Lucas P. Spaete
Research Associate, Boise State University
BA, Natural Resources, University of Michigan, 2005
MS, Applied Forest Ecology, Michigan Technological University, 2009
My interests focus on remote sensing of semi-arid rangeland environments with specific interest in using airborne and terrestrial LiDAR to capture shrub characteristics at the plot and landscape scale
Phone/Address
208-781-1488Department of Geosciences, 1910 University Dr, Boise, ID 83725-1535
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CZO Publications
Papers/Books
2019
Empirical methods for remote sensing of nitrogen in drylands may lead to unreliable interpretation of ecosystem function. Dashti, H., Glenn, N.F., Ustin, S., Mitchell, J.J., Qi, Y., Ilangakoon, N.T., Flores, A.N., Silvan-Cardenas, J., Zhao, K., Spaete, L.P., and M.A. de Graaff (2019): IEEE Transactions on Geoscience and Remote Sensing
2019
Regional scale dryland vegetation classification with an integrated lidar-hyperspectral approach. Dashti, H., Poley, A., Glenn, N.F., Ilangakoon, N., Spaete, L., Roberts, D., Enterkine, J., Flores, A.N., Ustin, S.L., and J.J. Mitchell (2019): Remote Sensing
2018
Constraining plant functional types in a semi-arid ecosystem with waveform lidar. Ilangakoon, N.T., Glenn, N.F., Dashti, H., Painter, T.H., Mikesell, T.D., Spaete, L.P., Mitchell, J.J. and K. Shannon (2018): Remote Sensing of Environment
2017
Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales. Li, A., Dhakal, S., Glenn, N.F., Spaete, L.P., Shinneman, D.J., Pilliod, D.S., Arkle, R.S. and S. McIlroy (2017): Remote Sensing
2015
Combining airborne LiDAR and hyperspectral data across local sites for upscaling shrubland structural information: lessons for HyspIRI . Mitchell, J., Spaete, L., Shrestha, R., and N. Glenn (2015): Remote Sensing of Environment
2013
Improved visibility calculations with tree trunk obstruction modeling from aerial LiDAR. Murgoitio, J, R Shrestha, N Glenn, and L Spaete (2013): International Journal of Geographical Information Science, 27 (10): 1865-1883
2013
Airborne LiDAR and terrestrial laser scanning derived vegetation obstruction factors for visibility models. Murgoitio, J, R Shrestha, N Glenn, and L Spaete (2013): Transactions in GIS
2011
Errors in LiDAR-derived shrub height and crown area on sloped terrain. Glenn, N, L Spaete, T Sankey, D Derryberry, S Hardegree, and J Mitchell (2011): Journal of Arid Environments, 75 (4): 377-382
2011
Vegetation and slope effects on accuracy of a LiDAR-derived DEM in the sagebrush steppe. Spaete, L, N Glenn, D Derryberry, T Sankey, J Mitchell, and S Hardegree (2011): Remote Sensing Letters, 2 (4): 317-326
Papers and books that explicitly acknowledge a CZO grant are highlighted in PALE ORANGE.
Other CZO Publications
2016
Spatial Pattern of Soil Organic Acquired from Hyperspectral Imagery at Reynolds Creek Critical one Observatory (RC-CZO). Li, A., Will, R., Glenn, N., Benner, S., and L. Spaete (2016): Whisper 2016, Los Angeles, CA
2015
Improving Ecosystem Dynamic Models in a Semi-arid Ecosystem by Integrating Different Sources of Remotely Sensed Data. Dashti, H., Glenn, N., Jessica, M., Spaete, L., Flores, A., Zhou, Q., and M. Masarik (2015): CSDMS Annual Meeting, Boulder, CO
2015
Estimation of sagebrush biochemical and biophysical parameters using hyperspectral imagery and inversion of radiative transfer models. Dashti, H., Glenn, N.F., Jessica, M., and L. Spaete (2015): 57th Idaho Academy of Science and Engineering (IASE) Annual Meeting and Symposium, Boise, ID
2015
Landsat 8 Coupled With LiDAR Estimate Semi-Arid Rangeland Biomass and Cover. Dhakal, S., Li, A., Spaete, L., Shinneman, D., Arkle, R., Pilliod, D., McIlroy, S., Baun, C., and N.F. Glenn (2015): American Geophysical Union, San Francisco, CA
2015
Characterization of low-height vegetation with waveform LiDAR. Ilangakoon, N., Glenn, N.F., and L. Spaete (2015): (IASE) Annual Symposium, Boise State University
2015
Individual and Plot Level Shrub Characterization with Full Waveform LiDAR. Ilangakoon, N., Glenn, N.F., Dashti, D., and L. Spaete (2015): NASA ARSET Workshop, Pocatello, ID
2015
Spatial Patterns of Vegetation Biomass and Soil Organic Carbon Acquired from Airborne Lidar and Hyperspectral Imagery at Reynolds Creek Critical Zone Observatory. Li, A., Will, R., Glenn, N., Benner, S., Spaete< L., and N. Ilangakoon (2015): American Geophysical Union, San Francisco, CA
2015
Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model. Will, R., Glenn, N., Benner, S., Pierce, J.L., Spaete, L., and A. Li (2015): American Geophysical Union, San Francisco, CA
2015
Mapping the organic carbon content of soils (SOC) in the Reynolds Creek Watershed. Will, R., Stanbery, C., Seyfried, M., Pierce, J., Lohse, K., Flores, A., Glenn, N., Spaete, L., Patton, N., Black, C., Good, A., and S. Benner (2015): Great Basin Conference, Boise, ID
2014
Mapping the organic carbon content of soils (SOC) in the Reynolds Creek Watershed. Will, R., Stanbery, C., Seyfried, M., Pierce, J., Lohse, K., Flores, A., Glenn, N., Spaete, L., Patton, N., Black, C., Good, A., and S. Benner (2014): All Hands Meeting, Fish Camp, CA
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