Classifying and Evaluating a Shelter Forest Site in a Coastal Area Using Remote Sensing Techniques
Document Type
Article
Publication Date
1991
Digital Object Identifier (DOI)
https://doi.org/10.1080/07038992.1991.10855301
Abstract
The classification of a forest site and the evaluation of site quality are two fundamental problems in afforestation and forest management. The key to solving these problems is to inventory the forest site resources efficiently. Since the traditional site survey approach requires a large effort in terms of human resources and takes a period of a few years, a more efficient method is desirable.
In this paper, Landsat Thematic Mapper data, topographic and stock maps, and other ground information have been applied to the classification and evaluation of a protected forest site at a mud flat coastal section in Dongtai, Jiangsu province, China. A linear mixed discrimination model with quantitative and qualitative variables, called quantitative theory II, and the fuzzy sets theory have been used. The shelter forest site is classified, evaluated, and mapped according to relationships among site types, landscapes, and their corresponding image characteristics. Experimental results obtained from the coastal area are presented and analyzed.
Was this content written or created while at USF?
No
Citation / Publisher Attribution
Canadian Journal of Remote Sensing, v. 17, issue 4, p. 323-331
Scholar Commons Citation
Pu, Ruiliang and Miller, John R., "Classifying and Evaluating a Shelter Forest Site in a Coastal Area Using Remote Sensing Techniques" (1991). School of Geosciences Faculty and Staff Publications. 414.
https://digitalcommons.usf.edu/geo_facpub/414
