Active Filters

  • (-) Keywords = forestry
  • (-) Publication Type ≠ Book Chapter
Search Results 1 - 20 of 42
Select Page
Virtual forests: a review on emerging questions in the use and application of 3D data in forestry
Murtiyoso, A., Holm, S., Riihimäki, H., Krucher, A., Griess, H., Griess, V. C., & Schweier, J. (2024). Virtual forests: a review on emerging questions in the use and application of 3D data in forestry. International Journal of Forest Engineering, 35(1), 29-42. https://doi.org/10.1080/14942119.2023.2217065
What drives forest multifunctionality in central and northern Europe? Exploring the interplay of management, climate, and policies
Toraño Caicoya, A., Vergarechea, M., Blattert, C., Klein, J., Eyvindson, K., Burgas, D., … Antón-Fernández, C. (2023). What drives forest multifunctionality in central and northern Europe? Exploring the interplay of management, climate, and policies. Ecosystem Services, 64, 101575 (14 pp.). https://doi.org/10.1016/j.ecoser.2023.101575
Risks, benefits, and knowledge gaps of non-native tree species in Europe
Dimitrova, A., Csilléry, K., Klisz, M., Lévesque, M., Heinrichs, S., Cailleret, M., … Montagnoli, A. (2022). Risks, benefits, and knowledge gaps of non-native tree species in Europe. Frontiers in Ecology and Evolution, 10, 908464 (16 pp.). https://doi.org/10.3389/fevo.2022.908464
Wood formation modeling - a research review and future perspectives
Eckes-Shephard, A. H., Ljungqvist, F. C., Drew, D. M., Rathgeber, C. B. K., & Friend, A. D. (2022). Wood formation modeling - a research review and future perspectives. Frontiers in Plant Science, 13, 837648 (21 pp.). https://doi.org/10.3389/fpls.2022.837648
Monocular depth estimation in forest environments
Hristova, H., Abegg, M., Fischer, C., & Rehush, N. (2022). Monocular depth estimation in forest environments. In A. Yilmaz, J. D. Wegner, R. Qin, F. Remondino, T. Fuse, & I. Toschi (Eds.), The international archives of the photogrammetry, remote sensing and spatial information sciences: Vol. XLII-B2-2022. Congress "Imaging today, foreseeing tomorrow", commission II (pp. 1017-1023). https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1017-2022
Comparison of single tree detection methods to extract support trees for cable road planning
Ramstein, L., Bont, L. G., Ginzler, C., & Schweier, J. (2022). Comparison of single tree detection methods to extract support trees for cable road planning. European Journal of Forest Research, 141, 1121-1138. https://doi.org/10.1007/s10342-022-01495-z
Abundance, species richness and diversity of forest bird assemblages – The relative importance of habitat structures and landscape context
Basile, M., Storch, I., & Mikusiński, G. (2021). Abundance, species richness and diversity of forest bird assemblages – The relative importance of habitat structures and landscape context. Ecological Indicators, 133, 108402 (13 pp.). https://doi.org/10.1016/j.ecolind.2021.108402
The distribution of a group of keystone species is not associated with anthropogenic habitat disturbance
Fitzpatrick, B. R., Baltensweiler, A., Düggelin, C., Fraefel, M., Freitag, A., Vandegehuchte, M. L., … Risch, A. C. (2021). The distribution of a group of keystone species is not associated with anthropogenic habitat disturbance. Diversity and Distributions, 27(4), 572-584. https://doi.org/10.1111/ddi.13217
What does a threatened saproxylic beetle look like? Modelling extinction risk using a new morphological trait database
Hagge, J., Müller, J., Birkemoe, T., Buse, J., Christensen, R. H. B., Gossner, M. M., … Drag, L. (2021). What does a threatened saproxylic beetle look like? Modelling extinction risk using a new morphological trait database. Journal of Animal Ecology, 90(8), 1934-1947. https://doi.org/10.1111/1365-2656.13512
The dendroclimatic value of oak stable isotopes
Urban, O., Ač, A., Kolář, T., Rybníček, M., Pernicová, N., Koňasová, E., … Büntgen, U. (2021). The dendroclimatic value of oak stable isotopes. Dendrochronologia, 65, 125804 (8 pp.). https://doi.org/10.1016/j.dendro.2020.125804
Testing a framework to co-construct social innovation actions: insights from seven marginalized rural areas
Govigli, V. M., Alkhaled, S., Arnesen, T., Barlagne, C., Bjerck, M., Burlando, C., … Górriz-Mifsud, E. (2020). Testing a framework to co-construct social innovation actions: insights from seven marginalized rural areas. Sustainability, 12(4), 1441 (26 pp.). https://doi.org/10.3390/su12041441
Identifying the tree species compositions that maximize ecosystem functioning in European forests
Baeten, L., Bruelheide, H., van der Plas, F., Kambach, S., Ratcliffe, S., Jucker, T., … Scherer-Lorenzen, M. (2019). Identifying the tree species compositions that maximize ecosystem functioning in European forests. Journal of Applied Ecology, 56(3), 733-744. https://doi.org/10.1111/1365-2664.13308
A single-tree processing framework using terrestrial laser scanning data for detecting forest regeneration
Heinzel, J., & Ginzler, C. (2019). A single-tree processing framework using terrestrial laser scanning data for detecting forest regeneration. Remote Sensing, 11(1), 60 (20 pp.). https://doi.org/10.3390/rs11010060
Rapid detection of windthrows using Sentinel-1 C-band SAR data
Rüetschi, M., Small, D., & Waser, L. T. (2019). Rapid detection of windthrows using Sentinel-1 C-band SAR data. Remote Sensing, 11(2), 115 (23 pp.). https://doi.org/10.3390/rs11020115
Ceduo castanile in aree ad elevato pericolo di frane superficiali. Quali opzioni gestionali?
Schwarz, M., Plinio Dazio, E., Pividori, M., Bonardi, M., & Conedera, M. (2019). Ceduo castanile in aree ad elevato pericolo di frane superficiali. Quali opzioni gestionali? Sherwood (241), 7-10.
Prediction of forest attributes with multispectral lidar data
Dalponte, M., Ene, L. T., Gobakken, T., Næsset, E., & Gianelle, D. (2018). Prediction of forest attributes with multispectral lidar data. In Observing, understandig and forecasting the dynamics of our planet (pp. 7528-7531). https://doi.org/10.1109/IGARSS.2018.8517320
Constrained spectral clustering of individual trees in dense forest using terrestrial laser scanning data
Heinzel, J., & Huber, M. (2018). Constrained spectral clustering of individual trees in dense forest using terrestrial laser scanning data. Remote Sensing, 10(7), 1056 (21 pp.). https://doi.org/10.3390/rs10071056
Review of studies on tree species classification from remotely sensed data
Fassnacht, F. E., Latifi, H., Stereńczak, K., Modzelewska, A., Lefsky, M., Waser, L. T., … Ghosh, A. (2016). Review of studies on tree species classification from remotely sensed data. Remote Sensing of Environment, 186, 64-87. https://doi.org/10.1016/j.rse.2016.08.013
TLS field data based intensity correction for forest environments
Heinzel, J., & Huber, M. O. (2016). TLS field data based intensity correction for forest environments. 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. 643-649). https://doi.org/10.5194/isprs-archives-XLI-B8-643-2016
Identifying key research objectives to make European forests greener for bats
Russo, D., Billington, G., Bontadina, F., Dekker, J., Dietz, M., Gazaryan, S., … Twisk, P. (2016). Identifying key research objectives to make European forests greener for bats. Frontiers in Ecology and Evolution, 4, 87 (8 pp.). https://doi.org/10.3389/fevo.2016.00087