A new methodology to estimate the discrete-return point density on airborne lidar surveys

References

• Anderson, E. S., J. A. Thompson, and R. E. Austin. 2005. “LIDAR Density and Linear Interpolator Effects on Elevation Estimates.” International Journal of Remote Sensing 26: 3889–3900.
   Web of Science ®Google Scholar
• Balsa-Barreiro, J., J. Pere, and J. L. Lerma. 2012. “Airborne Light Detection and Ranging (LiDAR) Point Density Analysis.” Scientific Research and Essays 7: 3010–3019.
   Google Scholar
• Baltsavias, E. 1999. “Airborne Laser Scanning: Basic Relations and Formulas.” ISPRS Journal of Photogrammetry and Remote Sensing 54: 199–214.
   Web of Science ®Google Scholar
• Bevington, P. R. 1969. Data Reduction and Error Analysis for the Physical Sciences. New York: McGraw-Hill.
   Google Scholar
• Borovkova, S., F. J. Permana, and I. Pavlyukevich. 2009. “Modelling Electricity Prices by Potential Lévy Diffusions.” Journal of Energy Markets 2: 83–110.
   Google Scholar
• County, K. 2003. “LiDAR Digital Ground Model Point Density.” King County. Accessed August 6, 2013. http://www5.kingcounty.gov/sdc/raster/elevation/LiDAR_Digital_Ground_Model_Point_Density.html 
   Google Scholar
• Efromovich, S. 2004. “Density Estimation for Biased Data.” Annals of Statistics 32: 1137–1161.
   Web of Science ®Google Scholar
• Ferguson, T. S. 1961a. “On the rejection of outliers.” Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability 1: 253–287.
   Google Scholar
• Ferguson, T. S. 1961b. “Rules for Rejection of Outliers.” Review of the International Statistical Institute 29: 29–43.
   Google Scholar
• Fox, A. J. 1972. “Outliers in Time Series.” Journal of the Royal Statistical Society, B 34: 350–363.
   Google Scholar
• Gentleman, J. F., and M. B. Wilk. 1975a. “Detecting Outliers in a Two Way Table; I. Statistical Behaviour of Residuals.” Technometrics 17: 1–14.
   Web of Science ®Google Scholar
• Gentleman, J. F., and M. B. Wilk. 1975b. “Detecting Outliers; II. Supplementing the Direct Analysis of Residuals.” Biometrics 31: 387–410.
   Web of Science ®Google Scholar
• Graphpad. 2013. “Quickcalcs: Outlier Calculator.” Graphpad Software. Accessed August 6. http://www.graphpad.com/quickcalcs/grubbs1 
   Google Scholar
• Grubbs, F. E. 1950. “Sample Criteria for Testing Outlying Observations.” Annals of Mathematical Statistics 21: 27–58.
   Google Scholar
• Grubbs, F. E. 1969. “Procedures for Detecting Outlying Observations in Samples.” Technometrics 11: 1–21.
   Web of Science ®Google Scholar
• Grubbs, F. E., and G. Beck. 1972. “Extension of Sample Sizes and Percentage Points for Significance Tests of Outlying Observations.” Technometrics 14: 847–854.
   Web of Science ®Google Scholar
• Gueudet, P., G. Wells, D. Maidment, and A. Neuenschwander. 2004. “Influence of the Post-Spacing Density of the LIDAR-Derived DEM on Flood Modeling.” Proceedings of the AWRA Spring Specialty Conference on GIS and Water Resources, AWRA, Nashville, TN, May 17–19.
   Google Scholar
• Guttman, I., and D. E. Smith. 1969. “Investigation of Rules for Dealing with Outliers in Small Samples from the Normal Distribution. I. Estimation of the Mean.” Technometrics 11: 527–554.
   Web of Science ®Google Scholar
• Guttman, I., and D. E. Smith. 1971. “Investigation of Rules for Dealing with Outliers in Small Samples from the Normal Distribution. II. Estimation of the Variance.” Technometrics 13: 101–113.
   Web of Science ®Google Scholar
• Habib, A. 2012. “Point Density and the Challenge in Processing Multi-Source Lidar Data.” GIM International 26: 6.
   Google Scholar
• Hawkins, D. M. 1973. “Repeated Testing for Outliers.” Statistica Neerlandica 27: 1–10.
   Google Scholar
• Hawkins, D. M. 1978a. “Analysis of Three Tests for One or Two Outliers.” Statistica Neerlandica 32: 137–148.
   Google Scholar
• Hawkins, D. M. 1978b. “Fractiles of an Extended Multiple Outlier Test.” Journal of Statistical Computation and Simulation 8: 227–236.
   Google Scholar
• Lari, Z., and A. Habib. 2012. “Alternative Methodologies for Estimation of Local Point Density Index: Moving Towards Adaptive LIDAR Data Processing.” International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 39 (Part B3): 127–132.
   Google Scholar
• Lari, Z., and A. Habib. 2013. “New Approaches for Estimating the Local Point Density and Its Impact on LiDAR Data Segmentation.” Photogrammetric Engineering and Remote Sensing 79: 195–207.
   Google Scholar
• Limbrunner, J. F., R. M. Vogel, and L. C. Brown. 2000. “Estimation of Harmonic Mean of a Lognormal Variable.” Journal of Hydrologic Engineering 5: 59–66.
   Web of Science ®Google Scholar
• Maune, D. 2001. Digital Elevation Model Technologies and Application: The DEM Users Manual. Bethesda, MD: ASPRS Publications.
   Google Scholar
• Mitchell, D. W. 2004. “More on Spreads and Non-Arithmetic Means.” Mathematical Gazette 88: 142–144.
   Google Scholar
• Naus, T. 2008. “Unbiased LiDAR Data Measurement (Draft).” ASPRS PAD LiDAR Committee, Portland. Accessed August 6, 2013. http://www.asprs.org/a/society/committees/lidar/Unbiased_measurement.pdf
   Google Scholar
• Nava-Ortega, R. A., E. Espino-Barr, M. Gallardo-Cabello, A. García-Boa, M. Puente-Gómez, and E. G. Cabral-Solís. 2012. “Growth Analysis of the Pacific Sierra Scomberomorus Sierra in Colima, México.” Revista De Biología Marina Y Oceanografía 47: 273–281.
   Web of Science ®Google Scholar
• PNOA (Spanish National Project of Aerial Orthophoto). 2009. Official Website PNOA. Accessed January 7, 2014. http://www.ign.es/PNOA
   Google Scholar
• Raber, G., J. R. Jensen, M. E. Hodgson, J. A. Tullis, B. A. Davis, and J. Berglund. 2007. “Impact of LiDAR Nominal Post-Spacing on DEM Accuracy and Flood Zone Delineation.” Photogrammetric Engineering & Remote Sensing 73: 793–804.
   Web of Science ®Google Scholar
• Rossman, L. A. 1990. “Design Stream Flows Based on Harmonic Means.” Journal of Hydraulic Engineering 116: 946–950.
   Web of Science ®Google Scholar
• Rost, H., and H. Grierson. 2008. “High Precision Projects Using LiDAR and Digital Imagery.” TS1I - Imaging and Data Applications on FIG Working-Week 2008, Stockholm, June 14–19.
   Google Scholar
• Sandhya, S. S., S. Somasundaram, and R. Ponraj. 2012. “Harmonic Mean Labeling of Some Cycle Related Graphs.” International Journal of Mathematical Analysis 6: 1997–2005.
   Google Scholar
• Sharma, R. 2008. “Some More Inequalities for Arithmetic Mean, Harmonic Mean and Variance.” Journal of Mathematical Inequalities 2: 109–114.
   Google Scholar
• Shih, P. T., and C. M. Huang. 2006. “Airborne LiDAR point cloud density indices.” American Geophysical Union, Fall Meeting, San Francisco, CA, December 11–15.
   Google Scholar
• Spizman, L., and M. A. Weinstein. 2008. “A Note on Utilizing the Geometric Mean: When, Why and How the Forensic Economist Should Employ the Geometric Mean.” Journal of Legal Economics 15: 43–55.
   Google Scholar
• Tesfamichael, S. G., F. B. Ahmed, and J. A. N. Van Aardt. 2010. “Investigating the Impact of Discrete-Return Lidar Point Density on Estimations of Mean and Dominant Plot-Level Tree Height in Eucalyptus Grandis Plantations.” International Journal of Remote Sensing 31: 2925–2940.
   Web of Science ®Google Scholar