Qiaoqiao Zhang
Biographic Data
| ID | 8336370 |
|---|---|
| NAME | Qiaoqiao Zhang |
| GIVEN NAMES | Qiaoqiao |
| FAMILY NAME | Zhang |
| SIGNATURE | ZHANG Q |
| AFFILIATIONS | College of Grassland Science Sichuan Agricultural University Chengdu China |
| ORCID | 0009-0005-7371-1756 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Influencing factors and mechanisms promoting proactive health behavior intention
Background: Promoting proactive health behaviors is an effective strategy for addressing public health challenges and advancing the "Healthy China" initiative. This study aims to explore the driving factors and mechanisms influencing proactive health behavior intention by integrating the theory of planned behavior (TPB) and the health belief model (HBM). Methods: A cross-sectional survey design was employed. A structured questionnaire was develop…
Machine Learning Models Based on UAV Oblique Images Improved Above‐Ground Biomass Estimation Accuracy Across Diverse Grasslands on the Qinghai–Tibetan Plateau
Unmanned aerial vehicles (UAVs) are becoming important tools for modern management and scientific research of grassland resources, especially in the dynamic monitoring of above‐ground biomass (AGB). However, current studies rely mostly on vertical images to construct models, with little consideration given to oblique images. Determination of image acquisition height often relies on experience and intuition, but there is limited comparison of mode…
No prominent works on this page.
Influencing factors and mechanisms promoting proactive health behavior intention
Background: Promoting proactive health behaviors is an effective strategy for addressing public health challenges and advancing the "Healthy China" initiative. This study aims to explore the driving factors and mechanisms influencing proactive health behavior intention by integrating the theory of planned behavior (TPB) and the health belief model (HBM). Methods: A cross-sectional survey design was employed. A structured questionnaire was develop…
Machine Learning Models Based on UAV Oblique Images Improved Above‐Ground Biomass Estimation Accuracy Across Diverse Grasslands on the Qinghai–Tibetan Plateau
Unmanned aerial vehicles (UAVs) are becoming important tools for modern management and scientific research of grassland resources, especially in the dynamic monitoring of above‐ground biomass (AGB). However, current studies rely mostly on vertical images to construct models, with little consideration given to oblique images. Determination of image acquisition height often relies on experience and intuition, but there is limited comparison of mode…
Artificial Intelligence (2 works) · Computer Science (2 works) · Agronomy (1 works) · Behavioral Health and Interventions (1 works) · Biology (1 works) · Engineering (1 works) · Environmental health (1 works) · Environmental Science (1 works) · Estimation (1 works) · Geology (1 works)