首页> 外文期刊>Journal of Coastal Conservation >Estimating soil salinity in different landscapes of the Yellow River Delta through Landsat OLI/TIRS and ETM plus Data
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Estimating soil salinity in different landscapes of the Yellow River Delta through Landsat OLI/TIRS and ETM plus Data

机译:通过Landsat OLI / TIRS和ETM plus数据估算黄河三角洲不同景观的土壤盐分

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摘要

Soil salinization has increasingly become a serious issue in coastal zone due to global climate changes and human disturbances. Assessment of soil salinity, especially at the landscape scale, is critical to coastal management and restoration. Two data from OLI/TIRS and ETM+ sensors of Landsat satellite were used to compare their ability to invert the spatial pattern of soil salinity in both farmland and salt marsh landscapes in the Yellow River Delta, China, respectively. The results showed that the in situ electrical conductivity (EC (a) ) of soil, representing soil salinity, were closely related with spectral parameters and salinity indices calculated by the remote sensing data. The results of multiple regression models have showed that nearly all the spectral parameters and salinity indices calculated by OLI/TRIS data were more sensitive to soil salinity than those by ETM+ data. Therefore, the models based on OLI/TIRS data are superior to those on ETM+ data in estimating the spatial pattern of soil salinity in farmland and salt marsh landscapes. Our results were very helpful to evaluate the levels of soil salinization in the Yellow River Delta.
机译:由于全球气候变化和人为干扰,土壤盐碱化已日益成为沿海地区的一个严重问题。对土壤盐分的评估,尤其是在景观尺度上,对沿海管理和恢复至关重要。利用来自Landsat卫星的OLI / TIRS和ETM +传感器的两个数据分别比较了它们反转中国黄河三角洲农田和盐沼景观中土壤盐分空间格局的能力。结果表明,代表土壤盐度的土壤原位电导率(EC(a))与光谱参数和遥感数据计算出的盐度指数密切相关。多元回归模型的结果表明,与ETM +数据相比,由OLI / TRIS数据计算出的几乎所有光谱参数和盐度指数对土壤盐分更敏感。因此,在估算农田和盐沼景观中土壤盐分的空间格局方面,基于OLI / TIRS数据的模型优于基于ETM +数据的模型。我们的结果对评价黄河三角洲土壤盐渍化水平非常有帮助。

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