Airborne lidar for woodland habitat quality monitoring: Exploring the significance of lidar data characteristics when modelling organism-habitat relationships

Remote Sensing

Volumn 7, Issue 4, 2015, Pages 3446-3466

  Hill, Ross A ^a   Hinsley, Shelley A ^b  

^a BOURNEMOUTH UNIVERSITY   (United Kingdom)

^b CENTRE FOR ECOLOGY AND HYDROLOGY   (United Kingdom)

Author keywords

Airborne laser scanning; Bird ecology; Forest; Habitat; Lidar; Remote sensing

Indexed keywords

BALLOONS; BIOLOGY; BIRDS; ECOSYSTEMS; FORESTRY; OPTICAL RADAR; QUALITY CONTROL; REGRESSION ANALYSIS; REMOTE SENSING; STRUCTURAL OPTIMIZATION;

AIRBORNE LASER SCANNING; AIRBORNE LIDAR DATA; BIRD ECOLOGIES; FOREST; HABITAT; LIDAR DATA ACQUISITIONS; ORDINARY LEAST-SQUARES REGRESSION ANALYSIS; STATISTICAL SIGNIFICANCE;

ECOLOGY;

BIRDS; ECOLOGY; FORESTS; REMOTE SENSING; STATISTICAL ANALYSIS;

EID: 84933559748     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs70403446     Document Type: Article

References (53)

1. MacArthur, R.H.; MacArthur, J. On bird species diversity. Ecology 1961, 42, 594-598.
2. Turner, W.; Spector, S.; Gardiner, N.; Fladeland, M.; Sterling, E.; Steininger, M. Remote sensing for biodiversity science and conservation. Trends Ecol. Evol. 2003, 18, 306-314.
3. Bergen, K.M.; Goetz, S.J.; Dubayah, R.O.; Henebry, G.M.; Hunsaker, C.T.; Imhoff, M.L.; Nelson, R.F.; Parker, G.G.; Radeloff, V.C. Remote sensing of vegetation 3-D structure for biodiversity and habitat: Review and implications for lidar and radar spaceborne missions. J. Geophys. Res.: Biogeosci. 2009, 114, doi:10.1029/2008JG000883.
4. Nelson, R.; Keller, C.; Ratnaswamy, M. Locating and estimating the extent of Delmarva fox squirrel habitat using an airborne LiDAR profiler. Remote Sens. Environ. 2005, 96, 292-301.
5. Coops, N.C.; Duffe, J.; Koot, C. Assessing the utility of lidar remote sensing technology to identify mule deer winter habitat. Can. J. Remote Sens. 2010, 36, 81-88.
6. Garabedian, J.E.; McGaughey, R.J.; Reutebuch, S.E.; Parresol, B.R.; Kilgo, J.C.; Moorman, C.E.; Peterson, M.N. Quantitative analysis of woodpecker habitat using high-resolution airborne LiDAR estimates of forest structure and composition. Remote Sens. Environ. 2014, 145, 68-80.
7. Vogeler, J.C.; Hudak, A.T.; Vierling, L.A.; Vierling, K.T. Lidar-derived canopy architecture predicts brown creeper occupancy of two western coniferous forests. Condor 2013, 115, 614-622.
8. Graf, R.F.; Mathys, L.; Bollmann, K. Habitat assessment for forest dwelling species using LiDAR remote sensing: Capercaillie in the Alps. For. Ecol. Manag. 2009, 257, 160-167.
9. Hinsley, S.A.; Hill, R.A.; Fuller, R.J.; Bellamy, P.E.; Rothery, P. Bird species distributions across woodland canopy structure gradients. Community Ecol. 2009, 10, 99-110.
10. Eldegard, K.; Dirksen, J.W.; Orka, H, O.; Halvorsen, R.; Naesset, E.; Gobakken, T.; Ohlson, M. Modelling bird richness and bird species presence in a boreal forest reserve using airborne laser-scanning and aerial images. Bird Study 2014, 61, 204-219.
11. Farrell, S.L.; Collier, B.A.; Skow, K.L.; Long, A.M.; Campomizzi, A.J.; Morrison, M.L.; Hays, K.B.; Wilkins, R.N. Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning. Ecosphere 2013, 4, doi:10.1890/ES12-000352.1.
12. Zellweger, F.; Braunisch, V.; Baltensweiller, A.; Bollmann, K. Remotely sensed forest structural complexity predicts multi species occurrence at the landscape scale. For. Ecol. Manag. 2013, 307, 303-312.
13. Vierling, K.T.; Vierling, L.A.; Gould, W.A.; Martinuzzi, S.; Clawges, R.M. Lidar:Shedding new light on habitat characterization and modelling. Front. Ecol. Environ. 2008, 6, 90-98.
14. Bellamy, P.E.; Hill, R.A.; Rothery, P.; Hinsley, S.A.; Fuller, R.J.; Broughton, R.K. Willow warbler Phylloscopus trochilus habitat in woods with different structure and management in southern England. Bird Study 2009, 56, 338-348.
15. Clawges, R.; Vierling, K.; Vierling, L.; Rowell, E. The use of airborne lidar to assess avian species diversity, density, and occurrence in a pine/aspen forest. Remote Sens. Environ. 2008, 112, 2064-2073.
16. Swatantran, A.; Dubayah, R.; Goetz, S.; Hofton, M.; Betts, M.G.; Sun, M.; Simard, M.; Holmes, R. Mapping migratory bird prevalence using remote sensing data fusion. PLoS One 2012, 7, doi:10.1371/journal.pone.0028922.
17. Vierling, L.A.; Vierling, K.T.; Adam, P.; Hudak, A.T. Using satellite and airborne lidar to model woodpecker habitat occupancy at the landscape scale. PLoS One 2013, 8, doi:10.1371/journal.pone.0080988.
18. Palminteri, S.; Powell, G.V.N.; Asner, G.P.; Peres, C.C. LiDAR measurements of canopy structure predict spatial distribution of a tropical mature forest primate. Remote Sens. Environ. 2012, 127, 98-105.
19. Zhao, F.; Sweitzer, R.A.; Guo, Q.; Kelly, M. Characterizing habitats associated with fisher den structures in the Southern Sierra Nevada, California using discrete return lidar. For. Ecol. Manag. 2012, 280, 112-119.
20. Melin, M.; Packalen, P.; Matala, J.; Mehtalalo, L.; Pusenius, J. Assessing and modeling moose (Alces alces) habitats with airborne laser scanning data. Int. J. Appl. Earth Obs. 2013, 23, 389-396.
21. Flaherty, S.; Lurz, P.W.W.; Patenaude, G. Use of LiDAR in the conservation management of the endangered red squirrel (Sciurus vulgaris L.). J. Appl. Remote Sens. 2014, 8, doi:10.1117/1.JRS.8.083592.
22. Jung, K.; Kaiser, S.; Bohm, S.; Nieschulze, J.; Kalko, E.K.V. Moving in three dimensions: Effects of structural complexity on occurrence and activity of insectivorous bats in managed forest stands. J. Appl. Ecol. 2012, 49, 523-531.
23. Müller, J.; Mehr, M.; Bässler, C.; Fenton, M.B.; Hothorn, T.; Pretzsch, H.; Klemmt, H.J.; Brandl, R. Aggregative response in bats: Prey abundance versus habitat. Oecologia 2012, 169, 673-684.
24. Lone, K.; Loe, L.E.; Gobakken, T.; Linnell, J.D.C.; Odden, J.; Remmen, J.; Mysterud, A. Living and dying in a multi-predator landscape of fear: Roe deer are squeezed by contrasting pattern of predation risk imposed by lynx and humans. Oikos 2014, 123, 641-651.
25. Ewald, M.; Dupke, C.; Heurich, M.; Muller, J.; Reineking, B. LiDAR remote sensing of forest structure and GPS telemetry data provide insights on winter habitat selection of European roe deer. Forests 2014, 5, 1374-1390.
26. Melin, M.; Matala, J.; Mehtatalo, L.; Tiilikainen, R.; Tikkanen, O.P.; Maltamo, M.; Pusenius, J.; Packalen, P. Moose(Alces alces) reacts to high summer temperatures by utilizing thermal shelters in boreal forests-An analysis based on airborne laser scanning of the canopy structure at moose locations. Glob. Change Biol. 2014, 20, 1115-1125.
27. Hinsley, S.A.; Hill, R.A.; Gaveau, D.L.A.; Bellamy, P.E. Quantifying woodland structure and habitat quality for birds using airborne laser scanning. Funct. Ecol. 2002, 16, 851-857.
28. Hill, R.A.; Hinsley, S.A.; Gaveau, D.L.A.; Bellamy, P.E. Predicting habitat quality for Great Tits (Parus major) with airborne laser scanning data. Int. J. Remote Sens. 2004, 25, 4851-4855.
29. Hinsley, S.A.; Hill, R.A.; Bellamy, P.E.; Balzter, H. The application of lidar in woodland bird ecology: Climate, canopy structure, and habitat quality. Photogramm. Eng. Rem. Sens. 2006, 72, 1399-1406.
30. Seavy, N.E.; Viers, J.H.; Wood, J.K. Riparian bird response to vegetation structure: A multiscale analysis using LiDAR measurements of canopy height. Ecol. Appl. 2009, 19, 1848-1857.
31. Smart, L.S.; Swenson, J.J.; Christensen, N.L.; Sexton, J.O. Three-dimensional characterization of pine forest type and red-cockaded woodpecker habitat by small-footprint, discrete-return lidar. For. Ecol. Manag. 2012, 281, 100-110.
32. Goetz, S.J.; Steinberg, D.; Betts, M.G.; Holmes, R.T.; Doran, P.J.; Dubayah, R.; Hofton, M. Lidar remote sensing variables predict breeding habitat of a neotropical migrant bird. Ecology 2010, 91, 1569-1576.
33. Vierling, K.T.; Swift, C.E.; Hudak, A.T.; Vogeler, J.C.; Vierling, L.A. Does the time lag between wildlife field data collection and LiDAR data acquisition matter for studies of wildlife distributions? A case study using bird communities. Remote Sens. Lett. 2014, 5, 185-193.
34. Patenaude, G.; Hill, R.A.; Milne, R.; Gaveau, D.L.A.; Briggs, B.B.J.; Dawson, T.P. Quantifying forest above ground carbon content using LiDAR remote sensing. Remote Sens. Environ. 2004, 93, 368-380.
35. Hill, R.A.; Thomson, A.G. Mapping woodland species composition and structure using airborne spectral and LiDAR data. Int. J. Rem. Sens. 2005, 26, 3763-3779.
36. Massey, M.E.; Welch, R.C. Monks Wood National Nature Reserve: The Experience of 40 Years 1953-1993; English Nature: Peterborough, UK, 1993.
37. Hill, R.A.; Wilson, A.K.; George, M.; Hinsley, S.A. Mapping tree species in temperate deciduous woodland using time-series multi-spectral data. Appl. Veg. Sci. 2010, 13, 86-99.
38. Hill, R.A.; Broughton, R.K. Mapping the understorey of deciduous woodland from leaf-on and leaf-offairborne LiDAR data: A case study in lowland Britain. ISPRS J. Photogramm. 2009, 64, 223-233.
39. Hinsley, S.A.; Rothery, P.; Bellamy, P.E. Influence of woodland area on breeding success in Great Tits (Parus major) and Blue Tits (Parus caeruleus). J. Avian Biol. 1999, 3, 271-281.
40. Przybylo, R.; Wiggins, D.A.; Merila, J. Breeding success in Blue Tits: Good territories or good parents? J. Avian Biol. 2001, 32, 214-218.
41. Gaveau, D.L.A.; Hill, R.A. Quantifying canopy height underestimation by laser pulse penetration in small-footprint airborne laser scanning data. Can. J. Remote Sens. 2003, 29, 650-657.
42. Zhang, K.Q.; Chen, S.C.; Whitman, D.; Shyu, M.L.; Yan, J.H.; Zhang, C.C. A progressive morphological filter for removing non-ground measurements from airborne lidar data. IEEE Trans. Geosci. Remote Sens. 2003, 41, 872-882.
43. Moran, M.D. Arguments for rejecting the sequential Bonferroni in ecological studies. Oikos 2003, 100, 403-405.
44. Nakagawa, S. A farewell to Bonferroni: The problems of low statistical power and publication bias. Behav. Ecol. 2004, 15, 1044-1045.
45. Lack, D. Ecological Isolation in Birds; Blackwell Scientific Publications: Oxford, UK,1971.
46. Perrins, C.M. British Tits; Collins: London, UK,1979.
47. Gosler, A. The Great Tit; Hamlyn Limited: London, UK,1993.
48. Naef-Daenzer, B.; Keller, L.F. The foraging performance of great and blue tits (Parus major and P. caeruleus) in relation to caterpillar development and its consequences for nestling growth and fledging weight. J. Anim. Ecol. 1999, 57, 607-697.
49. Minot, E.O. Effects of interspecific competition for food in breeding blue and great tits. J. Anim. Ecol. 1981, 50, 375-385.
50. Matthysen, E.; Adriaensen, F.; Dhondt, A.A. Multiple responses to increasing spring temperatures in the breeding cycle of blue and great tits (Cyanistes caeruleus, Parus. major). Glob. Change Biol. 2011, 17, 1-16.
51. Whitehouse, M.J.; Harrison, N.M.; Mackenzie, J.A.; Hinsley, S.A. Preferred habitat of breeding birds may be compromised by climate change: unexpected effects of an exceptionally cold, wet spring. PLoS One 2013, 8, doi:10.1371/journal.pone.0075536.
52. Wilsey, C.B.; Lawler, J.J.; Cimprich, D.A. Performance of habitat suitability models for the endangered black-capped vireo built with remotely-sensed data. Remote Sens. Environ. 2012, 119, 35-42.
53. Broughton, R.K.; Hill, R.A.; Freeman, S.N.; Hinsley, S.A. Describing habitat occupation by wood land birds with territory mapping and remotely sensed data: An example using the Marsh Tit (Poecile palustris). Condor 2012, 114, 812-822.