Analyzing Variability and Trends in NDVI: A Remote-Sensing Approach for Long-Term Monitoring of Urban Green Spaces.
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| Title: | Analyzing Variability and Trends in NDVI: A Remote-Sensing Approach for Long-Term Monitoring of Urban Green Spaces. |
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| Authors: | Kudaya, Franziska Sarah1 (AUTHOR) franziska.kudaya@tugraz.at, König, Albert Wilhelm1 (AUTHOR), Fuchs-Hanusch, Daniela1 (AUTHOR) |
| Source: | Remote Sensing. Aug2026, Vol. 18 Issue 16, p2652. 20p. |
| Subjects: | Normalized difference vegetation index, Vegetation dynamics, Phenology, Climate change adaptation, Remote sensing, Cities & towns, Landsat satellites, Urban plants |
| Geographic Terms: | Birmingham (England), Paris (France), Barcelona (Spain) |
| Abstract: | Highlights: What are the main findings? All four study sites exhibited an increase in vegetation extent over the observation period. Directional changes towards longer growing seasons and shifts in the timing of peak greenness were observed, although the magnitude and statistical significance varied among cities. Smaller, open green spaces showed greater interannual NDVI variability than larger, tree-dominated green spaces. What are the implications of the main findings? Changes in vegetation dynamics may alter the timing and magnitude of irrigation demand, highlighting the need to adapt urban green-space management under changing climatic conditions. Remote sensing technology can support long-term monitoring of urban green spaces for sustainable urban planning and water management. Urban greening is a cornerstone of climate adaptation strategies, yet its long-term sustainability under changing vegetation dynamics remains poorly understood. This study analyzes 40 years of Landsat data (1984–2024) using normalized difference vegetation index (NDVI) time series to quantify changes in vegetation extent, phenology and interannual stability across four European cities (Paris, Graz, Barcelona and Birmingham). The study investigates long-term phenological trends in heterogeneous urban green spaces. Results showed similar developments in greening measures at all four study sites: In Birmingham, Paris and Barcelona, vegetation extent increased by 12 to 23 absolute percentage points, while Graz showed a moderate increase of 4 percentage points. A general tendency towards a longer growing season was observed across the study sites, driven by directional changes towards an earlier Start of Season (SOS) and a delayed End of Season (EOS), although the magnitude and statistical significance varied between cities. Barcelona exhibited pronounced summer NDVI declines, whereas peak vegetation activity occurred earlier in Paris and slightly later in Birmingham. Interannual variation showed greater differences in smaller, fragmented open green spaces (Coefficient of Variation ≈ 0.3) compared to larger tree-dominated parks (Coefficient of Variation ≈ 0.1). These findings provide a harmonized long-term assessment of urban vegetation dynamics. European cities are becoming greener while simultaneously experiencing shifts in vegetation activity and, depending on location, strong declines during summer months. These long-term changes highlight the importance of considering vegetation dynamics when planning resilient urban green spaces under a changing climate. [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: 196630332 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Analyzing Variability and Trends in NDVI: A Remote-Sensing Approach for Long-Term Monitoring of Urban Green Spaces. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kudaya%2C+Franziska+Sarah%22">Kudaya, Franziska Sarah</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> franziska.kudaya@tugraz.at</i><br /><searchLink fieldCode="AR" term="%22König%2C+Albert+Wilhelm%22">König, Albert Wilhelm</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fuchs-Hanusch%2C+Daniela%22">Fuchs-Hanusch, Daniela</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Aug2026, Vol. 18 Issue 16, p2652. 20p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Normalized+difference+vegetation+index%22">Normalized difference vegetation index</searchLink><br /><searchLink fieldCode="DE" term="%22Vegetation+dynamics%22">Vegetation dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Phenology%22">Phenology</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change+adaptation%22">Climate change adaptation</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Cities+%26+towns%22">Cities & towns</searchLink><br /><searchLink fieldCode="DE" term="%22Landsat+satellites%22">Landsat satellites</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+plants%22">Urban plants</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Birmingham+%28England%29%22">Birmingham (England)</searchLink><br /><searchLink fieldCode="DE" term="%22Paris+%28France%29%22">Paris (France)</searchLink><br /><searchLink fieldCode="DE" term="%22Barcelona+%28Spain%29%22">Barcelona (Spain)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? All four study sites exhibited an increase in vegetation extent over the observation period. Directional changes towards longer growing seasons and shifts in the timing of peak greenness were observed, although the magnitude and statistical significance varied among cities. Smaller, open green spaces showed greater interannual NDVI variability than larger, tree-dominated green spaces. What are the implications of the main findings? Changes in vegetation dynamics may alter the timing and magnitude of irrigation demand, highlighting the need to adapt urban green-space management under changing climatic conditions. Remote sensing technology can support long-term monitoring of urban green spaces for sustainable urban planning and water management. Urban greening is a cornerstone of climate adaptation strategies, yet its long-term sustainability under changing vegetation dynamics remains poorly understood. This study analyzes 40 years of Landsat data (1984–2024) using normalized difference vegetation index (NDVI) time series to quantify changes in vegetation extent, phenology and interannual stability across four European cities (Paris, Graz, Barcelona and Birmingham). The study investigates long-term phenological trends in heterogeneous urban green spaces. Results showed similar developments in greening measures at all four study sites: In Birmingham, Paris and Barcelona, vegetation extent increased by 12 to 23 absolute percentage points, while Graz showed a moderate increase of 4 percentage points. A general tendency towards a longer growing season was observed across the study sites, driven by directional changes towards an earlier Start of Season (SOS) and a delayed End of Season (EOS), although the magnitude and statistical significance varied between cities. Barcelona exhibited pronounced summer NDVI declines, whereas peak vegetation activity occurred earlier in Paris and slightly later in Birmingham. Interannual variation showed greater differences in smaller, fragmented open green spaces (Coefficient of Variation ≈ 0.3) compared to larger tree-dominated parks (Coefficient of Variation ≈ 0.1). These findings provide a harmonized long-term assessment of urban vegetation dynamics. European cities are becoming greener while simultaneously experiencing shifts in vegetation activity and, depending on location, strong declines during summer months. These long-term changes highlight the importance of considering vegetation dynamics when planning resilient urban green spaces under a changing climate. [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/rs18162652 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 2652 Subjects: – SubjectFull: Normalized difference vegetation index Type: general – SubjectFull: Vegetation dynamics Type: general – SubjectFull: Phenology Type: general – SubjectFull: Climate change adaptation Type: general – SubjectFull: Remote sensing Type: general – SubjectFull: Cities & towns Type: general – SubjectFull: Landsat satellites Type: general – SubjectFull: Urban plants Type: general – SubjectFull: Birmingham (England) Type: general – SubjectFull: Paris (France) Type: general – SubjectFull: Barcelona (Spain) Type: general Titles: – TitleFull: Analyzing Variability and Trends in NDVI: A Remote-Sensing Approach for Long-Term Monitoring of Urban Green Spaces. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kudaya, Franziska Sarah – PersonEntity: Name: NameFull: König, Albert Wilhelm – PersonEntity: Name: NameFull: Fuchs-Hanusch, Daniela 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 |
