Deriving Wheat Crop Productivity Indicators Using Sentinel-1 Time Series
Deriving Wheat Crop Productivity Indicators Using Sentinel-1 Time Series
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DOI：
10.3390/rs12152385
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发表时间：
2020-07
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通讯作者：
Nikolaos-Christos Vavlas;T. Waine;J. Meersmans;P. Burgess;G. Fontanelli;G. Richter
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作者：
Nikolaos-Christos Vavlas;T. Waine;J. Meersmans;P. Burgess;G. Fontanelli;G. Richter
高频地球观测数据已被证明在识别作物和监测作物生长方面是有效的。本文的目的是利用合成孔径雷达(SAR)提取作物生产力的定量指标。这项研究表明，田间特定的合成孔径雷达时间序列可以用来表征生长和成熟期，并估计谷物的表现。英国哈彭登Rothamsted研究农场的冬小麦田被选为三个作物季节(2017至2019年)的分析对象。提取每个场的哨兵一号卫星的平均后向散射，并对后向散射交叉极化比(VH/VV)进行时间分析。生长期内不同曲线参数的计算包括：(I)将两条Logistic曲线与SAR时间序列的动态进行拟合，分别描述生长和成熟的时间和强度；(Ii)绘制相关的一阶和二阶导数，以帮助确定作物发育的关键阶段；以及(Iii)探索衍生指标的相关矩阵及其对产量的预测能力。结果表明，VH/VV值最大的年份与产量呈负相关(r=−0.5 6)，植被全盛期与产量呈正相关(r=0.6 1)。在植被高峰期(p=0.042)、生长中点(p=0.037)、生长季持续时间(p=0.039)和产量(p=0.016)方面观察到显著的季节变化，这与作物物候学的观察结果是一致的。需要进一步的研究，以更详细地了解所提出的新方法的不确定性，以及它在更广泛的农业生态系统中的有效性。
High-frequency Earth observation (EO) data have been shown to be effective in identifying crops and monitoring their development. The purpose of this paper is to derive quantitative indicators of crop productivity using synthetic aperture radar (SAR). This study shows that the field-specific SAR time series can be used to characterise growth and maturation periods and to estimate the performance of cereals. Winter wheat fields on the Rothamsted Research farm in Harpenden (UK) were selected for the analysis during three cropping seasons (2017 to 2019). Average SAR backscatter from Sentinel-1 satellites was extracted for each field and temporal analysis was applied to the backscatter cross-polarisation ratio (VH/VV). The calculation of the different curve parameters during the growing period involves (i) fitting of two logistic curves to the dynamics of the SAR time series, which describe timing and intensity of growth and maturation, respectively; (ii) plotting the associated first and second derivative in order to assist the determination of key stages in the crop development; and (iii) exploring the correlation matrix for the derived indicators and their predictive power for yield. The results show that the day of the year of the maximum VH/VV value was negatively correlated with yield (r = −0.56), and the duration of “full” vegetation was positively correlated with yield (r = 0.61). Significant seasonal variation in the timing of peak vegetation (p = 0.042), the midpoint of growth (p = 0.037), the duration of the growing season (p = 0.039) and yield (p = 0.016) were observed and were consistent with observations of crop phenology. Further research is required to obtain a more detailed picture of the uncertainty of the presented novel methodology, as well as its validity across a wider range of agroecosystems.