Proximal remote sensing and gross primary productivity in a temperate salt marsh
Salt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy p...
| Autores principales: | , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
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Elsevier
2023
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| Acceso en línea: | https://hdl.handle.net/10568/145216 |
| _version_ | 1855520602908000256 |
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| author | Vázquez-Lule, A. Vargas, R. |
| author_browse | Vargas, R. Vázquez-Lule, A. |
| author_facet | Vázquez-Lule, A. Vargas, R. |
| author_sort | Vázquez-Lule, A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Salt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy phenological phases, GPP rates, and spectral reflectance. We combined multi-annual PRS data (i.e., PhenoCam, discrete hyperspectral measurements, and automated spectral reflectance sensors) with GPP derived from eddy covariance. We tested the performance of empirical models to predict GPP from 12 common vegetation indices (VIs; e.g., NDVI, EVI, PSRI, GCC), Sun-Induced Fluorescence (SIF), and reflectance from different areas of the electromagnetic spectrum (i.e., VIS-IR, RedEdge, IR, and SIF) across the annual cycle and canopy phenological phases (i.e., Greenup, Maturity, Senescence, and Dormancy). Plant Senescence Reflectance Index (PSRI) from hyperspectral data and the Greenness Index (GCC) from PhenoCam, showed the strongest relationship with daily GPP across the annual cycle and within phenological phases (r2=0.30–0.92). Information from the visible-infrared electromagnetic region (VIS-IR) coupled with a partial least square approach (PLSR) showed the highest data-model agreement with GPP, mainly because of its relevance to respond to physiological and structural changes in the canopy, compared with indices (e.g., GCC) that particularly react to changes in the greenness of the canopy. The most relevant electromagnetic regions to model GPP were ∼550 nm and ∼710 nm. Canopy phenological phases impose challenges for modeling GPP with VIs and the PLSR approach, particularly during Maturity, Senescence, and Dormancy. As more eddy covariance sites are established in salt marshes, the application of PRS can be widely tested. Our results highlight the potential to use canopy reflectance from the visible spectrum region for modeling annual GPP in salt marshes as an example of advances within the AmeriFlux network. |
| format | Journal Article |
| id | CGSpace145216 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1452162025-10-26T13:01:55Z Proximal remote sensing and gross primary productivity in a temperate salt marsh Vázquez-Lule, A. Vargas, R. remote sensing carbon sequestration Salt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy phenological phases, GPP rates, and spectral reflectance. We combined multi-annual PRS data (i.e., PhenoCam, discrete hyperspectral measurements, and automated spectral reflectance sensors) with GPP derived from eddy covariance. We tested the performance of empirical models to predict GPP from 12 common vegetation indices (VIs; e.g., NDVI, EVI, PSRI, GCC), Sun-Induced Fluorescence (SIF), and reflectance from different areas of the electromagnetic spectrum (i.e., VIS-IR, RedEdge, IR, and SIF) across the annual cycle and canopy phenological phases (i.e., Greenup, Maturity, Senescence, and Dormancy). Plant Senescence Reflectance Index (PSRI) from hyperspectral data and the Greenness Index (GCC) from PhenoCam, showed the strongest relationship with daily GPP across the annual cycle and within phenological phases (r2=0.30–0.92). Information from the visible-infrared electromagnetic region (VIS-IR) coupled with a partial least square approach (PLSR) showed the highest data-model agreement with GPP, mainly because of its relevance to respond to physiological and structural changes in the canopy, compared with indices (e.g., GCC) that particularly react to changes in the greenness of the canopy. The most relevant electromagnetic regions to model GPP were ∼550 nm and ∼710 nm. Canopy phenological phases impose challenges for modeling GPP with VIs and the PLSR approach, particularly during Maturity, Senescence, and Dormancy. As more eddy covariance sites are established in salt marshes, the application of PRS can be widely tested. Our results highlight the potential to use canopy reflectance from the visible spectrum region for modeling annual GPP in salt marshes as an example of advances within the AmeriFlux network. 2023-10 2024-06-13T05:02:09Z 2024-06-13T05:02:09Z Journal Article https://hdl.handle.net/10568/145216 en Limited Access Elsevier Vázquez-Lule, A. and Vargas, R., 2023. Proximal remote sensing and gross primary productivity in a temperate salt marsh. Agricultural and Forest Meteorology, 341, 109639. https://doi.org/10.1016/j.agrformet.2023.109639 |
| spellingShingle | remote sensing carbon sequestration Vázquez-Lule, A. Vargas, R. Proximal remote sensing and gross primary productivity in a temperate salt marsh |
| title | Proximal remote sensing and gross primary productivity in a temperate salt marsh |
| title_full | Proximal remote sensing and gross primary productivity in a temperate salt marsh |
| title_fullStr | Proximal remote sensing and gross primary productivity in a temperate salt marsh |
| title_full_unstemmed | Proximal remote sensing and gross primary productivity in a temperate salt marsh |
| title_short | Proximal remote sensing and gross primary productivity in a temperate salt marsh |
| title_sort | proximal remote sensing and gross primary productivity in a temperate salt marsh |
| topic | remote sensing carbon sequestration |
| url | https://hdl.handle.net/10568/145216 |
| work_keys_str_mv | AT vazquezlulea proximalremotesensingandgrossprimaryproductivityinatemperatesaltmarsh AT vargasr proximalremotesensingandgrossprimaryproductivityinatemperatesaltmarsh |