DocumentCode :
182987
Title :
Land-use classification of Zhanghe river basin using the maximum likelihood and decision tree method
Author :
Hao Wang ; Hongrui Zhao ; Wanqing Li
Author_Institution :
Dept. of Civil Eng., Tsinghua Univ., Beijing, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
322
Lastpage :
327
Abstract :
For Zhanghe areas, we utilized the Landsat5 TM images of 2010 to complete the region´s land use classification based on the maximum likelihood method. Analyzing the constraints of land use classification in the research area, our classification method includes 4 aspects: cloud and hillshade were classified at first and then reprocessed separately; water body was classified combining supervised classification and interactive interpretation; cities and villages were distinguished based on prior knowledge; the slope hierarchy of arable land was accomplished by slope of the study area based on decision tree. 67% of regions of interest (ROIs) were randomly selected for sample training, while the rest 33% of ROIs participated in confusion matrix validation. The experiment shows that the classification accuracy is 91.50% and the Kappa coefficient is 0.8587.
Keywords :
decision trees; geophysical image processing; image classification; land use; maximum likelihood estimation; rivers; Kappa coefficient; Landsat5 TM images; ROI; Zhanghe areas; Zhanghe river basin; arable land slope hierarchy; cloud classification; confusion matrix validation; decision tree method; hillshade classification; interactive interpretation; land-use classification; maximum likelihood method; region land use classification; regions of interest; supervised classification; water body classification; Accuracy; Cities and towns; Decision trees; Earth; Remote sensing; Rivers; Satellites; decision tree; land use classification; maximum likelihood method; post classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5147-5
Type :
conf
DOI :
10.1109/FSKD.2014.6980854
Filename :
6980854
Link To Document :
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