Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                

Current issue: 58(5)

Scopus CiteScore 2023: 3.5
Scopus ranking of open access forestry journals: 17th
PlanS compliant
Select issue
Silva Fennica 1926-1997
1990-1997
1980-1989
1970-1979
1960-1969
Acta Forestalia Fennica
1953-1968
1933-1952
1913-1932

Articles by Terhikki Manninen

Category : Research article

article id 431, category Research article
Pauline Stenberg, Miina Rautiainen, Terhikki Manninen, Pekka Voipio, Heikki Smolander. (2004). Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands. Silva Fennica vol. 38 no. 1 article id 431. https://doi.org/10.14214/sf.431
Keywords: Landsat ETM ; Leaf Area Index; spectral vegetation indices; boreal coniferous forests
Abstract | View details | Full text in PDF | Author Info
Estimation of leaf area index (LAI) using spectral vegetation indices (SVIs) was studied based on data from 683 plots on two Scots pine and Norway spruce dominated sites in Finland. The SVIs studied included the normalised difference vegetation index (NDVI), the simple ratio (SR), and the reduced simple ratio (RSR), and were calculated from Landsat ETM images of the two sites. Regular grids of size 1 km2 with gridpoints placed at 50 m intervals were established at the sites and measurements of LAI using the LAI-2000 instrument were taken at the gridpoints. SVI-LAI relationships were examined at plot scale, where the plots were defined as circular areas of radius 70 m around each gridpoint. Plotwise mean LAI was computed as a weighted average of LAI readings taken around the gridpoints belonging to the plot. Mean LAI for the plots ranged from 0.36 to 3.72 (hemisurface area). All of the studied SVIs showed fair positive correlation with LAI but RSR responded more dynamically to LAI than did SR or NDVI. Especially NDVI showed poor sensitivity to changes in LAI. RSR explained 63% of the variation in LAI when all plots were included (n = 683) and the coefficient of determination rose to 75% when data was restricted to homogeneous plots (n = 381). Maps of estimated LAI using RSR showed good agreement with maps of measured LAI for the two sites.
  • Stenberg, Department of Forest Ecology, P.O. Box 27, FIN-00014 University of Helsinki, Finland E-mail: pauline.stenberg@helsinki.fi (email)
  • Rautiainen, Department of Forest Ecology, P.O. Box 27, FIN-00014 University of Helsinki, Finland E-mail: mr@nn.fi
  • Manninen, Finnish Meteorological Institute, Meteorological research, Ozone and UV radiation research, P.O. Box 503, FIN-00101 Helsinki, Finland E-mail: tm@nn.fi
  • Voipio, Finnish Forest Research Institute, Suonenjoki Research Station, FIN-77600 Suonenjoki, Finland E-mail: pv@nn.fi
  • Smolander, Finnish Forest Research Institute, Suonenjoki Research Station, FIN-77600 Suonenjoki, Finland E-mail: hs@nn.fi

Category : Research note

article id 228, category Research note
Aku Riihelä, Terhikki Manninen. (2008). Measuring the vertical albedo profile of a subarctic boreal forest canopy. Silva Fennica vol. 42 no. 5 article id 228. https://doi.org/10.14214/sf.228
Keywords: boreal forest; albedo; validation; canopy transmission
Abstract | View details | Full text in PDF | Author Info
The validation of airborne and satellite-derived albedo measurements suffers from the fact that the surface albedo of forest is difficult to measure in-situ over large areas. The goal of this study is to examine whether or not the estimation of the surface albedo of a forest stand from ground level measurements is possible. In addition, knowledge about the vertical behavior of albedo, and therefore transmitted solar radiation, is important in the modeling of interactions of sunlight with the forest canopy. Such modeling is useful for forest growth estimations among other things. To achieve these goals, an albedometer set-up capable of vertical albedo profiling has been used to obtain data from a boreal forest stand in Northern Finland during periods in summer 2006 and winter 2007. The results show a strong relationship between the data and fitted power-law regression curves. Power-law regression fits best likely because of the radiation transmission characteristics of boreal forest.
  • Riihelä, Finnish Meteorological Institute, P.O. Box 503, FI-00200 Helsinki, Finland E-mail: aku.riihela@fmi.fi (email)
  • Manninen, Finnish Meteorological Institute, P.O. Box 503, FI-00200 Helsinki, Finland E-mail: tm@nn.fi

Click this link to register to Silva Fennica.
If you are a registered user, log in to save your selected articles for later access.
Sign up to receive alerts of new content
Your selected articles