Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands
Vegetation phenology is an important indicator of climate change and ecosystem productivity. However, the monitoring of vegetation generative phenology through remote sensing techniques does not allow for species-specific retrieval in mixed ecosystems; hence, land surface phenology (LSP) is used ins...
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MDPI AG
2024-12-01
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| author | Michal Antala Anshu Rastogi Marcin Stróżecki Mar Albert-Saiz Subhajit Bandopadhyay Radosław Juszczak |
| author_facet | Michal Antala Anshu Rastogi Marcin Stróżecki Mar Albert-Saiz Subhajit Bandopadhyay Radosław Juszczak |
| author_sort | Michal Antala |
| collection | DOAJ |
| description | Vegetation phenology is an important indicator of climate change and ecosystem productivity. However, the monitoring of vegetation generative phenology through remote sensing techniques does not allow for species-specific retrieval in mixed ecosystems; hence, land surface phenology (LSP) is used instead of traditional plant phenology based on plant organ emergence and development observations. Despite the estimated timing of the LSP parameters being dependent on the vegetation index (VI) used, inadequate attention was paid to the evaluation of the commonly used VIs for LSP of different vegetation covers. We used two years of data from the experimental site in central European peatland, where plots of two peatland vegetation communities are under a climate manipulation experiment. We assessed the accuracy of LSP retrieval by simple remote sensing metrics against LSP derived from gross primary production and canopy chlorophyll content time series. The product of Near-Infrared Reflectance of Vegetation and Photosynthetically Active Radiation (NIRvP) and Green Chromatic Coordinates (GCC) was identified as the best-performing remote sensing metrics for peatland physiological and structural phenology, respectively. Our results suggest that the changes in the physiological phenology due to increased temperature are more prominent than the changes in the structural phenology. This may mean that despite a rather accurate assessment of the structural LSP of peatland by remote sensing, the changes in the functioning of the ecosystem can be underestimated by simple VIs. This ground-based phenological study on peatlands provides the base for more accurate monitoring of interannual variation of carbon sink strength through remote sensing. |
| format | Article |
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| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-12-01 |
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| series | Remote Sensing |
| spelling | doaj-art-c73775119d3e42ed9c24f40727cbceaa2025-01-10T13:20:00ZengMDPI AGRemote Sensing2072-42922024-12-011713210.3390/rs17010032Evaluating Remote Sensing Metrics for Land Surface Phenology in PeatlandsMichal Antala0Anshu Rastogi1Marcin Stróżecki2Mar Albert-Saiz3Subhajit Bandopadhyay4Radosław Juszczak5Laboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Piątkowska 94, 60-649 Poznań, PolandLaboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Piątkowska 94, 60-649 Poznań, PolandLaboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Piątkowska 94, 60-649 Poznań, PolandLaboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Piątkowska 94, 60-649 Poznań, PolandLaboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Piątkowska 94, 60-649 Poznań, PolandLaboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Piątkowska 94, 60-649 Poznań, PolandVegetation phenology is an important indicator of climate change and ecosystem productivity. However, the monitoring of vegetation generative phenology through remote sensing techniques does not allow for species-specific retrieval in mixed ecosystems; hence, land surface phenology (LSP) is used instead of traditional plant phenology based on plant organ emergence and development observations. Despite the estimated timing of the LSP parameters being dependent on the vegetation index (VI) used, inadequate attention was paid to the evaluation of the commonly used VIs for LSP of different vegetation covers. We used two years of data from the experimental site in central European peatland, where plots of two peatland vegetation communities are under a climate manipulation experiment. We assessed the accuracy of LSP retrieval by simple remote sensing metrics against LSP derived from gross primary production and canopy chlorophyll content time series. The product of Near-Infrared Reflectance of Vegetation and Photosynthetically Active Radiation (NIRvP) and Green Chromatic Coordinates (GCC) was identified as the best-performing remote sensing metrics for peatland physiological and structural phenology, respectively. Our results suggest that the changes in the physiological phenology due to increased temperature are more prominent than the changes in the structural phenology. This may mean that despite a rather accurate assessment of the structural LSP of peatland by remote sensing, the changes in the functioning of the ecosystem can be underestimated by simple VIs. This ground-based phenological study on peatlands provides the base for more accurate monitoring of interannual variation of carbon sink strength through remote sensing.https://www.mdpi.com/2072-4292/17/1/32climate changegross primary productionland surface phenologypeatlandvegetation indices |
| spellingShingle | Michal Antala Anshu Rastogi Marcin Stróżecki Mar Albert-Saiz Subhajit Bandopadhyay Radosław Juszczak Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands Remote Sensing climate change gross primary production land surface phenology peatland vegetation indices |
| title | Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands |
| title_full | Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands |
| title_fullStr | Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands |
| title_full_unstemmed | Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands |
| title_short | Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands |
| title_sort | evaluating remote sensing metrics for land surface phenology in peatlands |
| topic | climate change gross primary production land surface phenology peatland vegetation indices |
| url | https://www.mdpi.com/2072-4292/17/1/32 |
| work_keys_str_mv | AT michalantala evaluatingremotesensingmetricsforlandsurfacephenologyinpeatlands AT anshurastogi evaluatingremotesensingmetricsforlandsurfacephenologyinpeatlands AT marcinstrozecki evaluatingremotesensingmetricsforlandsurfacephenologyinpeatlands AT maralbertsaiz evaluatingremotesensingmetricsforlandsurfacephenologyinpeatlands AT subhajitbandopadhyay evaluatingremotesensingmetricsforlandsurfacephenologyinpeatlands AT radosławjuszczak evaluatingremotesensingmetricsforlandsurfacephenologyinpeatlands |