Zhitong Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Zhitong Liu has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jinshan Huang
School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China
1 shared publication - Junyu Huang
School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
1 shared publication - Renbo Luo
The School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
1 shared publication - Zhuowen Wu
School of Geography and Remote Sensing Guangzhou University Guangzhou China
1 shared publication
Latest Publications
- Open Access
- 25 November 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (23) , 10908
Three-Dimensional Air Quality Monitoring and Simulation of Campus Microenvironment Based on UAV Platform
This study innovatively employs drones equipped with air quality sensors to collect three-dimensional air quality data in a campus microenvironment. Data are accurately corrected using a BP neural network, and a cubic model is constructed using three-dimensional interpolation. Combining photogrammetry technology, this study analyzes air quality patterns, finding significant differences from macro trends. Construction activities and large electronic experimental equipment significantly increase PM2.5 levels in the air. In rainy weather, the respiration of vegetation is enhanced, leading to higher CO2 concentrations, while water bodies exhibit higher temperatures in rainy weather due to their high specific heat capacity. This research not only provides a new perspective for microenvironment air quality monitoring but also offers a scientific basis for future air quality monitoring and management.
- 25 November 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (23) , 10908
Open AccessThree-Dimensional Air Quality Monitoring and Simulation of Campus Microenvironment Based on UAV Platform
This study innovatively employs drones equipped with air quality sensors to collect three-dimensional air quality data in a campus microenvironment. Data are accurately corrected using a BP neural network, and a cubic model is constructed using three-dimensional interpolation. Combining photogrammetry technology, this study analyzes air quality patterns, finding significant differences from macro trends. Construction activities and large electronic experimental equipment significantly increase PM2.5 levels in the air. In rainy weather, the respiration of vegetation is enhanced, leading to higher CO2 concentrations, while water bodies exhibit higher temperatures in rainy weather due to their high specific heat capacity. This research not only provides a new perspective for microenvironment air quality monitoring but also offers a scientific basis for future air quality monitoring and management.