Prof. Moskal specializes in Remote Sensing and Earth Observation at the School of Environmental and Forest Sciences (SEFS), within the College of the Environment, at the University of Washington, Seattle and serves as the Director of the Precision Forestry Cooperative (PFC), which also houses her Remote Sensing and Geospatial Analysis Laboratory (RSGAL). She is affiliated with the UW Interdisciplinary PhD Program and the UW Department of Geography. Prof. Moskal has worked throughout the western U.S. and Canada, and her research has received substantial funding from the NSF, USDA Forest Service, as well as NASA. Prof. Moskal’s lab: RSGAL‘s goal is to understand multiscale and multidimensional dynamics of landscapes through the application of hyper-resolution remote sensing. RSGAL develops methods necessary to analyze hyper-resolution remotely sensed data by exploiting spatial, temporal and spectral domains of the data. RSGAL is dedicated to increasing the retention and success of underrepresented minorities in geosciences.
Research Keywords & Expertise
Ecosystem Services
TLS
ALT
MLS
Lidar precision forest...
Hyper-resolution (spat...
Fingerprints
17%
TLS
5%
Ecosystem Services
5%
MLS
Short Biography
Prof. Moskal specializes in Remote Sensing and Earth Observation at the School of Environmental and Forest Sciences (SEFS), within the College of the Environment, at the University of Washington, Seattle and serves as the Director of the Precision Forestry Cooperative (PFC), which also houses her Remote Sensing and Geospatial Analysis Laboratory (RSGAL). She is affiliated with the UW Interdisciplinary PhD Program and the UW Department of Geography. Prof. Moskal has worked throughout the western U.S. and Canada, and her research has received substantial funding from the NSF, USDA Forest Service, as well as NASA. Prof. Moskal’s lab: RSGAL‘s goal is to understand multiscale and multidimensional dynamics of landscapes through the application of hyper-resolution remote sensing. RSGAL develops methods necessary to analyze hyper-resolution remotely sensed data by exploiting spatial, temporal and spectral domains of the data. RSGAL is dedicated to increasing the retention and success of underrepresented minorities in geosciences.