Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India
Significant uncertainties in terrestrial carbon fluxes exist in regions with limited ground-based observations, impacting our understanding of ecosystem carbon dynamics and emission reduction needs. This is particularly true for areas with sparse measurement networks, like India. To address this, we...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | Environmental Research: Ecology |
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| Online Access: | https://doi.org/10.1088/2752-664X/adabed |
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| author | Aparnna Ravi Dhanyalekshmi Pillai Christoph Gerbig Stephen Sitch Sönke Zaehle Vishnu Thilakan Chandra Sekhar Jha Thara Anna Mathew |
| author_facet | Aparnna Ravi Dhanyalekshmi Pillai Christoph Gerbig Stephen Sitch Sönke Zaehle Vishnu Thilakan Chandra Sekhar Jha Thara Anna Mathew |
| author_sort | Aparnna Ravi |
| collection | DOAJ |
| description | Significant uncertainties in terrestrial carbon fluxes exist in regions with limited ground-based observations, impacting our understanding of ecosystem carbon dynamics and emission reduction needs. This is particularly true for areas with sparse measurement networks, like India. To address this, we explore the potential of satellite measurements from various missions such as Sentinel-5 Precursor and the Orbiting Carbon Observatory-2 to improve terrestrial biosphere CO _2 fluxes of India. We follow a data-driven approach, which simulates spatial and temporal distributions of gross primary productivity (GPP), net ecosystem exchange (NEE), and ecosystem respiration (R _eco ). We improve these model predictions by additionally using satellite-based solar-induced chlorophyll fluorescence (SIF), soil temperature , and soil moisture specific to the vegetation classes of the domain. Different model refinements were performed to present the improved hourly distributions of terrestrial biospheric CO _2 fluxes on a $0.1^{\circ}\times0.1^{\circ}$ grid from 2012 to 2020. Among them, the best-performing model simulations show reasonable agreement with eddy covariance observations for 2012–2018. For example, our best NEE and GPP predictions are highly correlated with observations with squared correlation coefficient ( R ^2 ) values of 0.68 (NEE) and 0.74 (GPP) at the monthly scale for 2018. Based on our improved estimations, the annual NEE and GPP show values within the range from −0.38 Pg C yr ^−1 to −0.53 Pg C yr ^−1 (land C sink) and 3.39 Pg C yr ^−1 to 3.88 Pg C yr ^−1 , respectively over India for 2012–2020. Our novel approach and findings highlight the potential of satellite-based SIF measurements to detail the ecosystem-scale vegetation responses across various biomes in India. The use of satellite observations, as demonstrated in this study, offers a scalable solution for regions lacking sufficient ground-based observations to estimate biospheric carbon fluxes reliably. |
| format | Article |
| id | doaj-art-88aa825c90d8439e9b766846ad52ab72 |
| institution | Kabale University |
| issn | 2752-664X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research: Ecology |
| spelling | doaj-art-88aa825c90d8439e9b766846ad52ab722025-01-29T13:01:50ZengIOP PublishingEnvironmental Research: Ecology2752-664X2025-01-014101500410.1088/2752-664X/adabedUsing satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of IndiaAparnna Ravi0https://orcid.org/0009-0007-2214-8427Dhanyalekshmi Pillai1https://orcid.org/0000-0002-8934-2140Christoph Gerbig2Stephen Sitch3Sönke Zaehle4Vishnu Thilakan5Chandra Sekhar Jha6Thara Anna Mathew7Indian Institute of Science Education and Research Bhopal (IISERB) , Bhopal, India; Max Planck Partner Group at IISERB , Bhopal, IndiaIndian Institute of Science Education and Research Bhopal (IISERB) , Bhopal, India; Max Planck Partner Group at IISERB , Bhopal, IndiaMax-Planck Institute of Biogeochemistry , Jena, GermanyUniversity of Exeter , Exeter EX4 4QF, United KingdomMax-Planck Institute of Biogeochemistry , Jena, GermanyIndian Institute of Science Education and Research Bhopal (IISERB) , Bhopal, India; Max Planck Partner Group at IISERB , Bhopal, IndiaNational Remote Sensing Centre (ISRO) , Balanagar, Hyderabad, IndiaIndian Institute of Science Education and Research Bhopal (IISERB) , Bhopal, India; Max Planck Partner Group at IISERB , Bhopal, IndiaSignificant uncertainties in terrestrial carbon fluxes exist in regions with limited ground-based observations, impacting our understanding of ecosystem carbon dynamics and emission reduction needs. This is particularly true for areas with sparse measurement networks, like India. To address this, we explore the potential of satellite measurements from various missions such as Sentinel-5 Precursor and the Orbiting Carbon Observatory-2 to improve terrestrial biosphere CO _2 fluxes of India. We follow a data-driven approach, which simulates spatial and temporal distributions of gross primary productivity (GPP), net ecosystem exchange (NEE), and ecosystem respiration (R _eco ). We improve these model predictions by additionally using satellite-based solar-induced chlorophyll fluorescence (SIF), soil temperature , and soil moisture specific to the vegetation classes of the domain. Different model refinements were performed to present the improved hourly distributions of terrestrial biospheric CO _2 fluxes on a $0.1^{\circ}\times0.1^{\circ}$ grid from 2012 to 2020. Among them, the best-performing model simulations show reasonable agreement with eddy covariance observations for 2012–2018. For example, our best NEE and GPP predictions are highly correlated with observations with squared correlation coefficient ( R ^2 ) values of 0.68 (NEE) and 0.74 (GPP) at the monthly scale for 2018. Based on our improved estimations, the annual NEE and GPP show values within the range from −0.38 Pg C yr ^−1 to −0.53 Pg C yr ^−1 (land C sink) and 3.39 Pg C yr ^−1 to 3.88 Pg C yr ^−1 , respectively over India for 2012–2020. Our novel approach and findings highlight the potential of satellite-based SIF measurements to detail the ecosystem-scale vegetation responses across various biomes in India. The use of satellite observations, as demonstrated in this study, offers a scalable solution for regions lacking sufficient ground-based observations to estimate biospheric carbon fluxes reliably.https://doi.org/10.1088/2752-664X/adabednet ecosystem exchangeVPRMSIFMODISeddy covarianceTROPOMI |
| spellingShingle | Aparnna Ravi Dhanyalekshmi Pillai Christoph Gerbig Stephen Sitch Sönke Zaehle Vishnu Thilakan Chandra Sekhar Jha Thara Anna Mathew Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India Environmental Research: Ecology net ecosystem exchange VPRM SIF MODIS eddy covariance TROPOMI |
| title | Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India |
| title_full | Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India |
| title_fullStr | Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India |
| title_full_unstemmed | Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India |
| title_short | Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India |
| title_sort | using satellite based sun induced chlorophyll fluorescence and spectral reflectance for improving terrestrial co2 flux estimates of india |
| topic | net ecosystem exchange VPRM SIF MODIS eddy covariance TROPOMI |
| url | https://doi.org/10.1088/2752-664X/adabed |
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