综合NDVI时序特征的冬小麦混合像元分解及面积估算

doi:10.11924/j.issn.1000-6850.casb19030086

摘要/Abstract

摘要： 基于MODIS数据进行面积提取易受混合像元影响，为了降低因混合像元导致的错分和漏分误差，该文提出一种线性的混合像元分解模型，建立MODIS混合像元中冬小麦占比与MODIS/NDVI时间序列影像波峰波谷差值之间的定量关系。基于2017年保定市MODIS数据和GF数据进行了模型构建，基于2014年数据进行了模型验证，结果显示纯度指数（PPI）精确度均值为0.485，基于混合像元分解模型得到的2014年保定市冬小麦面积推算值为40.05万hm2，基于GF数据得的2014年保定市冬小麦面积“真值”为37.39万hm2，绝对误差为2.66万hm2，相对误差率为7.11%。利用河北省冬小麦广泛种植的8个地市对模型的适用性进行评价，结果表明不同地市的冬小麦面积推算值和冬小麦面积“真值”间平均误差率为3.69%。基于该模型的冬小麦面积推算值误差相对较低，数据可靠性较高，且受地域影响较小，具有较为普遍适用性。

关键词: 间套作, 间套作, 水分利用效率, 产量, 评估方法

Abstract: Crop extraction based on MODIS data is easily affected by the mixed pixels. In order to reduce the omission and commission errors caused by mixed pixels, this paper proposed a linear mixed pixel decomposition model and establish a quantitative relation between winter wheat proportion and crest-trough differences of MODIS/NDVI time series images. This model was established based on MODIS and GF data of Baoding city of 2017, and verified based on MODIS and GF data of Baoding city of 2014. Results showed that the mean value of pixel purity index (PPI) accuracy was 0.485. The estimated value of winter wheat area of Baoding city in 2014 was 400.5 thousand hm2 based on mixed pixel decomposition model and the “actual value” of winter wheat area of Baoding city in 2014 was 373.9 thousand hm2 based on GF data, the absolute error was 26.6 thousand hm2 and the relative error rate was 7.11%. The applicability of this model was evaluated in 8 prefecture-level cities where winter wheat was widely cultivated in Hebei province. The result showed that the average error rate of different cities in Hebei province was 3.69%. The winter wheat estimation error based on the proposed model is relatively low, with relatively high data reliability. Besides, impact of terrain on the model is relatively low, and the model is widely applicable.

中图分类号:

S252

王利民,刘佳,姚保民,高建孟,杨福刚. 综合NDVI时序特征的冬小麦混合像元分解及面积估算[J]. 中国农学通报, 2019, 35(27): 23-33.

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