Undergraduate research published in remote sensing peer-reviewed journal: Carolynne Hultquist

Carolynne Hultquist, a newly graduated Geography BS student, published her research as lead author in a high-profile international journal Remote Sensing Letters. The research was completed while Carolynne worked in Professor Gang Chen’s lab. In the study, high spectral resolution remote sensing, geographic object-based image analysis (GEOBIA), and machine learning were applied to assess burn severity in a forest environment where trees have suffered from pre-fire disease-caused mortality. Results indicate a nonlinear relationship between remote sensing spectral reflectance and burn severity, and machine learning significantly outperformed conventional linear regression models. Image-texture was further found effective in burn severity mapping over diseased forests.