AN ADAPTIVE FUZZY RULE CLASSIFIER APPLIED TO LANDCOVER CLASSIFICATION OF TM

doi:10.6046/gtzyyg.2000.01.09

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Abstract

Based on self-organizing network and fuzzy logic reasoning, this paper discusses an adaptive fuzzy rule classifier for landcover classification. The fuzzy rules can be extracted from the nodes and weight vector of network which can adjust the node numbers (rule number accordingly) and weight vector. This classifier finished TMlandcover by fuzzy logic reasoning, and the unclassified pixels increase K adaptively to be classified; It improved 2.7% and 2.9% in overall accuracy and Kapp coefficient compared with MLC, deceased 1% in Kapp coefficient and no change in overall accuracy compared with self-organizing network. How to extract and express the non-spectral knowledge dissolved class confusion, is the key step to improve the classification.

Keywords Atmospheric water vapor Spatial heterogeneity Land surface temperature Error

Issue Date: 02 August 2011

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	CHEN Feng
	XIONG Yong-Zhu
	HUANG Shao-Peng
	YE Hong
	XIE Shun-sheng
	CAI Shui-ku
	WU xiao-jie

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CHEN Feng,XIONG Yong-Zhu,HUANG Shao-Peng, et al. AN ADAPTIVE FUZZY RULE CLASSIFIER APPLIED TO LANDCOVER CLASSIFICATION OF TM[J]. REMOTE SENSING FOR LAND & RESOURCES, 2000, 12(1): 44-50，56.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2000.01.09 OR https://www.gtzyyg.com/EN/Y2000/V12/I1/44

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