BSc + MSc thesis topics offered

Below we suggest a range of BSc and MSc topics. If you would like to propose your own idea for your thesis and would like the FORM team to help you by supervising your work, please reach out to us directly.

Assessing spruce mortality in mixed forests using RGBI aerial imagery and deep learning

Forest Resources Management

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.

Keywords

Tree Mortality; Climate Change; Remote Sensing; Deep Learning; RGBI Aerial Imagery

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Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-03-10 , Earliest start: 2025-03-10 , Latest end: 2026-03-10

Applications limited to ETH Zurich , Swiss Federal Institute for Forest, Snow and Landscape Research

Organization Forest Resources Management

Hosts Beloiu Schwenke Mirela

Topics Agricultural, Veterinary and Environmental Sciences

Designing an easy-to-apply Swiss wood valuation framework for scientific applications and decision support systems

Forest Resources Management

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

Keywords

Ecosystem services; wood production; forest management; wood valuation; decision support systems

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Master Thesis , ETH Zurich (ETHZ)

Description

Forests provide a wide range of ecosystem services. To provide these services, most forests (85% in Europe, Schelhaas et al. 2015) are influenced by forest management. Wood production is an important source of financing forest management and the traditional source of income for forest enterprises, including public forests. Wood is a heterogeneous good (e.g., Paul et al. 2020, Koster and Fuchs 2022). Depending on, e.g., tree species, tree diameter, and wood quality, different assortments can be produced. Wood assortments are defined by the potential uses of the wood and thus linked to market prices. The net revenues also depend on the harvest costs. These are influences, e.g., by the accessibility of the forest and the tree diameter. Volume production, as a typical output of forest growth models, is thus not a sophisticated indicator for income from wood production. The information for deriving revenues and costs based on forest growth simulations, e.g., in decision support systems, is largely available. However, various data sources, tables and tools need to be combined. This process involves many steps and is prone to errors. Scientific studies and decision support models thus often rely on simplified assumptions that fall short in capturing the heterogeneity of wood. This, however, limits their suitability to, for example, (1) develop efficient forest management plans, (2) forecast the economic performance of the forest sector, (3) identify trade-offs between private and public objectives, or (4) design efficient forest policies. Similar to a wood valuation framework developed for Germany (Fuchs et al., 2023(*)), this thesis seeks to develop a simple-to-apply but sophisticated wood valuation framework for the diverse conditions in Switzerland. This framework will make an important contribution as a module in future decision support models, Master’s and Doctoral theses. (*) see also R package woodValuationDE at external pagehttps://github.com/Forest-Economics-Goettingen/woodValuationDE and external pagehttps://cran.r-project.org/package=woodValuationDE

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Published since: 2025-03-10 , Earliest start: 2025-03-07 , Latest end: 2026-03-07

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Hangartner Ariane , Fuchs Jasper

Topics Agricultural, Veterinary and Environmental Sciences

The need for criteria and indicators to qualitatively assess forest development

Forest Resources Management

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.

Keywords

Climate change, forest ecosystem services, forest development models, decision support systems, sustainability indicators

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Bachelor Thesis

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Supervisor: Prof. Dr. Verena Griess The project has a flexible starting date. If the idea of participating in cutting-edge interdisciplinary research excites you, please contact verena.griess(at)usys.ethz.ch. The FORM team is looking forward to hearing from you! **References:** - The Montréal Process. "external pageCriteria and Indicators for the Conservation and Sustainable Management of Temperate and Boreal Forests". Accessed May 29, 2024. - Communication from the Commission to the European Parliament, The Council, The European Economic and Social Committee and the Committee of the Regions. “external pageNew EU Forest Strategy for 2030” Accessed May 29, 2024. - Raimo et al. (2022): external pageDeveloping fine-grained nationwide predictions of valuable forests using biodiversity indicator bird species. Ecological Applications 32(2). - Further reading - Bayram, B.Ç. external pageA sustainable forest management criteria and indicators assessment using fuzzy analytic hierarchy process. Environ Monit Assess 193, 425 (2021). - Blattert, C. et al. (2017): external pageManagement of ecosystem services in mountain forests: Review of indicators and value functions for model based multi-criteria decision analysis. Ecological indicators 79 (391-409) - FSC (2023): FSC-STD-60-004 external pageInternational Generic Indicators Standard (STD) V(2-1). - Mäkelä et al. (2021): external pageUsing stand-scale forest models for estimating indicators of sustainable forest management. Forest Ecology and Management 285 (164-178). - UNECE (2019): external pageGuidelines for the Development of a Criteria and Indicator Set for Sustainable Forest Management. Accessed May 29, 2024. - external pageCOMMISSION STAFF WORKING DOCUMENT IMPACT ASSESSMENT REPORT Accompanying the proposal for a Regulation of the European Parliament and of the Council on a monitoring framework for resilient European forests (2023). Accessed May 29, 2024. See Annex 5 Background on Forest Monitoring and forest-related Planning 5.2.1 Further information on indicators

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Published since: 2025-03-07 , Earliest start: 2025-03-07 , Latest end: 2026-02-28

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Hangartner Ariane

Topics Agricultural, Veterinary and Environmental Sciences

Economic perspectives on landscape connectivity and collaboration in bark beetle management

Forest Resources Management

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.

Keywords

Bark beetle; climate change; forest management; tree-species configuration; ecosystem services

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Master Thesis , ETH Zurich (ETHZ)

Description

As climate change accelerates, Norway spruce forests are increasingly affected by spruce bark beetle (Ips typographus) calamities (Seidl and Rammer, 2017; Seidl et al. 2014). Recently observed bark beetle outbreaks - associated with storms (trigger) and droughts (vulnerability) in Central Europe (Buras et al., 2020; Schuldt et al., 2020) - show the unprecedented impact on ecosystem service provision. There are different approaches for bark beetle management: Proactive, long-term adaptation of forests vs. reactive outbreak control (cf., Hlásny et al., 2019). Fuchs et al. (2021) showed that in the long run, from a purely economic, risk-averse perspective, proactive adaptation of tree-species composition is more promising than an intensive bark beetle monitoring with sanitation fellings. The study is, however, (1) limited to the spatial scale of a single stand and (2) assumes that there are alternative, highly productive conifers that are much less/not affected by the bark beetle. Studies by Dobor et al. (2020) and Honkaniemi et al. (2020) suggest that configuration (i.e., the spatially explicit allocation of stand types in the forest enterprise/landscape) may have a similar or even higher dampening effect on the spread of pests. For instance, when allocating Norway spruce stands in a matrix of European beech, the probability of finding a new host tree decreases; the landscape connectivity for bark beetles is lower. Applying this management approach to a spruce forest would drastically reduce the area share of this conifer. Maintaining remarkable area shares of highly productive conifers is, however, important for many provisioning ecosystem services (and to some extent also other services, such as carbon sequestration). A forest manager thus faces the problem of selecting a reasonable mix of adaptation strategies based on (1) species composition, (2) species configuration, and (3) reactive sanitation cuts. This decision likely interacts with the assumed probability of future storm events triggering bark beetle outbreaks. In addition, coordinated long-term management decisions at the landscape level are often hampered by the small ownership sizes typical for Central European private forests.

Goal

1. Does tree-species configuration perform better than tree-species composition and intensive bark beetle monitoring with timely sanitation felling in terms of its ability to reduce economic losses in wood production due to bark beetle infestations? 2. To what extent do the different management strategies interact? Are there relevant synergies? 3. To what extent can such adaptation gains be realized under increasing probabilities of storm events? 4. How important is cooperation between decision-makers in a landscape of small ownerships for the individual owner's adaptation gain? **Methods:** The thesis incorporates building a simulation model applying the concept of cellular automata. The forest landscape is divided into patches (grid cells). Each forest patch's future state (age of the forest, wind damage, bark beetle infestation) depends on its own state as well as on the state of the neighboring patches. This allows for implementing landscape connectivity for bark beetle outbreaks. The cellular automata can be built in NetLogo*. NetLogo is a beginner-friendly programming language for patch models and agent-based models. NetLogo allows for easily defining a landscape of forest patches with rule sets for their development and creating a graphical user interface. The model should include a (simple) forest growth simulation, storm events, probabilities for bark beetle outbreaks and their influence on neighboring patches, decision rules for forest management, and an economic valuation module. On this basis it is possible to simulate different landscapes, management scenarios, scenarios of cooperation between forest owners, and sensitivity analyses. *NetLogo is designed to be easy to learn and provides relevant features without having to implement them from scratch. For a first idea visit external pagehttps://ccl.northwestern.edu/netlogo/ and refer to the well-designed tutorials. **Wanted:** We search for a highly motivated student interested in forest management, simulation modeling, and forest economics. We will ask you to familiarize yourself with NetLogo to implement the model. Some background in forest growth and bark beetle ecology/management is recommended or needs to be acquired. You should be interested in implementing/applying valuation concepts for economic risk and return. Skills in R or Python may be helpful for the data analysis/plotting, Excel is the minimum requirement. The project has a flexible starting date. **You will get to:** - Deepen your knowledge about socioeconomical perspectives on forest management. - Gain experience in programming, simulation modeling, and scenario analysis. - Be a co-author on a publication resulting from this work. - Be part of a motivated team of scientists.

Contact Details

Supervisor: Dr. Jasper Fuchs, Prof. Dr. Verena Griess If the idea of participating in cutting-edge interdisciplinary research excites you, please contact jasper.fuchs(at)usys.ethz.ch. The FORM team is looking forward to hearing from you! **References:** - Buras, A., Rammig, A., Zang, C.S., 2020. Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003. Biogeosciences 17, 1655–1672. doi:10.5194/bg-17-1655-2020. - Dobor, L., Hlásny, T., Rammer, W., Zimová, S., Barka, I., Seidl, R., 2020. Spatial configuration matters when removing windfelled trees to manage bark beetle disturbances in Central European forest landscapes. J. Environ. Manage. 254, 109792. doi:10.1016/j.jenvman.2019.109792. - Fuchs, J.M., Hittenbeck, A., Brandl, S., Schmidt, M., Paul, C., 2021. Adaptation strategies for spruce forests—economic potential of bark beetle management and Douglas fir cultivation in future tree species portfolios. Forestry doi:10.1093/forestry/cpab040. - Hlásny, T., Krokene, P., Liebhold, A., Montagné-Huck, C., Müller, J., Qin, H., Raffa, K.F., Schelhaas, M.J., Seidl, R., Svoboda, M., Viiri, H., 2019. Living with Bark Beetles: Impacts, Outlook and Management Options. volume 8 of From Science to Policy / European Forest Institute. European Forest Institute, Joensuu. - Honkaniemi, J., Rammer, W., Seidl, R., 2020. Norway spruce at the trailing edge: The effect of landscape configuration and composition on climate resilience. Landscape Ecol 35, 591–606. doi:10.1007/s10980-019-00964-y. - Schuldt, B., Buras, A., Arend, M., Vitasse, Y., Beierkuhnlein, C., Damm, A., Gharun, M., Grams, T.E., Hauck, M., Hajek, P., Hartmann, H., Hiltbrunner, E., Hoch, G., Holloway-Phillips, M.,Körner, C., Larysch, E., Lübbe, T., Nelson, D.B., Rammig, A., Rigling, A., Rose, L., Ruehr, N.K., Schumann, K., Weiser, F., Werner, C., Wohlgemuth, T., Zang, C.S., Kahmen, A., 2020. A first assessment of the impact of the extreme 2018 summer drought on Central European forests. Basic Appl. Ecol. 45, 86–103. doi:10.1016/j.baae.2020.04.003. - Seidl, R., Rammer, W., 2017. Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes. Landscape Ecol 32, 1485–1498. doi:10.1007/s10980-016-0396-4. - Seidl, R., Schelhaas, M.J., Rammer, W., Verkerk, P.J., 2014. Increasing forest disturbances in Europe and their impact on carbon storage. Nat. Clim. Change 4, 806–810. doi:10.1038/nclimate2318.

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Published since: 2025-03-07 , Earliest start: 2025-03-07 , Latest end: 2026-03-31

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Fuchs Jasper

Topics Agricultural, Veterinary and Environmental Sciences , Economics

How does tree growth respond to release events?

Forest Resources Management

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.

Keywords

Forest disturbances; tree resilience; ecosystem services; tree growth response; forest management

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Master Thesis

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Published since: 2025-03-07 , Earliest start: 2025-03-07 , Latest end: 2026-03-07

Applications limited to ETH Zurich , Swiss Federal Institute for Forest, Snow and Landscape Research

Organization Forest Resources Management

Hosts Hangartner Ariane

Topics Agricultural, Veterinary and Environmental Sciences

The role of urban trees in mitigating air temperature and pollution in cities

Forest Resources Management

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.

Keywords

Urban trees; climate change; urbanization; air quality

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Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-03-07 , Earliest start: 2025-03-07 , Latest end: 2026-03-07

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Beloiu Schwenke Mirela

Topics Agricultural, Veterinary and Environmental Sciences

Enhancing tree species identification using multi-view Convolutional Neural Networks

Forest Resources Management

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.

Keywords

Tree species identification, deep learning, cnn

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Master Thesis

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Published since: 2025-03-03 , Earliest start: 2024-12-01 , Latest end: 2026-12-31

Applications limited to ETH Zurich , Department of Environmental Systems Science , University of Zurich

Organization Forest Resources Management

Hosts Drees Lukas , Hangartner Ariane , Beloiu Schwenke Mirela

Topics Agricultural, Veterinary and Environmental Sciences , Information, Computing and Communication Sciences , Engineering and Technology

Drivers of forest dynamics at the treeline

Forest Resources Management

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.

Keywords

Forestry, Climate change, Forest Management, Vegetation shifts, Forest dynamics, Statistical analysis

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Bachelor Thesis , Master Thesis

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Published since: 2025-02-18 , Earliest start: 2025-02-18 , Latest end: 2026-02-28

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Beloiu Schwenke Mirela , Hangartner Ariane

Topics Agricultural, Veterinary and Environmental Sciences

Quantifying forest diversity shifts after a storm using aerial images

Forest Resources Management

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.

Keywords

Forest dynamics; Deep Learning; CNN; species identification

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Semester Project , Bachelor Thesis , Master Thesis

Description

Forest ecosystems are facing rapid and severe changes due to climate change Increasingly frequent disturbances in Central Europe (Seidl et al., 2014; Senf and Seidl, 2021) affect ecosystem structure with cascading effects on ecosystem functioning and the provision of ecosystem services (Paul et al., 2020). Diversification strategies are discussed as a predictor for forest resilience (Lloret et al., 2024). Such strategies may be implemented in forest adaptation by diversifying the local tree-species composition (e.g., species mixtures vs. monocultures), the local forest structure (e.g., height distribution), and the management types across a landscape; all of which are discussed as strategies to increase resistance and resilience to disturbances (Elmqvist et al., 2003; Hof et al., 2017; Morin et al., 2011), and to reduce trade-offs between ecosystem functioning and multiple ecosystem services (Knoke et al., 2017; Topanotti, 2024). Transitions towards new forest management regimes, and in particular changes in tree-species composition, are slow processes due to the long production and planning periods in forest management. This contrasts with recent observations of increasingly severe events, such as the extreme mortality events following the drought in the year 2018 in Central Europe (Buras et al., 2020; Schuldt et al., 2020). Consequently, a new type of thinking developed that interprets disturbances as drivers of forest change rather than disruptions to a status-quo system that needs to be preserved (Buma and Schultz, 2020; Thom et al., 2017). Thom et al. (2017) showed that disturbance characteristics influence this adaptation-fostering effect of disturbances: An increasing frequency and intensity accelerated the adaptation process while an increasing size slowed it down. The study is based on simulation modeling in an unmanaged forest. In managed forests, however, post-disturbance management, such as salvage logging and planting, have a strong potential to alter these dynamics.

Goal

With this thesis, we aim to collect empirical datasets from managed and unmanaged forests and to assess how a large storm event (Lothar, 1999), and possibly triggered post-disturbance management, altered the local and regional tree-species diversity. **Research questions:** - Are time series of aerial images suitable to assess the influence of historic storm events on tree-species compositions? - How did storm Lothar and possible post-disturbance management influence local tree-species diversity? - How did storm Lothar and the possible post-disturbance management influence landscape diversity? - Do these influences depend on the patch size of the disturbance? - Do these influences differ between regions and their predominant forest management goals? **Methods:** Identify disturbed areas: use the BAFU Storm Lothar map to delineate affected areas as polygons and select undisturbed control sites for comparison. Data collection: Gather aerial image time series, LiDAR data for canopy structure, and other relevant datasets. Tree-species identification: Apply current machine learning methods to classify tree species using aerial images, validating with available ground-truth data available from cantonal offices. Analyze structural and landscape changes: Derive metrics for canopy height, cover, and landscape diversity to assess spatial and structural changes. Statistical analysis of tree-species diversity (Shannon, evenness, or Bray Curtis for changes) (1) before and after the event and (2) across the forest landscape (gamma-diversity). Identification of relevant covariates (incl. management goals in the forest area) to predict post-disturbance forest diversity. **Wanted:** We look for a highly motivated student with an interest in remote sensing, deep learning, forest ecosystems, and statistical analysis. You should be willing to learn new techniques and methods. A solid knowledge of GIS is a plus. The project has a flexible starting date. **You will get to:** - Learn new and highly required theoretical and practical knowledge about remote sensing and deep learning, and how to apply these skills to up-to-date questions in forest ecology and management. - Gain important statistical knowledge for future work. - Expand your network by discussing your work with experts from the intersecting fields of forest sciences and computer sciences. - Be a co-author on a publication resulting from this work. - Be part of a motivated team of scientists.

Contact Details

Supervisor: Dr. Mirela Beloiu Schwenke, Dr. Jasper Fuchs If the idea of participating in cutting-edge interdisciplinary research excites you, please contact mirela.beloiu(at)usys.ethz.ch. The FORM team is looking forward to hearing from you! **References:** - Buma, B., Schultz, C., 2020. Disturbances as opportunities: Learning from disturbance-response parallels in social and ecological systems to better adapt to climate change. Journal of Applied Ecology 57, 1113–1123. https://doi.org/10.1111/1365-2664.13606 - Buras, A., Rammig, A., Zang, C.S., 2020. Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003. Biogeosciences 17, 1655–1672. https://doi.org/10.5194/bg-17-1655-2020 - Elmqvist, T., Folke, C., Nyström, M., Peterson, G., Bengtsson, J., Walker, B., Norberg, J., 2003. Response diversity, ecosystem change, and resilience. Frontiers in Ecology and the Environment 1, 488–494. https://doi.org/10.1890/1540-9295(2003)001[0488:RDECAR]2.0.CO;2 - Hof, A.R., Dymond, C.C., Mladenoff, D.J., 2017. Climate change mitigation through adaptation: the effectiveness of forest diversification by novel tree planting regimes. Ecosphere 8, e01981. https://doi.org/10.1002/ecs2.1981 - Knoke, T., Messerer, K., Paul, C., 2017. The role of economic diversification in forest ecosystem management. Curr. Forestry Rep. 3, 93–106. https://doi.org/10.1007/s40725-017-0054-3 - Lloret, F., Hurtado, P., Espelta, J.M., Jaime, L., Nikinmaa, L., Lindner, M., Martínez-Vilalta, J., 2024. ORF, an operational framework to measure resilience in social–ecological systems: the forest case study. Sustain Sci 19, 1579–1593. https://doi.org/10.1007/s11625-024-01518-1 - Morin, X., Fahse, L., Scherer-Lorenzen, M., Bugmann, H., 2011. Tree species richness promotes productivity in temperate forests through strong complementarity between species. Ecology Letters 14, 1211–9. https://doi.org/10.1111/j.1461-0248.2011.01691.x - Schuldt, B., Buras, A., Arend, M., Vitasse, Y., Beierkuhnlein, C., Damm, A., Gharun, M., Grams, T.E.E., Hauck, M., Hajek, P., Hartmann, H., Hiltbrunner, E., Hoch, G., Holloway-Phillips, M., Körner, C., Larysch, E., Lübbe, T., Nelson, D.B., Rammig, A., Rigling, A., Rose, L., Ruehr, N.K., Schumann, K., Weiser, F., Werner, C., Wohlgemuth, T., Zang, C.S., Kahmen, A., 2020. A first assessment of the impact of the extreme 2018 summer drought on Central European forests. Basic and Applied Ecology 45, 86–103. https://doi.org/10.1016/j.baae.2020.04.003 - Seidl, R., Schelhaas, M.-J., Rammer, W., Verkerk, P.J., 2014. Increasing forest disturbances in Europe and their impact on carbon storage. Nat. Clim. Change 4, 806–810. https://doi.org/10.1038/nclimate2318 - Senf, C., Seidl, R., 2021. Mapping the forest disturbance regimes of Europe. Nat Sustain 4, 63–70. https://doi.org/10.1038/s41893-020-00609-y - Thom, D., Rammer, W., Seidl, R., 2017. Disturbances catalyze the adaptation of forest ecosystems to changing climate conditions. Global Change Biology 23, 269–282. https://doi.org/10.1111/gcb.13506 - Topanotti, L.R., 2024. Economic implications of tree species composition and structural diversity in European beech stands enriched with coniferous trees (doctoralThesis). https://doi.org/10.53846/goediss-10755

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Published since: 2025-02-04 , Earliest start: 2025-02-24

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Fuchs Jasper , Beloiu Schwenke Mirela

Topics Agricultural, Veterinary and Environmental Sciences , Engineering and Technology

Mapping forest diversity changes after disturbances using remote sensing data

Forest Resources Management

Forest ecosystems are rapidly changing due to climate-driven disturbances, impacting their structure, functioning, and ability to provide essential ecosystem services. Diversifying tree-species composition and management strategies is crucial for enhancing forest resilience, yet the slow pace of these changes contrasts with the urgency created by increasingly severe events like storms and droughts. This study aims to assess the impact of forest disturbances and post-disturbance management on tree-species diversity in European forests over the last 30 years. By evaluating remote sensing products and investigating disturbance impacts, the research will inform effective management strategies and forest policies to enhance resilience and adaptability.

Keywords

Machine learning; forest mapping; storms; forest diversity

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Semester Project , Master Thesis

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Goal

Assess the impact of forest disturbances and post-disturbance management on tree-species diversity in European forests over the last 30 years. ** Objectives:** 1. Evaluate the suitability of different remote sensing products (e.g., aerial images, satellite data) for assessing the impact of historic disturbance events on tree-species composition. 2. Assess recently impacted areas by disturbance alongside areas that have recovered to infer the recovery trajectory and today’s species-composition using the space-for-time analysis. 3. Investigate how disturbance patch size, disturbance agent, and regional differences, incl. different management objectives, influenced the impact of disturbance events on forest diversity. **Methods:** We will analyze remote sensing products, such as aerial images or Landsat time series data, and forest disturbance maps, to identify forest disturbance areas and assess changes in tree-species diversity over the past 30 years. Undisturbed areas with similar environmental conditions will be included as controls to isolate the effects of disturbances. Using disturbance maps and space-for-time analysis, we will evaluate species composition, canopy structure, and landscape diversity. Biodiversity metrics such as Shannon diversity, species richness, and evenness will be calculated to quantify changes. Statistical analyses will be applied to examine the influence of disturbance patch size and regional differences on recovery and diversity patterns. **Wanted:** A highly motivated student interested in remote sensing and biodiversity, willing to learn new practical techniques and ecological concepts. **You will get to:** - Learn about remote sensing and, more importantly, how to apply these technical skills to a relevant application for the forestry community. - Get familiar with the latest developments in forest ecology and remote sensing. - Gain important remote sensing knowledge for future work. - Be a co-author on a publication resulting from this work. - Be part of a motivated, fun, and energetic team of scientists.

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Published since: 2025-02-04

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Fuchs Jasper , Beloiu Schwenke Mirela

Topics Agricultural, Veterinary and Environmental Sciences , Engineering and Technology , Earth Sciences

Mechanisms of health and mortality in central European tree species

Forest Resources Management

Recent years have seen accelerated tree mortality due to heat and drought, with varying responses across tree species. Understanding the physiological mechanisms leading to mortality is critical, particularly in response to drought-induced stress. This study aims to assess the correlation between tree ring growth patterns and remote-sensing-based vegetation indices to examine changes in tree health across Switzerland over three decades. By integrating tree-ring-based measurements and multispectral Landsat time series data, this approach will help define species-specific mechanisms of tree mortality and improve forest health monitoring.

Keywords

tree growth; tree rings; satellite data; European forests

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Semester Project , Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-02-04 , Earliest start: 2025-02-17

Organization Forest Resources Management

Hosts Beloiu Schwenke Mirela , Waser Lars

Topics Agricultural, Veterinary and Environmental Sciences , Biology

Tree species regeneration in European forests

Forest Resources Management

Forest regeneration is crucial for ecosystem sustainability and resilience, with varying patterns across Europe due to climate, soil conditions, competition, and management practices. This study aims to analyze tree species regeneration over the past 30 years, identifying trends, dominant species, and the role of functional groups in shaping forest composition. By integrating forest inventory data, climate variables, and statistical models, the research will assess species-specific regeneration trends and the influence of environmental conditions.

Keywords

Forest composition; temperate forests; climatic drivers;

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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)

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Published since: 2025-02-04

Applications limited to ETH Zurich

Organization Forest Resources Management

Hosts Beloiu Schwenke Mirela , Fuchs Jasper

Topics Agricultural, Veterinary and Environmental Sciences , Engineering and Technology

Mapping spruce density using aerial imagery and deep learning

Forest Resources Management

Climate 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.

Keywords

spruce density mapping; deep learning for forestry; remote sensing (RGBI imagery); forest structure analysis

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Semester Project , Master Thesis

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Published since: 2024-12-18 , Earliest start: 2025-01-06 , Latest end: 2026-06-30

Applications limited to ETH Zurich , University of Zurich

Organization Forest Resources Management

Hosts Beloiu Schwenke Mirela , Drees Lukas

Topics Agricultural, Veterinary and Environmental Sciences , Information, Computing and Communication Sciences , Engineering and Technology

Tree species identification using deep learning

Forest Resources Management

Tree species maps are crucial for effective forest management, biomass assessment, and biodiversity monitoring. Remote sensing products offer flexible and cost-effective ways to assess forest characteristics, while deep learning methods promise high predictive accuracy and transformative applications in forestry. This study aims to apply novel deep learning approaches to detect and identify individual trees and tree species in mixed forests. By addressing the challenges of tree species identification, this research will enhance biodiversity assessment, forest resilience understanding, and management strategies.

Keywords

Tree species identification, computer vision, CNN

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Master Thesis , ETH Zurich (ETHZ)

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Published since: 2024-12-17 , Earliest start: 2025-01-06 , Latest end: 2026-08-31

Applications limited to ETH Zurich , Department of Environmental Systems Science , Department of Civil, Environmental and Geomatic Engineering , Institute of Geodesy and Photogrammetry

Organization Forest Resources Management

Hosts Schindler Konrad , Beloiu Schwenke Mirela , Hangartner Ariane

Topics Agricultural, Veterinary and Environmental Sciences , Information, Computing and Communication Sciences , Engineering and Technology