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Research on Object-Oriented Land Cover Information Extraction
Mu Fengyun,Luo Dan,Guan Dongjie,Wu Xiaochun
2014, 33(6):
104-108.
DOI: 10.3969/j.issn.1674-0696.2014.06.22
Taken Landsat-5 TM image in Shenyang city, Liaoning province as a data source, ERDAS software was used for supervised classification and eCognition software
for object-oriented classification. Multi-scale segmentation method in object-oriented classification and the nearest neighbor classification were selected to
classify. After classification, the error matrix of supervised classification was calculated to obtain overall accuracy, kappa coefficient, producer accuracy and user
accuracy. The best classification result and classification stability method were selected to assess accuracy in eCognition software. The results were
(supervised classification/object-oriented classification): settlement 91.14%/93.50%, farmland 86.91%/93.80%, forest 91.73%/ 96.70%, grassland 84.44%/91.36%,water
98.16%/96.18%. The result of object-oriented classification method improves the efficiency and accuracy of classification compared to traditional supervised
classification method.
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