Identification of hyperspectral features for subalpine typical vegetation in the upper reaches of the Minjiang River

doi:10.6046/gtzyyg.2016.03.27

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Abstract

Spectral characteristics analysis is the basis of spectral feature classification and matching in hyperspectral image processing. In this paper, the authors selected five kinds of subalpine forest vegetation to measure their field spectra in the upper reaches of the Minjiang River, which include gramineae mottled bamboo, herbaceous fern,pilea notate, arbor china fir and shrubs palm. Through constructing the high spectral similarity measure index, five measuring methods, i.e., Euclidean distance(ED), spectral angle mapper(SAM), spectral information divergence(SID), spectral information divergence-spectral angle mapper(SID(TAN))and spectral distance based on Douglas-Peucker(SDDP), were used to analyze the relative capability for recognizing forest vegetation on the plateau. According to the results obtained, the spectral feature difference in the five kinds of forest vegetation mainly lies in peaks and troughs in the spectral curves; pilea notate has the highest relative spectral discriminatory probability in ED similarity measurement; mottled bamboo and fern have the highest relative spectral discriminatory probability in SID and SID(TAN); China fir has the highest relative spectral discriminatory probability in SDDP. SAM, SDDP, ED, SID(TAN)and SID of the relative spectral discriminatory entropy are 1.51, 1.59, 1.61, 2.16 and 2.18 respectively. The research results showed that the means reduced the amount of calculation for doing the similarity measurement which extracted the spectral feature vectors with the SFT, DPBSR and DABSR, DPSR. In order to ensure the condition of similar recognition capability, the means can greatly improve the retrieval efficiency of the program, and hence they are the fast and efficient hyperspectral feature matching and retrieval methods.

Keywords mask remote sensing cloud-cloud shadow decision tree(DT)classifier random forests(RF) classifier

TP751.1

Issue Date: 01 July 2016

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	LU Fengling
	GONG Zaiwu

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LU Fengling,GONG Zaiwu. Identification of hyperspectral features for subalpine typical vegetation in the upper reaches of the Minjiang River[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 174-180.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.03.27 OR https://www.gtzyyg.com/EN/Y2016/V28/I3/174

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