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Articles containing the keyword 'photogrammetry'

Category: Research article

article id 10555, category Research article
Ferréol Berendt, Felix Wolfgramm, Tobias Cremer. (2021). Reliability of photo-optical measurements of log stack gross volume. Silva Fennica vol. 55 no. 3 article id 10555. https://doi.org/10.14214/sf.10555
Keywords: photogrammetry; timber trade; logistic; volume estimation; wood pile
Highlights: Gross volume estimations of larger log stacks showed a smaller deviation compared to those of piles with smaller volumes; Log stack quality affects estimation accuracy; The deviations between the manual section-wise estimations were of similar amplitude as those for the photo-optical estimations.
Abstract | Full text in HTML | Full text in PDF | Author Info

In terms of assessing economic impact, one of the most important elements in the wood supply chain is the measurement of round wood. Besides the one-by-one measurement of logs, logs are often measured when stacked at the forest road. The gross stacked volume includes the volume of the wood, bark and airspace and is widely used for industrial wood assortments. The increasing international attention given to photo-optical measurement systems for portable devices is due to their simplicity of use and efficiency. The aim of this study was to compare the gross volumes of hardwood log stacks measured using one widespread photo-optical app with two manual section-wise volume estimations of log stacks based on the German framework agreement for timber trade (RVR). The manual volume estimations were done starting from the left (RVRleft) and right (RVRright) sides of the log stacks. The results showed an average deviation of the photo-optical gross volume estimation in comparison to the manual estimation of –2.09% (RVRleft) and –3.66% (RVRright) while the deviation between RVRleft and RVRright was +2.54%. However, the log stack gross volume had a highly significant effect on the deviation and better accuracy with smaller deviation were reached for larger log stacks. Moreover, results indicated that the gross volume estimations of higher quality log stacks were closer for the three analyzed methods compared to estimations of poor-quality log stacks.

  • Berendt, Department of Forest Utilization and Timber Markets, Eberswalde University for Sustainable Development, 16225 Eberswalde, Germany ORCID https://orcid.org/0000-0002-6285-7590 E-mail: ferreol.berendt@hnee.de (email)
  • Wolfgramm, Landesforst MV Anstalt des öffentlichen Rechts, Forstamt Billenhagen, 18182 Blankenhagen, Germany E-mail: felixwolfgramm@yahoo.de
  • Cremer, Department of Forest Utilization and Timber Markets, Eberswalde University for Sustainable Development, 16225 Eberswalde, Germany E-mail: tobias.cremer@hnee.de
article id 10291, category Research article
Sakari Tuominen, Andras Balazs, Annika Kangas. (2020). Comparison of photogrammetric canopy models from archived and made-to-order aerial imagery in forest inventory. Silva Fennica vol. 54 no. 5 article id 10291. https://doi.org/10.14214/sf.10291
Keywords: distribution; prediction; forest resources; mapping; aerial imaging; digital stereo-photogrammetry
Highlights: Two photogrammetric canopy models were tested in forest inventory: one based on archived standard aerial imagery acquired for ortho-mosaic production and another based on stereo-photogrammetrically oriented aerial imaging adjusted for stereo-photogrammetric canopy modelling; Both data sets were tested in the estimation of forest variables; Despite the differences in imaging parameters, there was little difference in their performance in predicting the forest inventory variables.
Abstract | Full text in HTML | Full text in PDF | Author Info

In remote sensing-based forest inventories 3D point cloud data, such as acquired from airborne laser scanning, are well suited for estimating the volume of growing stock and stand height, but tree species recognition often requires additional optical imagery. A combination of 3D data and optical imagery can be acquired based on aerial imaging only, by using stereo photogrammetric 3D canopy modeling. The use of aerial imagery is well suited for large-area forest inventories, due to low costs, good area coverage and temporally rapid cycle of data acquisition. Stereo-photogrammetric canopy modeling can also be applied to previously acquired imagery, such as for aerial ortho-mosaic production, assuming that the imagery has sufficient stereo overlap. In this study we compared two stereo-photogrammetric canopy models combined with contemporary satellite imagery in forest inventory. One canopy model was based on standard archived imagery acquired primarily for ortho-mosaic production, and another was based on aerial imagery whose acquisition parameters were better oriented for stereo-photogrammetric canopy modeling, including higher imaging resolution and greater stereo-coverage. Aerial and satellite data were tested in the estimation of growing stock volume, volumes of main tree species, basal area and diameter and height. Despite the better quality of the latter canopy model, the difference of the accuracy of the forest estimates based on the two different data sets was relatively small for most variables (differences in RMSEs were 0–20%, depending on variable). However, the estimates based on stereo-photogrammetrically oriented aerial data retained better the original variation of the forest variables present in the study area.

  • Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: sakari.tuominen@luke.fi (email)
  • Balazs, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: andras.balazs@luke.fi
  • Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: annika.kangas@luke.fi
article id 7721, category Research article
Sakari Tuominen, Andras Balazs, Eija Honkavaara, Ilkka Pölönen, Heikki Saari, Teemu Hakala, Niko Viljanen. (2017). Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables. Silva Fennica vol. 51 no. 5 article id 7721. https://doi.org/10.14214/sf.7721
Keywords: forest inventory; digital photogrammetry; aerial imagery; hyperspectral imaging; radiometric calibration; UAVs; stereo-photogrammetric canopy modelling
Highlights: Hyperspectral imagery and photogrammetric 3D point cloud based on RGB imagery were acquired under weather conditions changing from cloudy to sunny; Calibration of hyperspectral imagery was required for compensating the effect of varying weather conditions; The combination of hyperspectral imagery and photogrammetric point cloud data resulted in accurate forest estimates, especially for volumes per tree species.
Abstract | Full text in HTML | Full text in PDF | Author Info

Remote sensing using unmanned aerial vehicle (UAV) -borne sensors is currently a highly interesting approach for the estimation of forest characteristics. 3D remote sensing data from airborne laser scanning or digital stereo photogrammetry enable highly accurate estimation of forest variables related to the volume of growing stock and dimension of the trees, whereas recognition of tree species dominance and proportion of different tree species has been a major complication in remote sensing-based estimation of stand variables. In this study the use of UAV-borne hyperspectral imagery was examined in combination with a high-resolution photogrammetric canopy height model in estimating forest variables of 298 sample plots. Data were captured from eleven separate test sites under weather conditions varying from sunny to cloudy and partially cloudy. Both calibrated hyperspectral reflectance images and uncalibrated imagery were tested in combination with a canopy height model based on RGB camera imagery using the k-nearest neighbour estimation method. The results indicate that this data combination allows accurate estimation of stand volume, mean height and diameter: the best relative RMSE values for those variables were 22.7%, 7.4% and 14.7%, respectively. In estimating volume and dimension-related variables, the use of a calibrated image mosaic did not bring significant improvement in the results. In estimating the volumes of individual tree species, the use of calibrated hyperspectral imagery generally brought marked improvement in the estimation accuracy; the best relative RMSE values for the volumes for pine, spruce, larch and broadleaved trees were 34.5%, 57.2%, 45.7% and 42.0%, respectively.

  • Tuominen, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 2, FI-00791 Helsinki, Finland ORCID http://orcid.org/0000-0001-5429-3433 E-mail: sakari.tuominen@luke.fi (email)
  • Balazs, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: andras.balazs@luke.fi
  • Honkavaara, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland E-mail: eija.honkavaara@nls.fi
  • Pölönen, University of Jyväskylä, Faculty of Information Technology, P.O. Box 35, FI-40014 Jyväskylä, Finland E-mail: ilkka.polonen@jyu.fi
  • Saari, VTT Microelectronics, P.O. Box 1000, FI-02044 VTT, Finland E-mail: heikki.saari@vtt.fi
  • Hakala, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland E-mail: teemu.hakala@nls.fi
  • Viljanen, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland E-mail: niko.viljanen@nls.fi
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
Keywords: forest inventory; remote sensing; spatial autocorrelation; spatial distribution; aerial imagery; stereo-photogrammetry
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.
Abstract | Full text in HTML | Full text in PDF | Author Info

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 E-mail: sakari.tuominen@luke.fi (email)
  • Pitkänen, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: timo.p.pitkanen@luke.fi
  • Balazs, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: andras.balazs@luke.fi
  • Kangas, Natural Resources Institute Finland (Luke), Economics and Society, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: Annika.Kangas@luke.fi
article id 2021, category Research article
Jonas Bohlin, Inka Bohlin, Jonas Jonzén, Mats Nilsson. (2017). Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory. Silva Fennica vol. 51 no. 2 article id 2021. https://doi.org/10.14214/sf.2021
Keywords: airborne laser scanning; National Forest Inventory; photogrammetry; aerial images; forest attribute estimation; image matching; large area
Highlights: Image based forest attribute map generated using NFI plots show similar accuracy as currently used LiDAR based forest attribute map; Also similar accuracies were found for different forest types; Aerial images from leaf-off season is not recommended.
Abstract | Full text in HTML | Full text in PDF | Author Info

Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m × 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping.

  • Bohlin, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden ORCID http://orcid.org/0000-0002-3318-5967 E-mail: jonas.bohlin@slu.se (email)
  • Bohlin, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden ORCID http://orcid.org/0000-0003-1224-6684 E-mail: inka.bohlin@slu.se
  • Jonzén, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden E-mail: jonas.jonzen@slu.se
  • Nilsson, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden ORCID http://orcid.org/0000-0001-7394-6305 E-mail: mats.nilsson@slu.se
article id 335, category Research article
Markus Holopainen, Mervi Talvitie. (2006). Effect of data acquisition accuracy on timing of stand harvests and expected net present value. Silva Fennica vol. 40 no. 3 article id 335. https://doi.org/10.14214/sf.335
Keywords: forest inventory; laser scanning; digital aerial photographs; digital photogrammetry; net present value; expected net present value loss
Abstract | View details | Full text in PDF | Author Info
Modern remote sensing provides cost-efficient spatial digital data that are more accurate than before. However, the influence of increased accuracy and cost-efficiency on simulations of forest management planning has not been evaluated. The aim of the present study was to analyse the effect of data acquisition accuracy on standwise forest inventory by comparing the accuracy and cost of traditional compartmentwise inventory methods with 2D and 3D measurements of digital aerial photographs and airborne laser scanning. Comparison was based on the expected net present value (NPV), i.e. economic losses that consisted of the inventory costs and incorrect timings of treatments. The reference data, totalling 700 ha, were measured from Central Park in the city of Helsinki, Finland. The data were simulated to final cut with a MOTTI simulator, which is a stand-level analysis tool that can be used to assess the effects of alternative forest management practices on growth and timber yield. The results showed that when inventory costs were not considered there were no significant differences between the expected NPV losses in 3D measurements of digital aerial photographs, laser scanning and the compartmentwise method. When inventory costs were taken into account, the compartmentwise method was still the most efficient inventory method in the study area. Forest inventories, however, are usually directed to larger areas when the costs per hectare of remote-sensing methods decrease. As a result of better accuracies, 3D and compartmentwise methods always produce better results than the 2D method when NPV losses are accounted. Simulations of this type are based on the accuracies and costs of the 3D data available today, assuming that the data can be used in tree-level measurements.
  • Holopainen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: markus.holopainen@helsinki.fi (email)
  • Talvitie, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: mt@nn.fi
article id 355, category Research article
Ilkka Korpela. (2006). Geometrically accurate time series of archived aerial images and airborne lidar data in a forest environment. Silva Fennica vol. 40 no. 1 article id 355. https://doi.org/10.14214/sf.355
Keywords: vegetation; canopy; monitoring; laser scanning; change detection; photogrammetry; 3D; aerial triangulation; direct georeferencing
Abstract | View details | Full text in PDF | Author Info
Reconstructing three-dimensional structural changes in the forest over time is possible using archived aerial photographs and photogrammetric techniques, which have recently been introduced to a larger audience with the advent of digital photogrammetry. This paper explores the feasibility of constructing an accurate time-series of archived aerial photographs spanning 42 years using different types of geometric data and estimation methods for image orientation. A recent airborne laser scanning (lidar) data set was combined with the image block and assessed for geometric match. The results suggest that it is possible to establish the multitemporal geometry of an image block to an accuracy that is better than 0.5 m in 3D and constant over time. Even geodetic ground control points can be omitted from the estimation if the most recent images have accurate direct sensor orientation, which is becoming a standard technique in aerial photography. This greatly reduces the costs and facilitates the work. An accurate multitemporal image block combined with recent lidar scanning for the estimation of topography allows accurate monitoring and retrospective analysis of forest vegetation and management operations.
  • Korpela, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ilkka.korpela@helsinki.fi (email)

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