Assessing Drought-Induced Tree Mortality in Open Mediterranean Forests Integrating Landsat Time Series, Spectral Unmixing, and UAS Validation.
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| Title: | Assessing Drought-Induced Tree Mortality in Open Mediterranean Forests Integrating Landsat Time Series, Spectral Unmixing, and UAS Validation. |
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| Authors: | Raunak, Alma1,2 (AUTHOR), Huesca, Margarita1,2 (AUTHOR) m.huescamartinez@utwente.nl, Nyktas, Panagiotis1,3 (AUTHOR), Paris, Claudia1 (AUTHOR) |
| Source: | Remote Sensing. Mar2026, Vol. 18 Issue 5, p792. 23p. |
| Subjects: | Tree mortality, Remote sensing, Abiotic stress, Normalized difference vegetation index, Forests & forestry, Drone aircraft, Forest monitoring |
| Geographic Terms: | Crete (Greece), Greece, Southern Europe |
| Abstract: | Highlights: What are the main findings? Spectral Unmixing in LandTrendr effectively detects drought-induced tree loss. Spectral Unmixing has the potential to improve three mortality detection at subpixel level. What is the implication of the main finding? UAS and satellite data integration enables early detection of tree mortality. UAS imagery provides a robust reference for tree mortality assessments. Drought-induced tree mortality is a growing threat to Mediterranean ecosystems, which host high biodiversity but face increasing water stress under climate change. Detecting mortality over large areas with satellite data remains challenging due to open canopies and mixed pixels that obscure vegetation signals. This study evaluates the performance of two widely used vegetation indices—the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI)—alongside a novel application of Spectral Unmixing derived vegetation cover Spectral Unmixing (SU) within the LandTrendr algorithm to track tree mortality in southwest Crete, Greece. High-resolution Unmanned Aerial System (UAS) imagery was used to validate satellite observations, demonstrating strong agreement with field data ( R 2 = 0.95) and confirming its suitability as reference data. LandTrendr applied to NDVI, NDWI, and SU detected major mortality events between 1995 and 2008, with SU identifying the largest affected area. While NDVI and NDWI achieved higher accuracy in distinguishing unaffected plots, SU performed best at detecting mortality. Regression analysis revealed a limited ability of all approaches to quantify mortality magnitude, though SU improved when high-mortality plots were excluded. Overall, NDVI effectively tracked canopy changes, NDWI provided early warnings of drought stress, and SU reduced soil interference to better capture mortality patterns. By integrating satellite time series with UAS validation, this study demonstrates a scalable approach for detecting forest decline and offers actionable insights to guide Mediterranean forest management under increasing drought pressure. [ABSTRACT FROM AUTHOR] |
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| Header | DbId: egs DbLabel: Engineering Source An: 192640049 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Assessing Drought-Induced Tree Mortality in Open Mediterranean Forests Integrating Landsat Time Series, Spectral Unmixing, and UAS Validation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Raunak%2C+Alma%22">Raunak, Alma</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huesca%2C+Margarita%22">Huesca, Margarita</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> m.huescamartinez@utwente.nl</i><br /><searchLink fieldCode="AR" term="%22Nyktas%2C+Panagiotis%22">Nyktas, Panagiotis</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Paris%2C+Claudia%22">Paris, Claudia</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Mar2026, Vol. 18 Issue 5, p792. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Tree+mortality%22">Tree mortality</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Abiotic+stress%22">Abiotic stress</searchLink><br /><searchLink fieldCode="DE" term="%22Normalized+difference+vegetation+index%22">Normalized difference vegetation index</searchLink><br /><searchLink fieldCode="DE" term="%22Forests+%26+forestry%22">Forests & forestry</searchLink><br /><searchLink fieldCode="DE" term="%22Drone+aircraft%22">Drone aircraft</searchLink><br /><searchLink fieldCode="DE" term="%22Forest+monitoring%22">Forest monitoring</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Crete+%28Greece%29%22">Crete (Greece)</searchLink><br /><searchLink fieldCode="DE" term="%22Greece%22">Greece</searchLink><br /><searchLink fieldCode="DE" term="%22Southern+Europe%22">Southern Europe</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? Spectral Unmixing in LandTrendr effectively detects drought-induced tree loss. Spectral Unmixing has the potential to improve three mortality detection at subpixel level. What is the implication of the main finding? UAS and satellite data integration enables early detection of tree mortality. UAS imagery provides a robust reference for tree mortality assessments. Drought-induced tree mortality is a growing threat to Mediterranean ecosystems, which host high biodiversity but face increasing water stress under climate change. Detecting mortality over large areas with satellite data remains challenging due to open canopies and mixed pixels that obscure vegetation signals. This study evaluates the performance of two widely used vegetation indices—the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI)—alongside a novel application of Spectral Unmixing derived vegetation cover Spectral Unmixing (SU) within the LandTrendr algorithm to track tree mortality in southwest Crete, Greece. High-resolution Unmanned Aerial System (UAS) imagery was used to validate satellite observations, demonstrating strong agreement with field data ( R 2 = 0.95) and confirming its suitability as reference data. LandTrendr applied to NDVI, NDWI, and SU detected major mortality events between 1995 and 2008, with SU identifying the largest affected area. While NDVI and NDWI achieved higher accuracy in distinguishing unaffected plots, SU performed best at detecting mortality. Regression analysis revealed a limited ability of all approaches to quantify mortality magnitude, though SU improved when high-mortality plots were excluded. Overall, NDVI effectively tracked canopy changes, NDWI provided early warnings of drought stress, and SU reduced soil interference to better capture mortality patterns. By integrating satellite time series with UAS validation, this study demonstrates a scalable approach for detecting forest decline and offers actionable insights to guide Mediterranean forest management under increasing drought pressure. [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/rs18050792 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 792 Subjects: – SubjectFull: Tree mortality Type: general – SubjectFull: Remote sensing Type: general – SubjectFull: Abiotic stress Type: general – SubjectFull: Normalized difference vegetation index Type: general – SubjectFull: Forests & forestry Type: general – SubjectFull: Drone aircraft Type: general – SubjectFull: Forest monitoring Type: general – SubjectFull: Crete (Greece) Type: general – SubjectFull: Greece Type: general – SubjectFull: Southern Europe Type: general Titles: – TitleFull: Assessing Drought-Induced Tree Mortality in Open Mediterranean Forests Integrating Landsat Time Series, Spectral Unmixing, and UAS Validation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Raunak, Alma – PersonEntity: Name: NameFull: Huesca, Margarita – PersonEntity: Name: NameFull: Nyktas, Panagiotis – PersonEntity: Name: NameFull: Paris, Claudia IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 5 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
