<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The purpose of the present study was to convey to the reader the method and application of the Finnish Multi-Source National Forest Inventory (MS-NFI) that was devised in the Finnish Forest Research Institute. The study area concerned is Stołowe Mountains National Park, which is located in the south-western Poland, near the border with the Czech Republic. To accomplish the above mentioned aim, the following data have been applied: timber volume derived from field sample plots, satellite image, digital map data and digital elevation model. The Pearson correlation coefficient between independent and dependent variables has been verified. Furthermore, the non-parametric k-nearest neighbours (k-NN) technique and genetic algorithm have been used in order to estimate forest stands biomass at the pixel level. The error estimates have been obtained by leave-one-out cross-validation method. The main computed forest stands features were total and mean timber volume as well as maximum and minimum biomass occurring in the examined area. In the final step, timber volume map of the growing stock has been created.</p></abstract>

The purpose of the present study was to convey to the reader the method and application of the Finnish Multi-Source National Forest Inventory (MS-NFI) that was devised in the Finnish Forest Research Institute. The study area concerned is Stołowe Mountains National Park, which is located in the south-western Poland, near the border with the Czech Republic. To accomplish the above mentioned aim, the following data have been applied: timber volume derived from field sample plots, satellite image, digital map data and digital elevation model. The Pearson correlation coefficient between independent and dependent variables has been verified. Furthermore, the non-parametric k-nearest neighbours (k-NN) technique and genetic algorithm have been used in order to estimate forest stands biomass at the pixel level. The error estimates have been obtained by leave-one-out cross-validation method. The main computed forest stands features were total and mean timber volume as well as maximum and minimum biomass occurring in the examined area. In the final step, timber volume map of the growing stock has been created.

Forest stands volume estimation by using Finnish Multi-Source National Forest Inventory in Stołowe Mountains National Park

Eberswalde University for Sustainable Development, Faculty of Forest and Environment, Alfred-Möller-Strasse 1, 16225 Eberswalde, Germany

Warsaw University of Life Sciences, Faculty of Forestry, Department of Forest Management, Geomatics and Forest Economics, Nowoursynowska 159, 02-776 Warsaw, Poland, phone: +48791709242

Folia Forestalia Polonica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The purpose of the present study was to convey to the reader the method and application of the Finnish Multi-Source National Forest Inventory (MS-NFI) that was...

Forest stands volume estimation by using Finnish Multi-Source National Forest Inventory in Stołowe Mountains National Park

Pubblicato online: 30 apr 2016

Pagine: 3 - 12

Ricevuto: 20 ott 2015

Accettato: 18 gen 2016

DOI: https://doi.org/10.1515/ffp-2016-0001

Parole chiave
forest inventory, genetic algorithm, k-nearest neighbours, satellite images, Stołowe Mountains National Park, stratification

© 2016 Przemko Pachana, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Forest stands volume estimation by using Finnish Multi-Source National Forest Inventory in Stołowe Mountains National Park

Pubblicato online: 30 apr 2016

Pagine: 3 - 12

Ricevuto: 20 ott 2015

Accettato: 18 gen 2016

DOI: https://doi.org/10.1515/ffp-2016-0001

Parole chiaveforest inventory, genetic algorithm, k-nearest neighbours, satellite images, Stołowe Mountains National Park, stratification

© 2016 Przemko Pachana, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
forest inventory, genetic algorithm, k-nearest neighbours, satellite images, Stołowe Mountains National Park, stratification