Contrast Analysis of Supervised Classification and Decision Tree Method to Extract the Qinzhou Bay Wetland

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Chinese Agricultural Science Bulletin ›› 2014, Vol. 30 ›› Issue (32) : 295-300. DOI: 10.11924/j.issn.1000-6850.2014-0726

Contrast Analysis of Supervised Classification and Decision Tree Method to Extract the Qinzhou Bay Wetland

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Abstract

Wetland ecosystem played an important role in the environment and sustainable socio-economic development. Based on the TM images in 2010 with a pretreatment of Tasseled Cap transformation, two different methods are used to extract the Qinzhou Bay coastal wetlands: Supervised Classification (SC) and Decision Trees (DT). Coastal wetlands were picked out by artificial visual interpretation as discriminant standard. The result showed that when the same evaluation template was used, the accuracy and Kappa coefficient of SC, DT was 92.00%, 0.8952 and 89.00%, 0.8582 respectively. The total area of coastal wetland was 218.3 km2 by artificial visual interpretation, and the extracted wetland area of SC, DT was 219 km2 and 193.70 km2 respectively. The result indicated that, for Qinzhou bay coastal wetland information extraction, the effect of the Supervised Classification (SC) was better than the Decision Tree (DT).

Key words

coastal wetland extraction; Supervised Classification; Decision Trees; Qinzhou Bay

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Contrast Analysis of Supervised Classification and Decision Tree Method to Extract the Qinzhou Bay Wetland. Chinese Agricultural Science Bulletin. 2014, 30(32): 295-300 https://doi.org/10.11924/j.issn.1000-6850.2014-0726

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