中国水稻科学

中国水稻科学

• 研究报告 • 上一篇    下一篇

基于Terra与Aqua MODIS增强型植被指数的县级水稻总产遥感估算

彭代亮1，2;黄敬峰1，3，4,*;孙华生5 ;王福民6   

  1. 1浙江大学 农业遥感与信息技术应用研究所, 浙江 杭州 310029； 2中国科学院 对地观测与数字地球科学中心， 北京 100190； 3浙江大学 污染环境修复与生态健康教育部重点实验室, 浙江 杭州 310029； 4浙江大学 浙江省农业遥感与信息技术应用重点研究实验室, 浙江 杭州 310029； 5徐州师范大学 测绘学院, 江苏 徐州221116； 6浙江大学 建筑工程学院，浙江 杭州 310058; *通讯联系人, E-mail: hjf@zju.edu.cn
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-09-10 发布日期:2010-09-10

County Level Rice Yield Estimation Based on Combination of Terra and Aqua MODIS EVIs

PENG Dai-liang1,2; HUANG Jing-feng1,3,4,*; SUN Hua-sheng5; WANG Fu-min6   

  1. 1Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310029, China; 2Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100190, China; 3Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang Province, Zhejiang University, Hangzhou 310029, China; 4 Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, Zhejiang University, Hangzhou 310029,China；5College of Surveying and Mapping, Xuzhou Normal University, Xuzhou 221116, China; 6College of Architectural and Civil Engineering, Zhejiang University, Hangzhou 310058, China; *Corresponding author, Email: hjf@zju.edu.cn
  • Received:1900-01-01 Revised:1900-01-01 Online:2010-09-10 Published:2010-09-10

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摘要： 以湖南省醴陵市为研究区域，在比较分析Terra卫星与Aqua 卫星中分辨率成像光谱仪增强型植被指数的基础上，结合这两个卫星提供的空间分辨率为250 m、时间分辨率为16 d的植被指数产品，建立水稻各主要生育期增强型植被指数平均值乘以水稻面积的结果与乡镇级水稻总产的一次线性、二次非线性及逐步回归模型。通过误差分析，选择最优遥感拟合模型，并在此基础上，预测下一年水稻总产。结果显示，水稻种植区Terra卫星与Aqua 卫星中分辨率成像光谱仪增强型植被指数有超过50%的偏差绝对值小于0.03；93.22%、99.50%的偏差绝对值分别小于0.08、0.10。水稻遥感拟合模型模拟结果相对误差小于0.1%，预测模型的估产结果比遥感拟合模型的拟合结果的误差大，但相对误差仍然小于5%。

关键词: 中分辨率成像光谱仪, 增强型植被指数

Abstract: Based on the comparison of enhanced vegetation indices(EVIs) from moderate resolution imaging spectroradiometer(MODIS), linear, quadratic nonlinear and stepwise regression models were constructed with the 16day and 250m resolution vegetative indices of Terra and Aqua(MOD13Q1, MYD13Q1) combined EVIs multiply by township rice planting area and total rice grain yield in Liling City, Hunan Province, China. The optimal fitting models were selected by error analysis, and then the total rice yield in the next year was forecasted. More than 50% absolute values of errors between Terra and Aqua MODIS EVIs were less than 0.03, and 93.22% and 99.50% of them were less than 0.08 and 0.10, respectively. The relative errors of total rice grain yield for all optimal fitting models were less than 0.10%, although forecasting errors were larger than that of fitting, the relative errors of forecasting total rice grain yield were less than 5%.

Key words: moderate resolution imaging spectroradiometer, enhanced vegetation index, rice, yield estimation, remote sensing