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High-resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles
Drag, L., Burner, R. C., Stephan, J. G., Birkemoe, T., Doerfler, I., Gossner, M. M., … Müller, J. (2023). High-resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles. Functional Ecology, 37(1), 150-161. https://doi.org/10.1111/1365-2435.14188
Improving country-wide individual tree detection using local maxima methods based on statistically modeled forest structure information
Schaller, C., Ginzler, C., van Loon, E., Moos, C., Seijmonsbergen, A. C., & Dorren, L. (2023). Improving country-wide individual tree detection using local maxima methods based on statistically modeled forest structure information. International Journal of Applied Earth Observation and Geoinformation, 123, 103480 (11 pp.). https://doi.org/10.1016/j.jag.2023.103480
Airborne-laser-scanning-derived auxiliary information discriminating between broadleaf and conifer trees improves the accuracy of models for predicting timber volume in mixed and heterogeneously structured forests
Bont, L. G., Hill, A., Waser, L. T., Bürgi, A., Ginzler, C., & Blattert, C. (2020). Airborne-laser-scanning-derived auxiliary information discriminating between broadleaf and conifer trees improves the accuracy of models for predicting timber volume in mixed and heterogeneously structured forests. Forest Ecology and Management, 459, 117856 (18 pp.). https://doi.org/10.1016/j.foreco.2019.117856
Assessing structural changes at the forest edge using kernel density estimation
Wang, Z., Ginzler, C., & Waser, L. T. (2020). Assessing structural changes at the forest edge using kernel density estimation. Forest Ecology and Management, 456, 117639 (13 pp.). https://doi.org/10.1016/j.foreco.2019.117639
LiDAR data as a proxy for light availability improve distribution modelling of woody species
Wüest, R. O., Bergamini, A., Bollmann, K., & Baltensweiler, A. (2020). LiDAR data as a proxy for light availability improve distribution modelling of woody species. Forest Ecology and Management, 456, 117644 (10 pp.). https://doi.org/10.1016/j.foreco.2019.117644
Allometric equations for integrating remote sensing imagery into forest monitoring programmes
Jucker, T., Caspersen, J., Chave, J., Antin, C., Barbier, N., Bongers, F., … Coomes, D. A. (2017). Allometric equations for integrating remote sensing imagery into forest monitoring programmes. Global Change Biology, 23(1), 177-190. https://doi.org/10.1111/gcb.13388
From field surveys to LiDAR: shining a light on how bats respond to forest structure
Froidevaux, J. S. P., Zellweger, F., Bollmann, K., Jones, G., & Obrist, M. K. (2016). From field surveys to LiDAR: shining a light on how bats respond to forest structure. Remote Sensing of Environment, 175, 242-250. https://doi.org/10.1016/j.rse.2015.12.038
Wide-area mapping of forest with national airborne laser scanning and field inventory datasets
Monnet, J. M., Ginzler, C., & Clivaz, J. C. (2016). Wide-area mapping of forest with national airborne laser scanning and field inventory datasets. In L. Halounova, V. Šafář, P. L. N. Raju, L. Plánka, V. Ždímal, T. Srinivasa Kumar, … Q. Weng (Eds.), The international archives of the photogrammetry, remote sensing and spatial information sciences: Vol. XLI-B8. XXIII ISPRS congress, commission VIII (pp. 727-731). https://doi.org/10.5194/isprs-archives-XLI-B8-727-2016
Environmental predictors of species richness in forest landscapes: abiotic factors versus vegetation structure
Zellweger, F., Baltensweiler, A., Ginzler, C., Roth, T., Braunisch, V., Bugmann, H., & Bollmann, K. (2016). Environmental predictors of species richness in forest landscapes: abiotic factors versus vegetation structure. Journal of Biogeography, 43(6), 1080-1090. https://doi.org/10.1111/jbi.12696
Local extremes in the lidar-derived snow cover of alpine glaciers
Helfricht, K., Lehning, M., Sailer, R., & Kuhn, M. (2015). Local extremes in the lidar-derived snow cover of alpine glaciers. Geografiska Annaler Series A: Physical Geography, 97(4), 721-736. https://doi.org/10.1111/geoa.12111
Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment
Zellweger, F., Morsdorf, F., Purves, R. S., Braunisch, V., & Bollmann, K. (2014). Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment. Biodiversity and Conservation, 23(2), 289-307. https://doi.org/10.1007/s10531-013-0600-7
Forest variable estimation using a high-resolution digital surface model
Järnstedt, J., Pekkarinen, A., Tuominen, S., Ginzler, C., Holopainen, M., & Viitala, R. (2012). Forest variable estimation using a high-resolution digital surface model. ISPRS Journal of Photogrammetry and Remote Sensing, 74, 78-84. https://doi.org/10.1016/j.isprsjprs.2012.08.006