基于GF-1与Landsat 8遥感数据的耕地表层土壤有机质含量反演精度对比研究

发布时间：2018-04-29 08:20

本文选题：高分一号 + Landsat　；参考：《浙江农业学报》2017年01期

【摘要】：以GF-1和Landsat 8遥感影像为数据源,以依安县、拜泉县为研究对象,结合研究区土壤采样的化验数据,比较2种遥感影像在反演土壤有机质含量方面的能力与差异。结果表明,2种遥感影像在可见光与近红外波段的反射率与土壤有机质含量显著相关,且在近红外波段相关性最大,利用GF-1近红外波段建立的指数模型比利用Landsat 8近红外波段建立的幂模型估测效果略好。引入蓝波段(深蓝波段)、红波段建立起来的多元回归模型比单波段模型具有更高的反演精度,尤以对Landsat 8遥感影像的改善效果更明显。与Landsat 8相比,GF-1遥感影像具有更高的空间分辨率和更短的重访周期,在土壤有机质含量的探测方面具有相近的预测能力,可以替代Landsat 8遥感影像。
[Abstract]:With GF-1 and Landsat 8 remote sensing images as data sources, Yian County and Baiquan County as research objects, the ability and difference of two remote sensing images in retrieving the content of soil organic matter were compared by combining the laboratory data of soil sampling in the study area. The results showed that the reflectivity of the two remote sensing images in the visible and near infrared bands was significantly correlated with the soil organic matter content, and the correlation was the greatest in the near infrared band. The exponential model based on GF-1 near infrared band is better than the power model established by Landsat 8 near infrared band. The multivariate regression model based on blue band (deep blue band and red band) has higher inversion accuracy than single band model, especially for the improvement of Landsat 8 remote sensing image. Compared with Landsat 8, the Landsat 1 remote sensing image has higher spatial resolution and shorter re-visit period, and has similar prediction ability in the detection of soil organic matter content, which can replace Landsat 8 remote sensing image.
【作者单位】：辽宁省交通高等专科学校测绘工程系;
【分类号】：TP79

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