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植被含水量(VWC)能够指示植被的水分状况,对植被生长、火灾、旱灾以及生态环境安全监测等具有重要意义,也是微波遥感估算土壤水分的重要参数之一。光谱指数法是估算植被含水量最常用的方法之一。结合地面观测及Landsat 8OLI传感器遥感影像,对平凉地区的植被含水量进行了遥感估算模型研究,结果表明:(1)平凉地区叶片含水量(FMC)与植被光谱指数没有相关关系,而等效水深(EWT)则与各植被光谱指数具有显著的相关关系(均超过95%显著性水平),其中RVI2与EWT的相关关系最显著且最稳定;(2)利用RVI2对研究区EWT进行遥感估算,其均方根误差(RMSE)为0.183,平均相对误差为8.9%,平均相对误差绝对值为26.4%;(3)研究区内大部分农田的植被含水量为0.6~0.9kg/m~2,少数农田的植被含水量达到1kg/m~2以上,这与实际考查基本一致,基本能够反映研究区内农田EWT的空间变化特征。
Vegetation water content (VWC) can indicate the water status of vegetation, and is of great significance to vegetation growth, fire and drought and the monitoring of ecological environment safety. It is also one of the important parameters for estimating soil moisture by microwave remote sensing. The spectral index method is one of the most commonly used methods for estimating vegetation water content. The results show that: (1) There is no correlation between leaf water content (FMC) and vegetation spectral index in Pingliang, but the equivalent water depth (EWT) was significantly correlated with vegetation index (all over 95%), among which the correlation between RVI2 and EWT was the most significant and the most stable; (2) Using RVI2 to estimate the EWT in the study area, The root mean square error (RMSE) was 0.183, the average relative error was 8.9%, and the average absolute value of relative error was 26.4%. (3) The vegetation water content of most farmland in the study area was 0.6-0.9 kg / m 2, The vegetation moisture content of a few farms reached more than 1kg / m ~ 2, which is basically consistent with the actual test, basically reflecting the spatial variation characteristics of farmland EWT in the study area.