Spatial statistical prediction of solar-induced chlorophyll fluorescence (SIF) from multivariate OCO-2 data
-
Updated
Oct 16, 2023 - Jupyter Notebook
#
oco-2
Here are 6 public repositories matching this topic...
A Dual-Transformer Network for Spatiotemporal Modeling of Carbon Dioxide Column Concentration (XCO2) Based on Dynamic Heterogeneous Graphs
-
Updated
Apr 8, 2026 - Python
Tool to gather and manage publication citations related to OCO-2 and OCO-3
-
Updated
Feb 5, 2026 - HTML
Python based Jupyter notebook for reconstruction of XCO₂ using a Transformer-based model for emission monitoring, integrating OCO-2 data with land-atmosphere variables to provide environmental context.
-
Updated
Apr 6, 2026 - Python
Winter wheat NDVI and NIRv for all 96 Bavarian districts, March-June 2017-2024, from 1.13 TB of DLR Sentinel-2 monthly composites masked with DLR 10 m crop maps. GPU pipeline (CuPy, exactextract) on Colab: 1.64 billion wheat pixels in 5.5 h. Over 151,793 OCO-2 footprints, SIF tracks NIRv (r=0.54) better than NDVI (r=0.42).
geospatial remote-sensing ndvi cupy sentinel-2 oco-2 zonal-statistics crop-monitoring winter-wheat solar-induced-fluorescence
-
Updated
Sep 19, 2026 - Jupyter Notebook
Add this topic to your repo
To associate your repository with the oco-2 topic, visit your repo's landing page and select "manage topics."