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Silva Fennica 1926-1997
Acta Forestalia Fennica

Articles containing the keyword 'semivariance'

Category : Article

article id 5598, category Article
Timo Kuuluvainen, Kari Leinonen, Markku Nygren, Antti Penttinen. (1996). Statistical opportunities for comparing stand structural heterogeneity in managed and primeval forests: an example from boreal spruce forest in southern Finland. Silva Fennica vol. 30 no. 2–3 article id 5598.
Keywords: boreal forests; Norway spruce; biodiversity; Picea abies; stand structure; semivariance; spatial analysis; K-function; structural variation
Abstract | View details | Full text in PDF | Author Info

The horizontal and vertical stand structure of living trees was examined in a managed and in a primeval Norway spruce-dominated forest in Southern Finland. Tree size distributions (DBHs, tree height) were compared using frequency histograms. The vertical distribution of tree heights was illustrated as tree height plots and quantified as the tree height diversity (THD) using the Shannon-Weaver formula. The horizontal spatial pattern of trees was described with stem maps and quantified with Ripley's K-function. The spatial autocorrelation of tree sizes was examined with semivariogram analysis. In the managed forest the DBH and height distributions of trees were bimodal, indicating a two-layered vertical structure with a single dominant tree layer and abundant regeneration in the understory. The primeval forest had a much higher total number of trees which were rather evenly distributed in different diameter and tree height classes. The K-function summaries for trees taller than 15 m indicated that the primeval stand was close to complete random pattern. The managed stand was regular at small distances (up to 4 m). The semivariograms of tree sizes (DBH tree height) showed that the managed forest had a clear spatial dependence in tree sizes up to inter-tree distances of about 12 meters. In contrast, the primeval spruce forest had a variance peak at very short inter-tree distances (< 1 m) and only weak spatial autocorrelation at short inter-tree distances (1–5 m). Excluding the understory trees (h < 15 m) from the analysis drastically changed the spatial structure of the forest as revealed by semivariograms. ln general, the structure of the primeval forest was both horizontally and vertically more variable and heterogeneous compared to the managed forest. The applicability of the used methods in describing fine-scale forest structure i discussed.

  • Kuuluvainen, E-mail: tk@mm.unknown (email)
  • Leinonen, E-mail: kl@mm.unknown
  • Nygren, E-mail: mn@mm.unknown
  • Penttinen, E-mail: ap@mm.unknown

Category : Review article

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.
Keywords: remote sensing; spatial information; semivariance; semivariogram; forest classification
Abstract | View details | Full text in PDF | Author Info
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 E-mail: (email)
  • Cieszewski, D. B. Warnell School of Forest Resources, University of Georgia, Athens, GA 30602, USA E-mail:
  • Zasada, Department of Forest Productivity, Faculty of Forestry, Warsaw Agricultural University, Poland E-mail:
  • Lowe, D. B. Warnell School of Forest Resources, University of Georgia, Athens, GA 30602, USA E-mail:

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