Timothy G. Gregoire

J. P. Weyerhaeuser, Jr., Professor of Forest Management

Selected Publications

Selected Publications

Owais, G., McKay, L. A., Gregoire, T. G., Guan, Y., Leaderer, B. P., and Holford, T. R. 2016. Spatiotemporal calibration and resolution refinement of output from deterministic models. Statistics in Medicine 35: 2422-2440. DOI: 10.1002/sim.6867.
 
Gregoire, T. G.,Næsset,E., McRoberts, R. E., Ståhl, G., Andersen, H-E., Ene, L. and Nelson, R. 2016. Statistical rigor in LiDAR-assisted estimation. Remote Sensing of Environment 173: 98-106 (in press)  doi: 10.1016/j.rse.2015.11.012
 
Ståhl, G., Saarela, S., Schnell, S., Holm, S., Breidenbach, J., Healy, S. P., Patterson, P. L., Magnussen, S., Næsset, E., McRoberts, R., and Gregoire, T. G. 2016. Use of models in large-area forest surveys: comparing model-assisted, model-based, and hybrid estimation. Forest Ecosystems 3:5. DOI 10.1186/s40663-016-0064-9.
 
Salas, C., Gregoire, T. G., Craven, D. J. and Gilabert, H. 2016. Modelación del crecimiento de bosques: estado del arte. (Forest growth modeling: the state of the art). Bosque 37(1) 3-12.
 
Chhetri, P. B., Katwal, S., Dukpa, T., Drukyel, S., Gregoire, T. G. 2016. The randomized branch sampling – a cost effective estimation method of above ground biomass. The Indian Forester 142(1) 47-61.
 
Ringvall, A. H., Ståhl, G., Ene, L. T., Næsset, E., Gobakken, T. & Gregoire, T. G.2016. A poststratified ratio estimator for model-assisted biomass estimation in sample-based airborne laser scanning surveys. Canadian Journal of Forest Research 46: 1386-1395.
 
Ene, L. T., Næsset, E., Gobakken, T., Mauya, E. W., Ballandsas, O-M., Gregoire, T. G., Ståhl, G., & Zahabu, E. 2016. Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data. Remote Sensing of Environment 186: 626-636.
 
Saarela, S., Holm, S., Grafström, A., Schnell, S., Næsset, E., Gregoire, T. G., Nelson, R. F., and Ståhl, G. 2016. Hierarchical model-based inference for forest inventory utilizing three sources of information,  Annals of Forest Science 73(4) 895-910.
 
Bukoski,J. J, Broadhead, J. S., Donato, D. C., Daniel Murdiyarso, D., Boone Kauffman, J., Gregoire, T. G. 2017. The use of mixed effects models for obtaining low-cost ecosystem carbon stock estimates in mangroves of the Asia-Pacific. PLOS ONE  12(1): e0169096. doi:10.1371/journal.pone.0169096
 
Calegario, N., Gregoire, T. G., daSilva, T. A., Filio, M. T. and Alves, J. A. 2017. Integrated System of Equations for Estimating Stem Volume, Density and Biomass for Australian Red Cedar Plantations. Canadian Journal of Forest Research 47: 681-689.
 
Saarela, S., Andersen, H-E, Grafström, A., Schnell, S., Gobakken, T., Næsset, E., Nelson, R. F. McRoberts, R. E., Gregoire, T. G., & Ståhl, G. 2017. A new prediction-based variance estimator for two-stage model-assisted surveys of forest resources. Remote Sensing of Environment 192: 1-11.
 
Strimbu, V. et al. 2017. Post-stratified change estimation for large-area forest biomass using repeated ALS strip sampling. Canadian Journal of Forest Research 47: 839-847.
 
Umunay, P. M and Gregoire, T. G.. 2017. Effect of light, fire and weed control on establishment of Pericopsis elata Harms regeneration. New Forests 48(6) 735-752..
 
Umunay, P.,Gregoire, T. G., Ashton. M. 2017. Estimating Biomass and Carbon for Gilbertiodendron dewevrei (De Wild) Leonard, a dominant canopy tree of African Tropical Rainforest: Implications for policies on carbon sequestration
Forest Ecology and Management 404: 31-44.
 
 
Babcock, C., Finley, A. O., Andersen, H-E, Pattison, R., Cook , B. D., Morton, D., Alonzo, M., Nelson, R., Gregoire, T. G., Ene, L., Gobakken, T., Næsset, E. 2018. Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations. Remote Sensing of Environment212: 212-230.
 
Birigazzi, L., Gamara, J. G. P., & Gregoire, T. G. 2018. Unbiased emission factor estimators for large-scale inventories: domain assessment techniques. Environmental and Ecological Statistics 25(2) 199-219.
 

Fattorini, L., Gregoire, T. G., & Trentini, S. 2018. The use of calibration weighting for variance estimation under systematic sampling: applications to forest cover assessment. Journal of Agricultural, Biological, and Environmental Statistics 23(3) 358-373. doi.org/10.1007/s13253-018-0325-x

 
Gregoire, T. G.& Affleck, D.L.R.A. 2018. Estimating desired sample size following simple random sampling of a skewed population. The American Statistician 72(2) 184-190.
 
Salas, C., Gregoire, T. G., Fuentes-Ramirez, A., Altamirano, A., and Yaitul, V. 2018. A study on the statistical effects of unbalanced data when fitting logistic regression models in ecology. Ecological Indicators 85: 502-508.
 
Saarela, S., Holm, S., Healey, S. P., Andersen, H-E., Petersson, H., Prentius W., Patterson, P. L. , Næsset, E. , Gregoire, T. G. and Ståhl, S. 2018.Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data. Remote Sensing 10, 1832  doi: 10.3390/rs10111832