There are 3 repositories under phenology topic.
Python-based extractor of vegetation metrics from satellite-based vegetation time-series imagery.
A Bayesian hierarchical model that quantifies long-term annual land surface phenology from sparse time series of vegetation indices.
R package: Extract Remote Sensing Vegetation Phenology by TIMESAT V3.3 Fortran library (only for windows)
An acquisition and processing toolkit for open access phenology data.
Sentinel-2 Crop Trait Retrieval Using Physiological and Phenological Priors from Field Phenotyping (Graf et al., 2023, RSE)
A final production version of the DDRP platform that includes cohorts, parallel processing, and improving mapping routines. The objective of the Degree-Day, establishment Risk, and Pest event mapping system (DDRP) is to predict phenology and climate suitability of invasive, biocontrol, and IPM species for the conterminous United States. DDRP is written entirely in the R statistical programming language (R Development Core Team 2019), making it flexible and extensible, and has a simple command-line interface that has already been adapted for online use. The platform can use a variety of gridded weather and climate data types for any historical (post-hoc), real-time, or future (downscaled GCM) time period. Model products include gridded (raster) and graphical outputs of number of completed generations, phenological/pest events, and climate suitability (i.e., establishment risk maps). The platform is described in a peer-reviewed paper in PLoS ONE (https://doi.org/10.1371/journal.pone.0244005).
A repository folder regarding phenology extraction scripts utilizing existing packages (i.e. TIMESAT, CropPhenology) and proposing new methodologies
PeaPod is a cloud-connected automated plant growth environment, designed as both a distributed phenotype research tool, and a precision agriculture food production.
A 3D Functionnal Structural Plant Model of perennial grasses morphogenesis and phenology
Sentinel-2 Top-Of-Atmosphere Radiometric Uncertainty Propagator (Graf et al., 2023, IEEE-JSTARS)
Spatio-Temporal Vegetation Segmentation By Using Convolutional Networks
DNN for phenological stage detection on herbarium specimens
This is a database of sightings of birds, moths, and butterfiles in support of the phenology mismatch project.
Extract phenological data from digitized herbarium specimens
Evaluation tools for assessing climate adaptation of fruit tree species
PhenoCam Lab for BIOL 368
R code for Zohner et al. (2023)
Spatiotemporal phenology research with interpretable models
Evaluating anomalously early spring onsets in the 21st century
An updated version of the DDRP platform (from v2) that uses newer R packages ("terra" and "sf"). The objective of the Degree-Day, establishment Risk, and Pest event mapping system (DDRP) is to predict phenology and climate suitability of invasive, biocontrol, and IPM species for the conterminous United States.
Understanding photothermal interactions can help expand production range and increase genetic diversity of lentil (Lens culinaris Medik.)
Python library for simulation of wheat phenological development, crop growth and yield.
Goals, progress, and issues on phenocam leaf phenology analysis.
Phenology of Georgia (Caucasus). Phenology is derived from NDVI (Modis satellite).
Master's thesis scripts to process proximal remote sensing sensors
The PiCam time-lapse camera system. A nRF52840 managed, low power sensor node and Raspberry Pi camera system designed for autonomous operations in remote regions for the collection of vegetation phenology data
Ecological and Environmental Sciences Honours Dissertation work by Erica Zaja, 2021. Supervised by Dr Isla Myers Smith and Team Shrub.
R, Python and JavaScript code for the the National Ecological Observatory Network’s Airborne Observation Platform (AOP) sampling design and publication, "Spanning Scales: The Airborne Spatial and Temporal Sampling Design of the National Ecological Observatory Network"
Scripts, data and outputs to process the data and recreate the figures from Rohwer, Ladwig et al. (2022)
A place to store my current phenology tool code.