A comparison of mangrove Canopy height using multiple independent measurements from land, air, and space

Remote Sensing

Volumn 8, Issue 4, 2016, Pages

  Lagomasino, David ^a,b   Fatoyinbo, Temilola ^b   Lee, SeungKuk ^b   Feliciano, Emanuelle ^b   Trettin, Carl ^c   Simard, Marc ^d  

^a UNIVERSITIES SPACE RESEARCH ASSOCIATION   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

^c USDA FOREST SERVICE   (United States)

^d CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Africa; Biomass; Blue carbon; Canopy height; DSM; H100; MRV; TDX; VHR

Indexed keywords

BIOMASS; CARBON; DEFORESTATION; OPTICAL RADAR;

AFRICA; CANOPY HEIGHTS; H100; INDEPENDENT MEASUREMENT; REMOTELY SENSED IMAGERY; SHUTTLE RADAR TOPOGRAPHY MISSION; VERIFICATION ACTIVITIES; VERIFICATION PROTOCOL;

ECOSYSTEMS;

EID: 84971616822     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs8040327     Document Type: Article

References (54)

1. Donato, D.C.; Kauffman, J.B.; Murdiyarso, D.; Kurnianto, S.; Stidham, M.; Kanninen, M. Mangroves among the most carbon-rich forests in the tropics. Nat. Geosci. 2011, 4, 293-297.
2. Siikamäki, J.; Sanchirico, J.N.; Jardine, S.L. Global economic potential for reducing carbon dioxide emissions from mangrove loss. Proc. Natl. Acad. Sci. USA 2012, 109, 14369-14374.
3. Murray, B.C.; Pendleton, L.; Jenkins, W.A.; Sifleet, S. Green Payments for Blue Carbon: Economic Incentives for Protecting Threatened Coastal Habitats; Nicholas Institute for Environmental Policy Solutions Report NI R 11-04; Duke University: Durham, NC, USA, 2011.
4. Alongi, D.M. Carbon cycling and storage in mangrove forests. Ann. Rev. Mar. Sci. 2014, 6, 195-219.
5. Alongi, D.M. Present state and future of the world's mangrove forests. Environ. Conserv. 2002, 29, 331-349.
6. Saatchi, S.S.; Harris, N.L.; Brown, S.; Lefsky, M.; Mitchard, E.T.A.; Salas, W.; Zutta, B.R.; Buermann, W.; Lewis, S.L.; Hagen, S. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl. Acad. Sci. USA 2011, 108, 9899-9904.
7. Baccini, A.; Goetz, S.J.; Walker, W.S.; Laporte, N.T.; Sun, M.; Sulla-Menashe, D.; Hackler, J.; Beck, P.S.A.; Dubayah, R.; Friedl, M.A. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Clim. Chang. 2012, 2, 182-185.
8. Hunter, M.O.; Keller, M.; Victoria, D.; Morton, D.C. Tree height and tropical forest biomass estimation. Biogeosciences 2013, 10, 8385-8399.
9. Gullison, R.E.; Frumhoff, P.C.; Canadell, J.G.; Field, C.B.; Nepstad, D.C.; Hayhoe, K.; Avissar, R.; Curran, L.M.; Friedlingstein, P.; Jones, C.D. Tropical forests and climate policy. Science 2007, 316, 985-986.
10. Pendleton, L.; Donato, D.C.; Murray, B.C.; Crooks, S.; Jenkins, W.A.; Sifleet, S.; Craft, C.; Fourqurean, J.W.; Kauffman, J.B.; Marbà, N.; et al. Estimating global "blue carbon" emissions from conversion and degradation of vegetated coastal ecosystems. PLoS ONE 2012, 7, e43542.
11. Simard, M.; Rivera-Monroy, V.H.; Mancera-Pineda, J.E.; Castañeda-Moya, E.; Twilley, R.R. A systematic method for 3D mapping of mangrove forests based on Shuttle Radar Topography Mission elevation data, ICEsat/GLAS waveforms and field data: Application to Ciénaga Grande de Santa Marta, Colombia. Remote Sens. Environ. 2008, 112, 2131-2144.
12. Fatoyinbo, T.E.; Simard, M. Height and biomass of mangroves in Africa from ICESat/GLAS and SRTM. Int. J. Remote Sens. 2013, 34, 668-681.
13. Lee, S.K.; Fatoyinbo, T.E. TanDEM-X Pol-InSAR inversion for mangrove canopy height estimation. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015, 8, 3608-3618.
14. Lagomasino, D.; Fatoyinbo, T.; Lee, S.; Simard, M. High-resolution forest canopy height estimation in an African blue carbon ecosystem. Remote Sens. Ecol. Conserv. 2015, 1, 51-60.
15. Saenger, P.; Snedaker, S.C. Pantropical trends in mangrove above-ground biomass and annual litterfall. Oecologia 1993, 96, 293-299.
16. Fatoyinbo, T.E.; Simard, M.; Washington-Allen, R.A.; Shugart, H.H. Landscape-scale extent, height, biomass, and carbon estimation of Mozambique's mangrove forests with Landsat ETM+ and Shuttle Radar Topography Mission elevation data. J. Geophys. Res. Biogeosci. 2008, 113, G02S06.
17. Cook, B.D.; Nelson, R.F.; Middleton, E.M.; Morton, D.C.; McCorkel, J.T.; Masek, J.G.; Ranson, K.J.; Ly, V.; Montesano, P.M. NASA Goddard's lidar, hyperspectral and thermal (G-LiHT) airborne imager. Remote Sens. 2013, 5, 4045-4066.
18. Hyyppä, J.; Hyyppä, H.; Litkey, P.; Yu, X.; Haggrén, H.; Rönnholm, P.; Pyysalo, U.; Pitkänen, J.; Maltamo, M. Algorithms and methods of airborne laser scanning for forest measurements. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2004, 36, 82-89.
19. Clark, M.L.; Clark, D.B.; Roberts, D.A. Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape. Remote Sens. Environ. 2004, 91, 68-89.
20. Lee, S.-K.; Fatoyinbo, T.; Osmanoglu, B.; Sun, G. Polarimetric SAR interferometry evaluation in mangroves. In Proceedings of the 2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, QC, Canada, 13-18 July 2014; pp. 4584-4587.
21. Montesano, P.; Sun, G.; Dubayah, R.; Ranson, K. The uncertainty of plot-scale forest height estimates from complementary spaceborne observations in the taiga-tundra ecotone. Remote Sens. 2014, 6, 10070-10088.
22. Neigh, C.S.R.; Masek, J.G.; Bourget, P.; Cook, B.; Huang, C.; Rishmawi, K.; Zhao, F. Deciphering the precision of stereo IKONOS canopy height models for US forests with G-LiHT airborne lidar. Remote Sens. 2014, 6, 1762-1782.
23. Cloude, S.R.; Papathanassiou, K.P. Polarimetric SAR interferometry. IEEE Trans. Geosci. Remote Sens. 1998, 36, 1551-1565.
24. Bento, C.M.; Beilfuss, R.D.; Hockey, P.A.R. Distribution, structure and simulation modelling of the Wattled Crane population in the Marromeu Complex of the Zambezi Delta, Mozambique. Ostrich J. Afr. Ornithol. 2007, 78, 185-193.
25. Tweddle, D. Lower Zambezi. 2013. Available online: http://www.feow.org/ecoregions/details/lower_Zambezi (accessed on 12 December 2014).
26. Beilfuss, R. Modelling trade-offs between hydropower generation and environmental flow scenarios: A case study of the Lower Zambezi River Basin, Mozambique. Int. J. River Basin Manag. 2010, 8, 331-347.
27. Ronco, P.; Fasolato, G.; Nones, M.; Di Silvio, G. Morphological effects of damming on Lower Zambezi River. Geomorphology 2010, 115, 43-55.
28. Beilfuss, R.; Brown, C. Assessing environmental flow requirements and trade-offs for the Lower Zambezi River and Delta, Mozambique. Int. J. River Basin Manag. 2010, 8, 127-138.
29. Timberlake, J. Biodiversity of the Zambezi Basin; Biodiversity Foundation for Africa: Bulawayo, Zimbabwe, 2000.
30. Stringer, C.E.; Trettin, C.C.; Zarnoch, S.J.; Tang, W. Carbon stocks of mangroves within the Zambezi River Delta, Mozambique. For. Ecol. Manag. 2015, 354, 139-148.
31. Feliciano, E.A. Multi-Scale Remote Sensing Assessments of Forested Wetlands: Applications to the Everglades National Park. Ph. D. Thesis, University of Miami, Miami, FL, USA, 2015.
32. Pavlis, N.K.; Holmes, S.A.; Kenyon, S.C.; Factor, J.K. The development and evaluation of the Earth Gravitational Model 2008 (EGM2008). J. Geophys. Res. Solid Earth 2012, 117.
33. Krieger, G.; Moreira, A.; Fiedler, H.; Hajnsek, I.; Werner, M.; Younis, M.; Zink, M. TanDEM-X: A satellite formation for high-resolution SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2007, 45, 3317-3341.
34. Lee, S.-K.; Kugler, F.; Papathanassiou, K.P.; Hajnsek, I. Quantification of temporal decorrelation effects at L-band for polarimetric SAR interferometry applications. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2013, 6, 1351-1367.
35. Kugler, F.; Schulze, D.; Hajnsek, I.; Pretzsch, H.; Papathanassiou, K.P. TanDEM-X Pol-InSAR performance for forest height estimation. IEEE Trans. Geosci. Remote Sens. 2014, 52, 6404-6422.
36. Neigh, C.S.R.; Masek, J.G.; Nickeson, J.E. High-resolution satellite data open for government research. Eos Trans. Am. Geophys. Union 2013, 94, 121-123.
37. Moratto, Z.M.; Broxton, M.J.; Beyer, R.A.; Lundy, M.; Husmann, K. Ames Stereo Pipeline, NASA's open source automated stereogrammetry software. In Proceedings of the Lunar and Planetary Science Conference, Woodlands, Singapore, 1-5 March 2010; Volume 41, p. 2364.
38. Ni, W.; Ranson, K.J.; Zhang, Z.; Sun, G. Features of point clouds synthesized from multi-view ALOS/PRISM data and comparisons with lidar data in forested areas. Remote Sens. Environ. 2014, 149, 47-57.
39. Hobi, M.L.; Ginzler, C. Accuracy assessment of digital surface models based onWorldView-2 and ADS80 stereo remote sensing data. Sensors 2012, 12, 6347-6368.
40. Giri, C.; Ochieng, E.; Tieszen, L.L.; Zhu, Z.; Singh, A.; Loveland, T.; Masek, J.; Duke, N. Status and distribution of mangrove forests of the world using earth observation satellite data. Glob. Ecol. Biogeogr. 2011, 20, 154-159.
41. Hajnsek, I.; Kugler, F.; Lee, S.-K.; Papathanassiou, K.P. Tropical-forest-parameter estimation by means of Pol-InSAR: The INDREX-II campaign. IEEE Trans. Geosci. Remote Sens. 2009, 47, 481-493.
42. McCuen, R.H.; Knight, Z.; Cutter, A.G. Evaluation of the Nash-Sutcliffe efficiency index. J. Hydrol. Eng. 2006, 11, 597-602.
43. Sexton, J.O.; Bax, T.; Siqueira, P.; Swenson, J.J.; Hensley, S. A comparison of lidar, radar, and field measurements of canopy height in pine and hardwood forests of southeastern North America. For. Ecol. Manag. 2009, 257, 1136-1147.
44. Bourgine, B.; Baghdadi, N. Assessment of C-band SRTM DEM in a dense equatorial forest zone. Comptes Rendus Geosci. 2005, 337, 1225-1234.
45. Fitchett, J.M.; Grab, S.W. A 66-year tropical cyclone record for south-east Africa: Temporal trends in a global context. Int. J. Climatol. 2014, 34, 3604-3615.
46. Smith, T.J.; Anderson, G.H.; Balentine, K.; Tiling, G.; Ward, G.A.; Whelan, K.R.T. Cumulative impacts of hurricanes on Florida mangrove ecosystems: Sediment deposition, storm surges and vegetation. Wetlands 2009, 29, 24-34.
47. Kugler, F.; Lee, S.-K.; Hajnsek, I.; Papathanassiou, K.P. Forest height estimation by means of Pol-InSAR data inversion: The role of the vertical wavenumber. IEEE Trans. Geosci. Remote Sens. 2015, 53, 5294-5311.
48. Jimenez, J.A.; Lugo, A.E.; Cintron, G. Tree mortality in mangrove forests. Biotropica 1985, 17, 177-185.
49. Putz, F.E.; Chan, H.T. Tree growth, dynamics, and productivity in a mature mangrove forest in Malaysia. For. Ecol. Manag. 1986, 17, 211-230.
50. Kellner, J.R.; Clark, D.B.; Hubbell, S.P. Pervasive canopy dynamics produce short-term stability in a tropical rain forest landscape. Ecol. Lett. 2009, 12, 155-164.
51. Lagomasino, D.; Price, R.M.; Whitman, D.; Melesse, A.; Oberbauer, S.F. Spatial and temporal variability in spectral-based surface energy evapotranspiration measured from Landsat 5TM across two mangrove ecotones. Agric. For. Meteorol. 2015, 213, 304-316.
52. Lagomasino, D.; Price, R.M.; Whitman, D.; Campbell, P.K.E.; Melesse, A. Estimating major ion and nutrient concentrations in mangrove estuaries in Everglades National Park using leaf and satellite reflectance. Remote Sens. Environ. 2014, 154, 202-218.
53. 2 eddy covariance. Biogeosciences 2013, 10, 2145-2158.
54. Shapiro, A.C.; Trettin, C.C.; Küchly, H.; Alavinapanah, S.; Bandeira, S. The Mangroves of the Zambezi Delta: Increase in Extent Observed via Satellite from 1994 to 2013. Remote Sens. 2015, 7, 16504-16518.