Almeida, D. R. A., Stark, S. C., Chazdon, R., Nelson, B. W., Cesar, R. G., Meli, P., … Brancalion, P. H. S. (2019). The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration. Forest Ecology and Management, 438, 34-43. doi:10.1016/j.foreco.2019.02.002
Anderson, K., Hancock, S., Disney, M., & Gaston, K. J. (2015). Is waveform worth it? A comparison of Li
DAR
approaches for vegetation and landscape characterization. Remote Sensing in Ecology and Conservation, 2(1), 5-15. doi:10.1002/rse2.8
Béland, M., Widlowski, J.-L., & Fournier, R. A. (2014). A model for deriving voxel-level tree leaf area density estimates from ground-based LiDAR. Environmental Modelling & Software, 51, 184-189. doi:10.1016/j.envsoft.2013.09.034
[+]
Almeida, D. R. A., Stark, S. C., Chazdon, R., Nelson, B. W., Cesar, R. G., Meli, P., … Brancalion, P. H. S. (2019). The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration. Forest Ecology and Management, 438, 34-43. doi:10.1016/j.foreco.2019.02.002
Anderson, K., Hancock, S., Disney, M., & Gaston, K. J. (2015). Is waveform worth it? A comparison of Li
DAR
approaches for vegetation and landscape characterization. Remote Sensing in Ecology and Conservation, 2(1), 5-15. doi:10.1002/rse2.8
Béland, M., Widlowski, J.-L., & Fournier, R. A. (2014). A model for deriving voxel-level tree leaf area density estimates from ground-based LiDAR. Environmental Modelling & Software, 51, 184-189. doi:10.1016/j.envsoft.2013.09.034
Bottalico, F., Chirici, G., Giannini, R., Mele, S., Mura, M., Puxeddu, M., … Travaglini, D. (2017). Modeling Mediterranean forest structure using airborne laser scanning data. International Journal of Applied Earth Observation and Geoinformation, 57, 145-153. doi:10.1016/j.jag.2016.12.013
Cao, L., Coops, N., Hermosilla, T., Dai, J., 2014a. Estimation of forest structural variables using small-footprint full-waveform LiDAR in a subtropical forest, China. 3rd Int. Work. Earth Obs. Remote Sens. Appl. EORSA 2014 - Proc. 443–447. https://doi.org/10.1109/EORSA.2014.6927930.
Cao, L., Coops, N., Hermosilla, T., Innes, J., Dai, J., & She, G. (2014). Using Small-Footprint Discrete and Full-Waveform Airborne LiDAR Metrics to Estimate Total Biomass and Biomass Components in Subtropical Forests. Remote Sensing, 6(8), 7110-7135. doi:10.3390/rs6087110
Cao, L., Coops, N. C., Innes, J. L., Dai, J., Ruan, H., & She, G. (2016). Tree species classification in subtropical forests using small-footprint full-waveform LiDAR data. International Journal of Applied Earth Observation and Geoinformation, 49, 39-51. doi:10.1016/j.jag.2016.01.007
Chasmer, L., Hopkinson, C., & Treitz, P. (2006). Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial lidar. Canadian Journal of Remote Sensing, 32(2), 116-125. doi:10.5589/m06-011
Chen, Y., Zhu, X., Yebra, M., Harris, S., & Tapper, N. (2016). Strata-based forest fuel classification for wild fire hazard assessment using terrestrial LiDAR. Journal of Applied Remote Sensing, 10(4), 046025. doi:10.1117/1.jrs.10.046025
Crespo-Peremarch, P., Ruiz, L. A., & Balaguer-Beser, A. (2016). A comparative study of regression methods to predict forest structure and canopy fuel variables from LiDAR full-waveform data. Revista de Teledetección, (45), 27. doi:10.4995/raet.2016.4066
Crespo-Peremarch, P., Ruiz, L.Á., 2017. Análisis comparativo del potencial del ALS y TLS en la caracterización estructural de la masa forestal basado en voxelización. Actas XVII Congr. la Asoc. Española Teledetección. Nuevas plataformas y sensores teledetección 131–135.
Crespo-Peremarch, P., Ruiz, L. Á., Balaguer-Beser, Á., & Estornell, J. (2018). Analyzing the role of pulse density and voxelization parameters on full-waveform LiDAR-derived metrics. ISPRS Journal of Photogrammetry and Remote Sensing, 146, 453-464. doi:10.1016/j.isprsjprs.2018.10.012
Crespo-Peremarch, P., Tompalski, P., Coops, N. C., & Ruiz, L. Á. (2018). Characterizing understory vegetation in Mediterranean forests using full-waveform airborne laser scanning data. Remote Sensing of Environment, 217, 400-413. doi:10.1016/j.rse.2018.08.033
Crespo-Peremarch, P., & Ruiz, L. A. (2020). A Full-Waveform Airborne Laser Scanning Metric Extraction Tool for Forest Structure Modelling. Do Scan Angle and Radiometric Correction Matter? Remote Sensing, 12(2), 292. doi:10.3390/rs12020292
Giannetti, F., Puletti, N., Quatrini, V., Travaglini, D., Bottalico, F., Corona, P., & Chirici, G. (2018). Integrating terrestrial and airborne laser scanning for the assessment of single-tree attributes in Mediterranean forest stands. European Journal of Remote Sensing, 51(1), 795-807. doi:10.1080/22797254.2018.1482733
Gini, C., 1912. Variabilità e mutabilità.
González-Ferreiro, E., Diéguez-Aranda, U., & Miranda, D. (2012). Estimation of stand variables in Pinus radiata D. Don plantations using different LiDAR pulse densities. Forestry: An International Journal of Forest Research, 85(2), 281-292. doi:10.1093/forestry/cps002
Student. (1908). The Probable Error of a Mean. Biometrika, 6(1), 1. doi:10.2307/2331554
Greaves, H. E., Vierling, L. A., Eitel, J. U. H., Boelman, N. T., Magney, T. S., Prager, C. M., & Griffin, K. L. (2015). Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial LiDAR. Remote Sensing of Environment, 164, 26-35. doi:10.1016/j.rse.2015.02.023
Hancock, S., Anderson, K., Disney, M., & Gaston, K. J. (2017). Measurement of fine-spatial-resolution 3D vegetation structure with airborne waveform lidar: Calibration and validation with voxelised terrestrial lidar. Remote Sensing of Environment, 188, 37-50. doi:10.1016/j.rse.2016.10.041
Heinzel, J., & Koch, B. (2011). Exploring full-waveform LiDAR parameters for tree species classification. International Journal of Applied Earth Observation and Geoinformation, 13(1), 152-160. doi:10.1016/j.jag.2010.09.010
Hermosilla, T., Ruiz, L. A., Kazakova, A. N., Coops, N. C., & Moskal, L. M. (2014). Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data. International Journal of Wildland Fire, 23(2), 224. doi:10.1071/wf13086
Hermosilla, T., Coops, N. C., Ruiz, L. A., & Moskal, L. M. (2014). Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data. Remote Sensing Letters, 5(4), 332-341. doi:10.1080/2150704x.2014.903350
Hilker, T., van Leeuwen, M., Coops, N. C., Wulder, M. A., Newnham, G. J., Jupp, D. L. B., & Culvenor, D. S. (2010). Comparing canopy metrics derived from terrestrial and airborne laser scanning in a Douglas-fir dominated forest stand. Trees, 24(5), 819-832. doi:10.1007/s00468-010-0452-7
Hill, R. A., & Broughton, R. K. (2009). Mapping the understorey of deciduous woodland from leaf-on and leaf-off airborne LiDAR data: A case study in lowland Britain. ISPRS Journal of Photogrammetry and Remote Sensing, 64(2), 223-233. doi:10.1016/j.isprsjprs.2008.12.004
Isenburg, M., 2017. LAStools.
Jung, S.-E., Kwak, D.-A., Park, T., Lee, W.-K., & Yoo, S. (2011). Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners. Remote Sensing, 3(11), 2346-2363. doi:10.3390/rs3112346
Kankare, V., Vastaranta, M., Holopainen, M., Räty, M., Yu, X., Hyyppä, J., … Viitala, R. (2013). Retrieval of Forest Aboveground Biomass and Stem Volume with Airborne Scanning LiDAR. Remote Sensing, 5(5), 2257-2274. doi:10.3390/rs5052257
Kükenbrink, D., Schneider, F. D., Leiterer, R., Schaepman, M. E., & Morsdorf, F. (2017). Quantification of hidden canopy volume of airborne laser scanning data using a voxel traversal algorithm. Remote Sensing of Environment, 194, 424-436. doi:10.1016/j.rse.2016.10.023
LaRue, E., Wagner, F., Fei, S., Atkins, J., Fahey, R., Gough, C., & Hardiman, B. (2020). Compatibility of Aerial and Terrestrial LiDAR for Quantifying Forest Structural Diversity. Remote Sensing, 12(9), 1407. doi:10.3390/rs12091407
Lefsky, M. A., Harding, D. J., Keller, M., Cohen, W. B., Carabajal, C. C., Del Bom Espirito-Santo, F., … de Oliveira, R. (2005). Estimates of forest canopy height and aboveground biomass using ICESat. Geophysical Research Letters, 32(22), n/a-n/a. doi:10.1029/2005gl023971
Liang, X., Kankare, V., Hyyppä, J., Wang, Y., Kukko, A., Haggrén, H., … Vastaranta, M. (2016). Terrestrial laser scanning in forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing, 115, 63-77. doi:10.1016/j.isprsjprs.2016.01.006
Lin, Y., & Herold, M. (2016). Tree species classification based on explicit tree structure feature parameters derived from static terrestrial laser scanning data. Agricultural and Forest Meteorology, 216, 105-114. doi:10.1016/j.agrformet.2015.10.008
Lindberg, E., Olofsson, K., Holmgren, J., & Olsson, H. (2012). Estimation of 3D vegetation structure from waveform and discrete return airborne laser scanning data. Remote Sensing of Environment, 118, 151-161. doi:10.1016/j.rse.2011.11.015
Liu, L., Pang, Y., Li, Z., Si, L., & Liao, S. (2017). Combining Airborne and Terrestrial Laser Scanning Technologies to Measure Forest Understorey Volume. Forests, 8(4), 111. doi:10.3390/f8040111
Luther, J. E., Fournier, R. A., van Lier, O. R., & Bujold, M. (2019). Extending ALS-Based Mapping of Forest Attributes with Medium Resolution Satellite and Environmental Data. Remote Sensing, 11(9), 1092. doi:10.3390/rs11091092
Maltamo, M., Næsset, E., Vauhkonen, J., 2014. Foresty Applications of Airborne Laser Scanning. Springer, Netherlands.
Olivier, M.-D., Robert, S., & Fournier, R. A. (2016). Response of sugar maple (Acer saccharum, Marsh.) tree crown structure to competition in pure versus mixed stands. Forest Ecology and Management, 374, 20-32. doi:10.1016/j.foreco.2016.04.047
Martinuzzi, S., Vierling, L. A., Gould, W. A., Falkowski, M. J., Evans, J. S., Hudak, A. T., & Vierling, K. T. (2009). Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability. Remote Sensing of Environment, 113(12), 2533-2546. doi:10.1016/j.rse.2009.07.002
McGaughey, R.J., 2014. FUSION/LDV: Software for LiDAR data analysis and visualization, Manual.
Morsdorf, F., Mårell, A., Koetz, B., Cassagne, N., Pimont, F., Rigolot, E., & Allgöwer, B. (2010). Discrimination of vegetation strata in a multi-layered Mediterranean forest ecosystem using height and intensity information derived from airborne laser scanning. Remote Sensing of Environment, 114(7), 1403-1415. doi:10.1016/j.rse.2010.01.023
Nie, S., Wang, C., Zeng, H., Xi, X., & Li, G. (2017). Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest. Ecological Indicators, 78, 221-228. doi:10.1016/j.ecolind.2017.02.045
Olsoy, P. J., Glenn, N. F., Clark, P. E., & Derryberry, D. R. (2014). Aboveground total and green biomass of dryland shrub derived from terrestrial laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing, 88, 166-173. doi:10.1016/j.isprsjprs.2013.12.006
Piboule, A., Krebs, M., Esclatine, L., Hervé, J.-C., 2015. Computree: A collaborative platform for use of terrestrial lidar in dendrometry, in: International IUFRO Conference MeMoWood. Nancy, France.
Pimont, F., Allard, D., Soma, M., & Dupuy, J.-L. (2018). Estimators and confidence intervals for plant area density at voxel scale with T-LiDAR. Remote Sensing of Environment, 215, 343-370. doi:10.1016/j.rse.2018.06.024
QGIS, D.T., 2016. QGIS Geographic Information System.
Ravaglia, Fournier, Bac, Véga, Côté, Piboule, & Rémillard. (2019). Comparison of Three Algorithms to Estimate Tree Stem Diameter from Terrestrial Laser Scanner Data. Forests, 10(7), 599. doi:10.3390/f10070599
Ruiz, L., Hermosilla, T., Mauro, F., & Godino, M. (2014). Analysis of the Influence of Plot Size and LiDAR Density on Forest Structure Attribute Estimates. Forests, 5(5), 936-951. doi:10.3390/f5050936
Ruiz, L. Á., Recio, J. A., Crespo-Peremarch, P., & Sapena, M. (2016). An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery. Geocarto International, 33(5), 443-457. doi:10.1080/10106049.2016.1265595
Srinivasan, S., Popescu, S., Eriksson, M., Sheridan, R., & Ku, N.-W. (2015). Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter. Remote Sensing, 7(2), 1877-1896. doi:10.3390/rs70201877
Team, R.C., 2013. R: A language and environment for statistical computing.
Torralba, J., Crespo-Peremarch, P., & Ruiz, L. A. (2018). Evaluación del uso de LiDAR discreto, full-waveform y TLS en la clasificación por composición de especies en bosques mediterráneos. Revista de Teledetección, (52), 27. doi:10.4995/raet.2018.11106
Treitz, P., Lim, K., Woods, M., Pitt, D., Nesbitt, D., & Etheridge, D. (2012). LiDAR Sampling Density for Forest Resource Inventories in Ontario, Canada. Remote Sensing, 4(4), 830-848. doi:10.3390/rs4040830
Valbuena, R., Packalén, P., Martı´n-Fernández, S., & Maltamo, M. (2012). Diversity and equitability ordering profiles applied to study forest structure. Forest Ecology and Management, 276, 185-195. doi:10.1016/j.foreco.2012.03.036
Valbuena, R., Packalen, P., Mehtätalo, L., García-Abril, A., & Maltamo, M. (2013). Characterizing forest structural types and shelterwood dynamics from Lorenz-based indicators predicted by airborne laser scanning. Canadian Journal of Forest Research, 43(11), 1063-1074. doi:10.1139/cjfr-2013-0147
Valbuena, R., Vauhkonen, J., Packalen, P., Pitkänen, J., & Maltamo, M. (2014). Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves. ISPRS Journal of Photogrammetry and Remote Sensing, 95, 23-33. doi:10.1016/j.isprsjprs.2014.06.002
Valbuena, R., Eerikäinen, K., Packalen, P., & Maltamo, M. (2016). Gini coefficient predictions from airborne lidar remote sensing display the effect of management intensity on forest structure. Ecological Indicators, 60, 574-585. doi:10.1016/j.ecolind.2015.08.001
Valbuena, R., Maltamo, M., Mehtätalo, L., & Packalen, P. (2017). Key structural features of Boreal forests may be detected directly using L-moments from airborne lidar data. Remote Sensing of Environment, 194, 437-446. doi:10.1016/j.rse.2016.10.024
van Rossum, G., 1995. Python tutorial, technical report CS-R9526. Amsterdam, The Netherlands.
Vaughn, N. R., Moskal, L. M., & Turnblom, E. C. (2012). Tree Species Detection Accuracies Using Discrete Point Lidar and Airborne Waveform Lidar. Remote Sensing, 4(2), 377-403. doi:10.3390/rs4020377
Vierling, L. A., Xu, Y., Eitel, J. U. H., & Oldow, J. S. (2013). Shrub characterization using terrestrial laser scanning and implications for airborne LiDAR assessment. Canadian Journal of Remote Sensing, 38(6), 709-722. doi:10.5589/m12-057
Watt, P. J., & Donoghue, D. N. M. (2005). Measuring forest structure with terrestrial laser scanning. International Journal of Remote Sensing, 26(7), 1437-1446. doi:10.1080/01431160512331337961
Wing, B. M., Ritchie, M. W., Boston, K., Cohen, W. B., Gitelman, A., & Olsen, M. J. (2012). Prediction of understory vegetation cover with airborne lidar in an interior ponderosa pine forest. Remote Sensing of Environment, 124, 730-741. doi:10.1016/j.rse.2012.06.024
Zeileis, A., Kleiber, C., Zeileis, M.A., 2009. Package “ineq.”.
[-]