Modelling lidar-derived boreal forest canopy cover with SPOT 4 HRVIR data

References

• Asner, G. P., G. V. N. Powell, J. Mascaro, D. E. Knapp, J. K. Clark, J. Jacobson, T. Kennedy-Bowdoin, A. Balaji, G. Paez-Acosta, E. Victoria, L. Secada, M. Valqui, and R. F. Hughes. 2010. “High-Resolution Forest Carbon Stocks and Emissions in the Amazon. ” Proceedings of the National Academy of Sciences of the United States of America 107: 16738–16742. doi:10.1073/pnas.1004875107.
   PubMed Web of Science ®Google Scholar
• Brown, L., J. M. Chen, S. G. Leblanc, and J. Cihlar. 2000. “A Shortwave Infrared Modification to the Simple Ratio for LAI Retrieval in Boreal Forests: An Image and Model Analysis. ” Remote Sensing of Environment 71: 16–25. doi:10.1016/S0034-4257(99)00035-8.
   Web of Science ®Google Scholar
• Chubey, M. S., S. E. Franklin, and M. A. Wulder. 2006. “Object-Based Analysis of Ikonos-2 Imagery for Extraction of Forest Inventory Parameters. ” Photogrammetric Engineering & Remote Sensing 72: 383–394.
   Web of Science ®Google Scholar
• Coulston, J. W., G. B. Moisen, B. T. Wilson, M. V. Finco, W. B. Cohen, and C. K. Brewer. 2012. “Modelling Percent Tree Canopy Cover: A Pilot Study. ” Photogrammetric Engineering & Remote Sensing 78: 715–727.
   Web of Science ®Google Scholar
• Eriksson, H. M., L. Eklundh, A. Kuusk, and T. Nilson. 2006. “Impact of Understory Vegetation on Forest Canopy Reflectance and Remotely Sensed LAI Estimates. ” Remote Sensing of Environment 103: 408–418. doi:10.1016/j.rse.2006.04.005.
   Web of Science ®Google Scholar
• FAO (Food and Agriculture Organization). 2004. “Global Forest Resources Assessment Update 2005. Terms and Definitions (Final Version).” Forest Resources Assessment Programme Working Paper 83/E, Rome, 36 p. Accessed March 12, 2013. http://ftp://ftp.fao.org/docrep/fao/007/ae156e/AE156E00.pdf.
   Google Scholar
• Gatziolis, D. 2012. “Comparison of LiDAR- and Photointerpretation-Based Estimates of Canopy Cover. ” In Monitoring across Borders: 2010 Joint Meeting of the Forest Inventory and Analysis (FIA) Symposium and the Southern Mensurationists, edited by W. McWilliams and F. A. Roesch, 231–235. e-Gen. Tech. Rep. SRS-157. Asheville, NC: US Department of Agriculture, Forest Service, Southern Research Station.
   Google Scholar
• Gemmell, F. 1999. “Estimating Conifer Forest Cover with Thematic Mapper Data Using Reflectance Model Inversion and Two Spectral Vegetation Indices in a Site with Variable Background Characteristics. ” Remote Sensing of Environment 69: 105–121. doi:10.1016/S0034-4257(99)00004-8.
   Web of Science ®Google Scholar
• Gemmell, F., and J. Varjo. 1999. “Utility of Reflectance Model Inversion versus Two Spectral Indices for Estimating Biophysical Characteristics in a Boreal Forest Test Site. ” Remote Sensing of Environment 68: 95–111. doi:10.1016/S0034-4257(98)00102-3.
   Web of Science ®Google Scholar
• Gemmell, F., J. Varjo, M. Strandstrom, and A. Kuusk. 2002. “Comparison of Measured Boreal Forest Characteristics with Estimates from TM Data and Limited Ancillary Information Using Reflectance Model Inversion. ” Remote Sensing of Environment 81: 365–377. doi:10.1016/S0034-4257(02)00012-3.
   Web of Science ®Google Scholar
• Gobakken, T., E. Næsset, R. Nelson, O. M. Bolladsås, T. G. Gregoire, G. Ståhl, S. Holm, H. O. Ørka, and R. Astrup. 2012. “Estimating Biomass in Hedmark County, Norway Using National Forest Inventory Field Plots and Airborne Laser Scanning. ” Remote Sensing of Environment 123: 443–456. doi:10.1016/j.rse.2012.01.025.
   Web of Science ®Google Scholar
• GOFC-GOLD. 2009. Reducing Greenhouse Gas Emissions from Deforestation and Degradation in Developing Countries: A Sourcebook of Methods and Procedures for Monitoring, Measuring and Reporting, 185 p. GOFC-GOLD Report Version COP14-2, GOFC-GOLD Project Office. Alberta: Natural Resources Canada.
   Google Scholar
• Gschwantner, T., K. Schadauer, C. Vidal, A. Lanz, E. Tomppo, L. di Cosmo, L. N. Robert, D. E. Duursma, and M. Lawrence. 2009. “Common Tree Definitions for National Forest Inventories in Europe. ” Silva Fennica 43: 303–321.
   Web of Science ®Google Scholar
• Hansen, M. C., R. S. Defrıes, J. R. G. Townshend, M. Carroll, C. Dimiceli, and R. A. Sohlberg. 2003. “Global Percent Tree Cover at a Spatial Resolution of 500 Metres: First Results of the MODIS Vegetation Continuous Fields Algorithm. ” Earth Interactions 7: 1–15. doi:10.1175/1087-3562(2003)0072.0.CO;2.
   Web of Science ®Google Scholar
• Heiskanen, J., M. Rautiainen, L. Korhonen, M. Mõttus, and P. Stenberg. 2011. “Retrieval of Boreal Forest LAI Using a Forest Reflectance Model and Empirical Regressions. ” International Journal of Applied Earth Observation and Geoinformation 13: 595–606. doi:10.1016/j.jag.2011.03.005.
   Web of Science ®Google Scholar
• Heiskanen, J., M. Rautiainen, P. Stenberg, M. Mõttus, V.-H. Vesanto, L. Korhonen, and T. Majasalmi. 2012. “Seasonal Variation in MODIS LAI for a Boreal Forest Area in Finland. ” Remote Sensing of Environment 126: 104–115. doi:10.1016/j.rse.2012.08.001.
   Web of Science ®Google Scholar
• Holmgren, J., M. Nilsson, and H. Olsson. 2003. “Simulating the Effects of LiDAR Scanning Angle for Estimation of Mean Tree Height and Canopy Closure. ” Canadian Journal of Remote Sensing 29: 623–632. doi:10.5589/m 03-030.
   Web of Science ®Google Scholar
• Jennings, S. B., N. D. Brown, and D. Sheil. 1999. “Assessing Forest Canopies and Understorey Illumination: Canopy Closure, Canopy Cover and Other Measures. ” Forestry 72: 59–74. doi:10.1093/forestry/72.1.59.
   Web of Science ®Google Scholar
• Korhonen, L., and J. Heikkinen. 2009. “Automated Analysis of in situ Canopy Images for the Estimation of Forest Canopy Cover. ” Forest Science 55: 323–334.
   Web of Science ®Google Scholar
• Korhonen, L., K. T. Korhonen, M. Rautiainen, and P. Stenberg. 2006. “Estimation of Forest Canopy Cover: A Comparison of Field Measurement Techniques. ” Silva Fennica 40: 577–588.
   Web of Science ®Google Scholar
• Korhonen, L., I. Korpela, J. Heiskanen, and M. Maltamo. 2011. “Airborne Discrete-Return LiDAR Data in the Estimation of Vertical Canopy Cover, Angular Canopy Closure and Leaf Area Index. ” Remote Sensing of Environment 115: 1065–1080. doi:10.1016/j.rse.2010.12.011.
   Web of Science ®Google Scholar
• Korpela, I., A. Hovi, and F. Morsdorf. 2012. “Understory Trees in Airborne LiDAR Data – Selective Mapping Due To Transmission Losses and Echo-Triggering Mechanisms. ” Remote Sensing of Environment 119: 92–104. doi:10.1016/j.rse.2011.12.011.
   Web of Science ®Google Scholar
• R Core Team. 2012. “R: A Language and Environment for Statistical Computing.” R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0. http://www.R-project.org/.
   Google Scholar
• Rahman, H., and G. Dedieu. 1994. “SMAC: A Simplified Method for the Atmospheric Corrections of Satellite Measurements in the Solar Spectrum. ” International Journal of Remote Sensing 15: 123–143. doi:10.1080/01431169408954055.
   Web of Science ®Google Scholar
• Rautiainen, M., J. Suomalainen, M. Mõttus, P. Stenberg, P. Voipio, J. Peltoniemi, and T. Manninen. 2007. “Coupling Forest Canopy and Understory Reflectance in the Arctic Latitudes of Finland. ” Remote Sensing of Environment 110: 332–343. doi:10.1016/j.rse.2007.03.002.
   Web of Science ®Google Scholar
• Smith, A. M. S., J. M. Falkowski, A. T. Hudak, J. S. Evans, A. P. Robinson, and C. M. Steele. 2009. “A Cross-Comparison of Field, Spectral, and LiDAR Estimates of Forest Canopy Cover. ” Canadian Journal of Remote Sensing 35: 447–459. doi:10.5589/m09-038.
   Web of Science ®Google Scholar
• Solberg, S., E. Næsset, and H. Lange. 2010. “Comparing Canopy Penetration of Repeated ALS Acquisitions. ” In Proceedings of Silvilaser 2010, edited by C. Teguem, 310–314. Freiburg: Department of Remote Sensing and Landscape Information Systems (FeLis), Albert-Ludwigs-University of Freiburg.
   Google Scholar
• Stenberg, P., M. Rautiainen, T. Manninen, P. Voipio, and H. Smolander. 2004. “Reduced Simple Ratio Better Than NDVI for Estimating LAI in Finnish Pine and Spruce Stands. ” Silva Fennica 38: 3–14.
   Web of Science ®Google Scholar
• Stojanova, D., P. Panov, V. Gjorkioski, A. Kobler, and S. Džeroski. 2010. “Estimating Vegetation Height and Canopy Cover from Remotely Sensed Data with Machine Learning. ” Ecological Informatics 5: 256–266. doi:10.1016/j.ecoinf.2010.03.004.
   Web of Science ®Google Scholar
• Wolter, P. T., P. A. Townsend, and B. R. Sturtevant. 2009. “Estimation of Forest Structural Parameters Using 5 and 10 Meter SPOT-5 Satellite Data. ” Remote Sensing of Environment 113: 2019–2036. doi:10.1016/j.rse.2009.05.009.
   Web of Science ®Google Scholar