Michigan Technological University

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School of Forest Resources and Environmental Science

Michael J. Falkowski

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Michael J. Falkowski

Assistant Professor, School of Forest Resources and Environmental Science

  • PhD, Natural Resources, University of Idaho
  • MS, Forestry, University of Idaho
  • BS, Geography, University of Wisconsin at Stevens Point
"Quantifying ecosystem composition and structure -in a spatially explicit manner- is paramount to the development and evaluation of effective sustainable forest management practices and policies"

Space Matters

Increasing concerns over climate change, biodiversity loss, and ecosystem disturbance have increased the demand for spatially explicit, large area ecosystem characterizations. To meet this need, my research is focused upon solving applied problems in ecosystem science and sustainable forest management. I am particularly interested in developing methods to quantify and monitor vegetation structure and composition across large spatial extents, primarily via remote sensing and spatial modeling.

I conduct research in a diversity of areas including LiDAR remote sensing of forest structure, spatial modeling of forest species composition and wildlife habitat suitability, as well as remote sensing of active fire and post-fire effects, among others. Although each of the aforementioned research areas are focused upon unique problems, there is one common thread throughout; integrating cutting edge spatial technologies with fundamental field measurements and established ecological theory to gain a better understanding of the natural environment.

Recent Publications

  • Hess, A.N., Falkowski, M.J., Pocewicz A., Webster, C.R., Martinuzzi, S., and A.J. Storer. 2013. Employing lidar data to identify butterfly habitat characteristics of four contrasting butterfly species across a diverse landscape. Remote Sensing Letters. Vol. 4, 354-363.
  • Henareh Khalyani, A., Mayer, A.L., Webster, C.R., and Falkowski, M.J. 2013. Ecological indicators for protection impact assessment at two scales in Bozin and Marakhil protected area, Iran. Ecological Indicators. Vol. 25, 99-107
  • Henareh Khalyani, A., Falkowski, M.J., and Mayer, A.L. 2012. Classification of Landsat images based on spectral and topographic variables for land cover change detection in Zagros forests. International Journal of Remote Sensing. Vol. 33, 6956-6974
  • Hudak, A.T., E.K. Strand, L.A. Vierling, J.C. Byrne, J. Eitel, S. Martinuzzi, and Falkowski, M.J. 2012. Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys. Remote Sensing of Environment. Vol. 123, 25-40
  • Tinkham, W., Smith, A., Hoffman, C., Hudak, A., Falkowski, M.J., Swanson, M., and Gessler, P.E. 2012. Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories. Canadian Journal of Forest Research. Vol. 42, 413-422
  • Hummel, S., Hudak, A, Uebler, E, Falkowski, M.J., and K. Megown. 2011. Comparable accuracy and cost of stand exam vs. LiDAR data informs landscape management on the Malheur National Forest. Journal of Forestry, July/August
  • Henareh Khalyani, A., Mayer, A.L., and Falkowski, M.J. 2012. Deforestation and landscape structure changes related to socioeconomic dynamics and climate change in Zagros forests. Journal of Land Use Science. DOI:10.1080/1747423X.2012.667451
  • Falkowski, M.J., and J. Manning. 2010. Parcel-based classification of agricultural crops via multi-temporal Landsat imagery in support of habitat availability monitoring for western burrowing owls in the Imperial Valley agro-ecosystem. Canadian Journal of Remote Sensing. Vol. 36, No. 6, 750-762.
  • Falkowski, M.J., Hudak, A.T., Crookston, N., Gessler, P.E., and Smith A.M.S., 2010. Landscape-scale parameterization of a tree-level forest growth model: a k-NN imputation approach incorporating LiDAR data. Canadian Journal of Forest Research. Vol. 40, 184-199.
  • Martinuzzi, S., Vierling, L.A., Gould, W.A., Falkowski, M.J., 2009. Evans, J.S., Hudak, A.T., and Vierling, K.T. Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability. Remote Sensing of Environment. Vol. 113, 2533-2546.
  • Falkowski, M.J., Wulder, M.A., White, J.C., and Gillis, M.D., 2009. Supporting large-area, sample-based forest inventories with very high spatial resolution satellite imagery. Progress in Physical Geography. Vol. 33, No. 3, 403–423.
  • Falkowski, M.J., Evans, J.S., Martinuzzi, S., Gessler, P.G., and Hudak, A.T., 2009. Characterizing forest succession with lidar data: An evaluation for the inland northwest, USA. Remote Sensing of Environment. Vol. 113, 946-956.
  • Falkowski, M.J., Smith, A.M.S., Gessler, P.E., Hudak, A.T., Vierling, L.A., and Evans, J.S., 2008. The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data. Canadian Journal of Remote Sensing, 34, S2, S338-S350.

School of Forest Resources and Environmental Science

Forestry and Wood Products Building
1400 Townsend Dr.
Houghton, Michigan 49931-1295

Ph. 906-487-2454
Toll-Free: 800-WOODS-MI
  (800-966-3764)
Email: forest@mtu.edu

Michigan Technological University

1400 Townsend Drive
Houghton, Michigan 49931-1295
906-487-1885

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