Marius Rüetschi

Function

Technical staff member

Land Change Science

Remote Sensing

Contact

marius.rueetschi(at)wslto make life hard for spam bots.ch

Swiss Federal Research Institute WSL
Zürcherstrasse 111
8903 Birmensdorf

Site

Birmensdorf Bi LH C 17

FURTHER INFORMATION

Projects

Sentinel-2 vegetation height models

The aim of the project is to generate annual vegetation height models for Switzerland based on satellite imagery from Sentinel-2. Within the framework of the Swiss NFI, a workflow will be implemented and the accuracy of the resulting products will be estimated.

Remote sensing-based national forest damage assessment system

In the FNEWs project, a national remote sensing-based monitoring system for forest damage is being set up for Germany. In the WSL's work package the potentials of Sentinel-1 C-band data are analysed, demonstrated and operational procedures are designed.

Nationwide shrub forest distribution maps based on remote sensing

Information on the distribution of shrub forest is of broad interest. The aim of this project is a robust workflow to produce an up-to-date, nationwide and high-resolution distribution map of the two dominant shrub forest species in the Alpine region based on remote sensing.

Storm damage indication map

Remote sensing methods allow a rapid, wide-area and objective overview of the forest damage after a storm event.

Countrywide Tree Type Mapping from Remote Sensing Surveys

Regularly updated information on the state, change and distribution of tree types (broadleaved and coniferous tree) is essential for forest related studies. The first data set consists of ADS80 aerial imagery. The follow-up product is currently being optimized using Sentinel satellite data.

Publications

Scientific publication article peer reviewed

Small, D.; Rohner, C.; Miranda, N.; Rüetschi, M.; Schaepman, M.E., 2022: Wide-area analysis-ready radar backscatter composites. IEEE Transactions on Geoscience and Remote Sensing, 60: 5201814 (14 pp.). doi: 10.1109/TGRS.2021.3055562

Iosifescu Enescu, I.; De Espona, L.; Haas-Artho, D.; Kurup Buchholz, R.; Hanimann, D.; Rüetschi, M.; Karger, D.N.; Plattner, G.; Hägeli, M.; Ginzler, C.; Zimmermann, N.E.; Pellissier, L., 2021: Cloud optimized raster encoding (CORE): a web-native streamable format for large environmental time series. Geomatics, 1, 3: 369-382. doi: 10.3390/geomatics1030021

Rüetschi, M.; Weber, D.; Koch, T.L.; Waser, L.T.; Small, D.; Ginzler, C., 2021: Countrywide mapping of shrub forest using multi-sensor data and bias correction techniques. International Journal of Applied Earth Observation and Geoinformation, 105: 102613 (10 pp.). doi: 10.1016/j.jag.2021.102613

Waser, L.T.; Rüetschi, M.; Psomas, A.; Small, D.; Rehush, N., 2021: Mapping dominant leaf type based on combined Sentinel-1/-2 data – Challenges for mountainous countries. ISPRS Journal of Photogrammetry and Remote Sensing, 180: 209-226. doi: 10.1016/j.isprsjprs.2021.08.017

Malkoç, E.; Rüetschi, M.; Ginzler, C.; Waser, L.T., 2021: Countrywide mapping of trees outside forests based on remote sensing data in Switzerland. International Journal of Applied Earth Observation and Geoinformation, 100: 102336 (10 pp.). doi: 10.1016/j.jag.2021.102336

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Further scientific publications

Rüetschi, M.; Weber, D.; Ginzler, Ch., 2022: Active Learning zur effizienten Erstellung fernerkundungsbasierter Karten. Geomatik Schweiz, Géomatique Suisse, Geomatica Svizzera, 120, 9-10: 206-209.

Rüetschi, M.; Small, D.; Waser, L.T.; Ginzler, C., 2019: Lokalisierung von Windwürfen mit Sentinel-1A/B-Daten: ein Versuch nach «Burglind». Schweizerische Zeitschrift für Forstwesen, 170, 2: 106-109. doi: 10.3188/szf.2019.0094

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