地理科学 ›› 1997, Vol. 17 ›› Issue (3): 265-270.doi: 10.13249/j.cnki.sgs.1997.03.265

• 论文 • 上一篇    下一篇

农业信息系统支持下的玉米遥感估产模型研究

刘湘南, 黄方   

  1. 东北师范大学城市与环境科学学院, 长春130024
  • 收稿日期:1996-01-12 修回日期:1997-05-18 出版日期:1997-05-20 发布日期:1997-05-20
  • 基金资助:
    国家“八五”科技攻关

STUDY ON MAIZE YIELD ESTIMATION MODEL BY REMOTE SENSING WITHIN AN AGRICULTURAL INFORMATION SYSTEM

Liu Xiangnan, Huang Fang   

  1. College of Urban and Environmental Sciences, Northeast Normal University, Changchun 130024
  • Received:1996-01-12 Revised:1997-05-18 Online:1997-05-20 Published:1997-05-20

摘要: 在县级农业信息系统的支持下,分析了玉米遥感估产机理,提出了遥感获取玉米估产因子的原理与方法,确定了探测玉米生长参数及评价玉米生态环境的遥感指数。在此基础上,分区、分阶段建立了玉米遥感综合估产模型。

Abstract: The integration of remote sensing and geographical information system technology is an optimal method for maize yield estimation.In this study,a county agricultural information system has been established,which supports various data capture,information complex and spatial analysis.Based on the system,maize yield estimation mechanism is explored with remote sensing,whereby maize yield factors can be derived from remote sensing indices.Some relative models between vegetation index (PVI,RVI,NDCI,WDVI,TSAVI,etc.) and Leaf Area Index (LAI),chlorophyll concentration and biomass are developed.Crop Water Stress Index (CWSI) is calculated to indicate the stress of maize growing conditions.Therefore,with the aid of the system,PVI,NDCI and CWSI,which respectively stand for maize biological parameters and imitate its ecological environment,are two categories index in a comprehensive yield estimation model.Then,considering the difference of maize growing environment in Lishu county,not only three yield classes of maize are determined but also three yield estimation models for each class are developed.Moreover,yield estimation models for each maize growing stage are discussed in this paper.