Adams T, Brack C, Farrier T, Pont D, Brownlie R (2011) So you want to use LiDAR? A guide on how to use LiDAR in forestry. N Z J Forest 55(4):19–23
Google Scholar
Balenović I, Alberti G, Marjanović H (2013) Airborne laser scanning - the status and perspectives for the application in the South-East European Forestry. South-East Eur For 4(2):59–79. https://doi.org/10.15177/seefor.13-07
Article
Google Scholar
Bergseng E, Ørka HO, Næsset E, Gobakken T (2015) Assessing forest inventory information obtained from different inventory approaches and remote sensing data sources. Ann Forest Sci 72(1):33–45
Article
Google Scholar
Bolduc P, Lowell K, Edwards G (1999) Automated estimation of localized forest volume from large-scale aerial photographs and ancillary cartographic information in a boreal forest. Int J Remote Sens 20:3611–3624. https://doi.org/10.1080/014311699211237
Article
Google Scholar
Bolton DK, White JC, Wulder MA, Coops NC, Hermosilla T, Yuan X (2018) Updating stand-level forest inventories using airborne laser scanning and Landsat time series data. Int J Appl Earth Obs Geoinf. https://doi.org/10.1016/j.jag.2017.11.016
Bouvier M, Durrieu S, Fournier R, Saint-Geours N, Guyon D, Grau E, De Boissieu F (2019) Influence of sampling design parameters on biomass predictions derived from airborne LiDAR data. Can J Remote Sens. https://doi.org/10.1080/07038992.2019.1669013
Bruchwald A (1999) Dendrometria. Wydawn, Warszawa ISBN:83-00-02889-7
Google Scholar
Bruchwald A, Dudek A, Michalak K, Rymer-Dudzińska T, Wróblewski L, Zasada M (2000) Wzory empiryczne do określania wysokości i pierśnicowej liczby kształtu grubizny drzewa (empirical formulae for defining height and dbh shape figure of thick wood). Sylwan 10:5–13 (in Polish)
Google Scholar
Bujang MA, Sa’at N, Sidik TMITAB (2017) Determination of minimum sample size requirement for multiple linear regression and analysis of covariance based on experimental and non-experimental studies. Epidemiol Biostat Public Health. https://doi.org/10.2427/12117
Coomes DA, Safka D, Shepherd J, Dalponte M, Holdaway R (2018) Airborne laser scanning of natural forests in New Zealand reveals the influences of wind on forest carbon. Forest Ecosyst 5:10. https://doi.org/10.1186/s40663-017-0119-6
Article
Google Scholar
DGLLP (2015) Appendix 1 of order no. 33. The State Forests National Forest Holding (in Polish)
EEA (2017) Forest: growing stock, increment and fellings. https://www.eea.europa.eu/data-and-maps/indicators/forest-growing-stock-increment-and-fellings-3/assessment. Accessed 15 Jun 2018
Google Scholar
Elith J, Leathwick JR, Hastie T (2008) A working guide to boosted regression trees. J Anim Ecol 77(4):802–813. https://doi.org/10.1111/j.1365-2656.2008.01390.x
Article
PubMed
CAS
Google Scholar
Ene LT, Næsset E, Gobakken T, Gregoire TG, Göran S, Holm S (2013) A simulation approach for accuracy assessment of two-phase post-stratified estimation in large-area LiDAR biomass surveys. Remote Sens Environ 133:210–224. https://doi.org/10.1016/j.rse.2013.02.002
Article
Google Scholar
Eurostat (2018) Labour cost levels by NACE Rev. 2 activity. http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lc_lci_lev&lang=en. Accessed 10 Apr 2018
Google Scholar
Evans D, Roberts S, Parker R (2006) LiDAR - a new tool for forest measurements? Forest Chron. https://doi.org/10.5558/tfc82211-2
Even B, Ørka HO, Næsset E, Gobakken T (2015) Assessing forest inventory information obtained from different inventory approaches and remote sensing data sources. Ann Forest Sci 72(1):33–45
Article
Google Scholar
FAO (2004) National forest inventory. Field manual template http://www.fao.org/3/ae578e/AE578E00.htm Accessed14 May 2018
Google Scholar
Fassnacht FE, Latifi H, Hartig F (2018) Using synthetic data to evaluate the benefits of large field plots for forest biomass estimation with LiDAR. Remote Sens Environ. https://doi.org/10.1016/j.rse.2018.05.007
FMM (2012) Forest management manual. In: Święcicki Z (ed) Instrukcja Urządzania Lasu cz. 1. Ośrodek Rozwojowo-Wdrożeniowy Lasów Państwowych w Bedoniu, Andrespol (in Polish)
Gieruszyński T (1948) Zastosowanie fotogrametrii przy urządzaniu gospodarstw leśnych. Wydawnictwa pomocnicze i techniczno-gospodarcze, Instytut Badawczy Leśnictwa, Seria B, Nr 16 (in Polish)
Gobakken T, Korhonen L, Næsset E (2013) Laser-assisted selection of field plots for an area-based forest inventory. Silv Fenn 47(5):943. https://doi.org/10.14214/sf.943
Article
Google Scholar
Gobakken T, Næsset E (2008) Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data. Can J For Res 38:1095–1109. https://doi.org/10.1139/X07-219
Article
Google Scholar
Gobakken T, Næsset E, Nelson R, Bollandsås OM, Gregoire TG, Ståhl G, Holm S, Ørka HO, Astrup R (2012) Estimating biomass in Hedmark County, Norway using national forest inventory field plots and airborne laser scanning. Remote Sens Environ. https://doi.org/10.1016/j.rse.2012.01.025
Green SB (1991) How many subjects does it take to do a regression analysis? Multivar Behav Res 26:499–510. https://doi.org/10.1207/s15327906mbr2603_7
Article
CAS
Google Scholar
Harris RJ (1985) A primer of multivariate statistics, 2nd edn. Academic Press, New York
Google Scholar
Helms JA (1998) The dictionary of forestry. Society of American Foresters, Bethesda
Google Scholar
Holopainen M, Vastaranta M, Juha H (2014) Outlook for the next generation’s precision forestry in Finland. Forests. 5:1682–1694. https://doi.org/10.3390/f5071682
Article
Google Scholar
Hugershoff R (1911) Die Photogrammetrie und ihre Bedeutung fUr das Forstwesen. Tharander forstliches Jahrbuch 62:123–132 (in German)
Google Scholar
Johnson L, Debora & Norman JK, Hann D (2004) The importance of forest stand-level inventory to sustain multiple forest values in the presence of endangered species. Develop change. https://www.thinkswap.com/au/anu/pols2011-development-and-change/importance-forest-stand-level-inventory-sustain-multiple. Accessed 10 Apr 2018
Google Scholar
Jung SL, Mui HP (2010) Estimation of stand volume of conifer forest: a Bayesian approach based on satellite-based estimate and forest register data. Forest Sci Technol 6(1):7–17. https://doi.org/10.1080/21580103.2010.9656352
Article
Google Scholar
Junttila V, Kauranne T, Leppänen V (2010) Estimation of forest stand parameters from airborne laser scanning using calibrated plot databases. For Sci 56:257–270
Google Scholar
Kangas A, Gobakken T, Puliti S, Hauglin M, Næsset E (2018) Value of airborne laser scanning and digital aerial photogrammetry data in forest decision making. Silv Fenn. https://doi.org/10.14214/sf.9923
Kankare V, Ivan I, Singleton A, Horák J, Inspektor T (2017) Outlook for the single-tree-level forest inventory in Nordic countries. In: Igor I, Alex S, Jiri H, Tomas I (eds) The rise of big spatial data. Lecture notes in geoinformation and cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-45123-7_14
Chapter
Google Scholar
Kauranne T, Pyankov S, Junttila V, Kedrov A, Tarasov A, Kuzmin A, Peuhkurinen J, Villikka M, Vartio V-M, Sirparanta S (2017) Airborne laser scanning based forest inventory: comparison of experimental results for the perm region, Russia and prior results from Finland. Forests 8:72. https://doi.org/10.3390/f8030072
Article
Google Scholar
Knofczynski TG (2017) Sample sizes for predictive regression models and their relationship to correlation coefficients. J Math Sci Math Educ 12(2) http://www.msme.us/2017-2-2.pdf. Accessed 10 Apr 2018
Köhl M, Magnussen SS, Marchetti M (2006) Sampling methods, remote sensing and GIS multiresource forest inventory. Trop Forest ISBN: 3540325727, 9783540325727
Koivuniemi J, Korhonen KT (2006) Inventory by compartments. In: Kangas A, Maltamo M (eds) Forest inventory – methodology and applications, Managing Forest ecosystems, vol 10. Springer, Dordrecht, pp 271–278
Chapter
Google Scholar
Leeuwen M, Nieuwenhuis M (2010) Retrieval of forest structural parameters using LIDAR remote sensing. Eur J Forest Res 129:749–770. https://doi.org/10.1007/s10342-010-0381-4
Article
Google Scholar
Mäkelä H, Pekkarinen A (2004) Estimation of forest stand volumes by Landsat TM imagery and stand-level field-inventory data. Forest Ecol Manag 196(2–3):245–255. https://doi.org/10.1016/j.foreco.2004.02.049
Article
Google Scholar
Maltamo M, Eerikäinen K, Pitkänen J, Hyyppä J, Vehmas M (2004) Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions. Remote Sens Environ 90(3):319–330. ISSN 0034-4257. https://doi.org/10.1016/j.rse.2004.01.006
Article
Google Scholar
Maltamo M, Packalen P (2014) Species-specific management inventory in Finland. Forest Appl Airborne Laser Scan. https://doi.org/10.1007/978-94-017-8663-8_12
McInerney D, Suarez MJ, Nieuwenhuis M (2011) Extending forest inventories and monitoring programmes using remote sensing: a review. Irish Forest 68:6–22
Google Scholar
Mcroberts R, Næsset E, Gobakken T (2013) Inference for lidar-assisted estimation of forest growing stock volume. Remote Sens Environ 128:268–275. https://doi.org/10.1016/j.rse.2012.10.007
Article
Google Scholar
Miścicki S, Stereńczak K (2013) Określanie miąższości i zagęszczenia drzew w drzewostanach centralnej Polski na podstaie danych lotniczego skanowania laserowego w dwufazowej metodzie inwentaryzacji zasobów drzewnych. Leśne Prace Badawcze 74:127–136 (in Polish)
Google Scholar
Montealegre A, Lamelas M, Riva J, García-Martín A, Escribano F (2016) Use of low point density ALS data to estimate stand-level structural variables in Mediterranean Aleppo pine forest. Forestry. https://doi.org/10.1093/forestry/cpw008
Mozgeris G (2008) Estimation and use of continuous surfaces of forest parameters: options for Lithuanian forest inventory. Baltic Forest 14(2):176–184
Google Scholar
Næsset E (1997) Estimating timber volume of forest stands using airborne laser scanner data. Remote Sens Environ 61:246–253
Article
Google Scholar
Næsset E (2002) Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sens Environ 80(1):88–99. https://doi.org/10.1016/S0034-4257(01)00290-5
Article
Google Scholar
Næsset E (2014) Area-based inventory in Norway – from innovation to an operational reality. In: Matti M, Erik N, Jari V (eds) Forestry applications of airborne laser scanning: concepts and case studies, vol 27, pp 215–240. https://doi.org/10.1007/978-94-017-8663-8_11
Chapter
Google Scholar
Næsset E, Bjerknes KO (2001) Estimating tree heights and number of stems in young forest stands using airborne laser scanner data. Remote Sens Environ 78:328–340
Article
Google Scholar
Næsset E, Gobakken T, Holmgren J, Hyyppä H, Hyyppä J, Maltamo M, Nilsson M, Olsson H, Persson Å, Söderman U (2004) Laser scanning of forest resources: the Nordic experience. Scand J Forest Res 19(6):482–499. https://doi.org/10.1080/02827580410019553
Article
Google Scholar
Nichiforel L, Keary K, Deuffic P, Weiss G, Thorsen B, Winkel G, Avdibegovic M, Dobšinská Z, Feliciano D, Gatto P, Górriz ME, Hoogstra-Klein M, Hrib M, Hujala T, Jager L, Jarský V, Jodłowski K, Lawrence A, Lukmine D, Bouriaud L (2018) How private are Europe’s private forests? A comparative property rights analysis. Land Use Policy doi:https://doi.org/10.1016/j.landusepol.2018.02.034
Packalén P, Pitkänen J, Maltamo M (2008) Comparison of individual tree detection and canopy height distribution approaches: a case study in Finland. Proceedings of SilviLaser 2008, 8th International Conference on LiDAR applications in Forest Assessment and Inventory, Heriot-Watt University, Edinburgh, UK, 17-19 September, 2008, pp 22-29
Pasalodos-Tato M (2010) Optimising forest stand management in Galicia, North-Western Spain. Dissertationes Forestales. Doi:https://doi.org/10.14214/df.102
Pont D, Watt M, Adams T, Marshall H, Lee J, Crawley D, Pete W (2012) Modelling variation in Pinus radiata stem velocity from area and crown-based LiDAR metrics. N Z J Forest Sci 43:1. https://doi.org/10.1186/1179-5395-43-1
Article
Google Scholar
R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna https://www.R-project.org/. Accessed 20 July 2018
Google Scholar
Redmond J, Gschwantner T, Riedel T, Alberdi I, Vidal C, Bosela M, Fischer C, Hernández L, Kučera M, Kuliešis A, Tomter S, Vestman M, Lanz A (2016) Comparison of wood resource assessment in national forest inventories. In: Claude V, Iciar AA, Laura HM, John JR (eds) National Forest Inventories: assessment of wood availability and use. Springer, Cham
Google Scholar
Roussel JR, Auty D, De Boissieu F, Meador AS (2018) Package lidR - Airborne LiDAR data manipulation and visualization for forestry applications. https://github.com/Jean-Romain/lidR. Accessed 20 July 2018
Google Scholar
Ruiz LA, Hermosilla T, Mauro F, Godino M (2014) Analysis of the influence of plot size and LiDAR density on forest structure attribute estimates. Forests 5(5):936–951. https://doi.org/10.3390/f5050936
Article
Google Scholar
Saarela S, Schnell S, Grafström A, Tuominen S, Nordkvist K, Hyyppä J, Kangas A, Ståhl G (2015) Effects of sample size and model form on the accuracy of model-based estimators of growing stock volume. Can J Forest Res 45:1524–1534. https://doi.org/10.1139/cjfr-2015-0077.
Article
Google Scholar
Siipilehto J (2000) A comparison of two parameter prediction methods for stand structure in Finland. Silv Fenn 34(4):617. https://doi.org/10.14214/sf.617
Article
Google Scholar
Smreček R, Danihelová Z (2013) Forest stand height determination from low point density airborne laser scanning data in Roznava Forest enterprise zone (Slovakia). iForest - Biogeosci Forest 6:48–54. https://doi.org/10.3832/ifor0767-006
Article
Google Scholar
Ståhl G, Saarela S, Schnell S, Holm S, Breidenbach J, Healey S, Patterson P, Magnussen S, Næsset E, Mcroberts R, Gregoire T (2016) Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation. Forest Ecosyst 3:5. https://doi.org/10.1186/s40663-016-0064-9
Article
Google Scholar
Stereńczak K (2010) Airborne laser scanner technology as a source of data for semi-automatic forest inventory. Sylwan 154:88–99 (in Polish)
Google Scholar
Stereńczak K, Lisańczuk M, Parkitna K, Mitelsztedt K, Mroczek P, Miścicki S (2018) The influence of number and size of sample plots on modelling growing stock volume based on airborne laser scanning. Drewno 61(201). https://doi.org/10.12841/wood.1644-3985.D11.04
The Forests Act (1991) Official journal of laws 05.45.435. https://www.lasy.gov.pl/pl/publikacje/in-english/the-act-on-forests/view. Accessed 20 July 2018 (in Polish)
Google Scholar
Tompalski P, Coops NC, White JC, Wulder MA (2015) Enriching ALS-derived area-based estimates of volume through tree-level downscaling. Forests 6:2608–2630
Article
Google Scholar
Tomppo E (1991) Satellite image-based national forest inventory of Finland. Int Arch Photogr Remote Sensing 28:419424 Proceedings of the Symposium on Global and Environmental Monitoring, Techniques and Impacts, 1721 Sept 1990, Victoria, British Columbia, Canada
Google Scholar
Tonolli S, Dalponte M, Vescovo L, Rodeghiero M, Bruzzone L, Gianelle D (2010) Mapping and modeling forest tree volume using forest inventory and airborne laser scanning. Eur J Forest Res 130:569–577. https://doi.org/10.1007/s10342-010-0445-5
Article
Google Scholar
Turner R, Goodwin N, Friend J, Mannes D, Rombouts J, Haywood A (2011) A national overview of airborne Lidar application in Australian forest agencies. SilviLaser 2011, Oct 16–19. Hobart, TAS, AU
Vauhkonen J, Ørka H, Holmgren J, Dalponte M, Heinzel J, Koch B (2014) Tree species recognition based on airborne laser scanning and complementary data sources. In: Matti M, Erik N, Jari V (eds) Forestry applications of airborne laser scanning. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8663-8_7
Chapter
Google Scholar
Vidal C, Alberdi I, Hernández L, Redmond JJ (2016) National forest inventories, assessment of wood availability and use. Springer International Publishing, Switzerland. https://doi.org/10.1007/978-3-319-44015-6
Book
Google Scholar
Voorhis C, Morgan B (2007) Understanding power and rules of thumb for determining sample size. Quant Method Psychol. https://doi.org/10.20982/tqmp.03.2.p043
Watt M, Adams T, Gonzalez AS, Marshall H, Watt P (2013) The influence of LiDAR pulse density and plot size on the accuracy of New Zealand plantation stand volume equations. N Z J Forest Sci 43:15. https://doi.org/10.1186/1179-5395-43-15
Article
Google Scholar
White J, Wulder M, Buckmaster G (2014) Validating estimates of merchantable volume from airborne laser scanning (ALS) data using weight scale data. Forest Chron 90:378–385. https://doi.org/10.5558/tfc2014-072
Article
Google Scholar
White J, Wulder M, Whitehead R (2013) A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area based approach. BC Forest Profess 20(6):20–21
Google Scholar
White JC, Nicholas CC, Michael AW, Mikko V, Thomas H, Piotr T (2016) Remote sensing technologies for enhancing forest inventories: a review. Can J Remote Sens 42(5):619–641. https://doi.org/10.1080/07038992.2016.1207484
Article
Google Scholar
White JC, Piotr T, Mikko V, Michael AW, Ninni S, Christoph S, Nicholas CC (2017) A model development and application guide for generating an enhanced forest inventory using airborne laser scanning data and an area-based approach. Canadian Forest Service, Canadian Wood Fibre Centre, Natural Resources, Canada. Information report FI-X-018
Wilson E (1920) The use of seaplanes in forest mapping. J Forest 18(1):1–5. https://doi.org/10.1093/jof/18.1.1
Article
Google Scholar
Woods M, Pitt D, Penner M, Lim K, Nesbitt D, Etheridge D, Treitz P (2011) Operational implementation of a LiDAR inventory in boreal Ontario. Forest Chron 87:512–528. https://doi.org/10.5558/tfc2011-050
Article
Google Scholar
Wulder M (1998) Optical remote-sensing techniques for the assessment of forest inventory and biophysical parameters. Prog Phys Geogr 22:449. https://doi.org/10.1191/030913398675385488
Article
Google Scholar
Wulder MA, Bater CW, Coops NC, Hilker T, White JC (2008) The role of LiDAR in sustainable forest management. For Chron 84(6):807–826. https://doi.org/10.5558/tfc84807-6
Article
Google Scholar
Yang TR, Kershaw JA, Weiskittel AR, Lam TY, McGarrigle E (2019) Influence of sample selection method and estimation technique on sample size requirements for wall-to-wall estimation of volume using airborne LiDAR. Forestry 92(3):311–323. https://doi.org/10.1093/forestry/cpz014
Article
Google Scholar
Zygmunt R, Banaś J, Bujoczek L, Zięba S (2017) Monetary value tariff of timber calculated using databases of forests. Sylwan. 161(2):91–100
Google Scholar