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Applied Statistics in Forestry and Environmental Sciences

Homepage of Lauri Mehtätalo

 

Teaching

Research

Publications

Curriculum vitae

Presentations

R-codes

Textbook

Textbook monograph

    1. Mehtätalo, Lauri and Lappi, Juha 2020. Biometry for Forestry and Environmental Data: with examples in R. New York: Chapman and Hall/CRC. 426 p. https://doi.org/10.1201/9780429173462

 

Refereed publications

    1. Kansanen, K., Packalen, P. Maltamo, M. and Mehtätalo, L. 2020. Horvitz-Thompson-like estimation with distance-based detection probabilities for circular plot sampling of forests. Biometrics (accepted). IF: 1.827 , JUFO: 2. Download
    2. Karjalainen, T., Mehtätalo, L., Packalen, P., Gobakken, T. Nęsset, E. and Maltamo, M. 2020. Field calibration of merchantable and sawlog volumes in airborne laser scanning -based forest inventories. Canadian Journal of Forest Research IF: 1.812 , JUFO: 3. Download
    3. Ikonen, P., Rantala, M., Miettinen, J., Kuittinen, S., Hujala, T., Mehtätalo, L. and Pappinen, A. 2020. Grounds for improving the implementation of game-oriented forest management - A double sampling survey of Finnish forest owners and professionals. Forest Policy and Economics 119: 102266. IF: 3.139 , JUFO: 2. Download
    4. Nghikembua M., Marker L.L. Brewer, B., Mehtätalo, L., Appiah, M. and Pappinen, A. 2020. Response of wildlife to bush thinning on the north central freehold farmlands of Namibia. Forest Ecology and Management 473: 118330. IF: 3.126 , JUFO: 3. Download
    5. Melin, M., Mehtätalo, L., Helle, P., Ikonen, K. and Packalen, T. 2020. Decline of the boreal willow grouse (Lagopus lagopus) has been accelerated by more frequent snow-free springs. Scientific reports 10: 6987. IF: 4.525 , JUFO: 1. Download
    6. Bronisz, K. and Mehtätalo, L. 2020. Seemingly Unrelated Mixed-Effects Biomass Models for Young Silver Birch Stands on Post-Agricultural Lands. Forests 11(4): 381. IF: 2.116 , JUFO: 1. Download
    7. Bronisz, K. and Mehtätalo, L. 2020. Mixed-effects Generalized height-diameter model for young silver birch stands on post-agricultural lands. Forest Ecology and Management 460: 117901. IF: 3.126 , JUFO: 3. Download
    8. Vospernik, S., Nothdurft, A. and Mehtätalo, L. 2020. Seasonal, medium-term and daily patterns of tree diameter growth in response to climate. Forestry: 93(1): 133-149. IF: 2.876 , JUFO: 2. Download
    9. Sobuj, N., Virjamo, V., Nissinen, K., Sivadasan, U., Mehtätalo, L., Nybakken, L., Peltola, H., and Julkunen-Tiitto, R. 2020. Responses of growth and phenolics accumulation to lateral bud removal in male and female saplings of Populus tremula (L.) under different climate treatments. Science of the Total Environment Volume 704, 135462. IF: 5.589 , JUFO: 2. Download
    10. Vrzakova, H., Begel, A., Mehtätalo, L. and Bednarik, R. 2020. Affect Recognition in Code Review: An In-situ Biometric Study of Reviewer's Affect. Journal of Systems and Software. 159: 110434. IF: 2.559, JUFO: 3. Download
    11. Kotivuori, E., Kukkonen, M., Mehtätalo, L., Maltamo, M., Korhonen, L., Packalen, P. 2019. Forest inventories for small areas using drone imagery without in-situ field measurements. Remote Sensing of Environment 237:111404. IF: 8.218, JUFO: 3. Download
    12. Thitz, P., Mehtätalo, L., Välimäki. P., Randriamanana, T., Lännenpää, M., Hagerman, A.E., Andersson, T., Julkunen-Tiitto, R., Nyman, T. 2019. Phytochemical Shift from Condensed Tannins to Flavonoids in Transgenic Betula pendula Decreases Consumption and Growth but Improves Growth Efficiency of Epirrita autumnata Larvae. Journal of Chemical Ecology (2019). IF: 3.151, JUFO: 1. Download
    13. Hou, Z., Mehtätalo, L. McRoberts, R.E., Ståhl, G., Rana, P., Siipilehto, J., Tokola, T., Xu, Q. 2019. Remote sensing-assisted data assimilation and simultaneous inference for forest inventory. Remote Sensing of Environment 234: 111431 IF: 8.218, JUFO: 3. Download
    14. Korrensalo, A., Mehtätalo, L., Alekseychik, P., Uljas, S., Mammarella, I., Vesala, T., Tuittila, E.-S. 2019. Varying Vegetation Composition, Respiration and Photosynthesis Decrease Temporal Variability of the CO2 Sink in a Boreal Bog. Ecosystems. https://doi.org/10.1007/s10021-019-00434-1. IF: 4.555, JUFO: 2. Download
    15. Kansanen, K., Vauhkonen, J., Lähivaara, T., Seppänen, A., Maltamo, M., Mehtätalo, L. 2019. Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching. ISPRS Journal of Photogrammetry and Remote Sensing 152: 66-78. https://doi.org/10.1016/j.isprsjprs.2019.04.007. IF 5.994, JUFO: 1. Download
    16. Laine, A.M., Mäkiranta, P., Mehtätalo, L., Korrensalo, A., Penttilä, T., Laiho, R. Minkkinen, K., Fritze H., Tuittila E.-S. 2019. Warming impacts on boreal fen CO2 exchange under wet and dry moisture scenario. Global Change Biology 25(6): 1995-2008. https://doi.org/10.1111/gcb.14617. IF 8.502, JUFO: 3. Download
    17. Packalen, P., Strunk, J., Packalen, T., Maltamo, M., Mehtätalo, L. 2019. Resolution dependence in an area-based approach to forest inventory with airborne laser scanning. Remote Sensing of Environment 224: 192-201. https://doi.org/10.1016/j.rse.2019.01.022. IF: 8.218, JUFO: 3. Download
    18. Laine, A.M., Mehtätalo, L., Tolvanen, A., Frolking, S., Tuittila, E-S. 2019. Impacts of drainage, restoration and warming on boreal wetland greenhouse gas fluxes, Science of The Total Environment 647: 169-181. https://doi.org/10.1016/j.scitotenv.2018.07.390. IF: 4.610, JUFO: 2. Download
    19. Toivakka, M., Pihlapuro, A., Tykkyläinen, M., Mehtätalo, L and Laatikainen, T. 2018. The usefulness of small-area-based socioeconomic characteristics in assessing the treatment outcomes of type 2 diabetes patients: a register-based mixed-effect study. BMC Public Health 2018(18):1258 https://doi.org/10.1186/s12889-018-6165-3. IF: 1.232, JUFO: 1. Download
    20. Levkoev E., Mehtätalo L., Luostarinen K., Pulkkinen P., Zhigunov A., Peltola H. (2018). Development of height growth and frost hardiness for one-year-old Norway spruce seedlings in greenhouse conditions in response to elevated temperature and atmospheric CO2 concentration. Silva Fennica vol. 52 no. 3 article id 9980. https://doi.org/10.14214/sf.9980. IF: 1.683, JUFO: 1. Download
    21. Nissinen K., Virjamo V., Mehtätalo, L., Lavola A., Valtonen A., Nybakken L., and Julkunen-Tiito R. 2018. A seven-year study of phenolic concentrations of the dioecious Salix myrsinifolia. Journal of Chemical Ecology 44(4): 416–430. IF: 2.385, JUFO: 1. Download
    22. Mäkiranta, P., Laiho, R., Mehtätalo, L., Straková, P., Sormunen, J., Minkkinen, K., Penttilä, T., Frize, H.m and Tuittila, E-S. 2018. Responses of phenology and biomass production of boreal fens to climate warming under different water-table level regimes. Global Change Biology 24(3): 944–956 . IF 8.502, JUFO: 3. Download
    23. Maltamo, M, Mehtätalo, L., Valbuena, R., Vauhkonen, J., and Packalen, P. 2018. Airborne laser scanning for tree diameter distribution modelling: a comparison of different modeling alternatives in a tropical single-species plantation. Forestry 91(1) 121–131, https://doi.org/10.1093/forestry/cpx041. IF: 2.232, JUFO: 1. Download
    24. Nissinen, K., Virjamo, V., Randriamanana, T., Sobuj, N., Sivadasan, U., Mehtätalo, L., Beuker, E., Julkunen-Tiitto, R., Nybakkenn, L. 2017. Responses of growth and leaf phenolics in European aspen (Populus tremula L.) to climate change during juvenile phase change. Canadian Journal of Forest Research 47(10): 1350-1363. DOI: 10.1139/cjfr-2017-0188. IF: 1.827, JUFO: 3. Download
    25. Thitz, P., Possen, B.J.H.M., Oksanen, E., Mehtätalo, L., Virjamo, V. and Vapaavuori E. 2017. Production of glandular trichomes responds to water stress and temperature in silver birch (Betula pendula Roth) leaves. Canadian Journal of Forest Research 47(8): 1075-1081, DOI: 10.1139/cjfr-2017-0036. IF: 1.827, JUFO: 3. Download
    26. Huuskonen,Hannu, Shikano Takahito, Mehtätalo Lauri, Kettunen Juho, Eronen Risto, Toiviainen Anni and Kekäläinen Jukka 2017. Anthropogenic environmental changes induce introgression in sympatric whitefish ecotypes. Biological Journal of the Linnean Society. doi https://doi.org/10.1093/biolinnean/blx010. IF: 1.984, JUFO: 1. Download
    27. Heinonen, T., Pukkala, T., Mehtätalo, L., Asikainen, A., Kangas, J., and Peltola, H. 2017. Scenario analyses for the effects of harvesting intensity on development of forest resources, timber supply, carbon balance and biodiversity of Finnish forestry. Forest Policy and Economics. 80: 80-96. IF 1.552, JUFO: 2. Download
    28. Lahtinen, H-M., Korkman, J., Laitila, A., and Mehtätalo, L. 2017. The effect of training on investigative interviewers’ attitudes and beliefs related to child sexual abuse. Investigative Interviewing: Research and Practice (II-RP) 8(1): 16-30. JUFO: 1. Download
    29. Cugunovs M., Tuittila E.-S., Mehtätalo L., Pekkola L., Sara-Aho I., Kouki J. 2017. Variability and patterns in forest soil and vegetation characteristics after prescribed burning in clear-cuts and restoration burnings. Silva Fennica vol. 51 no. 1 article id 1718. https://doi.org/10.14214/sf.1718. IF: 1.470, JUFO: 1. Download.
    30. Korrensalo, A., Hájek, T., Alekseychik, P., Rinne, J., Vesala, T., Mehtätalo, L., Mammarella, I., Tuittila, E-S. 2017. Species-specific temporal variation in photosynthesis as a moderator of peatland carbon sequestration. Biogeosciences, 14: 257-269. doi:10.5194/bg-14-257-2017. IF: 3.7, JUFO: 2. Download
    31. Valbuena, R., Maltamo, M., Mehtätalo, L. and Packalen, P. 2017. Key structural features of Boreal forests may be detected directly using L-moments from airborne lidar data. Remote Sensing of Environment 194: 437-446. IF: 6.393, JUFO: 3. Download
    32. Levkoev, E., Kilpeläinen, A., Luostarinen, K., Pulkkinen, P., Mehtätalo, L., Ikonen, V.-P., Jaatinen, R., Zhigunov, A., Kangas, J., Peltola, H. 2017. Differences in growth and wood density in clones and provenance hybrid clones of Norway spruce. Canadian Journal of Forest Research 47(3): 389-399, DOI: 10.1139/cjfr-2016-0285 IF: 1.827, JUFO: 3 Download
    33. Härkönen, L., Hyvärinen, P., Mehtätalo, L. & Vainikka, A. 2017. Growth, survival and social learning in the first hatchery generation of Eurasian perch (Perca fluviatilis). Aquaculture 466: 64–71. http://dx.doi.org/10.1016/j.aquaculture.2016.09.027. IF :1.893, JUFO: 2. Download
    34. Palander, T., Kärhä, K. and Mehtätalo, L. 2017. Applying polynomial regression modeling to productivity analysis of sustainable stump harvesting. Scandinavian Journal of Forest Reseach 32: 204-212. http://dx.doi.org/10.1080/02827581.2016.1238957. IF: 1.056, JUFO: 1. Download
    35. Melin, M., Mehtätalo, L., Miettinen, J., Tossavainen, S and Packalen, P. 2016. Forest structure as a determinant of grouse brood occurrence - An analysis linking LiDAR data with presence/absence field data. Forest Ecology and Management 380: 202–211. http://dx.doi.org/10.1016/j.foreco.2016.09.007. IF: 2.826, JUFO: 3. Download
    36. Salam, M.M.A., Kaipiainen, E., Mohsin, M., Villa, A., Kuittinen, S., Pulkkinen, P., Pelkonen, P., Mehtätalo, L., Pappinen, A. 2016. Effects of contaminated soil on the growth performance of young Salix (Salix schwerinii E. L. Wolf) and the potential for phytoremediation of heavy metals Journal of environmental management 183 (3) 467–477. 10.1016/j.jenvman.2016.08.082 IF: 3.131, JUFO: 1. Download
    37. Kansanen, K., Vauhkonen, J., Lähivaara, T., Mehtätalo, L. 2016. Stand density estimators based on individual tree detection and stochastic geometry. Canadian Journal of Forest Research 46(11): 1359-1366. 10.1139/cjfr-2016-0181. IF: 1.657, JUFO: 3. Download
    38. Korrensalo, A., Hájek, T., Vesala, T., Mehtätalo, L., Tuittila, E-S. 2016. Variation in photosynthetic properties among bog plants. Botany 94(12): 1127-1139, 10.1139/cjb-2016-0117. IF: 2.88, JUFO: 1. Download
    39. Laine, A.M., Tolvanen, A., Mehtätalo, L. and Tuittila, E.-S. 2016. Vegetation structure and photosynthesis respond rapidly to restoration in young coastal fens. Ecology and Evolution 6(19): 6880-6891, DOI: 10.1002/ece3.2348. IF: 2.537, JUFO: 1. Download
    40. Linnakoski, R., Mahilainen, S., Harrington, A., Vanhanen, H., Eriksson, M., Mehtätalo, L., Pappinen, A., Wingfield, M.J. 2016. The seasonal succession of fungi associated with Ips typographus beetles and their phoretic mites in an outbreak region of Finland. PLOS ONE. 10.1371/journal.pone.0155622. IF: 3.234, JUFO: 1. Download.
    41. Peltoniemi, K., Laiho, R., Juottonen, H., Bodrossy, L., Kell, D.K., Minkkinen, K, Mäkiranta, P., Mehtätalo, L, Penttilä, T., Siljanen, H.M.P., Tuittila, E-S., Tuomivirta, T., Fritze, H. 2016. Responses of methanogenic and methanotrophic communities to warming in varying moisture regimes of two boreal fens, Soil Biology and Biochemistry, 97: 144-156. http://dx.doi.org/10.1016/j.soilbio.2016.03.007. IF: 3.932, JUFO: 3. Download
    42. de Souza Vismara, E., Mehtätalo, L., and Ferreira Batista, J. L. 2016. Linear mixed-effects models and calibration applied to volume models in two rotations of Eucalyptus grandis plantations. Canadian Journal of Forest Research 46(1): 132-141, 10.1139/cjfr-2014-0435. IF: 1.657, JUFO: 3. Download
    43. Melin, M., Matala, J., Mehtätalo, L., Suvanto, A., and Packalen, P. 2016. Detecting moose (Alces alces L.) browsing damage in young boreal forests from airborne laser scanning data. Canadian Journal of Forest Research 46 (1): 10-19. IF: 1.657, JUFO: 3. Download
    44. Melin, M., Matala, J., Mehtätalo, L., Pusenius, J. & Packalen, P. 2016. Ecological dimensions of airborne laser scanning - analyzing the role of forest structure in moose habitat use within a year. Remote Sensing of Environment (173): 238–247, DOI: 10.1016/j.rse.2015.07.025. Download. IF: 6.393, JUFO: 3.
    45. Salam, M. M. A., Pelkonen, P., Mehtätalo, L. and Gong, J. 2015. Using Stem Analysis Data for Modelling the Volume of Kinuyanagi Willow (Salix schwerinii E. L. Wolf). Baltic Forestry 21(2): 259-271. IF: 0.412, JUFO: 1. Download
    46. Maanavilja, L., Kangas, L., Mehtätalo, L. and Tuittila, E.-S. 2015. Rewetting of drained boreal spruce swamp forests results in rapid recovery of Sphagnum production. Journal of Applied Ecology 52(5): 1355–1363. DOI: 10.1111/1365-2664.12474. Download. IF: 4.754, JUFO: 2
    47. Mehtätalo, L.. de-Miguel, S, and Gregoire, T.G. 2015. Modeling height-diameter curves for prediction. Canadian Journal of Forest Research, 45(7): 826-837, 10.1139/cjfr-2015-0054. Download. IF: 1.657, JUFO: 3
    48. Mehtätalo, L., Virolainen, A., Tuomela, J. and Packalen, P. 2015. Estimating tree height distribution using low-density ALS data with and without training data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(4): 1432-1441. DOI: 10.1109/JSTARS.2015.2418675. Download. IF: 2.827, JUFO: 1
    49. Vuorio, V., Tikkanen, O-P., Mehtätalo, L. and Kouki, J. 2015. The effects of forest management on terrestrial habitats of a rare and a common newt species. European Journal of Forest Research 134(2): 377-388. Download. IF: 1.682, JUFO: 2
    50. Vauhkonen, J. and Mehtätalo, L. 2015. Matching remotely sensed and field measured tree size distributions. Canadian Journal of Forest Research 45(3): 353-363, 10.1139/cjfr-2014-0285. Download. IF: 1.657, JUFO: 3
    51. Laine, A.M., Ehonen, S., Juurola, E., Mehtätalo, L. and Tuittila, E.-S. 2015. Performance of late succession species along a chronosequence: Environment does not exclude Sphagnum fuscum from the early stages of mire development. Journal of Vegetation Science 26(2): 291–301.. Download. IF: 3.372, JUFO: 1
    52. Korpela, I., Mehtätalo, L., Markelin, L., Seppänen, A. and Kangas, A. 2014.Tree species identification in aerial image data using directional reflectance signatures. Silva Fennica 48(3): 1087. http://dx.doi.org/10.14214/sf.1087. Download
    53. de-Miguel, S., Mehtätalo, L., and Durkaya, A. 2014. Developing generalized, calibratable, mixed-effects meta-models for large-scale biomass prediction. Canadian Journal of Forest Research 44(6): 648-656. Download
    54. Kangas, L., Maanavilja, L., Hájek T., Juurola, E., Chimner, R.A., Mehtätalo, L. and Tuittila, E-S. 2014. Photosynthetic traits of Sphagnum and feather moss species in undrained, drained and rewetted boreal spruce swamp forests. Ecology and Evolution 4(4): 381–396. Download
    55. Mehtätalo, L., Nyblom, J., and Virolainen, A. 2014. A model-based approach for the recovery of forest attributes using ALS data. Book chapter in Maltamo, M., Næsset, E. and Vauhkonen, J. (editors). Forestry applications of airborne laser scanning- Concepts and Case Studies. Springer, Managing Forest Ecosystems 27, pp 193-211. Download
    56. Melin, M., Matala, J., Mehtätalo, L., Tiilikainen, R., Tikkanen, O-P., Maltamo, M., Pusenius, J.& Packalen, P. 2014. Moose (Alces alces) reacts to high summer temperatures by utilising thermal shelters in boreal forests – an analysis based on airborne laser scanning of the canopy structure at moose locations. Global Change Biology 20(4): 1115–1125. Download
    57. Mehtätalo, L., Peltola, H., Kilpeläinen, A. and Ikonen, V.-P. 2014. The response of basal area growth of Scots pine to thinning: A longitudinal analysis of tree-specific series using a nonlinear mixed-effects model. Forest Science 60 (4): pp. 636-644. DOI: http://dx.doi.org/10.5849/forsci.13-059. Download
    58. Valbuena, R. Packalen, P. Mehtätalo, L. Garcia-Abril, A. Maltamo, M. 2013. Lorenz curve descriptors for characterizing forest structure and dynamics by means of airborne laser scanning. Canadian Journal of Forest Research 43: 1063–1074. Download
    59. Siipilehto, J., Mehtätalo, L. 2013. Parameter recovery vs. parameter prediction for the Weibull distribution validated for Scots pine stands in Finland. Silva Fennica 47(4). Download
    60. Kilpeläinen, J., Räisänen, M., Mehtätalo, L., Sutinen, S., Rummukainen, A., Repo, T. Lehto, T. 2013. The longevity of Norway spruce responses to boron fertilisation. Forest Ecology and Management 307: 90–100. Download
    61. Comas, C., Mehtätalo, L. and Miina, J. 2013. Analysing space-time tree interdependencies based on individual tree growth functions. Stochastic Environmental Research and Risk Assessment 27 (7), pp 1673-1681. Download
    62. Melin, M., Packalén, P., Matala, J., Mehtätalo, L., and Pusenius, J. 2013. Assessing and modeling moose (Alces alces) habitats with Airborne laser scanning data. International journal of applied earth observation and geoinformation 23: 389–396. http://dx.doi.org/10.1016/j.jag.2012.11.004. Download.
    63. Höglund, H., Hujala, T., Pykäläinen, J. and Mehtätalo, L. 2012. Metsikkökohtaiset käsittelyvaihtoehdot metsänomistajan oppimisen ja päätöksenteon tukena. Metsätieteen aikakauskirja 4/2012. Download.
    64. Maltamo, M., Mehtätalo, L., Vauhkonen, J. and Packalen, P. 2012. Predicting and calibrating tree attributes by means of airborne laser scanning and field measurements. Canadian Journal of Forest Research 42: 1896–1907. Download
    65. Islam, Md. N., Pukkala, T., Kurttila, M., Mehtätalo, L. and Heinonen, T. 2012. Effects of forest inventory errors on the area and spatial layout of harvest blocks. Eur. J. For. Res. 131 (6): 1943-1955. doi: 10.1007/s10342-012-0645-2. Download
    66. de Miguel, S., Mehtätalo, L., Shater, Z., Kraid, B., and Pukkala, T. 2012. Evaluating marginal and conditional predictions of taper models in the absence of calibration data. Candadian Journal of Forest research 42(7): 1383-1394. Download
    67. Mehtätalo, L. and Nyblom, J. 2012. A model-based approach for ALS inventory: application for square grid spatial pattern. Forest Science 58(2): 106-118. Download
    68. Wallenius, T., Laamanen, R, Peuhkurinen J, Mehtätalo, L ja Kangas, A. 2012. Analysing the agreement between an Airborne Laser Scanning based forest inventory and a control inventory – a case in the state owned forests in Finland. Silva Fennica 46(1): 111–129. Download
    69. Zubizarreta-Gerendiain, A., Gort, J., Mehtätalo, L., Peltola, H., Venäläinen, A., and Pulkkinen, P. 2012. Effects of cambial age, clone and climatic factors on ring width and ring density in Norway spruce (Picea abies) in southeastern Finland. Forest Ecology and Management Volume 263:9–16. Download
    70. Kangas, A., Mehtätalo, L., Vanhatalo, K. and Mäkinen, A. 2011. Sensitivity of harvest decisions to errors in stand characteristics. Silva Fennica 45(4): 693–709. Download
    71. Vauhkonen, J., Mehtätalo, L. & Packalén, P. 2011. Combining tree height samples produced by airborne laser scanning and stand management records to estimate plot volume in Eucalyptus plantations. Canadian Journal of Forest Research 41:(8) 1649-1658. Download
    72. Gort, J., Mehtätalo, L., Peltola, H., Zubizarreta-Gerendian, A., Pulkkinen, P. and Venäläinen, A. 2011. Effects of spacing and genetic entry on radial growth and ring density development in Scots pine (Pinus sylvestris L.). Annals of Forest Science 68(7): 1233-1243, DOI: 10.1007/s13595-011-0117-8 . Download
    73. Packalen, P., Mehtätalo, L. and Maltamo, M. 2011. ALS-based estimation of plot volume and site index in a eucalyptus plantation with a nonlinear mixed-effect model that accounts for the clone effect. Annals of Forest Science 68(6): 1085-1092. Download
    74. Mehtätalo, L., Comas, C., Pukkala, T., and Palahi, M. 2011. Combining a predicted diameter distribution with an estimate based on a small sample of diameters. Can. J. For. Res. 41:750-762, 10.1139/x11-008. Download
    75. Peuhkurinen, J., Mehtätalo, L. and Maltamo, M. 2011. Comparing individual tree detection and the area-based statistical approach for the retrieval of forest stand characteristics using airborne laser scanning in Scots pine stands. Can. J. For. Res. 41(3): 583-598. Download
    76. Pietilä, I., Kangas, A., Mäkinen, A. and Mehtätalo, L. 2010. Influence of growth prediction errors on the expected losses from forest decisions. Silva Fennica 44(5): 829–843. Download
    77. Islam, N., Kurttila, M., Mehtätalo, L. and Pukkala, T. 2010. Inoptimality losses in forest management decisions caused by errors in an inventory based on airborne laser scanning and aerial photographs. Can. J. For. Res. 40: 2427–2438. Download
    78. Mäkinen, A., Kangas, A., and Mehtätalo, L. 2010. Correlations, distributions and trends in forest inventory errors and their effects on forest planning. Can. J. For. Res. 40: 1386–1396. Download
    79. Mehtätalo, L. and Nyblom, J 2009. Estimating forest attributes using observations of canopy height: a model-based approach. For. Sci. 55(5): 411-422. Download
    80. Maltamo, M., Packalen.P., Suvanto, A., Korhonen K.T., Mehtätalo, L. and Hyvönen, P 2009. Combining ALS and NFI ground truth data for forest management planning – a case study in Kuortane, Western Finland. Eur. J. For. Res. 128 (3): 305-317 Download
    81. Leskinen, P., Miina, J., Mehtätalo, L., and Kangas, A 2009. Model correlation in stochastic forest simulators - a case of multilevel multivariate model for establishment of regeneration. Ecological Modelling 220(4): 545-555. Download
    82. Islam, Md. N., Kurttila, M, Mehtätalo, L. and Haara, A 2009. The effects of measurement error in the basal area of dominated tree species on holding-level forest plan. Silva Fennica 43(1): 71-85 Download
    83. Mehtätalo, L., Gregoire, T.G. & Burkhart, H.E. 2008. Comparing strategies for modeling tree diameter percentiles from remeasured plots. Environmetrics 19: 529-548. Download
    84. Leppänen, V-J., Tokola, T., Maltamo, M., Mehtätalo, L. Pusa, T. and Mustonen, J. 2008. Automatic delineation of forest stands from lidar data. International archives of the photogrammetry, remote sensing and spatial information sciences. 38(4/C1). Proceedings of ISPRS workshop GEOBIA 2008, Calgary, Alberta, Canada. Download
    85. Kangas, A., Mehtätalo, L. & Maltamo, M. 2007. Modeling percentile-based basal area weighted diameter distribution. Silva Fennica 41(3): 425-440. Download
    86. Siipilehto, J., Sarkkola, S. & Mehtätalo, L. 2007. Comparing regression estimation techniques when predicting diameter distributions of Scots pine on drained peatlands. Silva Fennica 41(2): 333-349. Download
    87. Maltamo, M., Korhonen, K.T., Packalén, P., Mehtätalo, L. & Suvanto A 2007. Testing the usability of angle count sample plots as ground truth in ALS-based forest inventories. Forestry 80(1): 73-81. Download
    88. Mehtätalo, L., Maltamo, M. & Packalén, P. 2007. Recovering plot-specific diameter distribution and height-diameter curve using ALS based stand characteristics. International archives of photogrammetry, remote sensing and spatial information sciences 36(3/W52): 288-293. Proceedings of the ISPRS Workshop ‘Laser Scanning 2007 and SilviLaser 2007’ Espoo, September 12-14, 2007, Finland Download
    89. Mehtätalo, L. 2006. Eliminating the effect of overlapping crowns from aerial inventory estimates. Canadian Journal of Forest Research 36(7): 1649-1660. Download
    90. Mehtätalo, L., Maltamo, M., and Kangas, A 2006. The use of quantile trees in predicting the diameter distribution of a stand. Silva Fennica 40(3) 501-516. Download
    91. Lappi, J., Mehtätalo, L. and Korhonen, K.T. 2006. Generalizing sample tree information. in Kangas, A. and Maltamo, M (editors) Forest inventory - methodology & applications. Springer. Go to the book homepage
    92. Mehtätalo, L. 2005. Localizing a predicted diameter distribution using sample information. Forest Science 51(4): 292-302. Download A correction to the paper was published in Forest Science 52(3): 334. Download the correction.
    93. Mehtätalo, L. and Kangas, A. 2005. An approach to optimizing data collection in an inventory by compartments. Canadian Journal of Forest Research 35(1): 100-112. Download
    94. Mehtätalo, L. 2005. Height-diameter models for Scots pine and birch in Finland. Silva Fennica 39(1): 55-66. Download
    95. Mehtätalo, L. 2004. Predicting stand characteristics using limited measurements. FFRI, research reports 929. 39 p. + appendices I-V. (dissertation).
    96. Mehtätalo, L. 2004. A longitudinal height-diameter model for Norway spruce in Finland. Canadian Journal of Forest Research 34(1): 131-140. Download
    97. Mehtätalo, L. 2004. An algorithm for ensuring compatibility between estimated percentiles of diameter distribution and measured stand variables. Forest Science 50(1):20-32.Download
    98. Mehtätalo, L. 2002. Valtakunnalliset puukohtaiset tukkivähennysmallit männylle, kuuselle, koivuille ja haavalle. Metsätieteen aikakauskirja 4/2002: 575-594. Download
    99. Kangas J., Store R., Leskinen P. and Mehtätalo L. 2000. Improving the quality of landscape ecological forest planning by utilizing advanced decision-support tools. Forest Ecology And Management 132(2-3): 157-171 Download

 

Other publications

    1. Mehtätalo, L. 2019. Reporting modern statistical analyses: reproducible and transparent. Silva Fennica vol. 53 no. 3 article id 10257. IF: 1.683, JUFO: 1. Download
    2. Mehtätalo. L. ja Pukkala, T 2019. Ilmastonmuutoksen torjunta edellyttää maltillisia hakkuita. Helsingin Sanomat 1.4. 2019. Lue kirjoitus
    3. Vauhkonen. J. and Mehtätalo. L. 2014. Rethinking single-tree remote sensing: Histogram matching of remotely sensed and field-measured tree size distributions. In Karjalainen M et al. (Eds): Abstract book of theFinnish Remote Sensing Days 2013, 23–24 October, Espoo, Finland. Reports of the Finnish Geodetic Institute 2014:1, p. 19.
    4. Melin, M., Packalen, P., Matala, J., Mehtätalo, L., Tiilikainen, R-, Tikkanen, O-P., Pusenius, J., Maltamo, M. 2013. Adaptive behavior of GPS-collared moose against thermal stress detected with airborne laser scanning. Programme & Abstract Book, 31st IUGB Congress, 27.-29.08.2013 Brussels – Belgium.
    5. Hujala, T., Höglund, H., Mehtätalo, L. and Pykäläinen, J. 2012. Trialogical Learning – A Concept For Enhancing Interactive Forest Planning. Proceedings of IUFRO 3.08.00 Small-Scale Forestry Conference 2012: Science for Solutions 24-27 September 2012 Amherst, Massachusetts USA. pp. 58-63. Download
    6. Mehtätalo, L. Virolainen. A, Tuomela, J. and Nyblom, J. 2010. A model-based approach for estimating the height distribution of eucalyptus plantations using low-density ALS data. Proceedings of SilviLaser 2010, The 10th annual conference on lidar applications for assessing forest ecosystems. Freiburg, Germany. Download
    7. Packalen, P., Mehtätalo, L. and Maltamo, M. 2010. ALS based estimation of plot volume and site index in a eucalyptus plantation with a nonlinear mixed effect model that accounts for the clone effect. Proceedings of SilviLaser 2010, The 10th annual conference on lidar applications for assessing forest ecosystems. Freiburg, Germany. Download
    8. Mehtätalo, L., Kangas, A. and Vanhatalo K. O. Modelling the probability of incorrect harvest decisions due to errors of stand characteristics. In "Proceedings of 90th anniversary of the Forestry Faculty in Prague. Forest, Wildlife and Wood Sciences for Society Development. Prague 16. – 18. April, 2009" pp 143-156. Download
    9. Mehtätalo, L. 2008. Tilastomenetelmät tutkijan työkaluina. Metsätieteen aikakauskirja 2/2008. Pääkirjoitus. Download
    10. Mehtätalo, L. 2008. Forest Biometrics with examples in R. Lecture notes for the forest biometrics course. 400 pages. Download
    11. Mehtätalo, L. 2004. Metsikön läpimittajakauman ennustaminen metsikkötunnusten ja järjestystunnuslukupuiden avulla. University of Joensuu. Department of statistics. Laudatur thesis of a secondary subject. 31 p. Download
    12. Mehtätalo, L. 2000. Mäntyvaltaisen päätehakkuuleimikon läpimittajakauman ennustaminen ja kalibrointi eri puustotunnuksilla. University of Joensuu, Faculty of forestry. M.Sc Thesis. 65 p.
    13. Mehtätalo, L. 2002. MELA2002 ja uudet tukkivähennysmallit. In Nuutinen, T. & Kiiskinen, A. (toim.). MELA2002 ja käyttöpuun kuvaus. MELA-käyttäjäpäivä 7.5.2002 Joensuu. Metsäntutkimuslaitoksen tiedonantoja 865: 32-46.

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Last Updated: April 20, 2020