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Silva Fennica 1926-1997
Acta Forestalia Fennica

Articles by Matti Katila

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.
Keywords: National Forest Inventory; satellite images; k-nearest neighbour estimation; Landsat; Mann-Kendall test; multitemporal inventory data; temporal trend analysis
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.
Abstract | Full text in HTML | Full text in PDF | Author Info

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 E-mail: (email)
  • Rajala, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail:
  • Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, FI-80100 Joensuu, Finland ORCID E-mail:

Category : Research note

article id 324, category Research note
Matti Katila. (2006). Empirical errors of small area estimates from the multisource National Forest Inventory in Eastern Finland. Silva Fennica vol. 40 no. 4 article id 324.
Keywords: k-nearest neighbours estimation; Landsat ETM ; multisource forest inventory; synthetic estimation
Abstract | View details | Full text in PDF | Author Info
The precision of multisource national forest inventory (MS-NFI) estimators and simple synthetic estimators based on NFI field data only was assessed employing an independent inventory data set of several small areas in Eastern Finland. There were seven test units of size 100 km2 and three test units of size 1 km2 for which a systematic field sampling was carried out. The ‘improved’ MS-NFI method yielded the most precise estimates for mean volume and mean volume of pine and spruce: relative root mean square errors (RMSE*) were 5%, 12% and 15% for 100 km2 test units and 13%, 27% and 40% for 1 km2 test units respectively. The stratified MS-NFI method was best for broad-leaved volume estimation. Synthetic estimation based on the NFI9 field plots post-stratified with coarse scale forest variable maps from NFI8 resulted in RMSE*s comparable to those of the ordinary MS-NFI in areas of 100 km2 for mean volume and mean volume of pine and spruce. The amount of variation between the field inventory estimates for the test units explained by the MS-NFI estimators remained the same or increased when the size of the area increased from of 1 km2 to 100 km2 and up to 2000 km2. The validation of the largest areas was made against the NFI9 field inventory estimates for groups of municipalities in the study area.
  • Katila, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland E-mail: (email)

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