3 research outputs found
Identification of tree species in Mt Chojnik (Karkonoski National Park) forest using airborne hyperspectal APEX data
We used hyperspectral data from APEX scanner (288 spectral bands in 380−2500 nm spectral range; 3,5 m spatial resolution) to classify five tree species occurring in the area of Mt. Chojnik in the Karkonoski National Park (south−western Poland). Data used to delimit learning and verification polygons were acquired during field research in August 2013, when ground truth polygons were acquired using device equipped with GPS receiver. Raw APEX data went through radiometric and geometric correction at VITO office. To reduce processing time, 40 most informative bands were selected using information content analysis. The Support Vector Machines (SVM) algorithm was used for classification of the following tree species: Fagus sylvatica L., Betula pendula Roth, Pinus sylvestris L., Picea alba L. Karst and Larix decidua Mill. Final classification had 78.66% overall accuracy with Kappa coefficient equal to 0.71. The best classified species included beech (87.09%) and pine (83.96%), while the worst results were obtained for larch (60.29%). Low accuracy for larch could be caused by the fact that most of larch trees in the research area grow in small patches, which made it hard to specify large enough sample of training data. All classified tree species had producer's accuracy of at least 60%, with the highest value reaching 87%. User's accuracies were from 53% for pine to 85% for beech. It is possible to classify tree species using hyperspectral data with moderate to high accuracy even if the data used lacked atmospheric correction. Further work will focus on improving the classification accuracy and use of neural networks based classification methods. Results from this paper will serve as basis for tree species map of the Karkonoski National Park
The Impact of Living and Working Longer on Pension Income in Five European Countries
Life expectancies are rapidly increasing and uncertain in all countries in Europe. To keep pension systems affordable, policy reforms are to be implemented which will encourage individuals to work longer and that adjust pension systems such that if life expectancy increases without adjustments in the retirement age, the pension income level decreases. In this paper we analyze the impact of working and living longer on pension incomes in five European countries and assess the impact of these policy reforms on the financial well-being of the elderly in these countries. The paper shows the diversity of the policy measures taken in the various countries. Furthermore, we analyze the financial incentives to work longer and to postpone claiming pension benefit in the five countries and we address the question, how attractive these options are. Moreover we analyze how increases in life expectancy and survival probabilities affect pension incomes