Energy Research at the University of Washington

L. Monika Moskal

Energy Research Area: Feedstock assessment with remote sensing

Assistant Professor of Remote Sensing and Biospatial Analysis
College of the Environment
School of Environmental and Forest Sciences

Feedstock assessment with remote sensing: To perform an accurate bioenergy feasibility assessment one needs to understand the current natural resources on the landscape that can provide feedstock. Remote sensing as a technology that can allow us to produce spatially explicit maps of natural resources such as: forest, rangelands, grasslands and agricultural areas; all contributing potential input as feedstock. One of the newest tools remote sensing scientists use is laser scanning technology called LiDAR, which can be applied both on the ground, air and space. LiDAR uses intensive pulses of light to capture information and give researchers a more comprehensive look at a surveyed area. This can give an accurate assessment of how much biomass potential there is for a (bioenergy) production facility in that area, helping to plan for future production.

Dr. Moskal's Remote Sensing and Geospatial Analysis Laboratory students collecting ground trothing data to calibrate aerial LiDAR which can be used to assess above ground biomass
Dr. Moskal's Remote Sensing and Geospatial Analysis Laboratory students collecting ground trothing data to calibrate aerial LiDAR which can be used to assess above ground biomass

Research Images

Using a terrestrial laser (LiDAR) to quantify above ground biomass

Record last updated on November 28th 2011 PDT.