Arboriculture & Urban Forestry 42(6): November 2016 The last issue in studies on urban forest is related to tree crown delineation and tree count- ing. One of the main aspects of urban manage- ment is to determine the precise number of urban natural and planted trees. Studies have been con- ducted to perform tree crown delineation and tree counting in urban environments. The common methods used to achieve this purpose include the use of LiDAR data and WorldView-2 imaging. Although both techniques have shown acceptable results, WorldView-2 is more applicable because it is more economical and uses spectral, spatial, textural, and color information. These studies have enabled tree crown delineation to be done automatically, but tree counting is still a manual process. Thus, tree counting has to be performed semi-automatically and manually despite the fact that this process is time-consuming and expensive. As remote-sensing techniques have been proven to detect and monitor urban forests, studies on remote sensing have gained increas- ing interest. Nonetheless, the work in this field remains limited, particularly in tropical areas. In conclusion, further studies on remote sens- ing in urban forests recommend to focus on the following: develop a vegetation index with an urban target, develop a high-accuracy algorithm to distinguish urban tree species automatically via high-resolution multispectral imaging, and develop a method for automatic tree counting. Acknowledgments. The authors would like to thank the Minis- try of Education (MOE) Malaysia and Universiti Putra Malaysia (UPM) for providing research grants through the Fundamental Research Grant Scheme (FRGS) and Research University Grant Scheme (RUGS). In addition, the anonymous reviewer comments helped to improve this manuscript and are highly appreciated. LITERATURE CITED Abowd, G.D., A.K. Dey, P.J. Brown, N. Davies, M. Smith, and P. Steggles. 1999. Towards a better understanding of context and context-awareness. pp. 304–307. Proceedings of the First Inter- national Symposium on Handheld and Ubiquitous Computing. Springer-Verlag, London, UK. Adeline, K.R.M., X. Briottet, N. Paparoditis, and J.P. Gastellu- Etchegorry. 2013. Material reflectance retrieval in urban tree shadows with physics-based empirical atmospheric correction. IEEE Urban Remote Sensing Event (JURSE), São Paulo, Brazil, 21–23 April. pp. 279–283. Akamphon, S., and K. Akamphon. 2014. Cost and benefit tradeoffs in using a shade tree for residential building energy saving. The international journal published by the Thai Society of Higher Education Institutes on Environment 7:19–24. 409 Andersen, H.E., S.E. Reutebuch, and G.F. Schreuder. 2001. Auto- mated individual tree measurement through morphological analysis of a LiDAR-based canopy surface model. First Interna- tional Precision Forestry Symposium, Seattle, Washington, U.S. pp. 11–22. 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Multiple attributes decision making for individual tree detec- tion using high-resolution laser scanning. Forest Ecology and Management 258:2501–2510. ©2016 International Society of Arboriculture
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