Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series
Capturing forest disturbances over time is increasingly important to determine the ecosystem's capacity to recover as well as aiding a timely response of foresters. With changes due to climate change increasing the frequencies, a better understanding of forest disturbances and their role in his...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2022.863116/full |
| _version_ | 1818231260877684736 |
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| author | Anne Gnilke Anne Gnilke Tanja G. M. Sanders Tanja G. M. Sanders |
| author_facet | Anne Gnilke Anne Gnilke Tanja G. M. Sanders Tanja G. M. Sanders |
| author_sort | Anne Gnilke |
| collection | DOAJ |
| description | Capturing forest disturbances over time is increasingly important to determine the ecosystem's capacity to recover as well as aiding a timely response of foresters. With changes due to climate change increasing the frequencies, a better understanding of forest disturbances and their role in historical development is needed to, on the one hand, develop forest management approaches promoting ecosystem resilience and, on the other hand, provide quick and spatially explicit information to foresters. A large, publicly available satellite imagery spanning more than two decades for large areas of the Earth's surface at varying spatial and temporal resolutions represents a vast, free data source for this. The challenge is 2-fold: (1) obtaining reliable information on forest condition and development from satellite data requires not only quantification of forest loss but rather a differentiated assessment of the extent and severity of forest degradation; (2) standardized and efficient processing routines both are needed to bridge the gap between remote-sensing signals and conventional forest condition parameters to enable forest managers for the operational use of the data. Here, we investigated abiotic and biotic disturbances based on a set of ground validated occurrences in various forest areas across Germany to build disturbance response chronologies and examine event-specific patterns. The proposed workflow is based on the R-package “npphen” for non-parametric vegetation phenology reconstruction and anomaly detection using MODIS EVI time series data. Results show the potential to detect distinct disturbance responses in forest ecosystems and reveal event-specific characteristics. Difficulties still exist for the determination of, e.g., scattered wind throw, due to its subpixel resolution, especially in highly fragmented landscapes and small forest patches. However, the demonstrated method shows potential for operational use as a semi-automatic system to augment terrestrial monitoring in the forestry sector. Combining the more robust EVI and the assessment of the phenological series at a pixel-by-pixel level allows for a changing species cover without false classification as forest loss. |
| first_indexed | 2024-12-12T10:47:34Z |
| format | Article |
| id | doaj.art-cc2dae44e2804a6f8a4bb96d4ef2cafd |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-12-12T10:47:34Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-cc2dae44e2804a6f8a4bb96d4ef2cafd2022-12-22T00:26:51ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2022-05-011310.3389/fpls.2022.863116863116Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly SeriesAnne Gnilke0Anne Gnilke1Tanja G. M. Sanders2Tanja G. M. Sanders3Department of Forest Ecology and Biodiversity, Thünen Institute of Forest Ecosystems, Eberswalde, GermanyDepartment of Disturbance Ecology and Vegetation Dynamics, University of Bayreuth, Bayreuth, GermanyDepartment of Forest Ecology and Biodiversity, Thünen Institute of Forest Ecosystems, Eberswalde, GermanyDepartment of Disturbance Ecology and Vegetation Dynamics, University of Bayreuth, Bayreuth, GermanyCapturing forest disturbances over time is increasingly important to determine the ecosystem's capacity to recover as well as aiding a timely response of foresters. With changes due to climate change increasing the frequencies, a better understanding of forest disturbances and their role in historical development is needed to, on the one hand, develop forest management approaches promoting ecosystem resilience and, on the other hand, provide quick and spatially explicit information to foresters. A large, publicly available satellite imagery spanning more than two decades for large areas of the Earth's surface at varying spatial and temporal resolutions represents a vast, free data source for this. The challenge is 2-fold: (1) obtaining reliable information on forest condition and development from satellite data requires not only quantification of forest loss but rather a differentiated assessment of the extent and severity of forest degradation; (2) standardized and efficient processing routines both are needed to bridge the gap between remote-sensing signals and conventional forest condition parameters to enable forest managers for the operational use of the data. Here, we investigated abiotic and biotic disturbances based on a set of ground validated occurrences in various forest areas across Germany to build disturbance response chronologies and examine event-specific patterns. The proposed workflow is based on the R-package “npphen” for non-parametric vegetation phenology reconstruction and anomaly detection using MODIS EVI time series data. Results show the potential to detect distinct disturbance responses in forest ecosystems and reveal event-specific characteristics. Difficulties still exist for the determination of, e.g., scattered wind throw, due to its subpixel resolution, especially in highly fragmented landscapes and small forest patches. However, the demonstrated method shows potential for operational use as a semi-automatic system to augment terrestrial monitoring in the forestry sector. Combining the more robust EVI and the assessment of the phenological series at a pixel-by-pixel level allows for a changing species cover without false classification as forest loss.https://www.frontiersin.org/articles/10.3389/fpls.2022.863116/fullforest disturbanceMODISground-truthingEVI anomalyphenological series |
| spellingShingle | Anne Gnilke Anne Gnilke Tanja G. M. Sanders Tanja G. M. Sanders Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series Frontiers in Plant Science forest disturbance MODIS ground-truthing EVI anomaly phenological series |
| title | Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series |
| title_full | Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series |
| title_fullStr | Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series |
| title_full_unstemmed | Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series |
| title_short | Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series |
| title_sort | distinguishing abrupt and gradual forest disturbances with modis based phenological anomaly series |
| topic | forest disturbance MODIS ground-truthing EVI anomaly phenological series |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2022.863116/full |
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