Version Control

A conceptual graphic of the proposed data analysis pipeline. Each step is represented by a stack of maps of the continental US. The top reads: "For each year, 1981-2023; geographic extent of all maps: NE US". Then, from left to right: "Inputs: Daily mean temperature (source: PRISM)", "Intermediat products: DOY maps for GDD thresholds", "Output: Mean DOY for each threshold, 1991-2020". Pointing downward from the intermediate products is an arrow labeled "Calculation of trends and variation for each thres — A conceptual diagram of the proposed data analysis pipeline

Theresa Crimmins

Estimating Trends in Phenology

Collaborators

Data Science Team

In collaboration with the National Phenology Network, we are creating an analytical pipeline to estimate spatial trends in the time to reach different thresholds of growing degree days in the Northeastern USA.

STAC Jupyter Notebook

STAC (Spatial Temporal Asset Catalog) is a specification for JSON files (and an API) which provide descriptions and links to spatial and temporal data.

SPARC'd

Collaborators

Sue Malusa (SNRE)

Melanie Culver (SNRE)

Data Science Team

Christophe Schnaufer

Julian Pistorius

Improved data sharing and search features for the SPARC’d application that manages data from trail cams used to monitor endangered wildcats and other wildlife.

AgBase

Collaborators

Fiona Mcarthy (University of Arizona, Animal and Comparative Biomedical Science…

Data Science Team

Christophe Schnaufer

AgBase is a curated resource providing functional analysis of agricultural plant and animal gene products.

Drone Processing Pipeline

Collaborators

GitHub Organization @agpipeline

Data Science Team

Christophe Schnaufer

David LeBauer

Our group built a high-throughput sensor data processing pipeline, including data from drones and other platforms, for agricultural research and beyond.