Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect
Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using sate...
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| Format: | Article |
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MDPI AG
2022-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/13/2985 |
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| author | Song Leng Alfredo Huete Jamie Cleverly Qiang Yu Rongrong Zhang Qianfeng Wang |
| author_facet | Song Leng Alfredo Huete Jamie Cleverly Qiang Yu Rongrong Zhang Qianfeng Wang |
| author_sort | Song Leng |
| collection | DOAJ |
| description | Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018–2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI <i>r</i><sup>2</sup>: 0.47~0.86, SIF <i>r</i><sup>2</sup>: 0.47~0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25~40% of the variability of the effective fluorescence yield (SIF<sub>yield</sub>) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8~60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology. |
| first_indexed | 2024-03-09T12:37:34Z |
| format | Article |
| id | doaj.art-15923d9e6a824e0a897289fd627c3969 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T12:37:34Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-15923d9e6a824e0a897289fd627c39692023-11-30T22:22:26ZengMDPI AGRemote Sensing2072-42922022-06-011413298510.3390/rs14132985Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical TransectSong Leng0Alfredo Huete1Jamie Cleverly2Qiang Yu3Rongrong Zhang4Qianfeng Wang5Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environment & Safety Engineering, Fuzhou University, Fuzhou 350116, ChinaFaculty of Science, University of Technology Sydney, Ultimo, NSW 2007, AustraliaCollege of Science and Engineering, James Cook University, Cairns, QLD 4878, AustraliaState Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Xianyang 712100, ChinaFujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environment & Safety Engineering, Fuzhou University, Fuzhou 350116, ChinaFujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environment & Safety Engineering, Fuzhou University, Fuzhou 350116, ChinaAccurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018–2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI <i>r</i><sup>2</sup>: 0.47~0.86, SIF <i>r</i><sup>2</sup>: 0.47~0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25~40% of the variability of the effective fluorescence yield (SIF<sub>yield</sub>) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8~60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology.https://www.mdpi.com/2072-4292/14/13/2985SIFEVIphenologyNATT |
| spellingShingle | Song Leng Alfredo Huete Jamie Cleverly Qiang Yu Rongrong Zhang Qianfeng Wang Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect Remote Sensing SIF EVI phenology NATT |
| title | Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect |
| title_full | Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect |
| title_fullStr | Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect |
| title_full_unstemmed | Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect |
| title_short | Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect |
| title_sort | spatiotemporal variations of dryland vegetation phenology revealed by satellite observed fluorescence and greenness across the north australian tropical transect |
| topic | SIF EVI phenology NATT |
| url | https://www.mdpi.com/2072-4292/14/13/2985 |
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