ANALYSE TO SPECTRAL CHARACTER OF THE VEGETATION ALONG YANHE RIVER

doi:10.6046/gtzyyg.2001.03.04

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Abstract

This paper introducs the spectral character of main vegetations along Yanhe river, which are determined by the contents of many materials within vegetations, such as chlorophyll, carotenoids, nitrogen, lignin and cellulose. The spectra are also affected by many factors, like Leaf Area Index, sun's position, atmosphere condition, background character, observation geometry and growthing period of vegetations.

Keywords Chaohu Lake sedimentation Evolution trend Remote sensing monitoring

Issue Date: 02 August 2011

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	YANG Ze-Dong
	CHEN You-Ming
	LIU Tong-Qing
	WANG Bai-Yan
	HUANG Yan
	YANG Yang

Cite this article:

YANG Ze-Dong,CHEN You-Ming,LIU Tong-Qing, et al. ANALYSE TO SPECTRAL CHARACTER OF THE VEGETATION ALONG YANHE RIVER[J]. REMOTE SENSING FOR LAND & RESOURCES, 2001, 13(3): 15-20.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2001.03.04 OR https://www.gtzyyg.com/EN/Y2001/V13/I3/15

[1] Clark R N, King T V, Ager C, Swayze G A. Vegetation Species and Stress Indicator Mapping in the San Luis Valley, Colorado using Imaging Spectrometer data［J］. Remote Sensing of Environment, 1997.

[2] Rencz A. Manual of Remote Sensing, Chapter 1［M］. New York: John Wiley and Sons, Inc., 1999.

[3] Blackburn G A. Spectral indices for estimating photosynthetic pigment concentration: a test using senscent tree leaves［J］. INT.J.Remote Sensing. 1998, 19(4):657-675.

[4] Bolster K L, Martin M E, Aber J D. Determination of carbon fraction and nitrogen concentration in tree foliage by near infrared reflectance: a comparison of statistical methods［J］. Canadian Journal of Forest Research 1996, 26:590-600.

[5] Raymond F, Kokaly, Roger N Clark, Eric Livo K. Mapping the Biology and Mineralogy of Yellowstone National Park using Imaging Spectroscopy, Summaries of the 7th Annual JPL Airborne Earth Science Workshop
[A]. In: Green R O, Vol 1. AVIRIS Workshop
[C], JPL Publication 97-21. 1998, 245-254.

[6] Shaw D T. High-spectral resolution data for monitoring Scots pine(pinus sylvestris L.) regeneration［J］. INT.J.Remote Sensing, 1998, 19(13): 2601-2608.

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