"nonlinear dimensionality reduction"

Crowd-Sourced Plant Occurrence Data Provide a Reliable Description of Macroecological Gradients

Deep learning algorithms classify plant species with high accuracy, and smartphone applications leverage this technology to enable users to identify plant species in the field. The question we address here is whether such crowd-sourced data contain …

Identifying Multiple Spatiotemporal Patterns: A Refined View on Terrestrial Photosynthetic Activity

Information retrieval from spatiotemporal data cubes is key to earth system sciences. Respective analyses need to consider two fundamental issues: First, natural phenomena fluctuate on different time scales. Second, these characteristic temporal …

Nonlinear Dimensionality Reduction: Alternative Ordination Approaches for Extracting and Visualizing Biodiversity Patterns in Tropical Montane Forest Vegetation Data

Ecological patterns are difficult to extract directly from vegetation data. The respective surveys provide a high number of interrelated species occurrence variables. Since often only a limited number of ecological gradients determine species …