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Acta Forestalia Fennica
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Articles by Jussi Peuhkurinen
Category : Research article
article id 1218,
category
Research article
Mikko Niemi,
Mikko Vastaranta,
Jussi Peuhkurinen,
Markus Holopainen.
(2015).
Forest inventory attribute prediction using airborne laser scanning in low-productive forestry-drained boreal peatlands.
Silva Fennica
vol.
49
no.
2
article id 1218.
https://doi.org/10.14214/sf.1218
Keywords:
remote sensing;
forest technology;
forest management planning;
mapping;
k-NN estimation;
random forests
Highlights:
Following current forest inventory practises, stem volume was predicted in low-productive drained peatlands (LPDPs) with a root mean square error (RMSE) of 13.7 m3 ha–1; When 30 reference plots measured from LPDPs were added to the prediction, RMSE was decreased to 10.0 m3 ha–1; Additional reference plots from LPDPs did not affect the forest inventory attribute predictions in productive forests.
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Nearly 30% of Finland’s land area is covered by peatlands. In Northern parts of the country there is a significant amount of low-productive drained peatlands (LPDPs) where the average annual stem volume growth is less than 1 m3 ha–1. The re-use of LPDPs has been considered thoroughly since Finnish forest legislation was updated and the forest regeneration prerequisite was removed from LPDPs in January 2014. Currently, forestry is one of the re-use alternatives, thus detailed forest resource information is required for allocating activities. However, current forest inventory practices have not been evaluated for sparse growing stocks (e.g., LPDPs). The purpose of our study was to evaluate the suitability of airborne laser scanning (ALS) for mapping forest inventory attributes in LPDPs. We used ALS data with a density of 0.8 pulses per m2, 558 field-measured reference plots (500 from productive forests and 58 from LPDPs) and k nearest neighbour (k-NN) estimation. Our main aim was to study the sensitivity of predictions to the number of LPDP reference plots used in the k-NN estimation. When the reference data consisted of 500 plots from productive forest stands, the root mean square errors (RMSEs) for the prediction accuracy of Lorey’s height, basal area and stem volume were 1.4 m, 2.7 m2 ha–1 and 13.7 m3 ha–1 in LPDPs, respectively. When 30 additional reference plots were allocated to LPDPs, the respective RMSEs were 1.1 m, 1.7 m2 ha–1 and 10.0 m3 ha–1. Additional reference plot allocation did not affect the predictions in productive forest stands.
-
Niemi,
Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland & Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430, Finland
E-mail:
mikko.t.niemi@helsinki.fi
- Vastaranta, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland & Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430, Finland E-mail: mikko.vastaranta@helsinki.fi
- Peuhkurinen, Arbonaut Oy Ltd., Latokartanontie 7 A, FI-00700, Finland E-mail: jussi.peuhkurinen@arbonaut.com
- Holopainen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland & Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430, Finland E-mail: markus.holopainen@helsinki.fi
article id 69,
category
Research article
Tarja Wallenius,
Risto Laamanen,
Jussi Peuhkurinen,
Lauri Mehtätalo,
Annika Kangas.
(2012).
Analysing the agreement between an Airborne Laser Scanning based forest inventory and a control inventory – a case study in the state owned forests in Finland.
Silva Fennica
vol.
46
no.
1
article id 69.
https://doi.org/10.14214/sf.69
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Airborne laser scanning based forest inventories have recently shown to produce accurate results. However, the accuracy varies according to the test area and used methodology and therefore, an unambiguous and practical quality assessment will be needed as a part of each inventory project. In this study, the accuracy of an ALS inventory was evaluated with a field sampling based control inventory. The agreement between the ALS inventory and the control inventory was analysed with four methods: 1) root mean square error (RMSE) and bias, 2) scatter plots with 95% confidence intervals, 3) Bland-Altman plots and 4) tolerance limits within Bland-Altman plots. Each method has its own special features which have to be taken into account when the agreement is analysed. The pre-defined requirements of the ALS inventory were achieved. A simplified control inventory approach with a slightly narrower focus is proposed to be used in the future. The Bland-Altman plots with the tolerance limits are proposed to be used in quality assessments of operational ALS inventories. Further studies to improve the efficiency of quality assessment are needed.
-
Wallenius,
Metsähallitus, P.O. Box 94, FI-01301 Vantaa, Finland
E-mail:
tarja.wallenius@metsa.fi
- Laamanen, Metsähallitus, P.O. Box 94, FI-01301 Vantaa, Finland E-mail: rl@nn.fi
- Peuhkurinen, Oy Arbonaut Ltd, Helsinki, Finland E-mail: jp@nn.fi
- Mehtätalo, University of Eastern Finland, School of Forest Sciences, Joensuu, Finland E-mail: lm@nn.fi
- Kangas, University of Helsinki, Department of Forest Sciences, Helsinki, Finland E-mail: ak@nn.fi
article id 203,
category
Research article
Matti Maltamo,
Jussi Peuhkurinen,
Jukka Malinen,
Jari Vauhkonen,
Petteri Packalén,
Timo Tokola.
(2009).
Predicting tree attributes and quality characteristics of Scots pine using airborne laser scanning data.
Silva Fennica
vol.
43
no.
3
article id 203.
https://doi.org/10.14214/sf.203
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The development of airborne laser scanning (ALS) during last ten years has provided new possibilities for accurate description of the living tree stock. The forest inventory applications of ALS data include both tree and area-based plot level approaches. The main goal of such applications has usually been to estimate accurate information on timber quantities. Prediction of timber quality has not been focused to the same extent. Thus, in this study we consider here the prediction of both basic tree attributes (tree diameter, height and volume) and characteristics describing tree quality more closely (crown height, height of the lowest dead branch and sawlog proportion of tree volume) by means of high resolution ALS data. The tree species considered is Scots pine (Pinus sylvestris), and the field data originate from 14 sample plots located in the Koli National Park in North Karelia, eastern Finland. The material comprises 133 trees, and size and quality variables of these trees were modeled using a large number of potential independent variables calculated from the ALS data. These variables included both individual tree recognition and area-based characteristics. Models for the dependent tree characteristics to be considered were then constructed using either the non-parametric k-MSN method or a parametric set of models constructed simultaneously by the Seemingly Unrelated Regression (SUR) approach. The results indicate that the k-MSN method can provide more accurate tree-level estimates than SUR models. The k-MSN estimates were in fact highly accurate in general, the RMSE being less than 10% except in the case of tree volume and height of the lowest dead branch.
-
Maltamo,
University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland
E-mail:
matti.maltamo@joensuu.fi
- Peuhkurinen, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: jp@nn.fi
- Malinen, Finnish Forest Research Institute, Joensuu Research Unit, FI-80101 Joensuu, Finland E-mail: jm@nn.fi
- Vauhkonen, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: jv@nn.fi
- Packalén, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: pp@nn.fi
- Tokola, University of Joensuu, Faculty of Forest Sciences, FI-80101 Joensuu, Finland E-mail: tt@nn.fi
article id 237,
category
Research article
Jussi Peuhkurinen,
Matti Maltamo,
Jukka Malinen.
(2008).
Estimating species-specific diameter distributions and saw log recoveries of boreal forests from airborne laser scanning data and aerial photographs: a distribution-based approach.
Silva Fennica
vol.
42
no.
4
article id 237.
https://doi.org/10.14214/sf.237
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The low-density airborne laser scanning (ALS) data based estimation methods have been shown to produce accurate estimates of mean forest characteristics and diameter distributions, according to several studies. The used estimation methods have been based on the laser canopy height distribution approach, where various laser pulse height distribution -derived predictors are related to the stand characteristics of interest. This approach requires very delicate selection methods for selecting the suitable predictor variables. In this study, we introduce a new nearest neighbor search method that requires no complicated selection algorithm for choosing the predictor variables and can be utilized in multipurpose situations. The proposed search method is based on Minkowski distances between the distributions extracted from low density ALS data and aerial photographs. Apart from the introduction of a new search method, the aims of this study were: 1) to produce accurate species-specific diameter distributions and 2) to estimate factual saw log recovery, using the estimated height-diameter distributions and a stem data bank. The results indicate that the proposed method is suitable for producing species-specific diameter distributions and volumes at the stand level. However, it is proposed, that the utilization of more extensive and locally emphasized reference data and auxiliary variables could yield more accurate saw log recoveries.
-
Peuhkurinen,
University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland
E-mail:
jp@nn.fi
- Maltamo, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mm@nn.fi
- Malinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jm@nn.fi
Category : Research note
article id 10197,
category
Research note
Ville Kankare,
Ville Luoma,
Ninni Saarinen,
Jussi Peuhkurinen,
Markus Holopainen,
Mikko Vastaranta.
(2019).
Assessing feasibility of the forest trafficability map for avoiding rutting – a case study.
Silva Fennica
vol.
53
no.
3
article id 10197.
https://doi.org/10.14214/sf.10197
Highlights:
A static trafficability map was developed to provide information about suitable harvesting season; The majority (91.7%) of the evaluated thinning stands were harvested without causing rutting damage if operations were timed correctly in relation to the static trafficability map information; The static trafficability map provides reliable and slightly conservative estimation of the forest trafficability for supporting forest operations.
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Information on forest trafficability (i.e. carrying capacity of the forest floor) is required before harvesting operations in Southern Boreal forest conditions. It describes the seasons when harvesting operations may take place without causing substantial damage to the forest soil using standard logging machinery. The available trafficability information have been based on subjective observations made during the wood procurement planning. For supporting forest operations, an open access map product has been developed to provide information on trafficability of forests. The forest stands are distributed into classes that characterize different harvesting seasons based on topographic wetness index, amount of vegetation, ground water height and ditch depth. The main goal of this case study was to evaluate the information of the static forest trafficability map in relation to the detected rutting within logging tracks measured in the field. The analysis concentrated on thinning stands since the effect of rutting is significant on the growth of the remaining trees. The results showed that the static trafficability map provided reliable and slightly conservative estimation of the forest trafficability. The majority (91.7%) of the evaluated stands were harvested without causing significant damage if harvesting was timed correctly compared to the trafficability information. However, it should be pointed out that the weather history at small scale, the skills of a driver, and effects of used machinery are not considered in the map product although they can have a considerable impact on the rutting.
-
Kankare,
School of Forest Sciences, University of Eastern Finland, P.O. Box 111, Joensuu FI-80101, Finland; Department of Forest Sciences, University of Helsinki, FI-00014 University of Helsinki, Finland
https://orcid.org/0000-0001-6038-1579
E-mail:
ville.kankare@uef.fi
- Luoma, Department of Forest Sciences, University of Helsinki, FI-00014 University of Helsinki, Finland E-mail: ville.luoma@helsinki.fi
- Saarinen, Department of Forest Sciences, University of Helsinki, FI-00014 University of Helsinki, Finland; School of Forest Sciences, University of Eastern Finland, P.O. Box 111, Joensuu FI-80101, Finland E-mail: ninni.saarinen@helsinki.fi
- Peuhkurinen, Arbonaut Oy, Malminkaari 13–19, FI-00700 Helsinki, Finland E-mail: jussi.peuhkurinen@arbonaut.com
- Holopainen, Department of Forest Sciences, University of Helsinki, FI-00014 University of Helsinki, Finland E-mail: markus.holopainen@helsinki.fi
- Vastaranta, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, Joensuu FI-80101, Finland E-mail: mikko.vastaranta@uef.fi
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