Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data
Global climate change and human activities have increased the frequency and severity of droughts. This has become a critical factor affecting vegetation growth and diversity, resulting in detrimental effects on agricultural production, ecosystem stability, and socioeconomic development. Therefore, a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/14/3641 |
| _version_ | 1797587573707636736 |
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| author | Xiujuan Dong Yuke Zhou Juanzhu Liang Dan Zou Jiapei Wu Jiaojiao Wang |
| author_facet | Xiujuan Dong Yuke Zhou Juanzhu Liang Dan Zou Jiapei Wu Jiaojiao Wang |
| author_sort | Xiujuan Dong |
| collection | DOAJ |
| description | Global climate change and human activities have increased the frequency and severity of droughts. This has become a critical factor affecting vegetation growth and diversity, resulting in detrimental effects on agricultural production, ecosystem stability, and socioeconomic development. Therefore, assessing the response of vegetation dynamics to drought can offer valuable insights into the physiological mechanisms of terrestrial ecosystems. Here, we applied long-term datasets (2001–2020) of solar-induced chlorophyll fluorescence (SIF) and normalized difference vegetation index (NDVI) to unveil vegetation dynamics and their relationship to meteorological drought (SPEI) across different vegetation types in the Yangtze River Basin (YRB). Linear correlation analysis was conducted to determine the maximum association of SPEI with SIF and NDVI; we then compared their responses to meteorological drought. The improved partial wavelet coherence (PWC) method was utilized to quantitatively assess the influences of large-scale climate patterns and solar activity on the relationship between vegetation and meteorological drought. The results show that: (1) Droughts were frequent in the YRB from 2001 to 2020, and the summer’s dry and wet conditions exerted a notable influence on the annual climate. (2) SPEI exhibits a more significant correlation with SIF than with NDVI. (3) NDVI has a longer response time (3–6 months) to meteorological drought than SIF (1–4 months). Both SIF and NDVI respond faster in cropland and grassland but slower in evergreen broadleaf and mixed forests. (4) There exists a significant positive correlation between vegetation and meteorological drought during the 4–16 months period. The teleconnection factors of Pacific Decadal Oscillation (PDO), El Niño Southern Oscillation (ENSO), and sunspots are crucial drivers that affect the interaction between meteorological drought and vegetation, with sunspots having the most significant impact. Generally, our study indicates that drought is an essential environmental stressor that disrupts vegetation growth over the YRB. Additionally, SIF demonstrates great potential in monitoring vegetation response to drought. These findings will be meaningful for drought prevention and ecosystem conservation planning in the YRB. |
| first_indexed | 2024-03-11T00:40:49Z |
| format | Article |
| id | doaj.art-34efd5fc5a7c43199bb6f3ca3b49d554 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T00:40:49Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-34efd5fc5a7c43199bb6f3ca3b49d5542023-11-18T21:13:39ZengMDPI AGRemote Sensing2072-42922023-07-011514364110.3390/rs15143641Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed DataXiujuan Dong0Yuke Zhou1Juanzhu Liang2Dan Zou3Jiapei Wu4Jiaojiao Wang5The Academy of Digital China, Fuzhou University, Fuzhou 350002, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Nature Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaThe Academy of Digital China, Fuzhou University, Fuzhou 350002, ChinaSchool of Resource Engineering, Longyan University, Longyan 364012, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Nature Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, ChinaGlobal climate change and human activities have increased the frequency and severity of droughts. This has become a critical factor affecting vegetation growth and diversity, resulting in detrimental effects on agricultural production, ecosystem stability, and socioeconomic development. Therefore, assessing the response of vegetation dynamics to drought can offer valuable insights into the physiological mechanisms of terrestrial ecosystems. Here, we applied long-term datasets (2001–2020) of solar-induced chlorophyll fluorescence (SIF) and normalized difference vegetation index (NDVI) to unveil vegetation dynamics and their relationship to meteorological drought (SPEI) across different vegetation types in the Yangtze River Basin (YRB). Linear correlation analysis was conducted to determine the maximum association of SPEI with SIF and NDVI; we then compared their responses to meteorological drought. The improved partial wavelet coherence (PWC) method was utilized to quantitatively assess the influences of large-scale climate patterns and solar activity on the relationship between vegetation and meteorological drought. The results show that: (1) Droughts were frequent in the YRB from 2001 to 2020, and the summer’s dry and wet conditions exerted a notable influence on the annual climate. (2) SPEI exhibits a more significant correlation with SIF than with NDVI. (3) NDVI has a longer response time (3–6 months) to meteorological drought than SIF (1–4 months). Both SIF and NDVI respond faster in cropland and grassland but slower in evergreen broadleaf and mixed forests. (4) There exists a significant positive correlation between vegetation and meteorological drought during the 4–16 months period. The teleconnection factors of Pacific Decadal Oscillation (PDO), El Niño Southern Oscillation (ENSO), and sunspots are crucial drivers that affect the interaction between meteorological drought and vegetation, with sunspots having the most significant impact. Generally, our study indicates that drought is an essential environmental stressor that disrupts vegetation growth over the YRB. Additionally, SIF demonstrates great potential in monitoring vegetation response to drought. These findings will be meaningful for drought prevention and ecosystem conservation planning in the YRB.https://www.mdpi.com/2072-4292/15/14/3641climate changemeteorological droughtvegetation dynamicsSIFNDVIYangtze River Basin |
| spellingShingle | Xiujuan Dong Yuke Zhou Juanzhu Liang Dan Zou Jiapei Wu Jiaojiao Wang Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data Remote Sensing climate change meteorological drought vegetation dynamics SIF NDVI Yangtze River Basin |
| title | Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data |
| title_full | Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data |
| title_fullStr | Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data |
| title_full_unstemmed | Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data |
| title_short | Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data |
| title_sort | assessment of spatiotemporal patterns and the effect of the relationship between meteorological drought and vegetation dynamics in the yangtze river basin based on remotely sensed data |
| topic | climate change meteorological drought vegetation dynamics SIF NDVI Yangtze River Basin |
| url | https://www.mdpi.com/2072-4292/15/14/3641 |
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