Predicting spring green-up across diverse North American grasslands

Existing models poorly predict the timing of spring green-up in grasslands. New model shows grassland green-up is driven by both precipitation and temperature.

Predicting spring green-up across diverse North American grasslands

Existing models of grassland phenology poorly predict green-up. Inclusion of precipitation, in addition to temperature, resulted in significantly better model results, although different thresholds apply across different climate regions.

phenor v2.0 preview

New hindcast and forecast capabilities

Calibrating vegetation phenology from Sentinel-2 using eddy covariance, PhenoCam, and PEP725 networks across Europe

The freely available Sentinel-2 imagery at a 10 m spatial resolution with a ~ 5-day repeat cycle provides an opportunity to map vegetation phenology at an unprecedented fine spatial scale. Several aspects of producing a new Sentinel-2 phenology product are studied.

Monitoring crop phenology using a smartphone based near-surface remote sensing approach

Smartphone repeat imagery quantifies important phenological stages of winter wheat. Small scale phenology or disturbances are not captured by satellite remote sensing. Using smartphone imagery can improve crop modeling and insurance for small farmers.

Assimilating phenology datasets automatically across ICOS ecosystem stations

We detail the procedure for the implementation of cameras on Integrated Carbon Observation System flux towers and how these images will help us understand the impact of leaf phenology and ecosystem function, distinguish changes in canopy structure from leaf physiology and at larger scales will assist in the validation of (future) remote sensing products.

An integrated phenology modelling framework in r

We present the phenor r package and modelling framework. The framework leverages measurements of vegetation phenology from four common phenology observation datasets, the PhenoCam network, the USA National Phenology Network, the Pan European Phenology Project, MODIS phenology combined with (global) retrospective and projected climate data.

Productivity of North American grasslands is increased under future climate scenarios despite rising aridity

We explore the potential responses of North American grasslands to climate change using a new, data-informed vegetation–hydrological model, a network of high-frequency ground observations across a wide range of grassland ecosystems and CMIP5 climate projections.