Multiple Vegetation Indicators Reveal Contrasting Post-Drought Recovery Time in the Yangtze River Basin Following the 2022 Extreme Drought.
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| Title: | Multiple Vegetation Indicators Reveal Contrasting Post-Drought Recovery Time in the Yangtze River Basin Following the 2022 Extreme Drought. |
|---|---|
| Authors: | Ma, Qingqing1,2 (AUTHOR), Chen, Lajiao1,2 (AUTHOR) chenlj@aircas.ac.cn, Li, Jiepeng1,2 (AUTHOR), Liu, Peng1,2 (AUTHOR) |
| Source: | Remote Sensing. Aug2026, Vol. 18 Issue 16, p2824. 27p. |
| Subjects: | Leaf area index, Normalized difference vegetation index, Restoration ecology, Plant communities, Remote sensing, Primary productivity (Biology) |
| Geographic Terms: | Yangtze River (China) |
| Abstract: | Highlights: What are the main findings? This study analyzes vegetation recovery after the extreme drought event across the Yangtze River Basin in 2022. Vegetation recovery timing exhibits distinct differences among multiple remote-sensing indicators. Recovery timing varies substantially across different vegetation types. LAI shows the shortest recovery time, whereas GPP presents the longest recovery period. Forest and grassland achieve faster recovery, while cropland and shrubland exhibit relatively slow recovery. What are the implications of the main findings? Multi-indicator comparisons are essential for comprehensively assessing post-drought vegetation resilience. Vegetation-type-dependent recovery differences provide references for ecological restoration under drought disturbance. Extreme drought events have become increasingly frequent under ongoing climatic change, thereby constraining vegetation growth and altering ecosystem processes. Vegetation recovery time following drought plays a crucial role in ecosystem stability, and extensive studies have been conducted to quantify vegetation recovery. However, most studies estimate vegetation recovery time using a single vegetation index, which does not adequately reflect how vegetation responds to drought conditions, since different vegetation indicators reflect different facets of vegetation dynamics. In this study, multiple vegetation indicators, including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), Gross Primary Productivity (GPP), and Solar-Induced Chlorophyll Fluorescence (SIF), were applied to investigate post-drought vegetation recovery in the Yangtze River Basin (YRB). The findings reveal that: (1) most vegetation recovered within four months after drought, with one-month recovery being the most prevalent, followed by four-month recovery; (2) the average recovery times derived from EVI, LAI, NDVI, GPP, and SIF were 2.23, 1.62, 2.45, 2.79, and 2.00 months respectively; (3) forests exhibited the fastest recovery rates, whereas shrublands recovered the slowest. This study assesses post-drought vegetation status via the recovery duration, offers theoretical basis for water resource allocation optimization, and provides important reference for coping with future ecological risks. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 196630504 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Multiple Vegetation Indicators Reveal Contrasting Post-Drought Recovery Time in the Yangtze River Basin Following the 2022 Extreme Drought. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ma%2C+Qingqing%22">Ma, Qingqing</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Lajiao%22">Chen, Lajiao</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> chenlj@aircas.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Jiepeng%22">Li, Jiepeng</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Peng%22">Liu, Peng</searchLink><relatesTo>1,2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Aug2026, Vol. 18 Issue 16, p2824. 27p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Leaf+area+index%22">Leaf area index</searchLink><br /><searchLink fieldCode="DE" term="%22Normalized+difference+vegetation+index%22">Normalized difference vegetation index</searchLink><br /><searchLink fieldCode="DE" term="%22Restoration+ecology%22">Restoration ecology</searchLink><br /><searchLink fieldCode="DE" term="%22Plant+communities%22">Plant communities</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Primary+productivity+%28Biology%29%22">Primary productivity (Biology)</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Yangtze+River+%28China%29%22">Yangtze River (China)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? This study analyzes vegetation recovery after the extreme drought event across the Yangtze River Basin in 2022. Vegetation recovery timing exhibits distinct differences among multiple remote-sensing indicators. Recovery timing varies substantially across different vegetation types. LAI shows the shortest recovery time, whereas GPP presents the longest recovery period. Forest and grassland achieve faster recovery, while cropland and shrubland exhibit relatively slow recovery. What are the implications of the main findings? Multi-indicator comparisons are essential for comprehensively assessing post-drought vegetation resilience. Vegetation-type-dependent recovery differences provide references for ecological restoration under drought disturbance. Extreme drought events have become increasingly frequent under ongoing climatic change, thereby constraining vegetation growth and altering ecosystem processes. Vegetation recovery time following drought plays a crucial role in ecosystem stability, and extensive studies have been conducted to quantify vegetation recovery. However, most studies estimate vegetation recovery time using a single vegetation index, which does not adequately reflect how vegetation responds to drought conditions, since different vegetation indicators reflect different facets of vegetation dynamics. In this study, multiple vegetation indicators, including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), Gross Primary Productivity (GPP), and Solar-Induced Chlorophyll Fluorescence (SIF), were applied to investigate post-drought vegetation recovery in the Yangtze River Basin (YRB). The findings reveal that: (1) most vegetation recovered within four months after drought, with one-month recovery being the most prevalent, followed by four-month recovery; (2) the average recovery times derived from EVI, LAI, NDVI, GPP, and SIF were 2.23, 1.62, 2.45, 2.79, and 2.00 months respectively; (3) forests exhibited the fastest recovery rates, whereas shrublands recovered the slowest. This study assesses post-drought vegetation status via the recovery duration, offers theoretical basis for water resource allocation optimization, and provides important reference for coping with future ecological risks. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18162824 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 27 StartPage: 2824 Subjects: – SubjectFull: Leaf area index Type: general – SubjectFull: Normalized difference vegetation index Type: general – SubjectFull: Restoration ecology Type: general – SubjectFull: Plant communities Type: general – SubjectFull: Remote sensing Type: general – SubjectFull: Primary productivity (Biology) Type: general – SubjectFull: Yangtze River (China) Type: general Titles: – TitleFull: Multiple Vegetation Indicators Reveal Contrasting Post-Drought Recovery Time in the Yangtze River Basin Following the 2022 Extreme Drought. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ma, Qingqing – PersonEntity: Name: NameFull: Chen, Lajiao – PersonEntity: Name: NameFull: Li, Jiepeng – PersonEntity: Name: NameFull: Liu, Peng IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 08 Text: Aug2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 16 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
