Temesgen, Hailemariam

Professor in Forest Biometrics & Measurements

Office Location: 
Snell 321
Email Address: 

PhD, 1999, Forest Biometrics, University of British Columbia
MS, 1992, Forest Management, Lakehead University
BS, 1986, Plant Sciences, Alemaya University of Agriculture

Areas of Interest: 

Forest measurements and biometrics, modeling, and LiDAR

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.

Graduate Students: Karin Kralicek (PhD), Joonghoon Shin (PhD), Bryce Frank (PhD), Al Pancoast (MS), Ty Nietupski (PhD), Karin Wolken (MS)

Post-Doctoral Fellows: Krishna Poudel, PhD and Francisco Mauro Gutiérrez, PhD

  • FOR 321, Forest Mensuration
  • FOR 524, Forest Biometrics
Recent Publications: 


Mauro, F., V.J. Monleon, H. Temesgen, and L.A. Ruiz. In press. Analysis of the spatial correlation in linear models to predict forest variables from LiDAR auxiliary information. Canadian Journal of Forest Research.

Huff, S., M. Ritchie, and H. Temesgen. 2017. Allometric equations for estimating aboveground biomass for common shrubs in northeastern California. Forest Ecology and Management. 398: 48-63.

Kiser, J., D. Dixie, and H. Temesgen. 2017. Growth response of coastal Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco) in western Oregon following mechanical commercial thinning damage. Mathematical and Computational Forestry & Natural-Resource Science. 9(1):22-29.

Kralicek, K., Bao Huy, K. P. Poudel, C. Salas, and H. Temesgen. 2017. Simultaneous estimation of above- and below-ground biomass in a tropical forest of Viet Nam. Forest Ecology and Management. 390: 147 – 156.

Mauro, F., Z. Haxtema, and H. Temesgen. 2017. Comparison of sampling methods for estimation of nearest-neighbor index values. Canadian Journal of Forest Research. 47 (6): 703-715.


Shin, J., H. Temesgen, J. Strunk, and T. Hilker. 2016. Comparing modeling methods for predicting forest attributes using LiDAR metrics and ground measurements. Canadian Journal of Remote Sensing. 42(6): 739-765.

Huy, B., K. Kralicek, K.P.  Poudel, Vu T.  Phương, V. K. Phung, D. H. Nguyen, and H. Temesgen. 2016. Allometric Equations for Estimating Tree Aboveground Biomass in Evergreen Broadleaf Forests of Viet Nam. Forest Ecology and Management. 382: 193-205.

Huy, B., K. P. Poudel, K. Kralicek, N.  Hung, P.  Khoa, Vu T.  Phương, and H. Temesgen. 2016. Allometric Equations for Estimating Tree Aboveground Biomass in Tropical Dipterocarp Forests of Southeast Asia. Forests. 7(8), 180.

Huy, B., K.P Poudel, and H.Temesgen. 2016. Aboveground Biomass Equations for Evergreen Broadleaf Forests in South Central Coastal Ecoregion of Viet Nam: Selection of Eco-regional or Pantropical Models. Forest Ecology and Management. 376: 276-283.

Strunk, J., L. Jeroue, J. Mills, and H. Temesgen. 2016. An Urban Forest-Inventory-and-Analysis Investigation in Oregon and Washington. Urban Forestry & Urban Greening. 18: 100-109.

Poudel, K.P. and H. Temesgen. 2016. Calibration of volume and component biomass equations for Douglas-fir and lodgepole pine trees in Western Oregon forests. Forestry Chronicle. 92(2): 172-182.

Poudel, K.P. and H. Temesgen. 2016. Developing Biomass Equations for Western Hemlock and Red Alder Trees in Western Oregon Forests. (4): 88. Forests.

Shettles, M., T. Hilker, and H. Temesgen. 2016. Examination of uncertainty in per unit area estimates of above ground biomass using terrestrial lidar. Canadian Journal of Forest Research. 46: 706-715.

Poudel, K.P. and H. Temesgen. 2016. Methods for Estimating Aboveground Biomass and its Components for Douglas-fir and lodgepole pine trees. Canadian Journal of Forest Research. 46: 77-87.


Temesgen, H., J. Strunk, H.E. Andersen, and J. Flewelling. (2015). Evaluating different models to predict biomass increment from multi-temporal lidar sampling and remeasured field inventory data in south-central Alaska. Mathematical and Computational Forestry & Natural-Resource Sciences, 7(2): 66-80. (pdf)

Shettles, M., H. Temesgen, A.N. Gray, and T. Hilker. (2015). Comparison of uncertainty in per unit area estimates of aboveground biomass for two selected model sets. Forest Ecology and Management, 354: 18-25. (pdf)

Packalen, P., J. Strunk, J. Pitkänen, H. Temesgen, and M. Maltamo. (2015). Edge-tree correction for area based method of airborne lidar. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(3): 1274-1280. (pdf)

Weiskittel, A., D.A. MaCFarlen, P.J. Radtke,  D.L. Affleck, H. Temesgen, C.W. Woodall, J.A. Westfall, and J.W. Coulston. (2015). A call to improve methods for estimating tree biomass for regional and national assessments.Journal of Forestry, 113(4): 414-424. (pdf)

Temesgen, H., D. Affleck, K.P. Poudel, A. Gray, and J. Sessions. (2015). A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models. Scandinavian Journal of Forest Research, 30 (4): 326-335. (pdf)

Temesgen, H., K.P. Poudel, A. Gray, D. Affleck, and J. Sessions. (2015). Measurements and Estimation of Above Ground Biomass of The Western U.S. Forests. Scandinavian Journal of Forest Research. 30(4): 326-335

Poudel, K.P., H. Temesgen, and A.N. Gray. 2015. Evaluation of Sampling Strategies to Estimate Crown Biomass of Conifers. Forest Ecosystems. 2:1. (pdf)


Temesgen, H. and Ver Hoef, J. 2014. Evaluation of the Spatial Linear Model, Random Forest, and Gradient Nearest Neighbor Methods for Imputing Potential Productivity and Biomass of the Pacific Northwest Forests. Forestry: An International Journal of Forest Research. 6: 1-12.(pdf)

Zhao X.H., J.J. Rivas, C.Y. Zhang, H. Temesgen, and K. v. Gadow. 2014. Forest Observational Studies - an Essential Infrastructure for Sustainable Use of Natural Resources. Forest Ecosystems. 1(8): 1-10. (pdf)

Strunk, J., H. Temesgen, H.E. Andersen, and Pakalen, P. 2014. Prediction of forest attributes with Landsat and a sample of lidar strips; A case study on the Kenai Peninsula, Alaska. Photogrammetric Engineering and Remote Sensing. 80: 143-150.(pdf)

Burkhart, H. and H. Temesgen. 2014. Overview of Forest Observational Studies around the world.  Forest Ecology and Management. 316: 1-2. (pdf)

Temesgen, H., C. Zhang, and X. Zhao. 2014. Modelling spatial variation in tree height-diameter  relationships of multi-species and multi-layered forests. Forest Ecology and Management. 316: 78-89. (pdf)

Gagliasso, D., S. Hummel, and H. Temesgen. 2014. A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area. Open Journal of Forestry (OJF)(pdf)


Goerndt, M.E., V.J. Monleon, and H. Temesgen. 2013.  Small area estimation of county-level forest attributes using ground data and remote sensed auxiliary information.  Forest Science. 59(2):1-13.(pdf)

Ver Hoef J. and H. Temesgen. 2013. A comparison of the spatial linear model to nearest neighbor (k-NN) methods for forestry applications. PLOS ONE. (3):1-11.(pdf)

Eskelson, B.N.I., P. D. Anderson, and H. Temesgen. 2013.  Monitoring of relative humidity in headwater forests using correlation with air temperature. Northwest Science. 87(1): 40-58.(pdf)


Strunk, J., H. Temesgen, and H.E. Andersen. 2012. Effects of LIDAR Pulse Density and Sample Size on the Precision of Selected Forest Inventory Attributes. Canadian Journal of Remote Sensing. 38(5): 644-654.(pdf)

Packalen, P., Temesgen, H., and Maltamo, M. 2012. Variable Selection Strategies for Nearest Neighbor Imputation in Remote Sensing Based Forest Inventory. Canadian Journal of Remote Sensing. 38(5): 557-569.(pdf)

Andersen, H. E., J. Strunk, and H. Temesgen. 2012. Using multi-level remote sensing and ground data to estimate forest biomass resources in remote regions: a case study in boreal forests of interior Alaska. Canadian Journal of Remote Sensing. 37: 596-611.

Haxtema, Z., H. Temesgen, and Marquardt. 2012. Evaluation of n-tree distance sampling for inventory of headwater riparian forests of western Oregon. Western Journal of Applied Forestry. 27:109-117.(pdf)

Groom, J.D., Hann, D.W., and Temesgen, H. 2012. Evaluation of mixed-effects models for predicting Douglas-fir mortality. Forest Ecology and Management. 276: 139-145. (pdf)

Eskelson, B.N.I., Hagar, J.C., and H. Temesgen. 2012. Estimation of snag density and snag quality attributes in western Washington and Oregon. Forest Ecology and Management. 272: 26–34. (pdf)

Marquardt, T., H. Temesgen, B.N.I. Eskelson, and P. Anderson. 2012. Evaluation of sampling methods to quantify abundance of hardwoods and snags within conifer dominated riparian zones.  Annals of Forest Science. (pdf)

Barrett, T.M., G. Latta, P. E. Hennon, B. N.I. Eskelson, and H. Temesgen. 2012. Modeling host-parasite distributions under changing climate Tsuga heterophylla and Arceuthobium tsugense in Alaska. Canadian Journal of Forest research. 42: 642-656. (pdf)


Temesgen, H., B.N.I Eskelson, T. Maness, D. Adams, and H. Burkhart. 2011. Teaching in Contemporary Forestry Resources Curricula: Applications to the Teaching of Forest measurements. Journal of Forestry. 109 (7):371-377. (Abstract)

Andersen, H. E., J. Strunk, and H. Temesgen. 2011. Using multi-level remote sensing and ground data to estimate forest biomass resources in remote regions: a case study in boreal forests of interior Alaska. Canadian Journal of Remote Sensing. 37: 596-611. (pdf)

Andersen, H. E., J. Strunk, and H. Temesgen. 2011. Using airborne lidar as a sampling tool for estimating forest biomass resources in the upper Tanana Valley of interior Alaska. Western Journal of Applied Forestry. 26: 157-164.  (pdf)

Eskelson, B.N.I., P. D. Anderson, J. Hagar, and H. Temesgen. 2011. Geostatistical modeling of riparian forest microclimate and its implications for sampling. Canadian Journal of Forest Research. 41:974-985.  (pdf)

Eskelson, B.N.I., L. Madison, J. Hagar, and H. Temesgen.  Estimating riparian understory vegetation cover with beta regression and copula models. Forest Science.  57: 212-221. (pdf)

Goerndt, M. E., V. J. Monleon, and H. Temesgen. 2011. A comparison of small-area estimation techniques to estimate selected stand attributes using LiDAR-derived auxiliary variables. Canadian Journal of Forest Research. 41: 1189-1201.(pdf)

Temesgen, H., V.J. Monleon, A. R. Weiskittel, and D.S. Wilson. 2011. Sampling strategies for efficient estimation of tree foliage biomass.  Forest Science. 57: 153-163.(pdf)


Goerndt, M.E., V.J. Monleon, and H. Temesgen. 2010.  Relating forest attributes with area- and tree-based LiDAR metrics for western Oregon. Western Journal of Applied Forestry. 25: 105-111.(pdf)

Marquardt, T, H. Temesgen and P. Anderson. 2010. Accuracy and suitability of selected sampling methods within conifer dominated riparian zones. Forest Ecology and Management. 260: 313-320.(pdf)

Latta, G., H. Temesgen, D.A. Adams, and T. Barrett. 2010. Analysis of potential impacts of climate change on forests of the United States Pacific Northwest. Forest Ecology and Management. 259: 720-729.(pdf)

Selected Publications: 


Eskelson, B.N.I., H. Temesgen, and T.M. Barrett. 2009. Imputing Mean Annual Change and Estimating Current Forest Attributes. Silva Fennica. 43:649-658.

Eskelson, B.N.I, H. Temesgen, and T. Barrett. 2009. Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods. Canadian Journal of Forest Research. 39: 1749-1765.

Latta, G., Temesgen, H., and T. Barrett. 2009. Mapping and imputing potential productivity of Pacific Northwest Forests using climate variables. Can. J. For. Res. 39: 1197-1207.  

Eskelson, B.N.I, H. Temesgen, V. LeMay, T. Barrett,  A. Hudak, and N. Crookston. 2009. The roles of nearest neighbor methods in imputing missing data in forest inventory and monitoring databases. Scand. J. For. Res. 24:193-205.

Garber, S.M., Temesgen, H., V.J. Monleon, and D.W. Hann. 2009.  Effects of height imputation strategies on stand volume estimation. Can. J. For. Res. 39: 694-703.

Eskelson, B.N.I, H. Temesgen, and T. Barrett.  2009. Estimating current forest attributes from paneled inventory data using plot-level imputation: a study from the Pacific Northwest. For. Sci. 55 (1): 64-71.

Weiskittel, A. R., P.J. Gould, and H. Temesgen. 2009. Sources of variation in the self-thinning boundary line for three ecologically-distinct species. For. Sci. 55 (1): 84-93.


Temesgen, H., T. Barrett, and G. Latta. 2008. Estimating Cavity Tree Abundance Using Nearest Neighbor Imputation Methods for western Oregon and Washington Forests.  Silva Fennica. 42(3): 337-354.

Eskelson, B.N.I, H. Temesgen, and T.M. Barrett.  2008. Comparison of Stratified and Non-stratified Most Similar Neighbour Approaches for Estimating Stand Tables. Forestry: Int. J. For. Res. 81: 125-134.

Temesgen, H., V.J. Monleon, and D.W. Hann.  2008. Analysis of nonlinear tree height prediction strategies for Douglas-fir forests. Can. J. For. Res. 38: 553-565.

Younger, N., H. Temesgen, and S. Garber. 2008. Taper and volume responses to sulfur treatment in coastal Oregon Douglas fir stands. West. J. Appl. For.  23(3): 142-148.

Weiskittel, A.R, H. Temesgen, D.S. Wilson, and D. A. Maguire.  2008. Sources of within- and between-stand variability in specific leaf area of three ecologically distinct conifer species.  Annals of Forest Sciences 65, 103-113.


Temesgen, H., M.E. Goerndt, G. P. Johnson, D.M. Adams, and R.A. Monserud. 2007. Forest measurement and biometrics in forest management: status and future needs of the Pacific Northwest USA. Journal of Forestry. 105: 233-238.

Temesgen, H., D.W. Hann, and V.J. Monleon. 2007. Regional height-diameter equations for major tree species of southwest Oregon. West. J. Appl. For.  22(3): 213-219.


Temesgen, H, P.J. Martin, D.A. Maguire, J.C. Tappeiner. 2006. Quantifying effects of different levels of dispersed canopy tree retention on stocking and yield of the regeneration cohort. For. Ecol. & Manage.  235: 44-53.

Temesgen, H. and A.R. Weiskittel. 2006. Leaf mass per area relationships across light gradients in hybrid spruce crowns. Trees: Structure & Function. 20: 522-530.  


Temesgen, H. and S.J. Mitchell. 2005.  An individual tree mortality model for South-eastern British Columbia.  West. J. Appl. For.  20(2): 101-109.

LeMay, V. and H. Temesgen. 2005. Connecting inventory information sources for landscape level analyses.   J. Forest Biometry, Modeling and Information Sciences. 1: 37-49.

LeMay, V.  and Temesgen, H.  2005.  Comparison of nearest neighbor methods for estimating basal area and stems per ha using aerial auxiliary variables.  For. Sci. 51 (2): 109-119.

Temesgen, H., V.M. LeMay, and S. J. Mitchell. 2005. Tree crown ratio models for multi-species and multi-layered stands.  For. Chron. 81(1): 133-141.


Boisvenue, C., H. Temesgen, and P.L. Marshall. 2004. Selecting a small tree height growth model for mixed-species stands in the Southern Interior of British Columbia, Canada. For. Ecol. & Manage. 177: 301-312.

Temesgen, H. and K. v. Gadow. 2004. Generalized height-diameter models for major tree species in complex stands of interior British Columbia, Canada. Europ. J. For. Res. 123(1): 45-51.

Hassani, B., T., P.L. Marshall, V.M. LeMay, Temesgen, H., and Zumrawi. 2004. Regeneration imputation models for complex stands of southeastern British Columbia. For. Chron. 80(2): 271-278.


Temesgen, H., V. LeMay, and I.R. Cameron. 2003. Bivariate distribution functions for predicting twig leaf area within hybrid spruce crowns. Can. J. For. Res. 33: 2044-2051.

Temesgen, H. 2003. Estimating tree-lists from aerial information: a comparison of a parametric and most similar neighbor approaches. Scand. J. For. Res. 18:279-288.

Temesgen, H. 2003. Evaluation of sampling alternatives to quantify tree leaf area. Can. J. For. Res. 33: 82-95. (Abstract)

Temesgen, H., V.M. LeMay, P.L. Marshall, and K. Froese. 2003. Imputing tree-lists from aerial attributes for complex stands of British Columbia. For. Ecol. & Manage. 177: 277-285.

Rowan, C.A., S.J. Mitchell and H. Temesgen. 2003. Effectiveness of wind firming treatments in Coastal British Columbia. Forestry. 76: 55-65.

pre 2003

Mitchell, S.J., H. Temesgen and Y.P. Kulis. 2001. Empirical modelling of cutblock edge windthrow risk on Vancouver Island, Canada, using stand level information. For. Ecol. & Manage. 154: 117-130.

Howard, A.F. and H. Temesgen. 1997. Potential financial returns from alternative silvicultural prescriptions in second-growth stands of coastal British Columbia. Can. J. For. Res. 27:1483-1495.

Recent Theses

Huff, Steve. 2016. Quantifying Aboveground Biomass for Common Shrubs in Northeastern California. MSc. Oregon State University.

Hoe, Michael. 2016. Multi-temporal LiDAR analysis of landscape effects in southwestern Oregon. MSc. Oregon State University.

Poudel, Krishna. 2015. Strategies for Sampling and Estimation of Aboveground Tree Biomass. PhD. Oregon State University.

Shettles, Michael. 2014. Error Propagation in Estimating Aboveground Biomass Using Terrestrial LiDAR. MSc. Oregon State University.

Jeroue, Lacey. 2014. Predicting urban tree attributes for major species found in urbanized areas of the western pacific states. MSc. Oregon State University.

Strunk, Jacob. 2012. Estimation of Modeling of Selected Forest Metrics with Lidar and Landsat. PhD. Oregon State University.

Gagliasso, Donald. 2012. Evaluating the Accuracy of Imputed Forest Biomass Estimates at the Project Level. MSc. Oregon State University.

Goerndt, Michael. 2010. Comparison and analysis of small area estimation methods for improving estimates of selected forest attributes. PhD. Oregon State University.

Haxton, Zane. 2010. An examination of several methods of quantifying forest structure in headwater riparian forests of western Oregon. MSc. Oregon State University.

Marquardt, Theresa. 2010. Accuracy and suitability of several stand sampling methods in riparian zones. MSc. Oregon State University.