Worldwide trait database addresses long-standing questions about trait-environment relationships and provides an unprecedented digital resource to inform Earth system models.
Mapping Vegetation Communities using Convolutional Neural Networks
Artificial intelligence applied to multiple remote sensing datasets accurately represents shrub distribution across hillslopes at the Kougarok field site.
Landscape Mapping using Remote Sensing and Neural Networks
A convolutional neural network (CNN) approach produced highly accurate vegetation classifications. Hyper-spectral datasets (e.g., AVIRIS) were most useful for our machine learning approaches. Accurate and high-resolution datasets generated using our approach are needed for Arctic models.
Microtopography Determines How CO2 and CH4 Exchanges Respond to Temperature and Precipitation in Polygonal Tundra
Microtopographic variation among troughs, rims, and centers strongly affects the movement of surface water and snow and thereby affects soil water contents and active layer development.