No abstract

Water tends to flow and accumulate in response to topographical characteristics of local area and gravitational potential energy. Remote sensing data like LiDAR (Light detecting and ranging) or satellite data can be used to identify local depressions where wet areas may occur. The aim of this study was to evaluate methods that can be used to identify wet areas, to determine correlation between topography of the area and forest regeneration and to prepare proposals for forest management that could be usable in Latvia. Study area includes fertile forest land on wet mineral soils and drained mineral soils with planted spruce (Picea abies) and available LiDAR data. Map examples have been made to demonstrate methodology which allows to identify depressions with potentially hindered run-off. Fill sinks algorithm has shown best results in identifying wet areas and correlation with wet areas that were detected in field studies is 62%. TWI index is not suitable for this study because of relatively flat area. Result of this study reveals that wet areas have significant effect on tree species. In depressions, despite the fact that there has been planted spruce, main species are birch (Betula pendula) and black alder (Alnus glutinosa). Wet areas have significant effect on tree height.

The aim of this study is to improve the practice of mechanical forest site preparation (FSP) by identifying typical characteristics of FSP, including the direction of FSP machinery, manoeuvre count depending on configuration of parcel and forest type and width of manoeuvre track; to evaluate the productivity depending on different forest growing conditions; to create schemes of technological corridors for commercial thinning; to improve scheme of FSP according to the scheme of technical corridors for commercial thinning and to evaluate changes in the count of manoeuvres and total distance travelled. In this study, we have developed methods to evaluate the quality of FSP. Methods used in this study include GIS analysis of vector data from FSP machinery tracking devices and LiDAR (Light detecting and ranging) data analysis for terrain information. Study shows that there is a significant difference in productivity when the machinery of FSP is driving in different angles to the longitudinal axis of parcel. Reduced productivity is justified by prioritizing topography of the forest floor. Slope is a decisive factor in the ground water movement and should be considered in FSP planning. Study shows that the developed method could be implemented in practice of forest management in 41% of sampled forest stands.