In recent years the science revolving image matching algorithms has gotten an upswing mostly due to its benefits in computer vision. This has led to new opportunities for photogrammetric methods to compete with LiDAR data when it comes to 3D-point clouds and generating surface models. In Sweden a project to create a high resolution national height model started in 2009 and today almost the entirety of Sweden has been scanned with LiDAR sensors. The objective for this project is to achieve a height model with high spatial resolution and high accuracy in height. As for today no update of this model is planned in the project so it’s up to each municipality or company who needs a recent height model to update themselves. This thesis aims to investigate the benefits and shortcomings of using photogrammetric measures for generating and updating surface models. Two image matching software are used, ERDAS photogrammetry and Spacemetric Keystone, to generate a 3D point cloud of a rural area in Botkyrka municipality. The point clouds are interpolated into surface models using different interpolation percentiles and different resolutions. The photogrammetric point clouds are evaluated on how well they fit a reference point cloud, the surfaces are evaluated on how they are affected by the different interpolation percentiles and image resolutions. An analysis to see if the accuracy improves when the point cloud is interpolated into a surface. The result shows that photogrammetric point clouds follows the profile of the ground well but contains a lot of noise in the forest covered areas. A lower image resolution improves the accuracy for the forest feature in the surfaces. The results also show that noise-reduction is essential to generate a surface with decent accuracy. Furthermore, the results identify problem areas in dry deciduous forest where the photogrammetric method fails to capture the forest.

Reindeer are important drivers of ecosystem processes in arctic and subarctic ecosystems, changing nutrient conditions and influencing vegetation by grazing and trampling. Mountain birch forests are one of the ecosystems impacted by reindeer grazing, but the effect on the 3D structure of these forests is not well understood. Drones are revolutionising ecological studies, allowing to create high-resolution 3D point clouds at low costs. I investigated the effect of year-round and autumn reindeer grazing on mountain birch forest vegetation in historically separated grazing areas at the Finnish-Norwegian border, using a combination of field data and drone data. The two sampling techniques were further compared to evaluate the possibility to use photogrammetric point clouds to characterise mountain birch forests. I found lower productivity in the year-round grazing regime, coinciding with generally higher vegetation density. Vertically, higher densities were found above browsing height, while the understory showed lower densities compared to autumn grazed areas. These results suggest that mountain birches allocate more biomass to the canopy area, which can be direct or indirect grazing effects. Nevertheless, overall productivity is lowered by grazing indicating changes in vegetation biomass and composition. The point clouds generally matched field data, but the understory vegetation tended to be underrepresented, arising the question if found effects are ecological or technical. As this could not be disentangled, cautious interpretation of my results is required. I conclude that using photogrammetric point clouds is a promising technique for ecological studies, but needs further development to improve accuracy and reliability of results.