Estimation of Hickory Yield Based on Landsat TM Remote Sensing Data

doi:10.13466/j.cnki.lyzygl.2017.04.020

Abstract

Abstract:

To establish the hickory yield model and vegetation index,the actual yield from 2008 to 2011 and Landsat TM remote sensing data of four growth stages in every year were used to systematically compare their relationship in hickory source region in Lin’an of Zhejiang Province.The results show that the NDVI of each growth stage has higher correlation with yield than SAVI,DVI.The model of each growth stage was built to predict hickory yield which used NDVI.The accuracy of four models was as follows: fruit expanding stage>flower bud differentiation and pollination stage>picking to defoliation stage>dormancy stage.Using the stepwise regression that the NDVI of every growth stage were factors,the model of hickory yield was established.The optimal model was y=126.51x₂+26.61x₁+12.56x₃-67.42(R²=0.642,SEE=12.17) which provided a feasible,rapid and effective method to predict the hickory production.

Key words: hickory, growth stage, remote sensing, stepwise regression, model

CLC Number:

S727.3
TP79

LI Xiaoyu, HUANG Xingzhao, WANG Xuejun, GAO Zuofeng. Estimation of Hickory Yield Based on Landsat TM Remote Sensing Data[J]. FOREST RESOURCES WANAGEMENT, 2017, (4): 131-134.

Figures/Tables 6

Fig.1

Tab.1

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Fig.2

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References 10

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植被指数	花芽分化及授粉期	果实膨大期	采摘至落叶期	休眠期
DVI	0.342	0.335	0.264	0.176
NDVI	0.504	0.595	0.435	0.284
SAVI	0.401	0.392	0.315	0.258

模型	R²	SEE	P	Sig
y=160.35x₂-45.71	0.595	17.64	0.000	0.000c
y=144.41x₂+24.65x₁-51.55	0.613	14.31	0.011	0.000b
y=126.51x₂+26.61x₁+12.56x₃-67.42	0.642	12.17	0.032	0.016a
y=208.73x₂+65.96x₁+50.73x₃ -229.88x₄+19.23	0.638	13.05	0.229

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