Martin ZÁPOTOCKÝ, Zuzana SLATKOVSKÁ, Milan KOREŇ

Identification of forest cover dynamics from time series of orthophotos on the territory of the University Forest Enterprise

Zápotocký, M., Slatkovská, Z., Koreň, M.: Identification of forest cover dynamics from time series of orthophotos on the territory of the University Forest Enterprise. Kartografické listy, 2017, 25 (2).

Abstract: Information about historical forest dynamics are crucial to derive its potential characteristics in the future. Studies about changes in a forest landscape require relevant maps. In recent years, a forestry research uses access to archived cartographic works to analyze changes in a forest cover over a wider time period. The availability of orthophotos from previous decades is a suitable basis for deriving the dynamics of the forest cover from the second half of the 20th century to the present. The aim of the paper is to propose a methodical procedure based on the identification of the forest cover on the basis of black and white historical and color current orthophotos. The forest cover is classified on the basis of object-oriented analysis using Trimble's eCognition Developer software. Consequently, this paper deals with a multi-temporal analysis of forest dynamics over the period under review. The multi-temporal analysis is aimed at assessing the forest area in each considered time period in hectares and percentages from the whole area and the absolute change of the forest cover between the individual time horizons in hectares. The area of interest is the University Forest Enterprise of the Technical University in Zvolen – Forest District Budča. Changes in forest dynamics were assessed in three time periods (1949, 1978 and 2009). Assessing the dynamics of the forest cover in the short term by means of orthophotos brings a relatively precise temporal-spatial context to the presented issue which is not only applied in a forestry research and operation, but also for the needs of teaching and understanding the dynamics of the forest environment.

Keywords: automatic classification, forest dynamics, multi-temporal analysis, orthophotos, University Forest Enterprise