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Irrigated Grassland Monitoring Using a Time Series of TerraSAR-X and COSMO-SkyMed X-Band SAR Data

机译:使用TerraSAR-X和COSMO-SkyMed X波段SAR数据的时间序列进行草地灌溉监测

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The objective of this study was to analyze the sensitivity of radar signals in the X-band in irrigated grassland conditions. The backscattered radar signals were analyzed according to soil moisture and vegetation parameters using linear regression models. A time series of radar (TerraSAR-X and COSMO-SkyMed) and optical (SPOT and LANDSAT) images was acquired at a high temporal frequency in 2013 over a small agricultural region in southeastern France. Ground measurements were conducted simultaneously with the satellite data acquisitions during several grassland growing cycles to monitor the evolution of the soil and vegetation characteristics. The comparison between the Normalized Difference Vegetation Index (NDVI) computed from optical images and the in situ Leaf Area Index (LAI) showed a logarithmic relationship with a greater scattering for the dates corresponding to vegetation well developed before the harvest. The correlation between the NDVI and the vegetation parameters (LAI, vegetation height, biomass, and vegetation water content) was high at the beginning of the growth cycle. This correlation became insensitive at a certain threshold corresponding to high vegetation (LAI ∼2.5 m2/m2). Results showed that the radar signal depends on variations in soil moisture, with a higher sensitivity to soil moisture for biomass lower than 1 kg/m2. HH and HV polarizations had approximately similar sensitivities to soil moisture. The penetration depth of the radar wave in the X-band was high, even for dense and high vegetation; flooded areas were visible in the images with higher detection potential in HH polarization than in HV polarization, even for vegetation heights reaching 1 m. Lower sensitivity was observed at the X-band between the radar signal and the vegetation parameters with very limited potential of the X-band to monitor grassland growth. These results showed that it is possible to track gravity irrigation and soil moisture variations from SAR X-band images acquired at high spatial resolution (an incidence angle near 30°).
机译:这项研究的目的是分析草地灌溉条件下X波段雷达信号的灵敏度。使用线性回归模型根据土壤水分和植被参数分析了后向散射雷达信号。 2013年,在法国东南部的一个小型农业地区,以高时间频率获取了雷达(TerraSAR-X和COSMO-SkyMed)和光学(SPOT和LANDSAT)图像的时间序列。在几个草地生长周期中,与卫星数据采集同时进行了地面测量,以监测土壤和植被特征的演变。从光学图像计算得到的归一化植被指数(NDVI)与原位叶面积指数(LAI)之间的比较显示,对数关系与对应于收获前发育良好的植被的日期的散射较大。在生长周期开始时,NDVI与植被参数(LAI,植被高度,生物量和植被含水量)之间的相关性很高。这种相关性在对应于高植被(LAI〜2.5 m 2 / m 2 )的某个阈值处变得不敏感。结果表明,雷达信号取决于土壤水分的变化,当生物量低于1 kg / m 2 时,对土壤水分的敏感性更高。 HH和HV极化对土壤水分的敏感性大致相似。即使在茂密和高植被的情况下,雷达波在X波段的穿透深度也很高。即使在植被高度达到1 m的情况下,在图像中也可以看到水淹区域,HH极化比HV极化具有更高的检测潜力。在雷达信号和植被参数之间的X波段观察到较低的灵敏度,而X波段监测草地生长的潜力非常有限。这些结果表明,可以从以高空间分辨率(入射角接近30°)获取的SAR X波段图像跟踪重力灌溉和土壤湿度变化。

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