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
- 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)
- 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)
- Hierarchical mapping of annual global land cover 2001 to present: The MODIS Collection 6 Land Cover product (2019)
- Long-term continuity in land surface phenology measurements: A comparative assessment of the MODIS land cover dynamics and VIIRS land surface phenology products (2019)
- Web-based Decision Analytics For Mapping Host Species Distributions and Forecasting the Spread of Forest Pests and Pathogens (2019)
- Evaluating machine learning approaches for mapping flood risk (2018)