潮滩土壤含水量具有变化频率快、空间变化大的特征,是影响潮滩地表反射率的重要因素。潮滩土壤含水量的精确提取,可为潮滩特征地物信息遥感反演提供基础。本文利用江苏大丰王港潮滩4种典型沉积物、449组不同含水量对应的实测光谱曲线数据进行特征分析,构建高光谱预测模型,实现了潮滩沉积物含水量的遥感反演。研究结果表明:(1)在短波红外波段,沉积物含水量与反射率之间存在良好的分段线性相关关系,分段点对应的含水量分别为42%和62%;(2)1165nm、1336nm、1568nm和1780nm特征波段反射率,对含水量变化具有良好响应,由特征波段组合计算得到的差值水指数DWI、比值水指数RWI和归一化水指数NDWI与含水量呈显著线性相关,可有效改善单波段反射率与含水量之间的分段线性关系;(3)3个水指数中,DWI反演的含水量精度优于RWI和NDWI,且对不同含水量大小均有良好适应性,而RWI和NDWI更适合含水量变化范围中等的情况;(4)对于粉砂、砂质粉砂、粉砂质砂和砂4种沉积物类型,DWI1336,1780验证组模拟含水量与实测含水量的相关系数,分别为0.891、0.915、0.920和0.905,均方根误差分别为9.87%、3.56%、4.24%和2.98%,表明由DWI构建的高光谱遥感反演模型,可有效实现潮滩表层含水量的时空变化预测。

Owing to the tidal fluctuation, interstitial water content in intertidal flat changes frequently and spatially. It gives important influence to the reflectance of surface spectrum in this area. Precisely prediction of tidal flat moisture content can make the extraction of surface feature information by remote sensing easier and more accurate. Based on detailed analysis of the characteristics of 449 sediment spectral curves with different moisture contents, three kinds of water content index namely difference water index (DWI), ratio water index (RWI) and normalized differential water index (NDWI) were proposed. And then they were used for the construction of water content reversion models and applied for the accurate prediction of moisture content in tidal flat for different sediment types. Results showed that: (1) Moisture content for sediment samples had a good segment linear correlation with its reflectance in short-wave infrared band area. The corresponding moisture contents for segmentation points were 42% and 62% respectively; (2) Reflectance of characteristic bands with central wavelengths at 1165nm, 1336nm, 1568nm and 1780nm has very good responses to the changes of water contents for different sediment types. DWI, RWI and NDWI calculated by the combinations of reflectance at characteristic bands had a significant linear correlation with moisture contents of different soil types; (3) Among the three moisture content reversion indexes, DWI had a better prediction accuracy than RWI and NDWI and a good adaptability for water contents distributed in wide ranges. In comparison, RWI and NDWI were more suitable for a moderate moisture content level. Much smaller or much larger of the water content level would lead to a relatively larger deviation for its prediction; and (4) Using the model constructed by DWI_1336,1780 (λ₁₃₃₆, λ₁₇₈₀), water contents were reserved and correlation coefficients between the predicted and observed ones were 0.891, 0.915, 0.920 and 0.905 for four different sediment types names silt, sandy silt, silty sand and sand while their root mean square errors were 9.87%, 3.56%, 4.24% and 2.98% respectively. So DWI is suitable for the prediction of spatial and temporal variation of the moisture contents in tidal flat areas.