Growth unveiled: decoding the start of grassland seasons in Austria
The start of the growing season (SOS) in grasslands is a critical factor that significantly affects grassland dynamics, production and quality. In the context of grassland fodder production, the exact detection of the start of the growing season allows farmers and land managers to precisely plan har...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | European Journal of Remote Sensing |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/22797254.2024.2323633 |
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| author | Aleksandar Dujakovic Andreas Schaumberger Andreas Klingler Konrad Mayer Clement Atzberger Anja Klisch Francesco Vuolo |
| author_facet | Aleksandar Dujakovic Andreas Schaumberger Andreas Klingler Konrad Mayer Clement Atzberger Anja Klisch Francesco Vuolo |
| author_sort | Aleksandar Dujakovic |
| collection | DOAJ |
| description | The start of the growing season (SOS) in grasslands is a critical factor that significantly affects grassland dynamics, production and quality. In the context of grassland fodder production, the exact detection of the start of the growing season allows farmers and land managers to precisely plan harvest schedules for hay production or silage making. However, the NDVI time-series based detection of the SOS for grassland poses challenges due to the gradual onset of greenness and the wide variety of environmental conditions. These challenges emphasize the need for novel approaches to improve satellite-based SOS detection accuracy. This study establishes a new methodology for identifying the SOS specifically tailored to grassland regions in Austria. To accomplish this, a synergistic approach combining remote sensing (MODIS NDVI at 250 m) and weather data analysis was adopted. Results indicate that the integrated approach outperforms alternative methods in estimating SOS. The study demonstrated a more robust and accurate estimates of SOS that were generally consistent with the phenological observations of a reference species (Forsythia suspensa) and in agreement with the observed SOS dates based on visual interpretation of 10 m resolution Sentinel-2 images. For future studies, the integration of additional validation techniques is crucial. |
| format | Article |
| id | doaj-art-d3539935fe7b4f1b96a2d34fb22fa105 |
| institution | OA Journals |
| issn | 2279-7254 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | European Journal of Remote Sensing |
| spelling | doaj-art-d3539935fe7b4f1b96a2d34fb22fa1052025-08-20T01:58:55ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542024-12-0157110.1080/22797254.2024.2323633Growth unveiled: decoding the start of grassland seasons in AustriaAleksandar Dujakovic0Andreas Schaumberger1Andreas Klingler2Konrad Mayer3Clement Atzberger4Anja Klisch5Francesco Vuolo6Institute of Geomatics, University of Natural Resources and Life Sciences Vienna, Vienna, AustriaDepartment of Geo-Information, Agricultural Research and Education Center (AREC), Irdning, Donnersbachtal, AustriaDepartment of Geo-Information, Agricultural Research and Education Center (AREC), Irdning, Donnersbachtal, AustriaClimate Research Department, GeoSphere Austria, Vienna, AustriaInstitute of Geomatics, University of Natural Resources and Life Sciences Vienna, Vienna, AustriaInstitute of Geomatics, University of Natural Resources and Life Sciences Vienna, Vienna, AustriaInstitute of Geomatics, University of Natural Resources and Life Sciences Vienna, Vienna, AustriaThe start of the growing season (SOS) in grasslands is a critical factor that significantly affects grassland dynamics, production and quality. In the context of grassland fodder production, the exact detection of the start of the growing season allows farmers and land managers to precisely plan harvest schedules for hay production or silage making. However, the NDVI time-series based detection of the SOS for grassland poses challenges due to the gradual onset of greenness and the wide variety of environmental conditions. These challenges emphasize the need for novel approaches to improve satellite-based SOS detection accuracy. This study establishes a new methodology for identifying the SOS specifically tailored to grassland regions in Austria. To accomplish this, a synergistic approach combining remote sensing (MODIS NDVI at 250 m) and weather data analysis was adopted. Results indicate that the integrated approach outperforms alternative methods in estimating SOS. The study demonstrated a more robust and accurate estimates of SOS that were generally consistent with the phenological observations of a reference species (Forsythia suspensa) and in agreement with the observed SOS dates based on visual interpretation of 10 m resolution Sentinel-2 images. For future studies, the integration of additional validation techniques is crucial.https://www.tandfonline.com/doi/10.1080/22797254.2024.2323633Start of growing season (SOS)NDVI time seriesMODISair temperature thresholdsgrassland management |
| spellingShingle | Aleksandar Dujakovic Andreas Schaumberger Andreas Klingler Konrad Mayer Clement Atzberger Anja Klisch Francesco Vuolo Growth unveiled: decoding the start of grassland seasons in Austria European Journal of Remote Sensing Start of growing season (SOS) NDVI time series MODIS air temperature thresholds grassland management |
| title | Growth unveiled: decoding the start of grassland seasons in Austria |
| title_full | Growth unveiled: decoding the start of grassland seasons in Austria |
| title_fullStr | Growth unveiled: decoding the start of grassland seasons in Austria |
| title_full_unstemmed | Growth unveiled: decoding the start of grassland seasons in Austria |
| title_short | Growth unveiled: decoding the start of grassland seasons in Austria |
| title_sort | growth unveiled decoding the start of grassland seasons in austria |
| topic | Start of growing season (SOS) NDVI time series MODIS air temperature thresholds grassland management |
| url | https://www.tandfonline.com/doi/10.1080/22797254.2024.2323633 |
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