Remote sensing from space may well become one of the world's most effective, accurate, and efficient ways to assess fire risk and thus manage large landscapes. The technology is evolving quickly, and researchers are busy keeping up. Some major western U.S. landscapes are just now being assessed for integrating remote sensing data with "on the ground" data that helps fine tune remote sensing models, and helps researchers assess which models work best. Drs. Jenny Rechel and Dar Roberts have worked together to gather Live Fuel Moisture (LFM) data from seven major western landscapes with similar mixed vegetation types. They compared their LFM data to multiple spectral indices and remote sensing models to assess which are the most accurate. They found that MODIS is overall the best remote sensing imagery to use when it comes to looking at LFM. They validated the LFM data with the satellite imagery, which confirmed their results. They found unexpected variation in the LFM measurements both across season and within sites. That the remote sensing data confirmed this variation, is more evidence for the power of using remote sensing imagery to assess LFM as a component of fire risk.