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Predicting selected forest stand characteristics with multispectral ALS data
Dalponte, M., Ene, L. T., Gobakken, T., Næsset, E., & Gianelle, D. (2018). Predicting selected forest stand characteristics with multispectral ALS data. Remote Sensing, 10(4), 586 (15 pp.). https://doi.org/10.3390/rs10040586
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
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
Dynamics of forage production in pasture-woodlands of the Swiss Jura mountains under projected climate change scenarios
Gavazov, K. S., Peringer, A., Buttler, A., Gillet, F., & Spiegelberger, T. (2013). Dynamics of forage production in pasture-woodlands of the Swiss Jura mountains under projected climate change scenarios. Ecology and Society, 18(1), 38 (13 pp.). https://doi.org/10.5751/ES-04974-180138
Community structure and diversity of bryophytes and vascular plants in abandoned fen meadows
Peintinger, M., & Bergamini, A. (2006). Community structure and diversity of bryophytes and vascular plants in abandoned fen meadows. Plant Ecology, 185(1), 1-17. https://doi.org/10.1007/s11258-005-9079-y