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应用生态学报 ›› 2002, Vol. ›› Issue (3): 290-294.

• 研究论文 • 上一篇    下一篇

基于GIS的浙江省水稻遥感估产最佳时相选择

黄敬峰1, 王人潮1, 蒋亨显1, 杨忠恩2   

  1. 1. 浙江大学农业遥感与信息技术应用研究所, 杭州 310029;
    2. 浙江省气候中心, 杭州 310029
  • 收稿日期:1999-12-13 修回日期:2000-07-21 出版日期:2002-03-15
  • 通讯作者: 黄敬峰,男,1963年生,博士,副教授,主要从事农业遥感与农业气象学研究,发表论文50余篇,主编出版<冬小麦气象卫星综合遥感>和<草地遥感>等专著.Tel:0571-86971272,E-mail:hjf@zju.edu.cn.
  • 基金资助:
    国防科工委“九五”科技攻关项目(Y971462)

Selection of optimum periods for rice estimation using remote sensing data based on GIS

HUANG Jingfeng1, WANG Renchao1, JIANG Hengxian1, YANG Zhong'en2   

  1. 1. Institute of Agricultural Remote Sensing and Information Application, Zhejiang University, Hangzhou 310029;
    2. Zhejiang Climate Center, Hangzhou 310029
  • Received:1999-12-13 Revised:2000-07-21 Online:2002-03-15

摘要: 水稻遥感估产最佳时相选择应包括水稻种植面积估算最佳时相和水稻产量预报最佳时相两部分.在水稻遥感估产最佳时相选择中,由于首次引入GIS技术提取水稻可能种植区域,缩小了研究范围,植被种类也较简单一,因此仅用农作物物候历即可确定水稻种植面积估算最佳时相,而不需要考虑所有的植被类型.利用盆栽试验和小区试验研究水稻产量与不同时期的农学参数、农学参数与植被指数及水稻产量与植被指数的关系,结果表明,水稻产量与农学参数、农学参数与光谱变量的关系均以孕穗期到抽穗期最好,水稻产量与光谱变量的关系则从分蘖盛期到抽穗期的极显著.因此,以孕穗期到抽穗期作为建立水稻遥感估产模型的最佳时期.再利用1998年各地的水稻发育期观测资料,确定各区水稻产量遥感最佳时相.

Abstract: The optimum temporal for rice estimation using remote sensing data included the optimum temporal for rice planting area estimation and the optimum temporal for rice yield estimation. Based on GIS,the rice potential planting area was extracted. Therefore, the study area became smaller and the plant species considered decreased. So the optimum temporal for rice planting area estimation were determined through comparing the crop phonological calendars. In order to select the optimum temporal for rice yield estimation using remote sensing data,the relationships between the rice yield and agronomic parameters,the agronomic parameters and spectral variables,the rice yield and spectral variables for different development stages using field experiment data in1989 and 1990 were studied. The result showed that the key period of rice production was from boot stage to heading stage. At last,the optimum temporal for rice yield estimation using remote sensing data was selected using the rice phenological calendars of 1998.

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