Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4, 21-28, 2014
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-4/21/2014/
doi:10.5194/isprsarchives-XL-4-21-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
23 Apr 2014
Comparison of Qinzhou bay wetland landscape information extraction by three methods
X. Chang1, Q. Zhang2, M. Luo1, and C. Dong1 1Land and Resources College, China West Normal University, Sichuan Nanchong, China
2Qingzhou University , Guangxi Qinzhou, China
Keywords: Coastal wetland extraction; Supervised Classification; Decision Trees; Bject-oriented; Qingzhou Bay Abstract. Wetland ecosystem plays an important role on the environment and sustainable socio-economic development. Based on the TM images in 2010 with a pretreament of Tasseled Cap transformation, three different methods are used to extract the Qinzhou Bay coastal wetlands using Supervised Classification (SC), Decision Trees (DT) and Object -oriented (OO) methods. Firstly coastal wetlands are picked out by artificial visual interpretation as discriminant standard. The result shows that when the same evaluation template used, the accuracy and Kappa coefficient of SC, DT and OO are 92.00 %, 0.8952; 89.00 %, 0.8582; 91.00 %, 0.8848 respectively. The total area of coastal wetland is 218.3 km2 by artificial visual interpretation, and the extracted wetland area of SC, DT and OO is 219 km2, 193.70 km2, 217.40 km2 respectively. The result indicates that SC is in the f irst place, followed by OO approach, and the third DT method when used to extract Qingzhou Bay coastal wetland.
Conference paper (PDF, 863 KB)


Citation: Chang, X., Zhang, Q., Luo, M., and Dong, C.: Comparison of Qinzhou bay wetland landscape information extraction by three methods, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4, 21-28, doi:10.5194/isprsarchives-XL-4-21-2014, 2014.

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