Xiangnan Liu
Biographic Data
| ID | 7910371 |
|---|---|
| NAME | Xiangnan Liu |
| GIVEN NAMES | Xiangnan |
| FAMILY NAME | Liu |
| SIGNATURE | LIU X |
| AFFILIATIONS | China University of Geosciences (Beijing) |
| ORCID | 0000-0003-0036-7091 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Resilience changes of carbon stocks to quantify the long‐term effects of ecological engineering projects in subtropical forests of China based on satellite‐derived net ecosystem production time series…
Understanding how resilient forests are to ecological engineering projects (EEPs) is essential to forest management and ecosystem health. Despite growing evidence that EEPs achieve increasing carbon stocks, whether such benefits can be sustainable and what are the consequences of EEPs on forest health remain unclear. This study aimed to investigate the long‐term effects of EEPs using forest resilience from aspects of resistance and recovery, by a…
Spatio-temporal Index Based on Time Series of Leaf Area Index for Identifying Heavy Metal Stress in Rice under Complex Stressors
Crops under various types of stresses, such as stress caused by heavy metals, drought and pest/disease exhibit similar changes in physiological-biochemical parameters (e.g., leaf area index [LAI] and chlorophyll). Thus, differentiating between heavy metal stress and nonheavy metal stress presents a great challenge. However, different stressors in crops do cause variations in spatiotemporal characteristics. This study aims to develop a spatiotempo…
Developing a New Spectral Index for Detecting Cadmium-Induced Stress in Rice on a Regional Scale
In natural farmland ecosystems, cadmium (Cd) pollution in rice has attracted increasing attention because of its high toxicity, relative mobility, and high water solubility. This study aims to develop a spectral index for detecting Cd stress in rice on a regional scale. Three experimental sites are selected in Zhuzhou City, Hunan Province. The hyperspectral data, chlorophyll (Chl) content, leaf area index, average leaf angle, Cd concentration in …
A Framework for Rice Heavy Metal Stress Monitoring Based on Phenological Phase Space and Temporal Profile Analysis
Previous studies make it possible to use remote sensing techniques to monitor heavy metal stress of rice synchronously and continuously. However, most studies mainly focus on the analysis of rice's visual symptoms and physiological functions rather than temporal information during the growth period, which may reflect significant changes of rice under heavy metal stress. In this paper, an enhanced spatial and temporal adaptive reflectance fusion m…
Comparative Analysis of GF-1 and HJ-1 Data to Derive the Optimal Scale for Monitoring Heavy Metal Stress in Rice
Remote sensing can actively monitor heavy metal contamination in crops, but with the increase of satellite sensors, the optimal scale for monitoring heavy metal stress in rice is still unknown. This study focused on identifying the optimal scale by comparing the ability to detect heavy metal stress in rice at various spatial scales. The 2 m, 8 m, and 16 m resolution GF-1 (China) data and the 30 m resolution HJ-1 (China) data were used to invert l…
Extraction of Rice Heavy Metal Stress Signal Features Based on Long Time Series Leaf Area Index Data Using Ensemble Empirical Mode Decomposition
The use of remote sensing technology to diagnose heavy metal stress in crops is of great significance for environmental protection and food security. However, in the natural farmland ecosystem, various stressors could have a similar influence on crop growth, therefore making heavy metal stress difficult to identify accurately, so this is still not a well resolved scientific problem and a hot topic in the field of agricultural remote sensing. This…
No prominent works on this page.
Extraction of Rice Heavy Metal Stress Signal Features Based on Long Time Series Leaf Area Index Data Using Ensemble Empirical Mode Decomposition
The use of remote sensing technology to diagnose heavy metal stress in crops is of great significance for environmental protection and food security. However, in the natural farmland ecosystem, various stressors could have a similar influence on crop growth, therefore making heavy metal stress difficult to identify accurately, so this is still not a well resolved scientific problem and a hot topic in the field of agricultural remote sensing. This…
Comparative Analysis of GF-1 and HJ-1 Data to Derive the Optimal Scale for Monitoring Heavy Metal Stress in Rice
Remote sensing can actively monitor heavy metal contamination in crops, but with the increase of satellite sensors, the optimal scale for monitoring heavy metal stress in rice is still unknown. This study focused on identifying the optimal scale by comparing the ability to detect heavy metal stress in rice at various spatial scales. The 2 m, 8 m, and 16 m resolution GF-1 (China) data and the 30 m resolution HJ-1 (China) data were used to invert l…
Developing a New Spectral Index for Detecting Cadmium-Induced Stress in Rice on a Regional Scale
In natural farmland ecosystems, cadmium (Cd) pollution in rice has attracted increasing attention because of its high toxicity, relative mobility, and high water solubility. This study aims to develop a spectral index for detecting Cd stress in rice on a regional scale. Three experimental sites are selected in Zhuzhou City, Hunan Province. The hyperspectral data, chlorophyll (Chl) content, leaf area index, average leaf angle, Cd concentration in …
A Framework for Rice Heavy Metal Stress Monitoring Based on Phenological Phase Space and Temporal Profile Analysis
Previous studies make it possible to use remote sensing techniques to monitor heavy metal stress of rice synchronously and continuously. However, most studies mainly focus on the analysis of rice's visual symptoms and physiological functions rather than temporal information during the growth period, which may reflect significant changes of rice under heavy metal stress. In this paper, an enhanced spatial and temporal adaptive reflectance fusion m…
Spatio-temporal Index Based on Time Series of Leaf Area Index for Identifying Heavy Metal Stress in Rice under Complex Stressors
Crops under various types of stresses, such as stress caused by heavy metals, drought and pest/disease exhibit similar changes in physiological-biochemical parameters (e.g., leaf area index [LAI] and chlorophyll). Thus, differentiating between heavy metal stress and nonheavy metal stress presents a great challenge. However, different stressors in crops do cause variations in spatiotemporal characteristics. This study aims to develop a spatiotempo…
Resilience changes of carbon stocks to quantify the long‐term effects of ecological engineering projects in subtropical forests of China based on satellite‐derived net ecosystem production time series…
Understanding how resilient forests are to ecological engineering projects (EEPs) is essential to forest management and ecosystem health. Despite growing evidence that EEPs achieve increasing carbon stocks, whether such benefits can be sustainable and what are the consequences of EEPs on forest health remain unclear. This study aimed to investigate the long‐term effects of EEPs using forest resilience from aspects of resistance and recovery, by a…
Environmental Science (6 works) · Remote Sensing in Agriculture (6 works) · Biology (5 works) · Ecology (5 works) · Land Use and Ecosystem Services (4 works) · Remote sensing (4 works) · Stress (linguistics (4 works) · Agronomy (3 works) · Geology (3 works) · Chemistry (2 works)