地表通量监测

MODIS水汽通量估算方法在华北平原农田的适应性验证

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  • 1. 中国科学院地理科学与资源研究所,北京 100101;
    2. 日本国立环境研究所,筑波 305-8056
孙志刚 (1978-), 男, 江苏盐城, 硕士。主要从事农田微气象, 遥感应用相关研究。 E-mail: sunzg@igsnrr.ac.cn

收稿日期: 2003-09-17

  修回日期: 2003-12-25

  网络出版日期: 2004-01-25

基金资助

中日合作研究项目“亚太地区环境创新战略(APEIS)”资助

Validation of the Feasibility of MOD16 Algorithm for Estimating Crop Field Vapor Flux in North China Plain

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  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. National Institute for Environmental Studies, Tsukuba 305-8506, Japan

Received date: 2003-09-17

  Revised date: 2003-12-25

  Online published: 2004-01-25

Supported by

The Asia-Pacific Environmental Innovation Strategy (ASEIS), NIES, Japan

摘要

利用遥感手段估算区域水汽通量对研究区域气候变化及生态系统功能评价颇具意义。但是由于估算模式涉及时空差异很大的地表特征参数很难完全通过遥感数据获得,因此MODIS水汽通量数据产品 (MOD16) 至今尚未问世。本研究以中科院禹城综合实验站2002年4~5月份冬小麦田的涡度相关实测水汽通量为标准,验证MOD16算法所估算的农田水汽通量,结果表明直接使用MOD16算法计算的麦田水汽通量比实测水汽通量平均偏大近20%。对其中的作物三基点温度、空气动力学阻抗计算方法和植被覆盖度进行修正,修正后的MOD16计算结果和实测值非常吻合,1:1曲线斜率为0.9706,相关系数R2为0.8845。这为利用MODIS数据大面积估算农田水汽通量提供了科学依据。

本文引用格式

孙志刚,王勤学,欧阳竹,渡边正孝 . MODIS水汽通量估算方法在华北平原农田的适应性验证[J]. 地理学报, 2004 , 59(1) : 49 -55 . DOI: 10.11821/xb200401006

Abstract

The MODIS product of the land surface vapor flux (MOD16) is not yet released by NASA because some parameters in the algorithm are very unstable in the time and space scales, which are difficult to be or cannot be derived from the remote sensing data. In this study, we validated the original algorithm of MOD16 with the ground measured data from April to May in 2002 (Yucheng Ecological Experimental Station in Shandong, CAS). The result showed that the estimated vapor flux was about 20% more than the observed values. We revised the original model by adjusting the crop physiological temperature parameters and coefficients for calculating the aerodynamic resistance, and the fractional vegetation cover according to the characteristics of winter wheat in Yucheng Station. The slope of the regression line plotted with the result simulated by the revised algorithm and the field measured data was 0.9706, and the correlation coefficient (R2

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