Josh uses geospatial analytics to understand how land use and vegetation dynamics interact with the climate system to produce changes in water and carbon cycles, particularly in managed lands like croplands and timber plantations. He develops remote sensing algorithms that blend imagery from multiple Earth-orbiting satellites to improve time series datasets for studies of phenological change. His interests also include remote sensing with Unmanned Aerial Systems (UAS) and big-data geocomputation.
Roles
Publications
- Long-term, medium spatial resolution annual land surface phenology with a Bayesian hierarchical model (2021)
- Longer greenup periods associated with greater wood volume growth in managed pine stands (2021)
- Multisensor fusion of remotely sensed vegetation indices using space-time dynamic linear models (2021)
- Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery (2020)
- Mapping Understory Invasive Plants in Urban Forests with Spectral and Temporal Unmixing of Landsat Imagery (2020)
- Predictors of fire-tolerant oak and fire-sensitive hardwood distribution in a fire-maintained longleaf pine ecosystem (2020)
- Sentinel-2 Leaf Area Index Estimation for Pine Plantations in the Southeastern United States (2020)
- A Land Surface Phenology Product for North America from Harmonized Landsat 8 and Sentinel-2 imagery (2019)
- An Empirical Assessment of the MODIS Land Cover Dynamics and TIMESAT Land Surface Phenology Algorithms (2019)
- Climate controls on springtime phenology in Eastern Temperate Forests of North America (2019)