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Articles containing the keyword 'inventories'

Category : Article

article id 5554, category Article
Simo Poso, Mark-Leo Waite. (1995). Calculation and comparison of different permanent sample plot types . Silva Fennica vol. 29 no. 2 article id 5554. https://doi.org/10.14214/sf.a9205
Keywords: forest inventories; forest monitoring; sampling; optimum sampling unit; permanent plot analysis
Abstract | View details | Full text in PDF | Author Info

A calculation procedure is presented for calculating and analysing remeasured permanent sample plots. Data for eight different fixed and variable size plot types were simulated on the basis of two stands whose trees were mapped and measured in 1982 and 1986. The accuracy and efficiency of the plot types were assessed and compared.

The calculation procedure is based on tree-wise expansion factors and the division of tree sampled into state/measurement classes. Nine classes were required for variable size plots and six for fixed size plots. A relascope plot with basal-area factor 1 (m2/ha) proved to be most efficient for estimating basal-area at a given time and a fixed size circular plot with radius 10 m for estimating basal-area increment over a given time period.

The main problems were related to the estimation of non-measurable variables, e.g., the initial diameters of ingrowth trees, i.e., trees having passed the threshold size during the measurement period. Most problematic were cut trees belonging to the ingrowth or sample enlargement classes. It is nevertheless thought that the system is appropriate for monitoring forest changes and making sensitivity analyses with permanent sample plots.

  • Poso, E-mail: sp@mm.unknown (email)
  • Waite, E-mail: mw@mm.unknown
article id 5553, category Article
Annika Kangas, Kari T. Korhonen. (1995). Generalizing sample tree information with semiparametric and parametric models. Silva Fennica vol. 29 no. 2 article id 5553. https://doi.org/10.14214/sf.a9204
Keywords: forest inventories; mixed models; volume; nonparametric models; semiparametric models
Abstract | View details | Full text in PDF | Author Info

Semiparametric models, ordinary regression models and mixed models were compared for modelling stem volume in National Forest Inventory data. MSE was lowest for the mixed model. Examination of spatial distribution of residuals showed that spatial correlation of residuals is lower for semiparametric and mixed models than for parametric models with fixed regressors. Mixed models and semiparametric models can both be used for describing the effect of geographic location on stem form.

  • Kangas, E-mail: ak@mm.unknown (email)
  • Korhonen, E-mail: kk@mm.unknown
article id 5524, category Article
Annika Kangas. (1994). Classical and model based estimators for forest inventory. Silva Fennica vol. 28 no. 1 article id 5524. https://doi.org/10.14214/sf.a9158
Keywords: models; forest inventories; estimation; systematic cluster sampling; covariance structure
Abstract | View details | Full text in PDF | Author Info

In this study, model-based and design-based inference methods are used for estimating mean volume and its standard error for systematic cluster sampling. Results obtained with models are compared to results obtained with classical methods. The data are from the Finnish National Forest Inventory. The variation of volume in ten forestry board districts in Southern Finland is studied. The variation is divided into two components: trend and correlated random errors. The effect of the trend and the covariance structure on the obtained mean volume and standard error estimates is discussed. The larger the coefficient of determination of the trend model, the smaller the model-based estimates of standard error, when compared to classical estimates. On the other hand, the wider the range and level of autocorrelation between the sample plots, the larger the model-based estimates of standard error.

  • Kangas, E-mail: ak@mm.unknown (email)
article id 5520, category Article
Kari T. Korhonen. (1993). Mixed estimation in calibration of volume functions of Scots pine. Silva Fennica vol. 27 no. 4 article id 5520. https://doi.org/10.14214/sf.a15681
Keywords: Pinus sylvestris; models; forest inventories; volume; estimation
Abstract | View details | Full text in PDF | Author Info

Regression models for estimating stem volume of Scots pine (Pinus sylvestris L.) were constructed using sample tree data measured in the 7th and 8th National Forest Inventory of Finland. Stem volume were regressed on diameter, basal area of growing stock, and geographic location. The results of the study show that using second order trend surface to describe the geographic variation of the residuals gives satisfactory results. Using mixed estimation for combining old and new sample tree data improves the efficiency of an inventory. The weight of the prior information must be low, because remarkable differences in stem form was found in the two inventories.

The PDF includes an abstract in Finnish.

  • Korhonen, E-mail: kk@mm.unknown (email)
article id 5509, category Article
Markku Siitonen. (1993). Experiences in the use of forest management planning models. Silva Fennica vol. 27 no. 2 article id 5509. https://doi.org/10.14214/sf.a15670
Keywords: forest policy; forest inventories; stand management; linear programming; forest resources
Abstract | View details | Full text in PDF | Author Info

Model-based information systems have proved valuable planning tools for analysing the production possibilities of forests as well as for understanding forest resources dynamics, stand management practices and forest economics. Computerized forest models implemented in the users’ information systems facilitate the transfer and application of research results in practical forestry.

Conclusions and visions concerning modelling are drawn from experiences in developing the MELA system and its application in solving timber production problems on both the national and forest holding level in Finland. The precondition for predicting forest resource dynamics and for planning the utilization of forests is to accept conditions, uncertainties and a restricted period of time.

The interactive process of forest resource, growth and drain monitoring, and forest management planning supported by forest research and modelling, are the means to enable an operational information base for a dynamic regulation and adaptation strategy for forest resource management under changing conditions and uncertainty.

The PDF includes an abstract in Finnish.

  • Siitonen, E-mail: ms@mm.unknown (email)
article id 5491, category Article
Kari T. Korhonen. (1992). Calibration of upper diameter models in large scale forest inventory. Silva Fennica vol. 26 no. 4 article id 5491. https://doi.org/10.14214/sf.a15652
Keywords: models; forest inventories; simulation; diameter; estimation
Abstract | View details | Full text in PDF | Author Info

Models for estimating the upper diameter of trees were constructed using sample tree data measured in the 7th National Forest Inventory in Finland. Calibration of the models was tested with data from the 8th National Forest Inventory. The results showed that using mixed estimation for combining the two data sets improves the reliability of the models. Models and methods used in this study can be recommended for use in forest inventories.

The PDF includes an abstract in Finnish.

  • Korhonen, E-mail: kk@mm.unknown (email)
article id 5453, category Article
Annika Kangas. (1991). Updated measurement data as prior information in forest inventory. Silva Fennica vol. 25 no. 3 article id 5453. https://doi.org/10.14214/sf.a15611
Keywords: forest inventories; mixed estimator; prior information; model-based inference
Abstract | View details | Full text in PDF | Author Info

Old inventory data has widely been used as prior information in forest inventory using the method of sampling with partial replacement (SPR). In this method knowledge about forest growth has not been utilized. However, the accuracy of the inventory results can be improved if this knowledge is utilized. The usability of the inventory results can be improved if the prior information is updated by treewise growth models. In this paper a statistical basis is presented for a method in which such information can be used. The applicability of the method is also discussed. An example is given to demonstrate the method.

The PDF includes an abstract in Finnish.

  • Kangas, E-mail: ak@mm.unknown (email)
article id 5444, category Article
Kari T. Korhonen, Matti Maltamo. (1991). The evaluation of forest inventory designs using correlation functions. Silva Fennica vol. 25 no. 2 article id 5444. https://doi.org/10.14214/sf.a15598
Keywords: forest inventories; correlation analysis; correlograms; sampling error; spatial correlation,
Abstract | View details | Full text in PDF | Author Info

Correlation functions of the mean volume, land use class and soil class were estimated using the data of the Finnish National Forest Inventory. Estimated functions were used for approximating the standard error of e.g. the mean volume of a cluster of plots. Standard error estimates can be used for comparing different inventory designs.

The PDF includes an abstract in Finnish.

  • Korhonen, E-mail: kk@mm.unknown (email)
  • Maltamo, E-mail: mm@mm.unknown
article id 5278, category Article
Shikui Peng. (1986). A comparison of replacement strategies in continuous forest inventory. Silva Fennica vol. 20 no. 3 article id 5278. https://doi.org/10.14214/sf.a15457
Keywords: forest inventories; sampling; Enso-Gutzeit; CFI; estimation; SPR
Abstract | View details | Full text in PDF | Author Info

Three replacement strategies in continuous forest inventory of the Enso-Gutzeit Company have been presented and discussed. The first strategy adopts data from only the last two inventory occasions; the second strategy employs data from all four occasions, in which there are two groups of permanent plots measured on the first three occasions and independently on the last two occasions; the third strategy also utilizes data from all four occasions, but includes only one group permanent plots measured on all four occasions. Results indicate that the last strategy is best for efficiency. The difference between the first two strategies is small. 

The PDF includes an abstract in Finnish.

  • Peng, E-mail: sp@mm.unknown (email)
article id 5219, category Article
Simo Poso, Tuomas Häme, Raito Paananen. (1984). A method for estimating the stand characteristics of a forest compartment using satellite imagery. Silva Fennica vol. 18 no. 3 article id 5219. https://doi.org/10.14214/sf.a15398
Keywords: forest inventories; remote sensing; satellite imagery; survey by stands; compartmentwise forest inventories; relascope plots
Abstract | View details | Full text in PDF | Author Info

The paper presents a method based on two phase sampling and applicable to forest inventories. The first phase estimates are obtained from satellite imagery and, if required, from extra material such as maps. Second phase estimates are measured in the field. The method is flexible and also applicable to compartmentwise forest inventories. The experiments were based on six study areas with 439 relascope plots. The correlation coefficients between first and second stage estimates varied largely according to the study area.

The PDF includes a summary in Finnish.

  • Poso, E-mail: sp@mm.unknown (email)
  • Häme, E-mail: th@mm.unknown
  • Paananen, E-mail: rp@mm.unknown

Category : Research article

article id 10247, category Research article
Agnese Marcelli, Walter Mattioli, Nicola Puletti, Francesco Chianucci, Damiano Gianelle, Mirko Grotti, Gherardo Chirici, Giovanni D' Amico, Saverio Francini, Davide Travaglini, Lorenzo Fattorini, Piermaria Corona. (2020). Large-scale two-phase estimation of wood production by poplar plantations exploiting Sentinel-2 data as auxiliary information. Silva Fennica vol. 54 no. 2 article id 10247. https://doi.org/10.14214/sf.10247
Keywords: national forest inventories; Sentinel-2; design-based inference; first-phase tessellation stratified sampling; regression estimator; second-phase stratified sampling; simulation study
Highlights: A two-phase sampling for large-scale assessment of fast-growing forest crops is developed; Vegetation indices from Sentinel-2 are exploited in a linear regression estimator; The linear regression estimator turns out to be better than the estimator based on the sole sample information; The approach represents a reference for supporting outside-forest resource monitoring and assessment.
Abstract | Full text in HTML | Full text in PDF | Author Info

Growing demand for wood products, combined with efforts to conserve natural forests, have supported a steady increase in the global extent of planted forests. Here, a two-phase sampling strategy for large-scale assessment of the total area and the total wood volume of fast-growing forest tree crops within agricultural land is presented. The first phase is performed using tessellation stratified sampling on high-resolution remotely sensed imagery and is sufficient for estimating the total area of plantations by means of a Monte Carlo integration estimator. The second phase is performed using stratified sampling of the plantations selected in the first phase and is aimed at estimating total wood volume by means of an approximation of the first-phase Horvitz-Thompson estimator. Vegetation indices from Sentinel-2 are exploited as freely available auxiliary information in a linear regression estimator to improve the design-based precision of the estimator based on the sole sample data. Estimators of the totals and of the design-based variances of total estimators are presented. A simulation study is developed in order to check the design-based performance of the two alternative estimators under several artificial distributions supposed for poplar plantations (random, clustered, spatially trended). An application in Northern Italy is also reported. The regression estimator turns out to be invariably better than that based on the sole sample information. Possible integrations of the proposed sampling scheme with conventional national forest inventories adopting tessellation stratified sampling in the first phase are discussed.

  • Marcelli, University of Tuscia, Department for Innovation in Biological, Agro-food and Forest systems, Viterbo, Italy; Fondazione Edmund Mach, Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, San Michele all’Adige, Italy E-mail: agnese.marcelli@student.unisi.it (email)
  • Mattioli, University of Tuscia, Department for Innovation in Biological, Agro-food and Forest systems, Viterbo, Italy; CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: walter.mattioli@crea.gov.it
  • Puletti, CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: nicola.puletti@crea.gov.it
  • Chianucci, CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: fchianucci@gmail.com
  • Gianelle, Fondazione Edmund Mach, Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, San Michele all’Adige, Italy E-mail: damiano.gianelle@fmach.it
  • Grotti, CREA, Research Centre for Forestry and Wood, Arezzo, Italy; University of Roma La Sapienza, Department of Architecture and Design, Rome, Italy E-mail: mirkogrotti@gmail.com
  • Chirici, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy E-mail: gherardo.chirici@unifi.it
  • D' Amico, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy E-mail: giovanni.damico@unifi.it
  • Francini, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy; University of Molise, Department of Agricultural, Environmental and Food Sciences, Campobasso, Italy E-mail: saverio.francini@gmail.com
  • Travaglini, University of Firenze, Department of Agriculture, Food, Environment and Forestry, Florence, Italy E-mail: davide.travaglini@unifi.it
  • Fattorini, University of Siena, Department of Economics and Statistics, Siena, Italy E-mail: lorenzo.fattorini@unisi.it
  • Corona, CREA, Research Centre for Forestry and Wood, Arezzo, Italy E-mail: piermaria.corona@crea.gov.it
article id 101, category Research article
Risto Laamanen, Annika Kangas. (2011). Large-scale forest owner’s information needs in operational planning of timber harvesting - some practical views in Metsähallitus, Finnish state-owned enterprise. Silva Fennica vol. 45 no. 4 article id 101. https://doi.org/10.14214/sf.101
Keywords: forest inventories; harvest planning; information needs
Abstract | View details | Full text in PDF | Author Info
  • Laamanen, Metsähallitus, Vantaa, Finland E-mail: risto.laamanen@metsa.fi (email)
  • Kangas, Metsähallitus, Vantaa, Finland E-mail: ak@nn.fi
article id 185, category Research article
Bianca N. I. Eskelson, Tara M. Barrett, Hailemariam Temesgen. (2009). Imputing mean annual change to estimate current forest attributes. Silva Fennica vol. 43 no. 4 article id 185. https://doi.org/10.14214/sf.185
Keywords: forest inventory and analysis; forest monitoring; national forest inventories; nearest neighbor imputation; Pacific Northwest; paneled inventory data
Abstract | View details | Full text in PDF | Author Info
When a temporal trend in forest conditions is present, standard estimates from paneled forest inventories can be biased. Thus methods that use more recent remote sensing data to improve estimates are desired. Paneled inventory data from national forests in Oregon and Washington, U.S.A., were used to explore three nearest neighbor imputation methods to estimate mean annual change of four forest attributes (basal area/ha, stems/ha, volume/ha, biomass/ha). The randomForest imputation method outperformed the other imputation approaches in terms of root mean square error. The imputed mean annual change was used to project all panels to a common point in time by multiplying the mean annual change with the length of the growth period between measurements and adding the change estimate to the previously observed measurements of the four forest attributes. The resulting estimates of the mean of the forest attributes at the current point in time outperformed the estimates obtained from the national standard estimator.
  • Eskelson, Oregon State University, Department of Forest Engineering, Resources and Management, 204 Peavy Hall, Corvallis, Oregon 97331, USA E-mail: bianca.eskelson@oregonstate.edu (email)
  • Barrett, Oregon State University, Department of Forest Engineering, Resources and Management, 204 Peavy Hall, Corvallis, Oregon 97331, USA E-mail: tmb@nn.us
  • Temesgen, Oregon State University, Department of Forest Engineering, Resources and Management, 204 Peavy Hall, Corvallis, Oregon 97331, USA E-mail: ht@nn.us
article id 255, category Research article
Claude Vidal, Adrian Lanz, Erkki Tomppo, Klemens Schadauer, Thomas Gschwantner, Lucio di Cosmo, Nicolas Robert. (2008). Establishing forest inventory reference definitions for forest and growing stock: a study towards common reporting. Silva Fennica vol. 42 no. 2 article id 255. https://doi.org/10.14214/sf.255
Keywords: national forest inventories; reference definitions; growing stock; harmonisation; analytical decomposition
Abstract | View details | Full text in PDF | Author Info
International agreements such as the Kyoto protocol and Convention on Biological Diversity (1992), as well as, criteria and indicator processes require reports on the status of nations’ forests. Any comparison of the current status and trends of forest resources among nations presumes that the nations’ applied definitions and concepts produce comparable estimates of the status of forests. In spite of this, the FAO has already collected global information for 60 years and made noticeable efforts in creating common definitions, but forest related data are still collected using diverse definitions, even regarding basic concepts such as forest and forest area. A simple consequence is that the cross-countries estimates are not comparable. The reasons behind the differences in the definitions are diverse histories, and sometimes different use of forests. In an ideal case, national forest inventories should fulfil both national and international needs. In addition to the FAO’s Forest Resources Assessment process, other efforts are made to assess the status of forests in European countries, e.g. European Forest Information and Communication System (EFICS). EFICS produced reports about forest inventories but does not suggest any common definition or method to convert estimates from one definition to another one. This article presents principles and methods to create commonly acceptable and adoptable definitions for forest inventories. The principles and methods are demonstrated using two examples: the reference definitions of forest and growing stock. The article is based on the work of COST Action E43 (http://www.metla.fi/eu/cost/e43/).
  • Vidal, Inventaire Forestier National, Château des Barres, Nogent-sur-Vernisson, France E-mail: claude.vidal@ifn.fr (email)
  • Lanz, WSL/FNP, Abteilung Landschaftsinventuren, Birmensdorf, Switzerland E-mail: al@nn.ch
  • Tomppo, Finnish Forest Research Institute, Vantaa Research Unit, Vantaa, Finland E-mail: et@nn.fi
  • Schadauer, Bundesamt und Forschungszentrum für Wald, Wien, Austria E-mail: ks@nn.at
  • Gschwantner, Bundesamt und Forschungszentrum für Wald, Wien, Austria E-mail: tg@nn.at
  • di Cosmo, ISAFA, Villazzano, Italy E-mail: ldc@nn.it
  • Robert, Inventaire Forestier National, Ch‰teau des Barres, Nogent-sur-Vernisson, France E-mail: nr@nn.fr
article id 376, category Research article
Nils Lexerød, Trond Eid. (2005). Recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway. Silva Fennica vol. 39 no. 3 article id 376. https://doi.org/10.14214/sf.376
Keywords: regeneration; national forest inventories; growth simulators; probability models; conditional models; Norway
Abstract | View details | Full text in PDF | Author Info
The objective of the present study was to develop recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway. The models were developed from permanent sample plots established by the National Forest Inventory, and they will be included in a growth simulator that is part of a large-scale forestry scenario model. The modelling was therefore restricted to independent variables directly or indirectly available from inventories for practical forest management planning. A two-stage modelling approach that suited the stochastic nature of recruitment in boreal forests was used. Models predicting the probability of recruitment were estimated in a first stage, and conditional models for the number of recruits were developed in a second. The probability models as well as the conditional models were biologically realistic and logical. The goodness of fit tests revealed that the probability models fitted the data well, while the coefficients of determination for the conditional models were relatively low. No independent test data were available, but comparisons of predicted and observed number of recruits in different sub-groups of the data revealed few large deviations. The high level of large random errors was probably due to the great variability observed in number of recruits rather than inappropriate specifications of the models. Provided the generally high level of uncertainty connected to analysis performed with large-scale forestry scenario models and the stochastic nature of recruitment, the presented models seem to give satisfactory levels of accuracy.
  • Lexerød, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail: nils.lexerod@umb.no (email)
  • Eid, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway. E-mail nils.lexerod@umb.no E-mail: te@nn.no

Category : Review article

article id 38, category Review article
Matieu Henry, Nicolas Picard, Carlo Trotta, Raphaël J. Manlay, Riccardo Valentini, Martial Bernoux, Laurent Saint-André. (2011). Estimating tree biomass of sub-Saharan African forests: a review of available allometric equations. Silva Fennica vol. 45 no. 3B article id 38. https://doi.org/10.14214/sf.38
Keywords: aboveground biomass; databases; inventories; models; Tier method; wood specific gravity
Abstract | View details | Full text in PDF | Author Info
In response to the growing interest in estimating carbon stocks in forests, available allometric equations have been compiled for sub-Saharan Africa. Tree, sprout and stand volume and biomass equations were reviewed. The 850 equations and 125 related references were incorporated into an open-access database on the Carboafrica website (http://www.carboafrica.net). The collected information provides a basic tool for the estimation of biomass and carbon stocks and other purposes, such as bioenergy and fodder supply assessment. A Tier-method approach was developed to illustrate the possible use of the equations. Current available biomass expansion factors that are used to convert a volume to the total aboveground biomass appear to be limited; incomplete species-specific allometric equations are preferred to generalised equations. The analysis of the database highlighted important gaps in available tools to assess forest carbon stocks and changes in these stocks. A quality control assessment revealed that 22% of the equations were misreported and recommendations were proposed to guide further research. Further statistical analyses, such as the Bayesian approach, would help to produce more accurate biomass estimates.
  • Henry, IRD, UMR Eco&Sols, Montpellier SupAgro, 2 place Viala, 34060 Montpellier, France; Di.S.A.F.Ri, Università degli Studi della Tuscia, Viterbo, Italy; and AgroParisTech-ENGREF, GEEFT, Montpellier, France E-mail: henry@unitus.it (email)
  • Picard, CIRAD, Montpellier, France E-mail: np@nn.fr
  • Trotta, Di.S.A.F.Ri, Università degli Studi della Tuscia, Viterbo, Italy E-mail: ct@nn.it
  • Manlay, IRD, UMR Eco&Sols, Montpellier SupAgro, 2 place Viala, 34060 Montpellier, France; and AgroParisTech-ENGREF, GEEFT, Montpellier, France E-mail: rjm@nn.fr
  • Valentini, Di.S.A.F.Ri, Università degli Studi della Tuscia, Viterbo, Italy E-mail: rv@nn.it
  • Bernoux, IRD, UMR Eco&Sols, Montpellier SupAgro, 2 place Viala, 34060 Montpellier, France E-mail: mb@nn.fr
  • Saint-André, CIRAD, Montpellier, France; and INRA, UR1138, Biogeochimie des Ecosystèmes Forestiers, Champenoux, France E-mail: lsa@nn.fr

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