other high resolution imagery to further enhance the information on coral reef
structure, and exploiting the information that can be derived from LiDAR-derived
seafloor intensity surfaces. In the future, as the technology advances, and research
efforts continue to refine signal processing techniques and algorithms, the capabilities and products that can be derived from LiDAR will similarly improve and
expand.
Acknowledgments This chapter was made possible with contributions from Tim Battista
(NOAA Biogeography Branch), Alan M. Friedlander (University of Hawaii/USGS), Curt D.
Storlazzi (USGS), Michael E. Field and (USGS) and Christopher L. Conger. Support for the
authors was provided by NOAA’s Coral Reef Conservation Program.
Suggested Reading
Brock JC, Purkis SJ (2009) The emerging role of LiDAR remote sensing in coastal research and
resource management. J Coast Res SI 53:1–5
Conger CL, Fletcher CH, Hochberg EH, Frazer N, Rooney J (2009) Remote sensing of sand
distribution patterns across an insular shelf: Oahu, Hawaii. Mar Geo 267:175–190
Costa BM, Battista TA, Pittman SJ (2009) Comparative evaluation of airborne LiDAR and shipbased multibeam sonar bathymetry and intensity for mapping coral reef ecosystems. Remote
Sens Environ 113:1082–1100
Pittman SJ, Costa BM, Battista TA (2009) Using LiDAR bathymetry and boosted regression trees
to predict the diversity and abundance of fish and corals. J Coast Res 53(SI):27–38
Pittman SJ, Brown KA (2011) Multiscale approach for predicting fish species distributions across
coral reef seascapes. PLoS ONE 6(5):e20583. doi:10.1371/journal.pone.0020583
Storlazzi CD, Logan JB, Field ME (2003) Quantitative morphology of a fringing reef tract from
high-resolution laser bathymetry: Southern Molokai, Hawaii. Geol Soc Am Bull 115:1344
References
Alvarez-Filip L, Dulvy NK, Gill JA, Cote IM, Watkinson AR (2009) Flattening of Caribbean
coral reefs: region-wide declines in architectural complexity. Proc Roy Soc Ser B
276:3019–3025
Baker WE, Emmitt GD, Robertson F, Atlas RM, Molinari JE, Bowdle DA, Paegle J, Hardesty M,
Menzies RT, Krishnamurti TN, Brown RA, Post MJ, Anderson JR, Lorenc AA, McElroy J
(1995) LiDAR-measured winds from space: a key component for weather and climate
prediction. Bull Am Meteorol Soc 76(6):869–888
Baltsavias EP (1999) Airborne laser scanning: basic relations and formulas. ISPRS J
Photogrammetry Remote Sens 54:214–1999
Banks KW, Riegl BM, Shinn EA, Piller WE, Dodge RE (2007) Geomorphology of the Southeast
Florida continental reef tract (Miami-Dade, Broward, and Palm Beach Counties, USA). Coral
Reefs 26:617–633
Brock JC, Wright WC, Clayton TD, Nayegandhi A (2004) LiDAR optical rugosity of coral reefs
in Biscayne National Park, Florida. Coral Reefs 23:48–59
Brock JC, Wright CW, Kuffner IB, Hernandez R, Thompson P (2006) Airborne LiDAR sensing
of massive stony coral colonies on patch reefs in the Northern Florida reef tract. Remote Sens
Environ 104:31–42
6 LiDAR Applications
169
structure, and exploiting the information that can be derived from LiDAR-derived
seafloor intensity surfaces. In the future, as the technology advances, and research
efforts continue to refine signal processing techniques and algorithms, the capabilities and products that can be derived from LiDAR will similarly improve and
expand.
Acknowledgments This chapter was made possible with contributions from Tim Battista
(NOAA Biogeography Branch), Alan M. Friedlander (University of Hawaii/USGS), Curt D.
Storlazzi (USGS), Michael E. Field and (USGS) and Christopher L. Conger. Support for the
authors was provided by NOAA’s Coral Reef Conservation Program.
Suggested Reading
Brock JC, Purkis SJ (2009) The emerging role of LiDAR remote sensing in coastal research and
resource management. J Coast Res SI 53:1–5
Conger CL, Fletcher CH, Hochberg EH, Frazer N, Rooney J (2009) Remote sensing of sand
distribution patterns across an insular shelf: Oahu, Hawaii. Mar Geo 267:175–190
Costa BM, Battista TA, Pittman SJ (2009) Comparative evaluation of airborne LiDAR and shipbased multibeam sonar bathymetry and intensity for mapping coral reef ecosystems. Remote
Sens Environ 113:1082–1100
Pittman SJ, Costa BM, Battista TA (2009) Using LiDAR bathymetry and boosted regression trees
to predict the diversity and abundance of fish and corals. J Coast Res 53(SI):27–38
Pittman SJ, Brown KA (2011) Multiscale approach for predicting fish species distributions across
coral reef seascapes. PLoS ONE 6(5):e20583. doi:10.1371/journal.pone.0020583
Storlazzi CD, Logan JB, Field ME (2003) Quantitative morphology of a fringing reef tract from
high-resolution laser bathymetry: Southern Molokai, Hawaii. Geol Soc Am Bull 115:1344
References
Alvarez-Filip L, Dulvy NK, Gill JA, Cote IM, Watkinson AR (2009) Flattening of Caribbean
coral reefs: region-wide declines in architectural complexity. Proc Roy Soc Ser B
276:3019–3025
Baker WE, Emmitt GD, Robertson F, Atlas RM, Molinari JE, Bowdle DA, Paegle J, Hardesty M,
Menzies RT, Krishnamurti TN, Brown RA, Post MJ, Anderson JR, Lorenc AA, McElroy J
(1995) LiDAR-measured winds from space: a key component for weather and climate
prediction. Bull Am Meteorol Soc 76(6):869–888
Baltsavias EP (1999) Airborne laser scanning: basic relations and formulas. ISPRS J
Photogrammetry Remote Sens 54:214–1999
Banks KW, Riegl BM, Shinn EA, Piller WE, Dodge RE (2007) Geomorphology of the Southeast
Florida continental reef tract (Miami-Dade, Broward, and Palm Beach Counties, USA). Coral
Reefs 26:617–633
Brock JC, Wright WC, Clayton TD, Nayegandhi A (2004) LiDAR optical rugosity of coral reefs
in Biscayne National Park, Florida. Coral Reefs 23:48–59
Brock JC, Wright CW, Kuffner IB, Hernandez R, Thompson P (2006) Airborne LiDAR sensing
of massive stony coral colonies on patch reefs in the Northern Florida reef tract. Remote Sens
Environ 104:31–42
6 LiDAR Applications
169