基于植被指数的藏北牧区土壤湿度反演

发布时间：2018-12-25 19:56

【摘要】：土壤湿度的遥感动态监测在农牧业生产中具有重要意义。近年来,多种基于遥感指数的土壤湿度监测方法被提出并得到广泛关注,但当前对不同深度土壤湿度的反演及植被指数反映土壤湿度滞后性的研究较少。该文针对遥感指数反演土壤湿度的精度问题,对MODIS(moderate resolutionimaging spectroradiometer)的2种植被指数产品归一化差异植被指数(normalized difference vegetation index,NDVI)和增强型植被指数(enhanced vegetation index,EVI)与土壤湿度实测值进行相关分析,并利用在其中一个样点得到相关系数最高的回归模型对距离较远的其它点进行土壤湿度值估算,最后用土壤湿度实测值对模型的精度进行验证。结果表明,2种植被指数均与土壤湿度值呈现出较强的相关性,且利用植被指数估算土壤湿度的延迟天数为5~10 d。在相同气候模式、土壤类型和植被类型的条件下,高程为影响回归模型精度的主要因素。该研究可为牧区多层深度土壤湿度反演方法的选择和监测提供参考依据。
[Abstract]:Remote sensing dynamic monitoring of soil moisture is of great significance in agricultural and animal husbandry production. In recent years, many soil moisture monitoring methods based on remote sensing index have been put forward and paid more attention to. However, there are few researches on soil moisture inversion and vegetation index reflecting soil moisture lag in different depth. Aiming at the precision of soil moisture retrieval by remote sensing index, the normalized difference vegetation index (normalized difference vegetation index,NDVI) and the enhanced vegetation index (enhanced vegetation index,) of MODIS (moderate resolutionimaging spectroradiometer) 2 planting were studied in this paper. EVI) is used to analyze the correlation between soil moisture and the measured values of soil moisture, and the regression model with the highest correlation coefficient is used to estimate the soil moisture values at other points far away. Finally, the accuracy of the model is verified by soil moisture measurement. The results showed that there was a strong correlation between planting cover index and soil moisture value, and the delay days of estimating soil moisture by vegetation index was 5 ~ 10 days. Under the same climate model, soil type and vegetation type, height is the main factor affecting the precision of regression model. This study can be used as a reference for the selection and monitoring of soil moisture inversion methods for multi-layer depth in pastoral areas.
【作者单位】：吉林农业大学资源与环境学院;吉林省商品粮基地土壤资源可持续利用重点实验室;
【基金】：公益性行业(农业)科研专项经费项目(201503116-06) 国家科技支撑计划项目(2013BAC09B01) 吉林省科技厅重大科技攻关专项(20130204050SF) 国家科技重大专项(2014ZX07201-011-006) 吉林农业大学科研启动基金项目(201240)
【分类号】：S152.71;S127

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