Ph.D. 1998, M.S. 1995, Oregon State University; J.D. 1979, Columbia; B.A. 1976 Claremont McKenna College. Teaching and research programs in the use and application of remote sensing, geographic information systems, and spatial technologies in managed and natural ecosytems.

Recent Publications

  • Holbrook, J., J. Squires, L. Olson, N. Decesara, and R. Lawrence.  In press.  Understanding and predicting habitat for wildlife conservation: The case of Canada lynx at the range periphery.  Ecography.
  • McCann, C., K.S. Repasky, M. Morin, R. Lawrence, and S. Powell.  In press.  A novel histogram based unsupervised classification technique to determine natural classes from biophysically relevant fit parameters to hyperspectral data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
  • McCann, C., K.S. Repasky, M. Morin, R. Lawrence, and S. Powell.  In press.  Using Landsat surface reflectance (LaSRC) data as a reference target for multi-swath hyperspectral data collected over mixed agricultural rangeland areas.  IEEE Transactions on Geoscience and Remote Sensing.
  • Young, N., R. Anderson, S. Chignell, A. Vorster, R. Lawrence, and P. Evangelista.  2017.  A survival guide to Landsat preprocessing.  Ecology 98:920-932.
  • Savage, S., R. Lawrence, and J. Squires.  2017.  Mapping post-disturbance forest landscape composition with Landsat satellite imagery.  Forest Ecology and Management 399:9-23.
  • Holbrook, J., J. Squires, L.E. Olson, R. Lawrence, and S. Savage.  2016.  Multi-scale habitat relationships of showshoe hares (Lepus americanus) in the Northern Rockies, USA: Implications for forest management.  Ecology and Evolution 2016:1-20.
  • Garroutte, E., A. Hansen, and R. Lawrence.  2016.  Using NDVI and EVI to map spatiotemporal variation in the biomass and quality of forage for migratory elk in the Greater Yellowstone Ecosystem.  Remote Sensing 8:404.
  • Long, J., and R.L. Lawrence. 2016. Mapping Percent tree mortality due to mountain pine beetle damage. Forest Science 62:392-402.
  • Savage, S.L., R.L. Lawrence, and J.R. Squires. 2015. Predicting relative species composition within mixed conifer forest pixels using zero-inflated models and Landsat imagery. Remote Sensing of Environment 171:326-336.
  • Lawrence, R.L., and C.J. Moran.  2015.  The AmericaView classification methods accuracy comparison project: A rigorous approach for model selection.  Remote Sensing of Environment 170:115-120.
  • Bellante, G.J., S.L. Powell, R.L. Lawrence, K.S. Repasky, T.A.O. Dougher.  2014.  Hyperspectral Detection of a subsurface CO2 Leak in the Presence of Water Stressed Vegetation.  PLoS ONE 9(10):e10829.
  • Long, J.A., R.L. Lawrence, P.R. Miller, L.A. Marshall, and M.C. Greenwood.  2014.  Adoption of cropping sequences in northeast Montana: A spatiotemporal analysis.  Agriculture, Ecosystems and Environment 197:77-87.
  • Long, J.A., R.L. Lawrence, P.R. Miller, and L.A. Marshall.  2014.  Changes in Field-Level Cropping Sequences: Indicators of Shifting Agricultural Practices. Agriculture, Ecosystems and Environment 189:11-20.
  • Porter, T.F., C. Chen, J.A. Long, R.L. Lawrence, and B.F. Sowell.  2014.  Estimating biomass on CRP pastureland: A comparison of remote sensing techniques.  Biomass and Bioenergy 66:268-274.
  • Olexa, E.M., and R.L. Lawrence.  2014.  Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland. International Journal of Applied Earth Observation and Geoinformation 30:30-41.
  • Johnson, J.E., J.A. Shaw, R.L. Lawrence, P.W. Nugent, J.A. Hogan, L.M. Dobeck, and L.H. Spangler.  2014.  Comparison of long-wave infrared imaging and visible/near-infrared imaging of vegetation for detecting leaking CO2 gas.  IEEE Journal on Selected Topics in Applied Earth Observations and Remote Sensing 7:1-7.
  • Vsevolozhskaya, O.A., M.A. Greenwood, G.J. Bellante, S.L. Powell, R.L. Lawrence, and K.S. Repasky.  2013.  Combining functions and the closure principle for performing follow-up tests in functional analysis of variance. Computational Statistics and Data Analysis 67:175-184.
  • Long J.A., R.L. Lawrence, M.C. Greenwood, L. Marshall, and P.R. Miller.  2013.  Object-oriented crop classification using multitemporal ETM+ SLC-off imagery and random forest.  GIScience & Remote Sensing 50:418-436.
  • Lawrence, R.L., and J. Jewett.  2013.  Remote sensing reveals relationships among whitebark pine, bark beetles and climate variability, pp. 66-67 in R.L. Dodge and R.G. Congalton, Meeting Environmental Challenges with Remote Sensing Imagery, American Geosciences Institute, Alexandria, VA.
  • Bellante, G.J., S.L. Powell, R.L. Lawrence, K.S. Repasky, T.A.O. Dougher.  2013.  Aerial detection of a simulated CO2 leak from a geologic sequestration site using hyperspectral imagery.  International Journal of Greenhouse Gas Control 13:124-137.


Recent Grants

  • Bioenergy Alliance Network for the Rockies, USDA. 2013-2018. $663,494.
  • Mapping Lynx Habitat with Landsat and Radarsat Imagery. USFS. 2012-2017. $480,385.
  • StateView Program for the State of Montana. USGS. 2013-2018. $125,000.
  • Habitat Use Patterns of Canada Lynx in Spruce-Beetle Damaged Forests. USFS. 2016-2017. $110,000.


Current Instructional Responsibilities

  • GPHY 426 - Remote Sensing & Digital Image Processing (Spring)
  • GPHY 429/LRES 525 - Applied Remote Sensing (Spring)
  • LRES 535 - Techniques of Spatial Analysis (Spring)