Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production
Gross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll con...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843222001698 |
| _version_ | 1818020005586927616 |
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| author | Shangrong Lin Dalei Hao Yi Zheng Hu Zhang Cong Wang Wenping Yuan |
| author_facet | Shangrong Lin Dalei Hao Yi Zheng Hu Zhang Cong Wang Wenping Yuan |
| author_sort | Shangrong Lin |
| collection | DOAJ |
| description | Gross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll content, is a good proxy of maximum photosynthetic capacity. More importantly, studies show that the red-edge reflectance-related chlorophyll content index (CIr) multiplied by the incident photosynthetic active radiation (PARin) strongly correlates to GPP estimated at carbon flux towers (GPPflux). Yet, to the best of our knowledge, there is no systematic study investigating the general relationship between fine spatial resolution CIr and GPP among biomes and the relationship between CIr and maximum photosynthetic capacity in GPP models. To provide an overview on incorporating space-borne CIr into a GPP model, we applied fine resolution Sentinel-2-derived CIr and GPPflux over 57 flux sites representative of 10 biomes. We investigated the relationship between CIr and GPPflux, and the spatio-temporal relationship between CIr and ecosystem maximum photosynthetic capacity indicated by the potential ecosystem light use efficiency (LUEpot). We also evaluated the relationship between other five vegetation indices (VIs) and GPPflux. Results showed that the CIr multiplied by PARin has a higher agreement (R2 > 0.5) with GPP than other VIs. A universal relationship exists between the CIr multiplied by PARin and GPP, except for forest biomes. The CIr also strongly (R2 > 0.5) relates to the LUEpot during the peak of the growing season. The CIr has a low spatial variance (CV = 0.25) among biomes, highlighting that CIr can be a proxy of maximum photosynthetic capacity in GPP models that do not require biome-dependent coefficients. This study provides insight for incorporating CIr into GPP models and better quantifying global terrestrial photosynthesis. |
| first_indexed | 2024-04-14T07:59:25Z |
| format | Article |
| id | doaj.art-5edad9e8fe96495a9f0778d66b505117 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-14T07:59:25Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-5edad9e8fe96495a9f0778d66b5051172022-12-22T02:04:56ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322022-09-01113102978Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary productionShangrong Lin0Dalei Hao1Yi Zheng2Hu Zhang3Cong Wang4Wenping Yuan5School of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, China; Corresponding author.Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USASchool of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, ChinaState Key Laboratory of Remote Sensing Science, Jointly Sponsored by Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing Normal University, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, ChinaKey Laboratory for Geographical Process Analysis & Simulation of Hubei Province/School of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, ChinaSchool of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, Guangdong, ChinaGross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll content, is a good proxy of maximum photosynthetic capacity. More importantly, studies show that the red-edge reflectance-related chlorophyll content index (CIr) multiplied by the incident photosynthetic active radiation (PARin) strongly correlates to GPP estimated at carbon flux towers (GPPflux). Yet, to the best of our knowledge, there is no systematic study investigating the general relationship between fine spatial resolution CIr and GPP among biomes and the relationship between CIr and maximum photosynthetic capacity in GPP models. To provide an overview on incorporating space-borne CIr into a GPP model, we applied fine resolution Sentinel-2-derived CIr and GPPflux over 57 flux sites representative of 10 biomes. We investigated the relationship between CIr and GPPflux, and the spatio-temporal relationship between CIr and ecosystem maximum photosynthetic capacity indicated by the potential ecosystem light use efficiency (LUEpot). We also evaluated the relationship between other five vegetation indices (VIs) and GPPflux. Results showed that the CIr multiplied by PARin has a higher agreement (R2 > 0.5) with GPP than other VIs. A universal relationship exists between the CIr multiplied by PARin and GPP, except for forest biomes. The CIr also strongly (R2 > 0.5) relates to the LUEpot during the peak of the growing season. The CIr has a low spatial variance (CV = 0.25) among biomes, highlighting that CIr can be a proxy of maximum photosynthetic capacity in GPP models that do not require biome-dependent coefficients. This study provides insight for incorporating CIr into GPP models and better quantifying global terrestrial photosynthesis.http://www.sciencedirect.com/science/article/pii/S1569843222001698Red-edge reflectanceCIrSentinel-2 MSIGPPPlant photosynthetic capacityAmeriFlux |
| spellingShingle | Shangrong Lin Dalei Hao Yi Zheng Hu Zhang Cong Wang Wenping Yuan Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production International Journal of Applied Earth Observations and Geoinformation Red-edge reflectance CIr Sentinel-2 MSI GPP Plant photosynthetic capacity AmeriFlux |
| title | Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production |
| title_full | Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production |
| title_fullStr | Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production |
| title_full_unstemmed | Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production |
| title_short | Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production |
| title_sort | multi site assessment of the potential of fine resolution red edge vegetation indices for estimating gross primary production |
| topic | Red-edge reflectance CIr Sentinel-2 MSI GPP Plant photosynthetic capacity AmeriFlux |
| url | http://www.sciencedirect.com/science/article/pii/S1569843222001698 |
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