Global retrieval of GOME-2 sun-induced chlorophyll fluorescence via neural networks trained on mixed-pixel simulations
• A simulation-trained neural network framework retrieved far-red SIF from GOME-2. • Mixed-pixel SCOPE + MODTRAN simulations supported physically informed model training. • Gridded NN-SIF was consistent across two GOME-2 sensors and with TROPOMI.
Authors
- Tianli Wang (ORCID: https://orcid.org/0000-0002-8431-9048)
- Z Y Li (ORCID: https://orcid.org/0009-0005-8068-8574)
- Ruilu Gao
- Jiaqi Lou
- Maofang Gao (ORCID: https://orcid.org/0000-0002-9674-6020)
- Shilei Li
- Chen Yang
- Yadong Yang
- Jianxi Huang
Institutions
- Institute of Agricultural Resources and Regional Planning (CN)
- Southwest Jiaotong University (CN)
Publication Details
- Journal
- International Journal of Applied Earth Observation and Geoinformation
- Published
- 2026-05-29
- DOI
- https://doi.org/10.1016/j.jag.2026.105373
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00