Determining Terrestrial Ecosystem Gross Primary Productivity From PACE OCI
| dc.contributor.author | Huemmrich, Karl | |
| dc.contributor.author | Caplan, Skye | |
| dc.contributor.author | Gamon, John A. | |
| dc.contributor.author | Campbell, Petya Entcheva | |
| dc.date.accessioned | 2026-03-26T14:26:07Z | |
| dc.date.issued | 2025-07-10 | |
| dc.description.abstract | Data from the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Ocean Color Instrument (OCI) were used to develop and test algorithms for remotely retrieving terrestrial ecosystem productivity. Gross primary productivity (GPP) was calculated from CO2 flux for 47 eddy covariance flux towers representing vegetation and climatic variability across the USA. Eight-day average GPP was matched with eight-day average mapped OCI reflectance data containing 49 spectral bands from ultraviolet through short wave infrared spectral regions. The data covered the growing season from March through September 2024. For the combination of all sites and dates, the red-edge chlorophyll index alone described 66% of the variation in GPP. Using a partial least squares regression (PLSR) on all spectral bands GPP retrieval was improved to 74%. Agricultural sites were often found to have high residuals in these regressions. By training PLSR by eco-climatic region, the overall GPP retrievals were improved to 86%. The success of these algorithms across multiple sites with different vegetation types and through the growing season demonstrates the utility of PACE OCI data to map GPP dynamics at continental scales. | |
| dc.description.sponsorship | The authors would like to thank the National Ecological Observatory Network (NEON), a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle. This material is based in part upon work supported by the National Science Foundation through the NEON Program. | |
| dc.description.uri | https://ieeexplore.ieee.org/document/11075694 | |
| dc.format.extent | 5 pages | |
| dc.genre | journal articles | |
| dc.identifier.citation | Huemmrich, Karl Fred, Skye Caplan, John A. Gamon, and Petya Krasteva Entcheva Campbell. “Determining Terrestrial Ecosystem Gross Primary Productivity From PACE OCI.” IEEE Geoscience and Remote Sensing Letters 22 (2025): 1–5. https://doi.org/10.1109/LGRS.2025.3587584. | |
| dc.identifier.uri | https://doi.org/10.1109/LGRS.2025.3587584 | |
| dc.identifier.uri | http://hdl.handle.net/11603/42181 | |
| dc.language.iso | en | |
| dc.publisher | IEEE | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC GESTAR II | |
| dc.relation.ispartof | UMBC Joint Center for Earth Systems Technology (JCET) | |
| dc.relation.ispartof | UMBC Geography and Environmental Systems Department | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | Attribution 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Reflectivity | |
| dc.subject | Neon | |
| dc.subject | Poles and towers | |
| dc.subject | Chlorophyll | |
| dc.subject | Ecosystems | |
| dc.subject | Hyperspectral imaging | |
| dc.subject | Training | |
| dc.subject | Vegetation mapping | |
| dc.subject | remote sensing | |
| dc.subject | productivity | |
| dc.subject | NASA | |
| dc.subject | Productivity | |
| dc.subject | terrestrial ecosystems | |
| dc.subject | Indexes | |
| dc.title | Determining Terrestrial Ecosystem Gross Primary Productivity From PACE OCI | |
| dc.type | Text | |
| dcterms.creator | https://orcid.org/0000-0003-4148-9108 | |
| dcterms.creator | https://orcid.org/0000-0002-0505-4951 |
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