| 引用本文: | 张敏讷,赵伟霞,李久生,等.基于冠层温度的水分亏缺指标空间分布图插值方法研究[J].灌溉排水学报,2022,41(6):31-38. |
| ZHANG Minne,ZHAO Weixia,LI Jiusheng,et al.基于冠层温度的水分亏缺指标空间分布图插值方法研究[J].灌溉排水学报,2022,41(6):31-38. |
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| 摘要: |
| 【目的】选择合理的基于冠层温度的水分亏缺指标空间分布插值方法。【方法】以实测数据为基础，基于ArcGIS的插值模块，研究10种插值方法对冠层温度和归一化相对冠层温度（NRCT）预测精度的影响。【结果】①冬小麦和夏玉米的冠层温度分布均具有强烈的空间相关性。②利用局部多项式法和泛克里金法插值时，冠层温度会出现异常值。③利用全局多项式法插值时，冠层温度和NRCT的实测值与预测值的标准均方根误差最高，分别为6%和29%，且预测值与实测值的Pearson相关系数仅为0.33。④利用普通克里金法插值时，冠层温度预测值与实测值平均值的差异小于0.5 ℃，冠层温度和NRCT的标准均方根误差最低，分别为4%和18%，Pearson相关系数为0.80。⑤不同插值方法下生成的冠层温度及NRCT空间分布图趋势基本相同，采用简单克里金法、析取克里金法、经验贝叶斯克里金法插值时，生成的空间分布图与普通克里金法生成的分布图更为相似，重叠部分面积均大于90%。【结论】综合冠层温度和NRCT的插值精度和空间分布图绘制效果，插值方法排序为普通克里金法>简单克里金法=析取克里金法>经验贝叶斯克里金法>径向基函数法（张力样条函数）>径向基函数法（规则样条函数）>反距离权重法。建议优先选择普通克里金法进行基于冠层温度水分亏缺指标的变量灌溉动态分区管理。 |
| 关键词: 冠层温度；归一化相对冠层温度；变量灌溉；动态分区；空间插值 |
| DOI：10.13522/j.cnki.ggps.2021491 |
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| Comparison of Different Interpolation Method for Calculating Spatial Distribution of Crop Water Deficit Based on Canopy Temperature |
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ZHANG Minne, ZHAO Weixia, LI Jiusheng, LI Yanfeng
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State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,
China Institute of Water Resources and Hydropower Research, Beijing 100048, China
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| Abstract: |
| 【Objective】Canopy temperature varies with leaf water content and can be used as a proxy of crop water deficit. In this paper, we compare different interpolation methods for calculating spatial distribution of crop water deficit based on canopy temperature. 【Method】The calculation was based on the 10 interpolation modules in ArcGIS. We studied two experimental sites cultivated with maize – winter wheat rotation. For each site, we analyzed the accuracy and zoning effect of canopy temperature, as well as the normalized relative canopy temperature (NRCT). The accuracy and robustness of each interpolation method was evaluated based on its characteristic value, normalized root mean square error (nRMSE) and Pearson correlation coefficient between predicted and ground-truth values, as well as spatial distributions of the predicted canopy temperature and NRCT. 【Result】The spatial distribution of canopy temperature of the winter wheat and summer maize both has a strong autocorrelation on the two sites. The canopy temperature estimated using local polynomial and universal Kriging interpolation is spatially abnormal. The nRMSE and NRCT between the measured canopy temperature and that predicted using global polynomial interpolation are the highest, being 5.9% and 28.6% respectively; their associated Pearson correlation coefficient is 0.33. The ordinary Kriging method is most accurate in that the difference between the predicted and measured canopy temperatures is less than 0.5 ℃; its associated nRMSE (3.6%) and NRCT (17.5%) are the least with a Pearson correlation coefficient 0.8. The spatial distribution of canopy temperature calculated by the simple Kriging method, disjunctive Kriging method and empirical Bayesian Kriging method is similar to that by the ordinary Kriging method; their overlapping percentage is greater than 90%.【Conclusion】Considering accuracy and spatial distribution of canopy temperature and NRCT, the interpolation methods is ranked in the following order based on their accuracy: ordinary Kriging method > simple Kriging method > disjunctive Kriging method > empirical Bayesian Kriging method > radial basis function method (tension spline function) > radial basis function method(regular spline function) > inverse distance weight method. Overall, the ordinary Kriging method is most accurate for estimating crop water deficit from canopy temperature. |
| Key words: canopy temperature; normalized relative canopy temperature; variable rate irrigation; dynamic zoning; spatial interpolation |
