Increased urbanization and the exploitation of green areas has resulted in fragmentation and reduced habitats for species and when more species becomes threatened, this has negative consequences on biodiversity on a landscape level. In order to strengthen and develop new areas of potential dispersal possibilities for species in the landscape effective methods are needed that produce data on a landscape level, which can later be used in landscape analysis. Due to continuous exploitation of green areas in urban environment tree avenues have become important dispersal corridors and refuges for various plant and animal species. Reliable information on tree avenues is needed if authorities are to formulate local, regional and global environmental targets to increase the number of geographically distributed tree avenues that provides the best ecological function and the maintenance or strengthening of other values. Today only a fraction of Sweden’s tree avenues with high cultural historical and nature conservation values have been documented along the state road network. Data of tree avenues must also be integrated in landscape analysis to develop a sustainable environment to improve ecological function and at the same time strengthen existing values. Therefore, it is also important to map young tree avenues in order to provide data in long-term planning perspectives, as they constitute important components of sustainable spatial and temporal landscape planning. This study presents a methodological development of how avenues can be effectively mapped with a combination of several remote sensing techniques, primarily using data from Light Ranging Detection Aperture Radar (LiDAR). A tree avenue database covering Sollentuna municipality, Stockholm County, Sweden has then been created with information about the location of tree avenues with tree species, age group, number of large trees, geographical orientation and crown width. The attributes were collected using interpretation of aerial photographs, GIS operations and field work. Finally, to highlight the potential use of a tree avenue database, the data was used in two landscape ecological connectivity models (Circuitscape and Linkage Mapper) using the marsh tit (Parus palustris) as model species. The results were examined to suggest where new tree avenues should be placed and how they should be designed to strengthen the ecological relationships of the marsh tit in Sollentuna municipality.
This new technical approach to evaluate tree avenues has proven to be successful. However, there are several aspects in the method that could be further developed to improve both efficiency and accuracy.
Landscape ecology, landscape planning, green infrastructure, GIS, LiDAR, remote sensing, Circuitscape, Linkage Mapper