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Articles containing the keyword 'remote sensing'.

Category: Research article

article id 10150, category Research article
Petri Forsström, Jouni Peltoniemi, Miina Rautiainen. (2019). Seasonal dynamics of lingonberry and blueberry spectra. Silva Fennica vol. 53 no. 2 article id 10150. https://doi.org/10.14214/sf.10150
Highlights: Seasonal series of multiangular spectra for lingonberry (Vaccinium vitis-idaea L.) and blueberry (Vaccinium myrtillus L.); Decidous blueberry has strong seasonal pattern while temporal variations of evergreen lingonberry were linked to phenological stages of flowering and berrying; Detection of flowers and berries from shrub spectra was possible; Collected spectral data are openly available through SPECCHIO Spectral Information System.

Accurate mapping of the spatial distribution of understory species from spectral images requires ground reference data which represent the prevailing phenological stage at the time of image acquisition. We measured the spectral bidirectional reflectance factors (BRFs, 350–2500 nm) at varying view angles for lingonberry (Vaccinium vitis-idaea L.) and blueberry (Vaccinium myrtillus L.) throughout the growing season of 2017 using Finnish Geospatial Research Institute’s FIGIFIGO field goniometer. Additionally, we measured spectra of leaves and berries of both species, and flowers of lingonberry. Both lingonberry and blueberry showed seasonality in visible and near-infrared spectral regions which was linked to occurrences of leaf growth, flowering, berrying, and leaf senescence. The seasonality of spectra differed between species due to different phenologies (evergreen vs. deciduous). Vegetation indices, normalized difference vegetation index (NDVI), moisture stress index (MSI), plant senescence reflectance index (PSRI), and red-edge inflection point (REIP2), showed characteristic seasonal trends. NDVI and PSRI were sensitive to the presence of flowers and berries of lingonberry, while with blueberry the effects were less evident. Off-nadir observations supported differentiating the dwarf shrub species from each other but showed little improvement for detection of flowers and berries. Lingonberry and blueberry can be identified by their spectral signatures if ground reference data are available over the entire growing season. The spectral data measured in this study are reposited in the publicly open SPECCHIO Spectral Information System.

  • Forsström, Aalto University, School of Engineering, Department of Built Environment, FI-00076 Aalto, Finland ORCID ID: https://orcid.org/0000-0002-2357-2517 E-mail: petri.forsstrom@aalto.fi (email)
  • Peltoniemi, Finnish Geospatial Research Institute (FGI), Department of Geodesy and Geodynamics, Geodeetinrinne 2, FI-02430 Masala, Finland ORCID ID: https://orcid.org/0000-0002-4701-128X E-mail: jouni.peltoniemi@nls.fi
  • Rautiainen, Aalto University, School of Engineering, Department of Built Environment, FI-00076 Aalto, Finland; Aalto University, Department of Electronics and Nanoengineering, FI-00076 Aalto, Finland ORCID ID: https://orcid.org/0000-0002-6568-3258 E-mail: miina.a.rautiainen@aalto.fi
article id 9923, category Research article
Annika Kangas, Terje Gobakken, Stefano Puliti, Marius Hauglin, Erik Naesset. (2018). Value of airborne laser scanning and digital aerial photogrammetry data in forest decision making. Silva Fennica vol. 52 no. 1 article id 9923. https://doi.org/10.14214/sf.9923
Highlights: Airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) are nearly equally valuable for harvest scheduling decisions even though ALS data is more precise; Large underestimates of stand volume are most dangerous errors for forest owner because of missed cutting probabilities; Relative RMSE of stand volume and the mean volume in a test area explain 77% of the variation between the expected losses due to errors in the data in the published studies; Increasing the relative RMSE of volume by 1 unit, increased the losses in average by 4.4 € ha–1.

Airborne laser scanning (ALS) has been the main method for acquiring data for forest management planning in Finland and Norway in the last decade. Recently, digital aerial photogrammetry (DAP) has provided an interesting alternative, as the accuracy of stand-based estimates has been quite close to that of ALS while the costs are markedly smaller. Thus, it is important to know if the better accuracy of ALS is worth the higher costs for forest owners. In many recent studies, the value of forest inventory information in the harvest scheduling has been examined, for instance through cost-plus-loss analysis. Cost-plus-loss means that the quality of the data is accounted for in monetary terms through calculating the losses due to errors in the data in the forest management planning context. These costs are added to the inventory costs. In the current study, we compared the losses of ALS and DAP at plot level. According to the results, the data produced using DAP are as good as data produced using ALS from a decision making point of view, even though ALS is slightly more accurate. ALS is better than DAP only if the data will be used for more than 15 years before acquiring new data, and even then the difference is quite small. Thus, the increased errors in DAP do not significantly affect the results from a decision making point of view, and ALS and DAP data can be equally well recommended to the forest owners for management planning. The decision of which data to acquire, can thus be made based on the availability of the data on first hand and the costs of acquiring it on the second hand.

  • Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80170 Joensuu, Finland ORCID ID:E-mail: annika.kangas@luke.fi (email)
  • Gobakken, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway ORCID ID:E-mail: terje.gobakken@nmbu.no
  • Puliti, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway ORCID ID:E-mail: stefano.puliti@nibio.no
  • Hauglin, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway ORCID ID:E-mail: marius.hauglin@nmbu.no
  • Naesset, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway ORCID ID:E-mail: erik.naesset@nmbu.no
article id 7743, category Research article
Sakari Tuominen, Timo Pitkänen, Andras Balazs, Annika Kangas. (2017). Improving Finnish Multi-Source National Forest Inventory by 3D aerial imaging. Silva Fennica vol. 51 no. 4 article id 7743. https://doi.org/10.14214/sf.7743
Highlights: 3D aerial imaging provides a feasible method for estimating forest variables in the form of thematic maps in large area inventories; Photogrammetric 3D data based on aerial imagery that was originally acquired for orthomosaic production was tested in estimating stand variables; Photogrammetric 3D data highly improved the accuracy of forest estimates compared to traditional 2D remote sensing imagery.

Optical 2D remote sensing techniques such as aerial photographing and satellite imaging have been used in forest inventory for a long time. During the last 15 years, airborne laser scanning (ALS) has been adopted in many countries for the estimation of forest attributes at stand and sub-stand levels. Compared to optical remote sensing data sources, ALS data are particularly well-suited for the estimation of forest attributes related to the physical dimensions of trees due to its 3D information. Similar to ALS, it is possible to derive a 3D forest canopy model based on aerial imagery using digital aerial photogrammetry. In this study, we compared the accuracy and spatial characteristics of 2D satellite and aerial imagery as well as 3D ALS and photogrammetric remote sensing data in the estimation of forest inventory variables using k-NN imputation and 2469 National Forest Inventory (NFI) sample plots in a study area covering approximately 5800 km2. Both 2D data were very close to each other in terms of accuracy, as were both the 3D materials. On the other hand, the difference between the 2D and 3D materials was very clear. The 3D data produce a map where the hotspots of volume, for instance, are much clearer than with 2D remote sensing imagery. The spatial correlation in the map produced with 2D data shows a lower short-range correlation, but the correlations approach the same level after 200 meters. The difference may be of importance, for instance, when analyzing the efficiency of different sampling designs and when estimating harvesting potential.

  • Tuominen, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID:E-mail: sakari.tuominen@luke.fi (email)
  • Pitkänen, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID:E-mail: timo.p.pitkanen@luke.fi
  • Balazs, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID ID:E-mail: andras.balazs@luke.fi
  • Kangas, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: Annika.Kangas@luke.fi
article id 1567, category Research article
Eetu Kotivuori, Lauri Korhonen, Petteri Packalen. (2016). Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland. Silva Fennica vol. 50 no. 4 article id 1567. https://doi.org/10.14214/sf.1567
Highlights: Pooled data from nine inventory projects in Finland were used to create nationwide laser-based regression models for dominant height, volume and biomass; Volume and biomass models provided regionally different means than real means, but for dominant height the mean difference was small; The accuracy of general volume predictions was nevertheless comparable to relascope-based field inventory by compartments.

The aim of this study was to examine how well stem volume, above-ground biomass and dominant height can be predicted using nationwide airborne laser scanning (ALS) based regression models. The study material consisted of nine practical ALS inventory projects taken from different parts of Finland. We used field sample plots and airborne laser scanning data to create nationwide and regional models for each response variable. The final models had one or two ALS predictors, which were chosen based on the root mean square error (RMSE), and cross-validated. Finally, we tested how much predictions would improve if the nationwide models were calibrated with a small number of regional sample plots. Although forest structures differ among different parts of Finland, the nationwide volume and biomass models performed quite well (leave-inventory-area-out RMSE 22.3% to 33.8%, mean difference [MD] –13.8% to 18.7%) compared with regional models (leave-plot-out RMSE 20.2% to 26.8%). However, the nationwide dominant height model (RMSE 5.4% to 7.7%, MD –2.0% to 2.8%, with the exception of the Tornio region – RMSE 11.4%, MD –9.1%) performed nearly as well as the regional models (RMSE 5.2% to 6.7%). The results show that the nationwide volume and biomass models provided different means than real means at regional level, because forest structure and ALS device have a considerable effect on the predictions. Large MDs appeared especially in northern Finland. Local calibration decreased the MD and RMSE of volume and biomass models. However, the nationwide dominant height model did not benefit much from calibration.

  • Kotivuori, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: eetu.kotivuori@uef.fi (email)
  • Korhonen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: lauri.korhonen@uef.fi
  • Packalen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland ORCID ID:E-mail: petteri.packalen@uef.fi
article id 1495, category Research article
Per-Ola Olsson, Tuula Kantola, Päivi Lyytikäinen-Saarenmaa, Anna Maria Jönsson, Lars Eklundh. (2016). Development of a method for monitoring of insect induced forest defoliation – limitation of MODIS data in Fennoscandian forest landscapes. Silva Fennica vol. 50 no. 2 article id 1495. https://doi.org/10.14214/sf.1495
Highlights: We developed and tested a method to monitor insect induced defoliation in forests based on coarse-resolution satellite data (MODIS); MODIS data may fail to detect defoliation in fragmented landscapes, especially if defoliation history is long. More homogenous forests results in higher detection accuracies; The method may be applied to future coarse and medium-resolution satellite data with high temporal resolution.

We investigated if coarse-resolution satellite data from the MODIS sensor can be used for regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed. Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for optimisation. The method was developed in fragmented and heavily managed forests in eastern Finland dominated by Scots pine (Pinus sylvestris L.) (pinaceae) and with defoliation of European pine sawfly (Neodiprion sertifer Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly (Diprion pini L.) (Hymenoptera: Diprionidae). The method was also applied to subalpine mountain birch (Betula pubescens ssp. Czerepanovii N.I. Orlova) forests in northern Sweden, infested by autumnal moth (Epirrita autumnata Borkhausen) and winter moth (Operophtera brumata L.). In Finland, detection accuracies were fairly low with 50% of the damaged stands detected, and a misclassification of healthy stands of 22%. In areas with long outbreak histories the method resulted in extensive misclassification. In northern Sweden accuracies were higher, with 75% of the damage detected and a misclassification of healthy samples of 19%. Our results indicate that MODIS data may fail to detect damage in fragmented forests, particularly when the damage history is long. Therefore, regional studies based on these data may underestimate defoliation. However, the method yielded accurate results in homogeneous forest ecosystems and when long-enough periods without damage could be identified. Furthermore, the method is likely to be useful for insect disturbance detection using future medium-resolution data, e.g. from Sentinel‑2.

  • Olsson, Lund University, Department of Physical Geography and Ecosystem Science, Sölvegatan 12, S-223 62 Lund, Sweden ORCID ID:E-mail: per-ola.olsson@nateko.lu.se (email)
  • Kantola, Texas A & M University, Knowledge Engineering Laboratory, Department of Entomology, College Station, TX, USA ORCID ID:E-mail: tuula.kantola@helsinki.fi
  • Lyytikäinen-Saarenmaa, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: paivi.lyytikainen-saarenmaa@helsinki.fi
  • Jönsson, Lund University, Department of Physical Geography and Ecosystem Science, Sölvegatan 12, S-223 62 Lund, Sweden ORCID ID:E-mail: anna_maria.jonsson@nateko.lu.se
  • Eklundh, Lund University, Department of Physical Geography and Ecosystem Science, Sölvegatan 12, S-223 62 Lund, Sweden ORCID ID:E-mail: lars.eklundh@nateko.lu.se
article id 1386, category Research article
Håkan Lideskog, Magnus Karlberg. (2016). Simulated continuous mounding improvements through ideal machine vision and control. Silva Fennica vol. 50 no. 2 article id 1386. https://doi.org/10.14214/sf.1386
Highlights: Different strategies for how to utilise machine vision to streamline the mounding head movements were developed and evaluated; The theoretical minimum rate of encountered obstacles while utilising machine vision in continuous mounding is presented, provided that an optimal continuous mounding has been performed; The needed minimum resolution of a machine vision system at work on a clearcut area was found.

To promote the growth and survival of regenerated forests, site preparation prior to tree planting on clearcuts is necessary. This is often performed with scarifiers, either through trenching or mounding. Mounding is generally considered better in a plant survival perspective but is inefficient on obstacle-rich clearcuts. By utilising machine vision through e.g. remote sensing methods, new strategies can enable efficient mound positioning. In this paper, three realistic strategies utilizing ideal clearcut object identification through machine vision have been developed that can be used for more efficient mounding. The results show that mounding efficiency can be significantly improved with a new mound positioning strategy that employs ideal object identification, especially on obstacle-rich clearcuts.

 

 

  • Lideskog, Luleå University of Technology, Department of Engineering Sciences and Mathematics, Division of Product and Production Development, SE-971 87 Luleå, Sweden ORCID ID:E-mail: hakan.lideskog@ltu.se (email)
  • Karlberg, Luleå University of Technology, Department of Engineering Sciences and Mathematics, Division of Product and Production Development, SE-971 87 Luleå, Sweden ORCID ID:E-mail: magnus.karlberg@ltu.se
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
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.
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 ORCID ID:E-mail: mikko.t.niemi@helsinki.fi (email)
  • 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 ORCID ID:E-mail: mikko.vastaranta@helsinki.fi
  • Peuhkurinen, Arbonaut Oy Ltd., Latokartanontie 7 A, FI-00700, Finland ORCID ID: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 ORCID ID:E-mail: markus.holopainen@helsinki.fi
article id 1022, category Research article
Eero Muinonen, Perttu Anttila, Jaakko Heinonen, Jukka Mustonen. (2013). Estimating the bioenergy potential of forest chips from final fellings in Central Finland based on biomass maps and spatially explicit constraints. Silva Fennica vol. 47 no. 4 article id 1022. https://doi.org/10.14214/sf.1022
The technical potential of forest chips from final fellings in Central Finland was estimated using a method based on biomass maps derived from a multi-source forest inventory technique. Image segmentation techniques were applied to a satellite image mosaic to detect stand boundaries. The technical potential of forest chips was computed based on primary forestry residues, i.e. logging residues and stumps from final fellings. Harvesting level definitions for final fellings were established using realized statistics for roundwood at the municipality level as well as larger area statistics. The sensitivity of the potential to ecological and technical constraints in the model was also examined. The technical recovery rate of stump harvesting according to biomass harvesting guidelines was evaluated separately. The critical prerequisites for using the advanced, spatially explicit approach to analysing forest energy potentials may lie in the existence of spatially explicit forest inventory data and the biometric models for tree biomass assortments. The method applied was capable of taking into account the constraints that rely upon map data, such the actual forwarding distance or steepness of the slope in the terrain. The calculation results can be used for strategic decision making in the field of forest bioenergy production.
  • Muinonen, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: eero.muinonen@metla.fi (email)
  • Anttila, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: perttu.anttila@metla.fi
  • Heinonen, Finnish Forest Research Institute, Joensuu Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail: jaakko.heinonen@metla.fi
  • Mustonen, Stora Enso, Talvikkitie 40 C, FI-01300 Vantaa, Finland ORCID ID:E-mail: jukka.mustonen@storaenso.com
article id 458, category Research article
Sakari Tuominen, Kalle Eerikäinen, Anett Schibalski, Markus Haakana, Aleksi Lehtonen. (2010). Mapping biomass variables with a multi-source forest inventory technique. Silva Fennica vol. 44 no. 1 article id 458. https://doi.org/10.14214/sf.458
Map form information on forest biomass is required for estimating bioenergy potentials and monitoring carbon stocks. In Finland, the growing stock of forests is monitored using multi-source forest inventory, where variables are estimated in the form of thematic maps and area statistics by combining information of field measurements, satellite images and other digital map data. In this study, we used the multi-source forest inventory methodology for estimating forest biomass characteristics. The biomass variables were estimated for national forest inventory field plots on the basis of measured tree variables. The plot-level biomass estimates were used as reference data for satellite image interpretation. The estimates produced by satellite image interpretation were tested by cross-validation. The results indicate that the method for producing biomass maps on the basis of biomass models and satellite image interpretation is operationally feasible. Furthermore, the accuracy of the estimates of biomass variables is similar or even higher than that of traditional growing stock volume estimates. The technique presented here can be applied, for example, in estimating biomass resources or in the inventory of greenhouse gases.
  • Tuominen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail: sakari.tuominen@metla.fi (email)
  • Eerikäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland ORCID ID:E-mail:
  • Schibalski, University of Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany ORCID ID:E-mail:
  • Haakana, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
  • Lehtonen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail:
article id 466, category Research article
Ilkka Korpela, Tuukka Tuomola, Timo Tokola, Bo Dahlin. (2008). Appraisal of seedling stand vegetation with airborne imagery and discrete-return LiDAR – an exploratory analysis. Silva Fennica vol. 42 no. 5 article id 466. https://doi.org/10.14214/sf.466
The potential for combined use of airborne discrete-return LiDAR and digital imagery in the classification and measurement of common seedling stand vegetation was examined in southern Finland (61°50’N, 24°20’E). Classification was based on spectral and textural image features in addition to geometric and radiometric features of the LiDAR. The accuracy of leaf-on, LiDAR-based terrain elevation models was tested as well as the accuracy of LiDAR in the measurement of vegetation heights. LiDAR-based canopy height and the range-normalized intensity of the LiDAR were strong explanatory variables in vegetation classification. Interspecies variation was observed in the height measurement accuracy of LiDAR for different tree, shrub and low vegetation canopies. Elevation models derived with 1–15 pulses per m2 showed an inherent noise of app. 15–25 cm, which restricts the use of LiDAR in regeneration assessment of very young stands. The spatial pattern of the competing vegetation was reproduced in classification-based raster surfaces, which could be useful in deriving meaningful treatment proposals.
  • Korpela, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland ORCID ID:E-mail: ilkka.korpela@helsinki.fi (email)
  • Tuomola, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland ORCID ID:E-mail:
  • Tokola, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland ORCID ID:E-mail:
  • Dahlin, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland ORCID ID:E-mail:
article id 261, category Research article
Miina Rautiainen, Matti Mõttus, Pauline Stenberg, Sanna Ervasti. (2008). Crown envelope shape measurements and models. Silva Fennica vol. 42 no. 1 article id 261. https://doi.org/10.14214/sf.261
This paper addresses tree crown envelope shape modeling from the perspective of optical passive remote sensing. The aims are 1) to review the specific requirements of crown shape models and ground measurement techniques in optical remote sensing, and 2) to present preliminary results from empirical, parametric crown shape and volume modeling of Scots pine and Norway spruce applicable in Finland. Results indicated that the basic dimensions (maximum radius, its height and crown length) of tree crowns were better predicted for pines, but the profile shape of the upper part of the crowns varied more than in spruce. Pine crowns were also slightly less concave than spruce crowns. No regularities were observed concerning the lower part of the crowns. The asymmetry of crowns increased as a function of tree age for both species, spruce crowns being more asymmetric than pine crowns. A comparison of measured crown volume with several simple geometrical crown shape envelopes showed that using a cone as a crown shape model for Scots pine and Norway spruce underestimates crown volume most severely. Other crown envelope shape models (e.g. ellipsoids) rendered crown volumes closer to the measured volume and did not differ considerably from each other.
  • Rautiainen, Tartu Observatory, 61602 Tõravere, Estonia, and Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: miina.rautiainen@helsinki.fi (email)
  • Mõttus, Tartu Observatory, 61602 Tõravere, Estonia ORCID ID:E-mail:
  • Stenberg, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Ervasti, City of Vantaa, Land Use and Environment / Green Area Unit, Kielotie 13, FI-01300 Vantaa, Finland ORCID ID:E-mail:
article id 471, category Research article
Michael Vohland, Johannes Stoffels, Christina Hau, Gebhard Schüler. (2007). Remote sensing techniques for forest parameter assessment: multispectral classification and linear spectral mixture analysis. Silva Fennica vol. 41 no. 3 article id 471. https://doi.org/10.14214/sf.471
One of the most common applications of remote sensing in forestry is the production of thematic maps, depicting e.g. tree species or stand age, by means of image classification. Nevertheless, the absolute quantification of stand variables is even more essential for forest inventories. For both issues, satellite data are attractive for their large-area and up-to-date mapping capacities. This study followed two steps, and at first a supervised parametric classification was performed for a German test site based on a radiometrically corrected Landsat-5 TM scene. There, eight forest classes were identified with an overall accuracy of 87.5%. In the following, the study focused on the estimation of one key stand variable, the stem number per hectare (SN), which was carried out for a number of Norway spruce stands that had been clearly identified in the multispectral classification. For the estimation of SN, the approach of Linear Spectral Mixture Analysis (LSMA) was found to be clearly more effective than spectral indices. LSMA is based on the premise that measured reflectances can be linearly modelled from a set of so-called endmember spectra. In this study, the endmember sets were held variable to decompose pixel values to abundances of a vegetation, a background (soil, litter, bark) and a shade fraction. Forest structure determines the visible portions of these fractions, and therefore, a multiple regression using them as predictor variables provided the best SN estimates. LSMA allows a pixel-by-pixel quantification of SN for complete satellite images. This opens the view to exploit these data for an improved calibration of large-scale multi-parameter assessment strategies (e.g. statistical modelling or the kNN method for satellite data interpretation).
  • Vohland, University of Trier, Faculty of Geography and Geosciences, Remote Sensing Department, Trier, Germany ORCID ID:E-mail:
  • Stoffels, University of Trier, Faculty of Geography and Geosciences, Remote Sensing Department, Trier, Germany ORCID ID:E-mail:
  • Hau, University of Trier, Faculty of Geography and Geosciences, Remote Sensing Department, Trier, Germany ORCID ID:E-mail:
  • Schüler, Research Institution for Forest Ecology and Forestry (FAWF), Department of Forest Growth and Silviculture, Trippstadt, Germany ORCID ID:E-mail:
article id 283, category Research article
Ilkka Korpela, Tuukka Tuomola, Esko Välimäki. (2007). Mapping forest plots: an efficient method combining photogrammetry and field triangulation. Silva Fennica vol. 41 no. 3 article id 283. https://doi.org/10.14214/sf.283
Intra stand spatial information is often collected in ecological investigations, when functioning or interactions in the ecosystem are studied. Local relative accuracy is often given priority in such cases. Forest maps with accurate absolute positions in a global coordinate system are needed in remote-sensing applications for validation and calibration purposes. Establishing the absolute position is particularly difficult under a canopy as is creating undistorted coordinate systems for large plots in the forest. We present a method that can be used for the absolute mapping of point features under a canopy that is efficient for large forest plots. In this method, an undistorted network of control points is established in the forest using photogrammetric observations of treetops. These points are used for the positioning of other points, using redundant observations of interpoint distances and azimuths and a least squares adjustment. The method provides decimetre-level accuracy and only one person is required to conduct the work. An estimate of the positioning accuracy of each point is readily available in the field. We present the method, a simulation study that explores the potential of the method and results from an experiment in a mixed boreal stand in southern Finland.
  • Korpela, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: ilkka.korpela@helsinki.fi (email)
  • Tuomola, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Välimäki, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland ORCID ID:E-mail:
article id 596, category Research article
Sakari Tuominen, Simo Poso. (2001). Improving multi-source forest inventory by weighting auxiliary data sources. Silva Fennica vol. 35 no. 2 article id 596. https://doi.org/10.14214/sf.596
A two-phase sampling design has been applied to forest inventory. First, a large number of first phase sample plots were defined with a square grid in a geographic coordinate system for two study areas of about 1800 and 4500 ha. The first phase sample plots were supplied by auxiliary data of Landsat TM and IRS-1C with principal component transformation for stratification and drawing the second phase sample (field sample). Proportional allocation was used to draw the second phase sample. The number of field sample plots in the two study areas was 300 and 380. The local estimates of five continuous forest stand variables, mean diameter, mean height, age, basal area, and stem volume, were calculated for each of the first phase sample plots. This was done separately by using one auxiliary data source at a time together with the field sample information. However, if the first phase sample plot for which the stand variables were to be estimated was also a field sample plot, the information of that field sample plot was eliminated according to the cross validation principle. This was because it was then possible to calculate mean square errors of estimates related to a specific auxiliary data source. The procedure produced as many estimates for each first phase sample plot and forest stand variable as was the number of auxiliary data sources, i.e. seven estimates: These were based on Landsat TM, IRS-1C, digitized aerial photos, ocular stereoscopic interpretation from aerial photographs, data from old forest inventory made by compartments, Landsat TM95–TM89 difference image and IRS96–TM95 difference image. The final estimates were calculated as weighted averages where the weights were inversely proportional to mean square errors. The alternative estimates were calculated by applying simple rules based on knowledge and the outliers were defined. The study shows that this kind of system for finding outliers for elimination and a weighting procedure improves the accuracy of stand variable estimation.
  • Tuominen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail: sakari.tuominen@metla.fi (email)
  • Poso, Department of Forest Resource Management, P.O. Box 27, FIN-00014 University of Helsinki, Finland ORCID ID:E-mail:
article id 669, category Research article
Simo Poso, Guangxing Wang, Sakari Tuominen. (1999). Weighting alternative estimates when using multi-source auxiliary data for forest inventory. Silva Fennica vol. 33 no. 1 article id 669. https://doi.org/10.14214/sf.669
Five auxiliary data sources (Landsat TM, IRS-IC, digitized aerial photographs, visual photo-interpretation and old forest compartment information) applying three study areas and three estimators, two-phase sampling with stratification, the k nearest neighbors and regression estimator, were examined. Auxiliary data were given for a high number of sample plots, which are here called first phase sample plots. The plots were distributed using a systematic grid over the study areas. Some of the plots were then measured in the field for the necessary ground truth. Each auxiliary data source in combination with field sample information was applied to produce a specific estimator for five forest stand characteristics: mean diameter, mean height, age, basal area, and volume of the growing stock. When five auxiliary data sources were used, each stand characteristic and each first phase sample plot were supplied with five alternative estimates with three alternative estimators. Mean square errors were then calculated for each alternative estimator using the cross validation method. The final estimates were produced by weighting alternative estimates inversely according to the mean square errors related to the corresponding estimator. The result was better than the final estimate of any of the single estimators. The improvement over the best single estimate, as measured in mean square error, was 16.9% on average for all five forest stand characteristics. The improvement was fairly equal for all five forest stand characteristics. Only minor differences among the accuracies of the three alternative estimators were recorded.
  • Poso, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland ORCID ID:E-mail: simo.poso@helsinki.fi (email)
  • Wang, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland ORCID ID:E-mail:
  • Tuominen, Department of Forest Resource Management, P.O. Box 24 (Unioninkatu 40 B), FIN-00014 University of Helsinki, Finland ORCID ID:E-mail:
article id 692, category Research article
Eero Mattila. (1998). Use of satellite and field information in a forest damage survey of eastern Finnish Lapland in 1993. Silva Fennica vol. 32 no. 2 article id 692. https://doi.org/10.14214/sf.692
The study area consists of the Finnish part of a Landsat 5 TM image from 1990. Three independent field samples were measured during 1991–93 in the study area. The first sample was used to compile training areas for supervised maximum likelihood classification of the image. Classification accuracy was studied in the second sample. The spectral separability of the forest strata usable in practical forestry was poor. The extent of the damage area was estimated by the principle of stratified sampling. The estimate included considerable bias because the field sample had not been objectively selected from the image classes. The third field sample was measured as part of the National Forest Inventory of Finland. It is wholly objective, and about ten times larger than the two earlier field samples. The poor spectral separability of the forest strata was confirmed by the NFI sample. However, this sample could be used in stratified sampling with little or no bias in the estimation of the damage area estimate. 14 different damage types were separated according to specific damaging agent. A thematic map was produced which presents the spatial distribution of two damage-rich image classes. The study area comprises 18 300 sq.km, of which 38% were damaged. At first sight it would appear that the proportion of damaged forest has tripled in ten years. However, this is not the case because now special attention was paid to forest health in the field work. Despite this, it is possible that some damage caused by unfavourable climatic phenomena in the ’80s was still perceptible in 1993. No damage caused directly by air pollution has yet been verified in the study area.
  • Mattila, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland ORCID ID:E-mail: eero.mattila@metla.fi (email)

Category: Review article

article id 1095, category Review article
Jonas Fridman, Sören Holm, Mats Nilsson, Per Nilsson, Anna Hedström Ringvall, Göran Ståhl. (2014). Adapting National Forest Inventories to changing requirements – the case of the Swedish National Forest Inventory at the turn of the 20th century. Silva Fennica vol. 48 no. 3 article id 1095. https://doi.org/10.14214/sf.1095
Highlights: National Forest Inventories supply invaluable long term time series of forest state. Recent developments and international harmonization of modern NFIs widen the scope to even include ecosystem goods, e.g. biodiversity and carbon sequestration. The combination of NFI field data with remote sensing techniques can give good estimates for areas smaller than national and regional level.
National Forest Inventories (NFIs) are becoming increasingly important worldwide in order to provide information about the multiple functions of forests, e.g. their provision of raw materials to industry, biodiversity and their capacity to store carbon for mitigating climate change. In several countries the history of NFIs is very long. For these countries a specific challenge is to keep the inventories up-to-date without sacrificing the advantages associated with long time series. At the turn of the 20th century European NFIs faced some major challenges. In this article we describe the history and the recent developments of the Swedish NFI as an example from which general observations are made and discussed. The Swedish NFI started in 1923 and has evolved from an inventory with a narrow focus on wood resources to an inventory today which aims to provide information about all major forest ecosystem services. It can be concluded that the traditional approaches of most European NFIs, e.g. to collect data through sample plot field inventories, has proved to be applicable even for a wide range of new information requirements. Specifically, detailed data about land use, trees, vegetation, and soils has found new important uses in connection with biodiversity assessments and the estimation of greenhouse gas emissions. Though time-consuming and difficult, making NFI information comparable across countries through harmonization appears to be a useful approach. The European National Forest Inventory Network (ENFIN) was formed in 2003 and has been successful in pan-European NFI harmonization.
  • Fridman, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: jonas.fridman@slu.se (email)
  • Holm, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: soren.holm@slu.se
  • Nilsson, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: mats.nilsson@slu.se
  • Nilsson, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: per.nilsson@slu.se
  • Ringvall, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: Anna.Ringvall@slu.se
  • Ståhl, Swedish University of Agricultural Sciences (SLU), SE-901 83 Umeå, Sweden ORCID ID:E-mail: goran.stahl@slu.se
article id 369, category Review article
Jaroslaw Zawadzki, Chris J. Cieszewski, Michal Zasada, Roger C. Lowe. (2005). Applying geostatistics for investigations of forest ecosystems using remote sensing imagery. Silva Fennica vol. 39 no. 4 article id 369. https://doi.org/10.14214/sf.369
Geostatistically based methods that utilize textural information are frequently used to analyze remote sensing (RS) images. The role of these methods in analyzing forested areas increased rapidly during the last several years following advancements in high-resolution RS technology. The results of numerous applications of geostatistical methods for processing RS forest images are encouraging. This paper summarizes such results. Three closely related topics are reviewed: 1) specific properties of geostatistical measures of spatial variability calculated from digital images of forested areas, 2) determination of biophysical forest parameters using semivariograms and characterization of forest ecosystem structure at the stand level, and 3) forest classification methods based on spatial information.
  • Zawadzki, Environmental Engineering Department, Warsaw Technical University, Ul. Nowowiejska 20, 00-653 Warsaw, Poland ORCID ID:E-mail: jaroslaw.zawadzki@is.pw.edu.pl (email)
  • Cieszewski, D. B. Warnell School of Forest Resources, University of Georgia, Athens, GA 30602, USA ORCID ID:E-mail:
  • Zasada, Department of Forest Productivity, Faculty of Forestry, Warsaw Agricultural University, Poland ORCID ID:E-mail:
  • Lowe, D. B. Warnell School of Forest Resources, University of Georgia, Athens, GA 30602, USA ORCID ID:E-mail:

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.

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 ORCID ID: https://orcid.org/0000-0001-6038-1579 E-mail: ville.kankare@uef.fi (email)
  • Luoma, Department of Forest Sciences, University of Helsinki, FI-00014 University of Helsinki, Finland ORCID ID: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 ORCID ID:E-mail: ninni.saarinen@helsinki.fi
  • Peuhkurinen, Arbonaut Oy, Malminkaari 13–19, FI-00700 Helsinki, Finland ORCID ID:E-mail: jussi.peuhkurinen@arbonaut.com
  • Holopainen, Department of Forest Sciences, University of Helsinki, FI-00014 University of Helsinki, Finland ORCID ID:E-mail: markus.holopainen@helsinki.fi
  • Vastaranta, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, Joensuu FI-80101, Finland ORCID ID:E-mail: mikko.vastaranta@uef.fi
article id 1125, category Research note
Anssi Krooks, Sanna Kaasalainen, Ville Kankare, Marianna Joensuu, Pasi Raumonen, Mikko Kaasalainen. (2014). Predicting tree structure from tree height using terrestrial laser scanning and quantitative structure models. Silva Fennica vol. 48 no. 2 article id 1125. https://doi.org/10.14214/sf.1125
Highlights: The analysis of tree structure suggests that trees of different height growing in similar conditions have similar branch size distributions; There is potential for using the tree height information in large-scale estimations of forest canopy structure.
We apply quantitative structure modelling to produce detailed information on branch-level metrics in trees. Particularly we are interested in the branch size distribution, by which we mean the total volume of branch parts distributed over the diameter classes of the parts. We investigate the possibility of predicting tree branch size distributions for trees in similar growing conditions. The quantitative structure model enables for the first time the comparisons of structure between a large number of trees. We found that the branch size distribution is similar for trees of different height in similar growing conditions. The results suggest that tree height could be used to estimate branch size distribution in areas with similar growing conditions and topography.
  • Krooks, Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland ORCID ID:E-mail: Anssi.Krooks@fgi.fi
  • Kaasalainen, Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland ORCID ID:E-mail: Sanna.Kaasalainen@fgi.fi (email)
  • Kankare, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland ORCID ID:E-mail: ville.kankare@helsinki.fi
  • Joensuu, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland ORCID ID:E-mail: marianna.joensuu@alumni.helsinki.fi
  • Raumonen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland ORCID ID:E-mail: Pasi.Raumonen@tut.fi
  • Kaasalainen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland ORCID ID:E-mail: Mikko.Kaasalainen@tut.fi

Category: Discussion article

article id 610, category Discussion article
Risto Päivinen, Perttu Anttila. (2001). How reliable is a satellite forest inventory? Silva Fennica vol. 35 no. 1 article id 610. https://doi.org/10.14214/sf.610
  • Päivinen, European Forest Institute, Torikatu 34, FIN-80101 Joensuu, Finland ORCID ID:E-mail: risto.paivinen@efi.fi (email)
  • Anttila, European Forest Institute, Torikatu 34, FIN-80101 Joensuu, Finland ORCID ID:E-mail:

Category: Article

article id 5610, category Article
Timo Tokola, Juho Heikkilä. (1997). Improving satellite image based forest inventory by using a priori site quality information. Silva Fennica vol. 31 no. 1 article id 5610. https://doi.org/10.14214/sf.a8511

The purpose of this study was to test the benefits of a forest site quality map, when applying satellite image-based forest inventory. By combining field sample plot data from national forest inventories with satellite imagery and forest site quality data, it is possible to estimate forest stand characteristics with higher accuracy for smaller areas. The reliability of the estimates was evaluated using the data from a stand-wise survey for area sizes ranging from 0.06 ha to 300 ha. When the mean volume was estimated, a relative error of 14 per cent was obtained for areas of 50 ha; for areas of 30 ha the corresponding figure was below 20 per cent. The relative gain in interpretation accuracy, when including the forest site quality information, ranged between 1 and 6 per cent. The advantage increased according to the size of the target area. The forest site quality map had the effect of decreasing the relative error in Norway spruce (Picea abies) volume estimations, but it did not contribute to Scots pine (Pinus sylvestris) volume estimation procedure.

  • Tokola, ORCID ID:E-mail:
  • Heikkilä, ORCID ID:E-mail:
article id 5307, category Article
Simo Poso, Raito Paananen, Markku Similä. (1987). Forest inventory by compartments using satellite imagery. Silva Fennica vol. 21 no. 1 article id 5307. https://doi.org/10.14214/sf.a15464

A method for using satellite data in forest inventories and updating is described and tested. The stand characteristics estimated by the method showed high correlation with the same characteristics measured in the field. The correlation coefficients for volume, age and mean height were about 0.85. It seems that the method is applicable to practical forestry. Extensive work in programming, however, is required.

The PDF includes an abstract in Finnish.

  • Poso, ORCID ID:E-mail:
  • Paananen, ORCID ID:E-mail:
  • Similä, ORCID ID:E-mail:
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

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, ORCID ID:E-mail:
  • Häme, ORCID ID:E-mail:
  • Paananen, ORCID ID:E-mail:
article id 7505, category Article
Rauno Väisänen, Kari Heliövaara. (1994). Assessment of insect occurrence in boreal forests based on satellite imagery and field measurements. Acta Forestalia Fennica no. 243 article id 7505. https://doi.org/10.14214/aff.7505

The presence/absence data of 27 forest insect taxa (Retinia resinella, Formica spp., Pissodes spp., several scolytids) and recorded environmental variation were used to investigate the applicability of modelling insect occurrence based on satellite imagery. The sampling was based on 1,800 sample plots (25 m by 25 m) placed along the sides of 30 equilateral triangles (side 1 km) in a fragmented forest area (approximately 100 km2) in Evo, Southern Finland. The triangles were overlaid on land use maps interpreted from satellite images (Landsat TM 30 m multispectral scanner imagery 1991) and digitized geological maps. Insect occurrence was explained using either environmental variables measured in the field or those interpreted from the land use and geological maps. The fit of logistic regression models carried between species, possibly because some species may be associated with characteristics of single trees while other species with stand characteristics. The occurrence of certain insect species at least, especially those associated with Scots pine, could be relatively accurately assessed indirectly on the basis of satellite imagery and geological maps. Models based on both remotely sensed and geological data better predicted the distribution of forest insects except in the case of Xylechinus pilosus, Dryocetes sp. and Trypodendron lineatum, where the differences were relatively small in favour of the models based on field measurements. The number of species was related to habitat compartment size and distance from the habitat edge calculated from the land use maps, but logistic regressions suggested that other environmental variables in general masked the effect of these variables in species occurrence at the present scale.

  • Väisänen, ORCID ID:E-mail:
  • Heliövaara, ORCID ID:E-mail:
article id 7668, category Article
Tuomas Häme. (1991). Spectral interpretation of changes in forest using satellite scanner images. Acta Forestalia Fennica no. 222 article id 7668. https://doi.org/10.14214/aff.7668

Spectral characteristics of rapid changes in forest and the spectral separability of change categories were studied through the analysis of satellite scanner images. A computational model of the spectral reflectance of a Scots pine (Pinus sylvestris L.) stand as a function of time was constructed and compared with empirical data. The study area, centred at 61°51’ N, 24°22’ E, was located in boreal forest in Southern Finland. Ground truth data consisted of forest stands and sample plots. Spectral data comprised multitemporal Landsat Thematic Mapper and Spot images as well as spectroradiometer measurements. The separability of the changes was tested with statistical tests and classifications. The separability varied according to the change category. A scheme for fully automated change monitoring system was presented.

The PDF includes a summary in Finnish.

  • Häme, ORCID ID:E-mail:
article id 4651, category Article
Kullervo Kuusela. (1956). Outlines of cartographical and timber surveying unit. Silva Fennica no. 90 article id 4651. https://doi.org/10.14214/sf.a9113

After the Second World War Finnish Forest Service was faced with large e-mapping and timber surveying project in Northern Finland. The funds for mapping were very limited. In order to re-map the large areas, the only way was to look for alternative methods for the ground methods. The photogrammetric equipment of Finnish Army was made available to the civil service. Consequently, since 1947 several forest mapping projects were carried out in co-operation between the Forest Service and the Army Topographic Service.

When more funds were coming available for the project, new instruments were acquired. The article describes the present mapping procedure and suggests alternative ways in procedure and utilization of new equipment. It concludes that if the forest area under modern timber management plans is several million acres, the ideal implemental framework for mapping and timber surveying unit in Finland should be the following: Radial Secator RS I and slotted templates for the radial line plot, Stereotope Plotter for drafting general maps, the old Delft Scanning Stereoscope for photo interpretation, and Aero-Sketchmaster for transport of the photo details.

  • Kuusela, ORCID ID:E-mail:
article id 4618, category Article
Lauri Olenius. (1951). Ilmakuvien käyttö valtion metsätaloudessa. Silva Fennica no. 69 article id 4618. https://doi.org/10.14214/sf.a14014
English title: Use of aerial mapping in state forestry.

Silva Fennica Issue 69 includes presentations held in 1948-1950 in the fourth professional development courses, arranged for foresters working in the Forest Service. The presentations focus on practical issues in forest management and administration, especially in regional level. The education was arranged by Forest Service.

Forest Service begun the aerial mapping of the state forests in northern Finland in 1948. This presentation describes the state of the work, practices and methods of the work.

  • Olenius, ORCID ID:E-mail:
article id 4617, category Article
Olavi Linnamies. (1951). Ilmakuvamittauksesta. Silva Fennica no. 69 article id 4617. https://doi.org/10.14214/sf.a14013
English title: Aerial mapping.

Silva Fennica Issue 69 includes presentations held in 1948-1950 in the fourth professional development courses, arranged for foresters working in the Forest Service. The presentations focus on practical issues in forest management and administration, especially in regional level. The education was arranged by Forest Service.

This presentation describes the development of aerial mapping, its principles and methods. The use of aerial photographs and the costs of the method is discussed.

  • Linnamies, ORCID ID:E-mail:

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