2024

• Schriver R, Sessions J, Strimbu BM. Landscape Restoration Using Individual Tree Harvest Strategies. Sustainability. 2024; 16(12):5124. https://doi.org/10.3390/su16125124
• West, T.; Strimbu, B.M. 2024. Elliott State Research Forest Timber Cruise, Oregon, 2015–2016. Data, 9, 16. https://doi.org/10.3390/data9010016

2023

• Wickramarathna, S., Goetz III, J., Souder, J., Protzman, B., Shepard, B., Herban, S., Mauro, F., Temesgen, H., & Strimbu, B. M. Assessment of herbaceous vegetation classification using orthophotos produced from the image acquired with unmanned aerial systems. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 51(3), 13227. https://doi.org/10.15835/nbha51313227
• Strimbu, B.M., and Valeriu-Norocel Nicolescu. 2023. Coppice Management for Young Sycamore Maple (Acer pseudoplatanus L.) Forests 14, no. 2: 297. https://doi.org/10.3390/f14020297

2022

• Morgan C.J., Powers M, Strimbu B.M. Estimating Tree Defects with Point Clouds Developed from Active and Passive Sensors. Remote Sensing. 2022; 14(8):1938. https://doi.org/10.3390/rs14081938
• Fang R and Strimbu B.M. Comparison of stem volume estimates from terrestrial point clouds for mature Douglas-fir (Pseudotsuga menziessi (Mirb.) Franco),  Information Processing in Agriculture 2022 https://doi.org/10.1016/j.inpa.2022.03.003

• West T, Sessions J, Strimbu BM. Steep Slope Harvest System Models for Small to Large Trees. Forests. 2022; 13(2):305. https://doi.org/10.3390/f13020305  

• de Oliveira Neto, R.R., Leite, H.G., Gleriani, J.M. and Strimbu, B.M. Estimation of Eucalyptus productivity using efficient artificial neural network. Eur J Forest Res 2022, 141: 129–151. https://doi.org/10.1007/s10342-021-01431-7

2021 

• Wickramarathna, S., Van Den Hoek, J., Strimbu, B.M.  Automated detection of individual Juniper tree location and forest cover changes using Google Earth Engine. Annals of Forest Research 2021, 64(1): 61 - 72. DOI: 10.15287/afr.2020.2145

• Strimbu, B.M., Paun.A., Amarioarei, A., Paun, M., Strimbu, V.F. Efficient synthetic generation of ecological data with preset spatial association of individuals. Canadian Journal of Forest Research. https://doi.org/10.1139/cjfr-2020-0490

• Souder J. and Strimbu B.M. Forest Chemicals in Trees to Tap: How Forest Practices Affect Oregon's Municipal Water edited by Jon Souder, pp 160-221, Oregon Forest Research Institute, Portland OR,  Aug 2021
• Strimbu B.M. , Souder J. and  Behan J. Natural Organic Matter and Disinfectant Byproducts in Trees to Tap: How Forest Practices Affect Oregon's Municipal Water edited by Jon Souder, pp 222-247, Oregon Forest Research Institute, Portland OR,  Aug 2021

• Garms , C.G. and Strimbu, B.M.Impact of stem lean on estimation of Douglas-fir (Pseudotsuga menziesii) diameter and volume using mobile lidar scans. Canadian Journal of Forest Research. https://doi.org/10.1139/cjfr-2020-0484

• Heffernan, S.; Strimbu, B.M. Estimation of Surface Canopy Water in Pacific Northwest Forests by Fusing Radar, Lidar, and Meteorological Data. Forests 2021, 12, 339. https://doi.org/10.3390/f12030339

• West, T.; Sessions, J.; Strimbu, B.M. Heuristic Optimization of Thinning Individual Douglas-Fir. Forests 2021, 12, 280. https://doi.org/10.3390/f12030280

• Strimbu, B.M., Amarioarei, A. & Paun, M. Nonlinear parsimonious forest modeling assuming normal distribution of residuals. Eur J Forest Res 140(3). https://doi.org/10.1007/s10342-021-01355-2

• Strimbu, B.M.; Mueller-Warrant, G.; Trippe, K. Agricultural Crop Change in the Willamette Valley, Oregon, from 2004 to 2017. Data, 6, 17. https://doi.org/10.3390/data6020017

2020

• Paun, M.; Gunaime, N.; Strimbu, B.M. Impact of Algorithm Selection on Modeling Ozone Pollution: A Perspective on Box and Tiao (1975). Forests, 11, 1311.

• Garms , C.G., Simpson, C.H., Parrish, C.E., Wing, M.G. and Strimbu, B.M. Assessing lean and positional error of individual mature Douglas-fir (Pseudotsuga menziesii) trees using active and passive sensors. Canadian Journal of Forest Research, 50 (11): 1228 - 1243

• Riddell, A.P., Fitzgerald. F.A.,Qi, C., and Strimbu, B.M. Classification Strategies for Unbalanced Binary Maps: Finding Ponderosa Pine (Pinus ponderosa) in the Willamette Valley. Remote Sensing 2020, 12(20), 3325

• Garms CG, Flores-Rentería L, Waring K, Whipple A, Wing MA, Strimbu BM Augmenting size models for Pinus strobiformis seedlings using dimensional estimates from unmanned aircraft systems. Canadian Journal of Forest Research, 50(9): 890-904
• Amarioarei, A., Paun, M., and Strimbu BM. Development of Nonlinear Parsimonious Forest Models Using Efficient Expansion of the Taylor Series: Applications to Site Productivity and Taper. Forests 11(4): 458-484
• Marin, Gh., Abrudan, I, and Strimbu BM. Regional Variability of the Romanian Main Tree Species Growth Using National Forest Inventory Increment Cores. Forests 11(4): 409-427
• Strimbu BM. Unmanned aerial systems for land monitoring. 81 p.  Oregon State University. ISBN 9781732664401

2019

• Marin, Gh., Abrudan, I, and Strimbu BM  2019. Increment cores of the National Forest Inventory from Romania. Mathematical and Computational Forestry & Natural-Resource Sciences 11(2): 294-302
• Strimbu BM, Qi C, Sessions J 2019. Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices. Remote Sensing 11(16): 1877-1897
• Maturbong B, Wing M, Strimbu BM, Burnett M. 2019. Forest inventory sensivity to UAS-based image processing algorithms. Annals of Forest Research  62(1)
• Fang R. and Strimbu B.M. 2019 Comparison of Mature Douglas-Firs’ Crown Structures Developed with Two Quantitative Structural Models Using TLS Point Clouds for Neighboring Trees in a Natural Regime Stand Remote Sensing 11(14): 1661-1687

2018

• Strimbu BM, Paun M, Popescu SC, Montes C. 2018. A scalar measure tracing tree species composition in space or time.Physica A: Statistical Mechanics and its Applications 512: 682-692
• Strimbu BM, Amarioarei A, McTague JP, Paun M 2018. A posteriori bias correction of three models used for environmental reporting. Forestry 91(1): 49-62
• Zhou, T., Popescu S.C., Lawing, A.M., Eriksson, M., Strimbu, B.M., Bukner, P.C. 2018. Bayesian and Classical Machine Learning Methods: A Comparison for Tree Species Classification with LiDAR Waveform Signatures. Remote Sensing 10(1): 39

2017

• Rong F and Strimbu BM 2017. Photogrammetric point cloud trees.  Mathematical and Computational Forestry and Natural-Resource Sciences 9(2) 30-33
• Strimbu, B. M., A. Amarioarei, and M. Paun. 2017. A parsimonious approach for modeling uncertainty within complex nonlinear relationships. Ecosphere 8(9):e01945. 10.1002/ecs2.1945
• Fang R and Strimbu B.M. 2017 Stem Measurements and Taper Modeling Using Photogrammetric Point Clouds. Remote Sensing 9 (7), 716-737
• Strimbu, B.M., Petritan, I.C., Montes, C., Biris, I.A., 2017. An assessment of the O-ring methodology using virgin stands of mixed European beech – Sessile oak. Forest Ecology and Management 384, 378-388.

2016

• Feldbacher, E., Paun, M., Reckendorfer, W., Sidoroff, M., Stanica, A., Strimbu, B., Tusa, I., Vulturescu, V., Hein, T., 2016. Twenty years of research on water management issues in the Danube Macro-region — past developments and future directions. Science of The Total Environment 572, 1297-1306.

2015

• Strimbu, V.F., Strimbu, B.M., 2015. A graph-based segmentation algorithm for tree crown extraction using airborne LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing 104, 30-43.
• Strimbu, B.M. and Burkhart H. 2015. Complex Forest Ecosystems: From Tree to Landscape. Forest Science 61(3): 409-410
• Brust, M.R., Strimbu, B.M., 2015. A networked swarm model for UAV deployment in the assessment of forest environments. In, 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), pp. 1-6.
• Strimbu, B. 2015. Dendrometry Field Manual. Scholar Archives@Oregon State University

2014

• Strimbu, B.M. 2014. Comparing the efficiency of intensity based forest inventories with sampling error based forest inventories. Forestry. 87(2): 249-255

2012

• Strimbu, B.M. and Paun, M. 2012. Sensitivity of forest plan value to parameters of simulated annealing Canadian Journal of Forest Research 48(1): 28-38
• Strimbu, B.M. (2012) Correction for bias of models with lognormal distributed variables in absence of original data. Annals of Forest Research 55(2): 265-279
• Strimbu, B.M. and Innes, J.L. (2012) Framework for assessing the impact of human activities on the environment: the impact of forest harvesting and petroleum drilling on habitat of moose (Alces alces) and marten (Martens americana) Biodiversity and Conservation 21(4): 933-955
• Walker MH, Murimi MW, Kim Y, Hunt A. Erickson D., Strimbu B. (2012) Multiple point-of-testing nutrition counseling sessions reduce risk factors for chronic disease among older adults. Journal of Nutrition in Gerontology and Geriatrics 31(2): 146-157

2011

• Strimbu, B.M. and Innes, J.L. (2011) An analytical platform for cumulative impact assessment based on multiple futures: the impact of petroleum drilling and forest harvesting on moose (Alces alces) and marten (Martes americana) habitats in northeastern British Columbia. Journal of Environmental Management 92(7): 1740-1752
• Strimbu, B.M. (2011) Modeling the travel distances of debris flows and debris slides: quantifying hillside morphology. Annals of Forest Research 54-1:119-134

2010

• Strimbu, B.M. (2010) Defining conditions for a measure describing the composition of mixed-species stands. Journal of Forests 125-6:11-16
• Strimbu, B.M., Innes, J.L. and Strimbu, V.F. (2010) A deterministic harvest scheduler using perfect bin-packing theorem. European Journal of Forest Research 129-5:961-974
• Long, W.D. and Strimbu, B.M. (2010) Generating 3D forests for resources inventory. Journal of Forests 125-3:32-37

2009

• Strimbu, B.M., Hickey, G.M., Strimbu, V.G. and Innes, J.L. (2009) On the use of statistical tests with non-normally distributed data in landscape change detection. Forest Science 55-1:72-83

2005

• Bogdan M Strimbu, Gordon M Hickey, and Vladimir G Strimbu (2005) Forest conditions and management under rapid legislation change in Romania. Forestry Chronicle 81(3): 350-358