth and Gaussian Splatting
Kyle Gao, Liangzhi Li, Hongjie He +3
Recently released open-source pre-trained foundational image segmentation and object detection models (SAM2+GroundingDINO) allow for geometrically consistent segmentation of object…
Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery
Willow Liu, Shuxin Qiao, Kyle Gao +4
This research addresses the need for high-definition (HD) maps for autonomous vehicles (AVs), focusing on road lane information derived from aerial imagery. While Earth observation…
Enhanced 3D Urban Scene Reconstruction and Point Cloud Densification using Gaussian Splatting and Google Earth Imagery
Kyle Gao, Dening Lu, Hongjie He +2
3D urban scene reconstruction and modelling is a crucial research area in remote sensing with numerous applications in academia, commerce, industry, and administration. Recent adva…
Deep Learning for Wildfire Risk Prediction: Integrating Remote Sensing and Environmental Data
Zhengsen Xu, Jonathan Li, Sibo Cheng +8
Wildfires pose a significant threat to ecosystems, wildlife, and human communities, leading to habitat destruction, pollutant emissions, and biodiversity loss. Accurate wildfire ri…
NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)
Kyle Gao, Yina Gao, Hongjie He +3
In March 2020, Neural Radiance Field (NeRF) revolutionized Computer Vision, allowing for implicit, neural network-based scene representation and novel view synthesis. NeRF models h…
Monitoring surface deformation over oilfield using MT-InSAR and production well data
Sarah Narges Fatholahi, Hongjie He, Lanying Wang +2
Surface displacements associated with the average subsidence due to hydrocarbon exploitation in southwest of Iran which has a long history in oil production, can lead to significan…
The impact of data volume on performance of deep learning based building rooftop extraction using very high spatial resolution aerial images
Hongjie He, Ke Yang, Yuwei Cai +15
Building rooftop data are of importance in several urban applications and in natural disaster management. In contrast to traditional surveying and mapping, by using high spatial re…
A Deep Learning Approach Based on Graphs to Detect Plantation Lines
Diogo Nunes Gonçalves, Mauro dos Santos de Arruda, Hemerson Pistori +8
Deep learning-based networks are among the most prominent methods to learn linear patterns and extract this type of information from diverse imagery conditions. Here, we propose a…