Forest Resources ManagementOpen OpportunitiesClimate change is increasing tree mortality due to drought and biotic infestations, but current detection methods are limited by data availability and low transferability. This study aims to use deep learning with true color near-infrared RGBI aerial imagery to detect spruce mortality in mixed forests. By integrating field inventories and RGB imagery, the method will be analyzed using R or ArcGIS Pro to accurately assess vegetation conditions. - Environmental Sciences, Geomatic Engineering, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| Climate change is causing increased tree mortality due to drought and biotic infestations, but current methods for automatic detection are limited by data availability and low transferability. This study aims to develop a deep learning approach using true color near-infrared RGBI aerial imagery to detect spruce mortality in mixed forests. By integrating field inventories and RGB imagery, the method will be analyzed using R or ArcGIS Pro. The latest advancements in remote sensing data offer a promising solution to accurately assess vegetation conditions at various scales. - Environmental Sciences
- ETH Zurich (ETHZ), Master Thesis
| Forests provide essential ecosystem services, with wood production being a key source of income for forest management. However, wood is a heterogeneous good, and deriving accurate revenues and costs from forest growth simulations is complex. This project aims to develop a sophisticated wood valuation framework for Switzerland, addressing the limitations of current models. The framework will enhance decision support systems, aiding in efficient forest management, economic forecasting, and policy design - Environmental Sciences
- ETH Zurich (ETHZ), Master Thesis
| Climate change is altering forest composition and structure globally, necessitating forecasts of management approaches to sustain forest ecosystem services (ESS). Models of forest development (MFD) and decision support systems (DSS) are key tools, but linking their outputs to specific ESS indicators remains challenging. This project aims to identify and assess the use of criteria and indicators in forestry, evaluate modelling results from MFD and DSS, and match these outputs with relevant forest characteristics such as biodiversity and carbon storage. The goal is to develop proxies for assessing the potential diversity of future forests. - Environmental Sciences
- Bachelor Thesis
| Climate change is accelerating the impact of spruce bark beetle (Ips typographus) calamities on Norway spruce forests, particularly in Central Europe. Proactive, long-term adaptation of tree-species composition is more promising than reactive outbreak control for managing these beetle outbreaks. However, studies suggest that the spatial configuration of tree species may have an even greater effect on reducing pest spread. This project aims to evaluate the effectiveness of different management strategies, their interactions, and the importance of cooperation among forest owners in mitigating economic losses and enhancing ecosystem services. - Agricultural, Veterinary and Environmental Sciences, Environment and Resource Economics
- ETH Zurich (ETHZ), Master Thesis
| Forest stands are frequently affected by natural and manmade disturbances, such as windthrow, insect calamities, or tree harvests. Small-scale disturbances, which cause partial stand removal, are more common and lead to changes in light, microclimate, and wind forces for remaining trees. The response of trees to these disturbances varies based on species, morphology, and life history, influencing forest resilience. This project aims to develop and test hypotheses on factors determining tree response to disturbances, using long-term data from research plots in Switzerland. - Environmental Sciences, Forestry Sciences
- Master Thesis
| Urban areas face increasing challenges from rising temperatures and air pollution, exacerbated by climate change and urbanization. Urban trees are recognized for their potential to mitigate these issues through shading, transpiration, and pollutant removal, though they can also affect air circulation. This study aims to assess the role of urban trees in reducing air temperatures and improving air quality in Zurich. We will analyze extensive microclimate, pollution, and tree canopy data using remote sensing, GIS, and statistical methods. - Environmental Sciences, Forestry Sciences
- ETH Zurich (ETHZ), Master Thesis
| Tree species identification is crucial for biodiversity monitoring, forest management, and understanding ecological processes. Advances in computer vision and deep learning have enabled the use of multi-view convolutional neural networks (CNNs) to classify species by integrating complementary information from different views. This thesis explores the integration of multi-view data and citizen science images to develop a scalable, high-accuracy tree species identification framework. By addressing challenges related to data variability and leveraging diverse georeferenced plant images, the study aims to enhance the training and generalization of multi-view CNN models. - Computer Vision, Forestry Sciences, Photogrammetry and Remote Sensing
- Master Thesis
| High temperatures and altered precipitation patterns are expected to shift climate zones and vegetation, causing species to move to higher elevations or latitudes. Trees unable to adapt may face climate change-induced stress. This study aims to understand forest dynamics at the treeline by assessing environmental factors at 274 European sites. Using high-resolution climatic and edaphic data, statistical analysis will be performed. The project seeks a motivated student interested in modeling and forest dynamics, offering opportunities to learn about tree growth, gain statistical skills, network with experts, co-author publications, and join a dynamic team. - Management and Evironment
- Bachelor Thesis, Master Thesis
| Forest ecosystems in Central Europe are experiencing rapid changes due to climate change, with frequent disturbances affecting ecosystem structure and functioning. Diversification strategies, such as varying tree-species composition and forest structure, are discussed as predictors for forest resilience. This thesis aims to assess how the large storm event Lothar (1999) and subsequent post-disturbance management influenced local and regional tree-species diversity. By collecting empirical datasets from managed and unmanaged forests, the study will explore the suitability of aerial image time series to evaluate these impacts. - Forestry Sciences, Geomatic Engineering
- Bachelor Thesis, Master Thesis, Semester Project
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