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Articles containing the keyword 'aerial photographs'

Category : Article

article id 4705, category Article
Aarne Nyyssönen, Simo Poso. (1962). Koe metsikköluokitusten suorittamiseksi ilmakuvien avulla. Silva Fennica no. 112 article id 4705. https://doi.org/10.14214/sf.a14232
English title: Tree stand classifications from aerial photographs: an experiment.
Original keywords: metsänarviointi; ilmakuvat; metsäninventointi; menetelmät
English keywords: forest inventory; stratification; aerial photographs; forest mensuration; methods
Abstract | View details | Full text in PDF | Author Info

In connection to the Third National Forest Inventory of Finland, two survey strips in the northernmost Finland were photographed on scale 1:15,000. Infrared films and a yellow filter were used. For the present experiment a total length of 66 km of the strips was photographed. The strips were surveyed visually from the ground by stands. Sample plots were measured at kilometre intervals. The aerial photographs were surveyed the distances covered in the ground. The work was aided by stereograms which showed 16 large-size sample plots localised on aerial photographs.

The main groups of land identified along the survey line were productive and poorly productive forest land, wasteland and another land, in addition, peatland and firm land were distinguished. Although some differences were noted, the two survey methods provided fairly similar results. For an estimation of the tree species composition the material is one-sided since the district is mainly Scots pine. The principal tree species was successfully distinguished on aerial photographs in 78 out of 82 comparable pairs.

The mean of ground observations of dominant height of the stands was 10.9 m, that of observations on aerial photographs 11.2 m. The result of stand volume estimates reveals a distinct correlation between the various methods of estimation.

In an earlier study it was shown that it is possible, using a stand volume table based on characteristics revealed in aerial photography, to create a general idea of stand volume on the southern half of the country. A few additional factors, of interest for the stratification necessary in forest inventories, were also studied. A distinct correlation was observed between the results of aerial and ground survey for all the characteristics discussed. The present experiment showed that the prerequisites for stratification through aerial photographs do exist. Further investigation is needed into the most appropriate methods for stratification in each situation.

The PDF includes a summary in English.

  • Nyyssönen, E-mail: an@mm.unknown (email)
  • Poso, E-mail: sp@mm.unknown
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.
Original keywords: metsäopetus; metsänhoitajien jatkokurssit; jatkokoulutus; ilmakuvaus; kaukokartoitus; kartoitus
English keywords: remote sensing; aerial photographs; forest education; aerial mapping
Abstract | View details | Full text in PDF | Author Info

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, E-mail: ol@mm.unknown (email)

Category : Research article

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 367, category Research article
Sakari Tuominen, Markus Haakana. (2005). Landsat TM imagery and high altitude aerial photographs in estimation of forest characteristics. Silva Fennica vol. 39 no. 4 article id 367. https://doi.org/10.14214/sf.367
Keywords: multi-source forest inventory; satellite imagery; high-altitude aerial photographs; image texture
Abstract | View details | Full text in PDF | Author Info
Satellite sensor data have traditionally been used in multi-source forest inventory for estimating forest characteristics. Their advantages generally are large geographic coverage and large spectral range. Another remote sensing data source for forest inventories offering a large geographic coverage is high altitude aerial photography. In high altitude aerial photographs the spectral range is very narrow but the spatial resolution is high. This allows the extraction of texture features for forest inventory purposes. In this study we utilized a Landsat 7 ETM satellite image, a photo mosaic composed of high altitude panchromatic aerial photographs, and a combination of the aforementioned in estimating forest attributes for an area covering approximately 281 000 ha in Forestry Centre Häme-Uusimaa in Southern Finland. Sample plots of 9th National Forest Inventory (NFI9) were used as field data. In the estimation, 6 Landsat 7 ETM image channels were used. For aerial photographs, 4 image channels were composed from the spectral averages and texture features. In combining both data sources, 6 Landsat channels and 3 aerial image texture channels were selected for the analysis. The accuracy of forest estimates based on the Landsat image was better than that of estimates based on high altitude aerial photographs. On the other hand, using the combination of Landsat ETM spectral features and textural features on high altitude aerial photographs improved the estimation accuracy of most forest attributes.
  • Tuominen, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland E-mail: sakari.tuominen@metla.fi (email)
  • Haakana, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland E-mail: mh@nn.fi
article id 544, category Research article
Perttu Anttila. (2002). Updating stand level inventory data applying growth models and visual interpretation of aerial photographs. Silva Fennica vol. 36 no. 2 article id 544. https://doi.org/10.14214/sf.544
Keywords: aerial photographs; stand level inventory; MELA; updating of inventory data; visual interpretation
Abstract | View details | Full text in PDF | Author Info
In this study two procedures for updating stand level inventory data were developed and tested. The development of the growing stock of 62 stands over 12 years was simulated in the MELA stand simulator with no prior information of rapid changes, such as clear-cuttings. The acceptability of the simulation was decided standwise with visual interpretation of aerial false-colour photographs. If the simulated data were not accepted, new stand attributes were assessed with photo interpretation in procedure 1. In procedure 2, on the other hand, it was possible to utilise old management proposals. In case a cutting or other operation had been proposed and it looked like the operation had been realised, the interpreters accepted the proposal. Otherwise the last implemented operation and implementation year were interpreted. In case no operation had been carried out during the updating period but the growth model updated data were not acceptable, the same stand characteristics were estimated as in procedure 1. Stands where a proposal had been accepted or an operation interpreted were later updated again in MELA so that the program simulated the operations. The Root Mean Squared Errors of stem volume were 62 and 57 m3 per ha (34 and 30%) with procedures 1 and 2. With procedure 2 the accuracy of updating was comparable with a stand level field inventory carried out in the study area. The productivity of the photo interpretation procedures was 57 and 84 ha per h, respectively, whereas the productivity of a field inventory has been 3.3–5 ha per h.
  • Anttila, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: perttu.anttila@joensuu.fi (email)
article id 682, category Research article
Guangxing Wang, Simo Poso, Mark-Leo Waite, Markus Holopainen. (1998). The use of digitized aerial photographs and local operation for classification of stand development classes. Silva Fennica vol. 32 no. 3 article id 682. https://doi.org/10.14214/sf.682
Keywords: calibration; classification; digitized aerial photographs; plot window location; local operation
Abstract | View details | Full text in PDF | Author Info
The increasing capacity of modern computers has created the opportunity to routinely process the very large data sets derived by digitizing aerial photographs. The very fine resolution of such data sets makes them better suited than satellite imagery for some applications; however, there may be problems in implementation resulting from variation in radial distortion and illumination across an aerial photograph. We investigated the feasibility of using local operators (e.g., non-overlapping moving window means and standard deviations) as auxiliary data for generating stand development classes via three steps: (i) derive 6 local operators intended to represent texture for a 16 by 16 m window corresponding to a forest inventory sampling unit, (ii) apply a calibration process (e.g., accounting for location relative to a photo's principal point and solar position) to these local operators, and (iii) apply the calibrated local operators to classify the forest for stand development. Results indicate that calibrated local operators significantly improve the classification compared to what is possible using uncalibrated local operators and satellite images.
  • Wang, Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, IL, USA E-mail: wang12@staff2.cso.uiuc.edu (email)
  • Poso, Department of Forest Resource Management, P.O. Box 24, FIN-00014 University of Helsinki, Finland E-mail: sp@nn.fi
  • Waite, Department of Forest Resource Management, P.O. Box 24, FIN-00014 University of Helsinki, Finland E-mail: mlw@nn.fi
  • Holopainen, Department of Forest Resource Management, P.O. Box 24, FIN-00014 University of Helsinki, Finland E-mail: mh@nn.fi

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