Employing measures of heterogeneity and an object-based approach to extrapolate tree species distribution data

Diversity

Volumn 6, Issue 3, 2014, Pages 396-414

  Jones, Trevor G ^a   Coops, Nicholas C ^a   Gergel, Sarah E ^a   Sharma, Tara ^b  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b PARKS CANADA   (Canada)

Author keywords

Extrapolation; Heterogeneity; Hyperspectral; Landsat; LiDAR; Object based; Segmentation

Indexed keywords

FOREST ECOSYSTEM; HETEROGENEITY; IMAGE ANALYSIS; LANDSAT; LIDAR; REMOTE SENSING; SEGMENTATION; SPATIAL DATA; SPATIAL DISTRIBUTION; SPATIAL RESOLUTION; SPECIES DIVERSITY; SPECIES RICHNESS; SPECTRAL ANALYSIS; TREE;

EID: 84906914204     PISSN: None     EISSN: 14242818     Source Type: Journal    
DOI: 10.3390/d6030396     Document Type: Article

References (31)

1. Cohen, W.B.; Goward, S.N. Landsat's role in ecological applications of remote sensing. Bioscience 2004, 54, 535-545.
2. Woodcock, C.E.; Allen, R.; Anderson, M.; Belward, A.; Bindschadler, R.; Cohen, W.; Gao, F.; Goward, S.N.; Helder, D.; Helmer, E.; et al. Free Access to Landsat Imagery. Science 2008, 320, 1011.
3. Huang, C.; Asner, G.P. Applications of Remote Sensing to Alien Invasive Plant Studies. Sensors 2009, 9, 4869-4889.
4. Thompson, S.D.; Gergel, S.E. Conservation implications of mapping rare ecosystems using high spatial resolution imagery: Recommendations for heterogeneous and fragmented landscapes. Landsc. Ecol. 2008, 23, 1023-1037.
5. Hill, R.A.; Smith, G.N. Land cover heterogeneity in Great Britain as identified in Land Cover Map 2000. Int. J. Rem. Sens. 2005, 26, 5467-5473.
6. Lindenmayer, D.B.; Franklin, J.F.; Fischer, J. General management principles and a checklist of strategies to guide forest biodiversity conservation. Biol. Conserv. 2006, 131, 433-445.
7. Morgan, J.L.; Gergel, S.E. Quantifying historic landscape heterogeneity from aerial photographs using object-based analysis. Landsc. Ecol. 2010, 25, 985-998.
8. Castilla, G.; Hay, G.J. Image objects and geographic objects. In Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications Series; Blaschke, T., Lang, S., Hay, G., Eds.; Springer-Verlag: Berlin, Germany, 2008; pp. 91-110.
9. Hay, G.J.; Castilla, G. Geographic object-based image analysis (GEOBIA): A new name for a new discipline. In Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications Series; Blaschke, T., Lang, S., Hay, G., Eds.; Springer-Verlag: Berlin, Germany, 2008; pp. 75-89.
10. Chubey, M.S.; Franklin, S.E.; Wulder, M.A. Object-based analysis of Ikonos-2 imagery for extraction of forest inventory parameters. Rem. Sens. Environ. 2006, 72, 383-394.
11. Wulder, M.A.; White, J.C.; Hay, G.J.; Castilla, G. Pixels to objects to information: Spatial context in forest characterization with remote sensing. In Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications Series; Blaschke, T., Lang, S., Hay, G., Eds.; Springer-Verlag: Berlin, Germany, 2008; pp. 345-363.
12. Definiens Developer 7 User Guide. Definiens: Munchen, Germany, 2010.
13. Wulder, M.A.; Seemann, D. Forest inventory height update through the integration of LiDAR data with segmented Landsat imagery. Can. J. Rem. Sens. 2003, 29, 536-543.
14. British Columbian Ministry Of Forests and Range. Biogeoclimactic Zones of British Columbia. Available online: http://www.for.gov.bc.ca (accessed on 1 January 2012).
15. British Columbia Conservation Data Centre. Available online: http://a100.gov.bc.ca/pub/eswp/ (accessed on 1 January 2012).
16. Green, R.N. Terrestrial Ecosystem Mapping of the Southern Gulf Islands; B.A. Blackwell and Associates Ltd.: North Vancouver, BC, Canada 2007.
17. Jones, T.G.; Coops, N.C.; Sharma, T. Assessing the utility of airborne hyperspectral and LiDAR data for species distribution mapping in the coastal Pacific Northwest. Rem. Sens. Environ. 2010, 114, 2841-2852.
18. Chavez, P.S. Image-based atmospheric corrections: Revisited and improved. Photogramm. Eng. Rem. Sens. 1996, 62, 1025-1036.
19. Breiman, L.; Friedman, J.; Stone, C.J.; Olshen, R.A. Classification and Regression Trees; Wadsworth: Belmont, California, USA, 1984.
20. Steinberg, D.; Colla, P. CART: Tree-Structured Non-Parametric Data Analysis; Salford Systems: San Diego, CA, USA, 1995; pp. 336.
21. Bater, C.W.; Coops, N.C. Evaluating error associated with lidar-derived DEM interpolation. Comput. Geosci. 2009, 35, 289-300.
22. Breiman, L.; Friedman, J.; Stone, C.J.; Olshen, R.A. Classification and Regression Trees; Chapman and Hall: London, UK, 1998.
23. Venables, W.N.; Ripley, B.D. Modern Applied Statistics with S; Springer-Verlag: New York, NY, USA, 2002.
24. Yu, Q.; Gong, P.; Clinton, N.; Biging, G.; Kelly, M.; Schirokauer, D. Object based detailed vegetation classification with airborne high spatial resolution remote sensing imagery. Photogramm. Eng. Rem. Sens. 2006, 72, 799-811.
25. Smith, G.M. The development of integrated object-based analysis of EO data within UK national land cover products. In Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications Series; Blaschke, T., Lang, S., Hay, G., Eds.; Springer-Verlag: Berlin, Germany, 2008; pp. 513-528.
26. Sinclair, T.R.; Hoffer, R.M.; Schreiber, M.M. Reflectance and internal structure of leaves from several crops during a growing season. Agro. J. 1971, 63, 864-868.
27. Kumar, L.; Schmidt, K.; Dury, S.; Skidmore, A. Imaging spectrometry in vegetation science. In Imaging Spectroscopy: Basic Principles and Prospective Applications; Van der Meer, F.D., de Jong, S.M., Eds.; Springer Publishers: Dordrecht, Netherlands, 2006; pp. 111-155.
28. Van der Meer, F.D. 2006. Basic principles of spectrometry. In Imaging Spectroscopy: Basic Principles and Prospective Applications; Van der Meer, F.D., de Jong, S.M., Eds.; Springer Publishers: Dordrecht, Netherlands, 2006; pp. 3-16.
29. Jones, T.G.; Coops, N.C.; Sharma, T. Exploring the utility of hyperspectral imagery and LiDAR data for predicting Quercus garryana ecosystem distribution and aiding in habitat restoration. Restor. Ecol. 2011, 19, 245-256.
30. Jones, T.G.; Coops, N.C.; Sharma, T. Assessing the utility of airborne hyperspectral and LiDAR data for species distribution mapping in the coastal Pacific Northwest, Canada. Rem. Sens. Environ. 2010, 114, 2841-2852.
31. Wulder, M.A.; Bater, C.W.; Coops, N.C.; Hilker, T.; White, J.C. The role of LiDAR in sustainable forest management. Forest. Chron. 2008, 84, 1-19.