
Remote Sensing
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Head: Christian Ginzler
We develop and apply comprehensive and robust methods to extract and classify natural objects from continuous and discrete raster datasets. Relevant features are acquired to describe changes in landscape and land resources at different levels using image data. Mathematical-statistical methods are adopted for automatic detection and description of image objects. Thus we contribute concepts, methods and data to describe/detect area wide changes and processes in the resources of landscape.
Tasks and main research:
- Development and application of methods to extract natural objects from continuous data.
- Development of methods for a comprehensive description of natural and anthropogenetic boundaries in continuous pattern (e.g. map signatures, vegetation transition, forest borders).
- Development and application of methods to extract 3D-information from remotely sensed data for description of natural structures and changes. The main focus lies on wood and its embedding/interaction within/with the landscape.
- Conception and development of data acquisition based on high resolution remote sensing data.
- Conception, development and maintenance of the software interface in area wide data acquisition using airborne remote sensing data.
- Scientific expert advice and support in the fields of photogrammetry and survey at WSL. Maintenance, enhancements and future development in these specific fields.
- Adequate presentation of scientific results on national level and in noted international journals and at international congresses/workshops/symposia.
About our research:
FURTHER INFORMATION
Publications
Boch, S.; Ginzler, C.; Holderegger, R.; Schmidt, B.R.; Bergamini, A., 2022: Aires centrales, piliers de l’infrastructure écologique: situation et évolution. Hotspot, 45: 8-9.
Boch, S.; Ginzler, C.; Holderegger, R.; Schmidt, B.R.; Bergamini, A., 2022: Kerngebiete der Ökologischen Infrastruktur: Zustand und Entwicklung. Hotspot, 45: 8-9.
Wang, Z.; Ginzler, C.; Eben, B.; Rehush, N.; Waser, L.T., 2022: Assessing changes in mountain treeline ecotones over 30 years using CNNs and historical aerial images. Remote Sensing, 14, 9: 2135 (22 pp.). doi: 10.3390/rs14092135
Rauchenstein, K.; Ecker, K.; Bader, E.; Ginzler, C.; Düggelin, C.; Bontadina, F.; Obrist, M.K., 2022: LiDAR metrics predict suitable forest foraging areas of endangered Mouse-eared bats (Myotis myotis). Forest Ecology and Management, 515: 120210 (10 pp.). doi: 10.1016/j.foreco.2022.120210
Hegetschweiler, K.T.; Stride, C.B.; Fischer, C.; Ginzler, C.; Hunziker, M., 2022: Integrating recreation into National Forest Inventories – Results from a forest visitor survey in winter and summer. Journal of Outdoor Recreation and Tourism, 100489 (12 pp.). doi: 10.1016/j.jort.2022.100489
Ljungqvist, F.C.; Seim, A.; Tegel, W.; Krusic, P.J.; Baittinger, C.; Belingard, C.; Bernabei, M.; Bonde, N.; Borghaerts, P.; Couturier, Y.; Ginzler, C.; Büntgen, U., 2022: Regional patterns of late medieval and early modern European building activity revealed by felling dates. Frontiers in Ecology and Evolution, 9: 825751 (20 pp.). doi: 10.3389/fevo.2021.825751
Toosi, N.B.; Soffianian, A.R.; Fakheran, S.; Waser, L.T., 2022: Mapping disturbance in mangrove ecosystems: incorporating landscape metrics and PCA-based spatial analysis. Ecological Indicators, 136: 108718 (10 pp.). doi: 10.1016/j.ecolind.2022.108718
Ackermann, J.; Adler, P.; Koukal, T.; Martin, K.; Waser, L.T., 2022: Fernerkundungsdaten zur Schaderfassung in der forstlichen Praxis. AFZ, der Wald, 77, 2: 20-24.
Pazúr, R.; Huber, N.; Weber, D.; Ginzler, C.; Price, B., 2022: A national extent map of cropland and grassland for Switzerland based on Sentinel-2 data. Earth System Science Data, 14, 1: 295-305. doi: 10.5194/essd-14-295-2022
Bont, L.G.; Fraefel, M.; Frutig, F.; Holm, S.; Ginzler, C.; Fischer, C., 2022: Improving forest management by implementing best suitable timber harvesting methods. Journal of Environmental Management, 302: 114099 (18 pp.). doi: 10.1016/j.jenvman.2021.114099
Chen, S.; Wei, Q.; Wang, W.; Tang, J.; Luo, B.; Wang, Z., 2022: Remote sensing scene classification via multi-branch local attention network. IEEE Transactions on Image Processing, 31: 99-109. doi: 10.1109/TIP.2021.3127851
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
Floris, A.; Marty, M.; Rizzo, M.; Ginzler, C.; Maistrelli, F.; Gasparini, P., 2021: Modelli digitali di altezza della vegetazione da immagini stereometriche con tecniche di Image Matching.. In: Borgogno-Mondino, E.; Zamperlin, P. (eds), 2021: Geomatics and geospatial technologies. 24th Italian conference, ASITA 2021. Genoa, Italy, July 1-2, 9, 16, 23, 2021. Proceedings. 24th Italian conference, ASITA 2021, Genoa, Italy. 181-193.
Breidenbach, J.; Waser, L.T.; Debella-Gilo, M.; Schumacher, J.; Rahlf, J.; Hauglin, M.; Puliti, S.; Astrup, R., 2021: National mapping and estimation of forest area by dominant tree species using Sentinel-2 data. Canadian Journal of Forest Research, 51, 3: 365-379. doi: 10.1139/cjfr-2020-0170
Kükenbrink, D.; Gardi, O.; Morsdorf, F.; Thürig, E.; Schellenberger, A.; Mathys, L., 2021: Above-ground biomass references for urban trees from terrestrial laser scanning data. Annals of Botany, 128, 6: 709-724. doi: 10.1093/aob/mcab002
Price, B.; Huber, N.; Pazur, R.; Rüetschi, M.; Ginzler, C., 2021: Die Lebensraumkarte der Schweiz im Überblick. Carte synoptique des habitats de Suisse. Nature + Paysage. Natur + Landschaft: Inside, 14-15.
Hepenstrick, D.; Bergamini, A.; Webster, C.; Ginzler, C.; Holderegger, R., 2021: Factors determining bryophyte species richness and community composition on insular siliceous erratic boulders in calcareous landscapes. Journal of Vegetation Science, 32, 6: e13094 (15 pp.). doi: 10.1111/jvs.13094
Mazzotti, G.; Webster, C.; Essery, R.; Jonas, T., 2021: Increasing the physical representation of forest‐snow processes in coarse‐resolution models: lessons learned from upscaling hyper‐resolution simulations. Water Resources Research, 57, 5: e2020WR029064 (21 pp.). doi: 10.1029/2020WR029064
Malle, J.; Rutter, N.; Webster, C.; Mazzotti, G.; Wake, L.; Jonas, T., 2021: Effect of forest canopy structure on wintertime Land Surface Albedo: evaluating CLM5 simulations with in‐situ measurements. Journal of Geophysical Research D: Atmospheres, 126, 9: e2020JD034118 (15 pp.). doi: 10.1029/2020JD034118
Huber, N.; Bugmann, H.; Cailleret, M.; Bircher, N.; Lafond, V., 2021: Stand-scale climate change impacts on forests over large areas: transient responses and projection uncertainties. Ecological Applications, 31, 4: e02313 (19 pp.). doi: 10.1002/eap.2313
20 from 359 publications
Staff
Remote Sensing
teamleader, senior scientist | |
scientific staff member | |
scientific assistant | |
technical staff member | |
master student | |
visiting scientist | |
temporary employee | |
temporary employee | |
visiting scientist | |
scientific staff member | |
PhD student | |
scientific staff member | |
scientific staff member | |
master student | |
technical staff member | |
technical staff member | |
technical staff member | |
technical staff member | |
technical staff member | |
IT specialist | |
visiting scientist | |
technical staff member | |
scientific staff member | |
scientific staff member | |
technical staff member | |
scientific staff member |