Physical Sciences and Mathematics Commons^™

Examining Interactions Between And Among Predictors Of Net Ecosystem Exchange: A Machine Learning Approach In A Semi-Arid Landscape, Qingtao Zhou, Aaron Fellows, Gerald N. Flerchinger, Alejandro N. Flores

Geosciences Faculty Publications and Presentations

Net ecosystem exchange (NEE) is an essential climate indicator of the direction and magnitude of carbon dioxide (CO₂) transfer between land surfaces and the atmosphere. Improved estimates of NEE can serve to better constrain spatiotemporal characteristics of terrestrial carbon fluxes, improve verification of land models, and advance monitoring of Earth’s terrestrial ecosystems. Spatiotemporal NEE information developed by combining ground-based flux tower observations and spatiotemporal remote sensing datasets are of potential value in benchmarking land models. We apply a machine learning approach (Random Forest (RF)) to develop spatiotemporally varying NEE estimates using observations from a flux tower and several …