Hailemariam, Temesgen
Position Type:
Faculty
Job Title:
Giustina Professor of Forest Management and Director of the Center for Intensive Planted-forest Silviculture
Department:
Forest Engineering, Resources & Management
Office Location:
334 Peavy Forest Science Center (PFSC)
Phone Number:
Advising:
Graduate Major Advisor
Education
PhD, 1999, Forest Biometrics, University of British Columbia
MS, 1992, Forest Management, Lakehead University
BS, 1986, Plant Sciences, Alemaya University of Agriculture
Research Areas
Forest Biometrics and Geomatics
Research Interests
- Biometrics
- Forest Measurements
Forest measurements and biometrics, modeling, and LiDAR
Bio
Current Programs:
Develop imputation and sampling techniques to assess, monitor, and analyze forest resources; develop quantitative methods to characterize, quantify, and integrate tree/crown attributes and site productivity; and integrate airborne LiDAR and ground data to estimate status, change, and trends.
Develop imputation and sampling techniques to assess, monitor, and analyze forest resources; develop quantitative methods to characterize, quantify, and integrate tree/crown attributes and site productivity; and integrate airborne LiDAR and ground data to estimate status, change, and trends.
Graduate Students:
Courses Taught:
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FOR 321Forest Mensuration
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FOR 524Forest Biometrics
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FOR 550Sustainable Forest Management
Selected Publications:
- Allensworth, E., H. Temesgen, B. Frank, and A. Gray. 2021. Comparison of imputation methods for predicting height-to-crown-base for Douglas-fir in Southwest Oregon. Forest Ecology and Management. 498. 119574.
- Mauro, F., A.T. Hudak, P.A. Fekety, B. Frank, H. Temesgen, D.M. Bell, M.J. Gregory, and R. McCarley. 2020. Regional modeling of forest fuels and structural attributes using airborne laser scanning data in Oregon. Remote Sensing. 13(2), 261; https://doi.org/10.3390/rs13020261
- Nietupski, T.C., R.E. Kennedy, H. Temesgen, B. K. Kerns. 2021. Spatiotemporal Image Fusion in Google Earth Engine for Annual Estimates of Land Surface Phenology in a Heterogenous Landscape. Remote Sensing. Volume 99, 102323.
- Huy, B., L.C. Nam, K.P. Poudel, and H. Temesgen. 2020. Individual tree diameter growth modeling system for Dalat pine (Pinus dalatensis Ferré) of the upland mixed tropical forests. Forest Ecology and Management. 480:118612.
- Frank, B., F. Mauro, and H. Temesgen. 2020. Model-based estimation of forest inventory attributes using lidar: a comparison of the area-based and semi-individual tree crown approaches. Remote Sensing. 2(16), 2525.
- Frank, B., F. Mauro, H. Temesgen, and K.R. Ford. 2019. Analysis of Classification Methods for Identifying Stands for Commercial Thinning Using LiDAR. Canadian Journal of Remote Sensing, Vol. 45(5), 673-690
- Mauro, F., M. Ritchie, B. Wing, B. Frank, V.J. Monleon, H. Temesgen, and A. Hudak. 2019. Estimation of changes of forest structural attributes at three different spatial aggregation levels in Northern California using multi-temporal LiDAR. Remote Sensing. 11 (8), 923
- Huy, B., K.P. Poudel, and H. Temesgen. 2019. Individual plant allometric equations for estimating above-ground biomass and its components for a common bamboo species (Bambusa procera A. Chev. & A. Camus) in tropical forests. Forests. 10, 316.
- Huy, B., G. T. Thanh, K.P. Poudel, B.M. Frank, and H. Temesgen. 2019. Taxon- specific modeling systems for improving reliability of tree aboveground biomass and its components estimates in tropical dry dipterocarp forests. Forest Ecology and Management. 437: 156-174.
- Mauro, F., B. Frank, V. J. Monleon, H. Temesgen, and Kevin R. Ford. 2019. Prediction of diameter distributions and tree-lists in southwestern Oregon using LiDAR and stand-level auxiliary information. Canadian Journal of Forest Research. 49: 775-787.
- Poudel, K.P., Temesgen, H., P.J. Radtke, and A. Gray. 2019. Estimating Individual Tree Aboveground Biomass of Tree Species in the Western U.S.A. Canadian Journal of Forest Research. 49: 701-714.
- Hoe, M., C. Dunn, and H. Temesgen. 2018. Estimating fire induced basal area mortality with multi-temporal LiDAR. International Journal of Wildland Fire. 27 (9), 581-594
For a full list of publications, visit: