ALBERT

Description: The objective of this paper is to assess WorldView-2 (WV2) and Landsat OLI (L8) images in the detection of bark beetle outbreaks in the Sumava National Park. WV2 and L8 images were used for the classification of forests infected by bark beetle outbreaks using a Support Vector Machine (SVM) and a Neural Network (NN). After evaluating all the available results, the SVM can be considered the best method used in this study. This classifier achieved the highest overall accuracy and Kappa index for both classified images. In the cases of WV2 and L8, total overall accuracies of 86% and 71% and Kappa indices of 0.84 and 0.66 were achieved with SVM, respectively. The NN algorithm using WV2 also produced very promising results, with over 80% overall accuracy and a Kappa index of 0.79. The methods used in this study may be inspirational for testing other types of satellite data (e.g., Sentinel-2) or other classification algorithms such as the Random Forest Classifier.

Description: Typically, lane departure warning systems rely on lane lines being present on the road.However, in many scenarios, e.g., secondary roads or some streets in cities, lane lines are eithernot present or not sufficiently well signaled. In this work, we present a vision-based method tolocate a vehicle within the road when no lane lines are present using only RGB images as input.To this end, we propose to fuse together the outputs of a semantic segmentation and a monoculardepth estimation architecture to reconstruct locally a semantic 3D point cloud of the viewed scene.We only retain points belonging to the road and, additionally, to any kind of fences or walls thatmight be present right at the sides of the road. We then compute the width of the road at a certainpoint on the planned trajectory and, additionally, what we denote as the fence-to-fence distance.Our system is suited to any kind of motoring scenario and is especially useful when lane lines arenot present on the road or do not signal the path correctly. The additional fence-to-fence distancecomputation is complementary to the road’s width estimation. We quantitatively test our methodon a set of images featuring streets of the city of Munich that contain a road-fence structure, so asto compare our two proposed variants, namely the road’s width and the fence-to-fence distancecomputation. In addition, we also validate our system qualitatively on the Stuttgart sequence of thepublicly available Cityscapes dataset, where no fences or walls are present at the sides of the road,thus demonstrating that our system can be deployed in a standard city-like environment. For thebenefit of the community, we make our software open source.

Description: Achieving public support and understanding in addressing the challenges of climate change and the bark beetle calamity is a prerequisite for the successful future of Czech forestry. The most important instrument for achieving public support is communication. To be effective, this communication has to be built on a communication strategy reflecting the long-term goals of forest policy and has to be based on both current analyses and other relevant information, which, in turn, is based on the research results of the public perception of the forests and forestry. This article deals with the results of current research studies and formulates conclusions in relation to this communication strategy. Among other things, these results indicate the willingness of a large part of the public to actively participate in voluntary assistance to forestry, markedly differing opinions among individual groups on forest functions, and rather below-average interest in information concerning forests and forestry.