Abstract
Savannas are heterogeneous systems characterized by the coexistence of grasses and woody trees. Growing recognition of the importance of the structural component of biodiversity has highlighted the need to understand the spatial distribution and temporal dynamics of woody plant structural diversity. Advances in LiDAR technology have enabled three dimensional information of vegetation to be obtained remotely over large areas. Whilst the use of LiDAR has gained considerable momentum in forested areas there has been limited application to savanna systems. We explore the applicability of LiDAR and object-based image analysis to the monitoring of woody structural diversity in a savanna system. We demonstrate how an object-based approach to image analysis significantly improves the accuracy of woody layer classification form in a heterogeneous landscape. Furthermore we illustrate how standard approaches to LiDAR derived canopy models suffer from interpolation artifacts in savannas, due to the heterogeneity of the woody layer. By integrating LiDAR with high resolution aerial photography, through object-based analysis, these artifacts can be removed to produce a robust canopy model. The object-based integration of LiDAR with aerial imagery holds immense potential for structural diversity monitoring in savannas.
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References
Blaschke T and Strobel J (2001) What’s wrong with pixels? Some recent developments interfacing remote sensing and GIS. GIS - Zeitschrift fur Geoinformationssysteme 6:12-17
Braack L (1997) An objectives hierarchy for the management of the KNP. A revision of parts of the management plan for the Kruger National Park.Volume VII
Dowling R and Accad A (2003) Vegetation classification of the riparian zone along the Brisbane River, Queensland Australia, using light detection and ranging (lidar) data and forward looking digital video. Can. J. Remote Sensing 29:556-563.
Gillson L (2004a) Evidence of hierarchical patch dynamics in an East African savanna? Landscape Ecology 19:883-894.
Gillson L (2004b) Testing non-equilibrium theories in savannas: 1400 years of vegetation change in Tsavo National Park, Kenya. Ecological Complexity 1:281-298
Laliberte AS, Rango A, Harvstad KM, Paris JF, Beck RF, McNeely R, Gonzalez AL (2004) Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico. Remote Sensing of Environment 93:198-210
Lefsky MA, Cohen BW, Parker GG, Harding DJ (2002) Lidar remote sensing for ecosystem studies. Bioscience 52:19-30
Lovell JL, Jupp DLB, Culvenor DS and Coops NC (2003. Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests. Canadian Journal of Remote Sensing 29:607-622.
Maier B, Tiede D, Dorren L (2006) Assessing mountain forest structure using airborne laser scanning and landscape metrics. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI-4/C42
Menges CH, Van Zyl JJ, Ahmad W and Hill GJE (1999) Classification of vegetation communities in the tropical savannas of northern Australia using AirSAR data. Pacific Rim AIRSAR Significant Results and Planning Workshop, Maui, Hawaii, 24-26 August
Noss RF (1990) Indicators for monitoring biodiversity: A hierarchical approach. Conservation Biology 4:355-364
Pickett STA, Cadenasso ML, Benning TL (2003) Biotic and Abiotic Variability as Key Determinants of Savanna Heterogeneity at Multiple Spatiotemporal Scales. In: du Toit JT, Rogers KH, Biggs H (ed) The Kruger Experience: Ecology and Management of Savanna Heterogeneity. Island Press, Washington, DC,pp 23-40
Rogers KH (2003) Adopting a heterogeneity paradigm: Implications for management of protected savannas. In: du Toit JT, Rogers KH, Biggs H (ed) The Kruger Experience: Ecology and Management of Savanna Heterogeneity. Island Press, Washington, DC,pp 41-58
Sankaran M, Hanan NP, Scholes RJ, Ratnam J, Augustine DJ, Cade BS, Gignoux J, Higgins SI, Le Roux X, Ludwig F, Ardo J, Banyikwa F, Bronn A, Bucini G, Caylor KK, Coughenour MB, Diouf A, Ekaya W, Feral CJ, February EC, Frost PGH, Hiernaux P, Hrabar H, Metzger KL, Prins HHT, Ringrose S, Sea W, Tews J, Worden J, Zambatis N (2005) Determinants of woody cover in African savannas. Nature 438:846-849
Scholes RJ and Walker BH (1993) An African savanna: a synthesis of the Nylsvley study. Cambridge University Press
Tiede D, Lang S, Hoffmann C (2006) Supervised and forest type-specific multi-scale segmentation for a one-level-representation of single trees. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. No. XXXVI-4/C42
Turner MG (1989) Landscape Ecology: The effect of pattern on process. Ann. Rev. Ecol. Syst. 20:171-197
Waring RH, Way J, Hunt ER Jr, Morrissey L, Ranson KJ, Weishampel JF, Oren R and Franklin SE (1995) Imaging radar for ecosystem studies. BioScience 45: 715-723
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Levick, S., Rogers, K. (2008). Structural biodiversity monitoring in savanna ecosystems: Integrating LiDAR and high resolution imagery through object-based image analysis. In: Blaschke, T., Lang, S., Hay, G.J. (eds) Object-Based Image Analysis. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77058-9_26
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DOI: https://doi.org/10.1007/978-3-540-77058-9_26
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