Skattningar i gallringsskog med hjälp av flygburen laserskanning : beräkningar med massaslutenhet
This master’s thesis is a remote sensing study of an area-based method used to detect forest in need of thinning by use of laser data and field samples. Only pine-dominated forest has been included in the study and height limits were set to match empirical restrictions. The study area was in the mun...
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| Format: | Other/Unknown Material |
| Language: | Swedish English |
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SLU/Dept. of Forest Resource Management
2010
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| Online Access: | https://stud.epsilon.slu.se/2257/ |
| Summary: | This master’s thesis is a remote sensing study of an area-based method used to detect forest in need of thinning by use of laser data and field samples. Only pine-dominated forest has been included in the study and height limits were set to match empirical restrictions. The study area was in the municipality of Älvsbyn (Latitude 65° 40´ N, Longitude 21° 00´ E), in northern Sweden. The Swedish authority Lantmäteriet is currently laser scanning most parts of Sweden, providing new opportunities and applications. The primary aim of the national laser scanning is to create a new elevation model, useful in consequence analysis of climate changes. The laser data are, therefore, small footprint with 0.5 – 1 returns m-2 and classed into ground, water or unknown. However the opportunity in question is that the same laser data may also be useful for measuring forest, as shown in this study. The use of these laser data may be advantageous for forestry since the data are provided to the public at a low cost. The direction of this study that differs from other laser studies is the use of volume density (in Swedish, “massaslutenhet” ;Skogsord 1983) as a variable to describe the forest. If volume density and height of the forest are known, the basal area and volume can be calculated as well. These connections were founded by Jonsson (1914) and have been used for forest estimation based on aerial photos (Åge 1983). Volume density index may also be a useful variable in deciding whether to thin the forest or not. Raster images of basal area, height, volume density, and volume were created over the study area using estimations based on regression analysis. The accuracy was high inside the field samples and over fitting could be rejected by cross validation. A model using the raster images were created in the program ArcGIS to enable a user to decide what kind of forest to identify for thinning operations. The output from this model was compared and evaluated with an existing stand registry. To summarize, this study manifests that ... |
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