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FOREST RESOURCES WANAGEMENT ›› 2017, Vol. 0 ›› Issue (4): 131-134.doi: 10.13466/j.cnki.lyzygl.2017.04.020

• Scientific Research • Previous Articles     Next Articles

Estimation of Hickory Yield Based on Landsat TM Remote Sensing Data

LI Xiaoyu1(), HUANG Xingzhao2(), WANG Xuejun1, GAO Zuofeng1   

  1. 1. Academy of Forest Inventory and Planning,SFA,Beijing 100714,China
    2. School of Forestry and Landscape Architecture,Anhui Agricultural University,Hefei 230036,China
  • Received:2017-04-10 Revised:2017-05-15 Online:2017-08-28 Published:2020-09-24
  • Contact: HUANG Xingzhao E-mail:lixiaoyu@afip.com.cn;xingzhaoh@ahua.edu.cn

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: