By Guofan Shao, Keith M. Reynolds
ISBN-10: 1402043058
ISBN-13: 9781402043055
ISBN-10: 1402043872
ISBN-13: 9781402043871
This booklet is the main accomplished and up to date therapy of computing device functions in forestry. it's the first textual content on software program for wooded area administration to stress integration of computing device functions. It additionally deals very important new insights on the way to proceed advancing computational applied sciences in woodland management.
The authors are internationally-recognized gurus within the topics presented.
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A variety of forest models are described in Chapter 6. Modeling approach is also introduced in other chapters. 4 Visualization Visualization is one of the most rapidly advancing of all contemporary computer technologies for forest management. Visualization techniques can be used to display trees, stands, and forested landscapes in virtual environments of 2D or 3D static graphics as well as in 2D, 3D, or 4D animations. Forest visualization can help forest managers better understand habitat disturbance, visual impacts, operational considerations, and overall or specific design features of forest management activities (PFC 2005).
M. R. ). Forecasting Forest Stand Dynamics. Lakehead University, Thunder Bay, Ontario, pp. 42-61. D. Dissertation, University of British Columbia, Canada. , 2000, Growth, yield models for uneven-aged stands: past, present and future, Forest Ecology and Management, 132: 259-279. , 2005, Possibilities of applying GIS in forest ecosystem management, Ekologia-Bratislava 24: 66-79. Population Action International (PAI), 1999, Forest Futures: Population, Consumption and Wood Resources (September 3, 2005).
Thus, Lowell (1998) developed additional spectral tests to exclude shadows and road areas. Pitkänen (2001) compared different approaches for masking the non forested areas of the image, a process which he termed binarization. As one of the simplest methods of tree identification, the local-maxima approach can be applied to relatively coarse-scale imagery, where the pixel size is not much smaller than the size of the individual tree. For example, Wulder et al. 5 meters could be identified. Wulder et al.
Computer Applications in Sustainable Forest Management Including Perspectives on Collaboration and I by Guofan Shao, Keith M. Reynolds
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