Research on Object-oriented Classification of Agricultural Land Based on High Resolution Images

doi:10.6046/gtzyyg.2010.04.24

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Abstract

This paper has explored the method and scheme for classifying different kinds of agricultural land from the high resolution remote sensing images by using multi-scale segmentation technology and rule-based image analysis approaches. Firstly, optimal segmentation scale was examined to construct a multi-scale segmentation level network according to the size of objects. Secondly, on the basis of spectrum, shape, texture and topology characteristics of images, several features of NDVI, shape indices, brightness, mean spectral value of red band, and ratio of near-infrared band, the standard deviation of near-infrared band and homogeneity were selected to classify objects into four agricultural land categories. The results show that these characteristics are effective in identifying agricultural land type and that the precision is higher than that of the traditional maximum likelihood classification.

Keywords GPS Cadastration controlling network Precision analysis Height fitting

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	TP 79

Issue Date: 02 August 2011

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	GAO Wei
	QI Jian-guo

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GAO Wei,QI Jian-guo. Research on Object-oriented Classification of Agricultural Land Based on High Resolution Images[J]. REMOTE SENSING FOR LAND & RESOURCES, 2010, 22(4): 117-121.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2010.04.24 OR https://www.gtzyyg.com/EN/Y2010/V22/I4/117

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