2026 2nd International Conference on Remote Sensing and Information Technology
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RSIT 2025 Successfully Concluded Online

The 2025 International Conference on Remote Sensing and Information Technology (RSIT 2025) was successfully held online on May 16, 2025. The conference served as an international platform for scholars, researchers, and practitioners to exchange ideas and discuss the latest advances in remote sensing technologies and information applications.

 

 

 

Group Photo

During the conference, several distinguished scholars delivered insightful keynote speeches. Prof. Pedro Cabral from Nanjing University of Information Science and Technology presented on “Remote Sensing of Global Ecosystem Changes,” providing valuable perspectives on environmental monitoring and global sustainability. Prof. Yanni Dong from Wuhan University shared her research on “Object Detection and Tracking: Pixel-Object-Temporal Scales,” addressing the challenges in multi-scale image analysis. Prof. Yi Wang from China University of Geosciences delivered a talk on “Spatiotemporal Modeling and Dynamic Assessment of Landslide Hazards under Climate Change,” highlighting innovative approaches to natural disaster risk management.

In addition, Dr. Muhammad Bilal from King Fahd University of Petroleum and Minerals introduced “A Novel Remote Sensing Index for Mapping Wildfire Burned Areas,” demonstrating advanced methodologies for environmental monitoring. Prof. Mir Sajjad Hussain Talpur from Sindh Agriculture University presented “Detection of Cyber-Attacks Using Machine Learning Techniques,” showcasing the intersection between information technology and cybersecurity.

RSIT 2025 fostered active academic exchange and collaboration across disciplines, contributing to the continuous advancement of remote sensing and information technology research worldwide. The organizing committee extends its sincere appreciation to all speakers, participants, and supporters for their valuable contributions to the success of this event.

 

 

Remote sensing global changes of ecosystem

 

 

 

Object detection and tracking: pixel-object-time scale

 

 

 

A Novel Remote Sensing index for Mapping of Wildfire Burned Area

 

 

 

Spatiotemporal modeling and dynamic assessment of

landslide hazard under the background of climate change