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Articles containing the keyword 'satellite images'.

Category: Research article

article id 10347, category Research article
Matti Katila, Tuomas Rajala, Annika Kangas. (2020). Assessing local trends in indicators of ecosystem services with a time series of forest resource maps. Silva Fennica vol. 54 no. 4 article id 10347. https://doi.org/10.14214/sf.10347
Highlights: Untitled Document Contextual Mann-Kendall test detects significant trends in time-series of forest maps; Trends become more consistent as the areal unit size used for test input increases; Changes in different scales reflect different phenomena in forests; Significant trends were detected even after multiple testing correction.

Since the 1990’s, forest resource maps and small area estimates have been produced by combining national forest inventory (NFI) field plot data, optical satellite images and numerical map data using a non-parametric k-nearest neighbour method. In Finland, thematic maps of forest variables have been produced by the means of multi-source NFI (MS-NFI) for eight to ten times depending on the geographical area, but the resulting time series have not been systematically utilized. The objective of this study was to explore the possibilities of the time series for monitoring the key ecosystem condition indicators for forests. To this end, a contextual Mann-Kendall (CMK) test was applied to detect trends in time-series of two decades of thematic maps. The usefulness of the observed trends may depend both on the scale of the phenomena themselves and the uncertainties involved in the maps. Thus, several spatial scales were tested: the MS-NFI maps at 16 × 16 m2 pixel size and units of 240 × 240 m2, 1200 × 1200 m2 and 12  000 × 12  000 m2 aggregated from the MS-NFI map data. The CMK test detected areas of significant increasing trends of mean volume on both study sites and at various unit sizes except for the original thematic map pixel size. For other variables such as the mean volume of tree species groups, the proportion of broadleaved tree species and the stand age, significant trends were mostly found only for the largest unit size, 12  000 × 12  000 m2. The multiple testing corrections decreased the amount of significant p-values from the CMK test strongly. The study showed that significant trends can be detected enabling indicators of ecosystem services to be monitored from a time-series of satellite image-based thematic forest maps.

  • Katila, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, FI-00790 Helsinki, Finland; ORCID ID: https://orcid.org/0000-0001-6946-5736 E-mail: matti.katila@luke.fi (email)
  • Rajala, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland ORCID ID:E-mail: tuomas.rajala@luke.fi
  • Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, FI-80100 Joensuu, Finland ORCID ID: https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
article id 587, category Research article
Erkki Tomppo, Kari T. Korhonen, Juha Heikkinen, Hannu Yli-Kojola. (2001). Multi-source inventory of the forests of the Hebei Forestry Bureau, Heilongjiang, China. Silva Fennica vol. 35 no. 3 article id 587. https://doi.org/10.14214/sf.587
A multi-source forest inventory method is applied to the estimation of forest resources in the area of the Hebei Forest Bureau in Heilongjiang province in North-East China. A stratified systematic cluster sampling design was utilised in field measurements. The design was constructed on the basis of information from earlier stand-level inventories, aerial orthophotographs, experiences from other sampling inventories and the available budget. Sample tree volumes were estimated by means of existing models. New models were constructed and their parameters estimated for tallied tree volumes and volume increments. The estimates for the area of the Bureau were computed from field measurements, and for the areas of the forest farms estimated from field measurements and satellite images. A k-nearest neighbour method was utilised. This method employing satellite image data makes it possible to estimate all variables, particularly for smaller areas than that possible using field measurements only. The methods presented, or their modifications, could also be applied to the planning and realisation of forest inventories elsewhere in Temperate or Boreal zones. The inventory in question gave an estimate of 114 m3/ha (the multi-source inventory 119 m3/ha) instead of 72 m3/ha as previously estimated from available information. Totally nineteen tree species, genera of species or tree species groups were identified (Appendix 1). The forests were relatively young, 60% of them younger than 40 years and 85% younger than 60 years.
  • Tomppo, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail: erkki.tomppo@metla.fi (email)
  • Korhonen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail:
  • Heikkinen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail:
  • Yli-Kojola, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland ORCID ID:E-mail:

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 7675, category Article
Erkki Tomppo. (1992). Satellite image aided forest site fertility estimation for forest income taxation. Acta Forestalia Fennica no. 229 article id 7675. https://doi.org/10.14214/aff.7675

Two operative forest site class estimation methods utilizing satellite images have been developed for forest income taxation purposes. For this, two pixelwise classification methods and two post-processing methods for estimating forest site fertility are compared using different input data. The pixelwise methods are discriminant analysis, based on generalized squared distances, and logistic regression analysis. The results of pixelwise classifications are improved either with mode filtering within forest stands or assuming a Markov random field type dependence between pixels. The stand delineation is obtained by using ordinary segmentation techniques. Optionally, known stand boundaries given by the interpreter can be applied. The spectral values of images are corrected using a digital elevation model of the terrain. Some textural features are preliminary tested in classification. All methods are justified by using independent test data.

A test of the practical methods was carried out and a cost-benefit analysis computed. The estimated cost saving in site quality classification varies from 14% to 35% depending on the distribution of the site classes of the area. This means a saving of about 2.0–4.5 million FMK per year in site fertility classification for income taxation purposes. The cost savings would rise even to 60% if that version of the method were chosen where field checking is totally omitted. The classification accuracy at the forest holding level would still be similar to that of traditional method.

The PDF includes a summary in Finnish.

  • Tomppo, ORCID ID:E-mail:

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