22 citations · 30 across the 5 of their papers we have counts for
5 papers
Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression
Sanjit Dandapanthula, Margaret Johnson, Madeleine Pascolini-Campbell +2
Accurate and high-resolution estimation of land surface temperature (LST) is crucial in estimating evapotranspiration, a measure of plant water use and a central quantity in agricu…
A Bayesian hierarchical framework for fusion of remote sensing data: An example with solar-induced fluorescence
Manju Johny, Jonathan Hobbs, Vineet Yadav +4
Solar-induced chlorophyll fluorescence (SIF) has emerged as an effective indicator of vegetation productivity and plant health. The global quantification of SIF and its associated…
Modelling wildland fire burn severity in California using a spatial Super Learner approach
Nicholas Simafranca, Bryant Willoughby, Erin O'Neil +5
Given the increasing prevalence of wildland fires in the Western US, there is a critical need to develop tools to understand and accurately predict burn severity. We develop a mach…
Automatic Dynamic Relevance Determination for Gaussian process regression with high-dimensional functional inputs
Luis Damiano, Margaret Johnson, Joaquim Teixeira +2
In the context of Gaussian process regression with functional inputs, it is common to treat the input as a vector. The parameter space becomes prohibitively complex as the number o…
Fine-scale spatiotemporal air pollution analysis using mobile monitors on Google Street View vehicles
Yawen Guan, Margaret Johnson, Matthias Katzfuss +4
People are increasingly concerned with understanding their personal environment, including possible exposure to harmful air pollutants. In order to make informed decisions on their…