Quan Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Quan Liu has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Fengmei Yao
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
2 shared publications - Hairu Zhang
National Academy of Economic Strategy, Chinese Academy of Social Sciences, Beijing, China
2 shared publications - Jiahua Zhang
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2 shared publications - Qi Liu
School of Computer Engineering, Jiangsu University of Technology, Changzhou, China
2 shared publications - Xianglei Meng
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
2 shared publications - Sha Zhang
School of Geographical Sciences, Hebei Normal University, Shijiazhuang, China
1 shared publication
Latest Publications
- 1 October 2021
- Published by Elsevier in Science of The Total Environment
- Vol. 789, 147803
Evaluating the performance of eight drought indices for capturing soil moisture dynamics in various vegetation regions over China
- 1 October 2021
- Published by Elsevier in Science of The Total Environment
- Vol. 789, 147803
Evaluating the performance of eight drought indices for capturing soil moisture dynamics in various vegetation regions over China
- Open Access
- 10 August 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (16) , 3159
The Impact of Seasonality and Response Period on Qualifying the Relationship between Ecosystem Productivity and Climatic Factors over the Eurasian Steppe
As climate change intensifies, surface vegetation productivity and carbon exchange between terrestrial ecosystems and the atmosphere are significantly affected by the variation of climatic factors. Due to the sensitivity of grasslands to these climatic factors, it is crucial to understand the response of vegetation greenness, or carbon exchange within grasslands, to environment factor dynamics. In this study, we used solar-induced chlorophyll fluorescence (SIF), precipitation (P), vapor pressure deficit (VPD), evaporative stress (ES), and root zone soil moisture (RSM) derived from remote sensing, reanalysis, and assimilation datasets to explore the response of vegetation greenness within Eurasian Steppe to climatic factors. Our results indicated deseasonlization based on the Seasonal-Trend decomposition using Loess (STL) method, which was an effective means to remove the seasonality disturbances that affect the qualification of the relationship between SIF and the four climatic factors. The response of SIF had a time lag effect on these climatic factors, and the longer the response period, the greater the impact on the correlation of SIF with P, VPD, ES, and RSM. We also found, among the four factors, that the response of SIF to ES was the timeliest. The findings of this study emphasized the impact of the seasonality and time lag effect on the dynamic response between variables, and provided references to the attribution and monitoring of vegetation greenness and ecosystem productivity.
- 10 August 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (16) , 3159
Open AccessThe Impact of Seasonality and Response Period on Qualifying the Relationship between Ecosystem Productivity and Climatic Factors over the Eurasian Steppe
As climate change intensifies, surface vegetation productivity and carbon exchange between terrestrial ecosystems and the atmosphere are significantly affected by the variation of climatic factors. Due to the sensitivity of grasslands to these climatic factors, it is crucial to understand the response of vegetation greenness, or carbon exchange within grasslands, to environment factor dynamics. In this study, we used solar-induced chlorophyll fluorescence (SIF), precipitation (P), vapor pressure deficit (VPD), evaporative stress (ES), and root zone soil moisture (RSM) derived from remote sensing, reanalysis, and assimilation datasets to explore the response of vegetation greenness within Eurasian Steppe to climatic factors. Our results indicated deseasonlization based on the Seasonal-Trend decomposition using Loess (STL) method, which was an effective means to remove the seasonality disturbances that affect the qualification of the relationship between SIF and the four climatic factors. The response of SIF had a time lag effect on these climatic factors, and the longer the response period, the greater the impact on the correlation of SIF with P, VPD, ES, and RSM. We also found, among the four factors, that the response of SIF to ES was the timeliest. The findings of this study emphasized the impact of the seasonality and time lag effect on the dynamic response between variables, and provided references to the attribution and monitoring of vegetation greenness and ecosystem productivity.