中国农业气象

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基于遥感技术监测作物收获指数(HI)的可行性分析

杜鑫;吴炳方;蒙继华;李强子;   

  1. 中国科学院遥感应用研究所;
  • 出版日期:2010-06-10 发布日期:2010-06-10
  • 基金资助:
    国家自然科学基金项目(40801144);; 中国科学院知识创新工程重大项目(KSCX1-YW-09-01);; 国家科技支撑计划项目(2008BADA8B02)

Feasibility Analysis for Acquiring Crop Harvest Index(HI) with Remote Sensing

DU Xin,WU Bing-fang,MENG Ji-hua,LI Qiang-zi(Institute of Remote Sensing Applications,Chinese Academy of Sciences,Beijing 100101,China)   

  • Online:2010-06-10 Published:2010-06-10

摘要: 鉴于作物收获指数(HI)在遥感定量监测作物单产研究中的重要性,本文通过分析作物HI的形成机制和总结目前相关的遥感技术应用情况,探讨了利用遥感技术估算HI的可行性,认为结合遥感信息的时空特点,可以对HI的形成过程进行动态监测,进而建模估算最终的HI。通过分析,文中将遥感估算HI方法归纳为三类:(1)通过高时间分辨率的遥感数据对作物的整个生长过程进行监测,然后基于作物生长过程的遥感监测实现HI实时估算;(2)通过遥感技术手段获取影响HI形成的因素,然后基于环境影响因子的遥感监测进行HI的估算;(3)随着雷达、激光雷达数据获取和测量精度的提高,将可能基于作物结构参数的遥感监测来反演HI。并且分析了不同遥感数据的自身特点及其用于监测HI的缺陷和不足之处,指出遥感数据源的多元化趋势和新型传感器的出现必将推动遥感估算HI模型的改进和估算精度的提高;鉴于遥感信息的优势主要体现在空间差异化,认为遥感估算HI的结果验证应该以像元尺度为主,结合其他数据(区域统计数据等)对比分析为辅。

关键词: 作物, 收获指数, 遥感监测

Abstract: As crop Harvest Index(HI) was very important to estimate crop yield accurately by remote sensing technology,the feasibility of estimating crop HI with remote sensing technology was discussed through analyzing HI mechanism and reviewing remote sensing technology application.HI process dynamic could be monitored,and the model to estimate HI could be established,combining temporal-spatial character of remote sensing information.There were three methods to estimate HI by remote sensing technology according to this study.First,describing and analyzing the crop growing process with high temporal resolution remote sensing data.Second,acquiring the environmental parameters with remote sensing and then to estimate the HI using these parameters.Third,by crop structural parameters acquired from radar or laser radar data.The characteristics of different kinds of remote sensing data were analyzed and their advantage and disadvantage in estimating crop HI were discussed.With the multi-development of remote sensing data sources and launch of satellite with new remote sensing sensors,the crop HI estimation model would be improved with a higher accuracy.The validation should be done not only at a pixel scale(with field observation),but also comparing with the other information data sources,such as the regional statistical data,due to the characteristics of remote sensing data in spatial distribution.

Key words: Crop, Crop, Harvest index, Monitoring with remote sensing