【摘要】 针对低分辨率遥感数据在区域地表蒸散(evapotranspiration,ET)估算中存在的空间尺度效应问题,提出一种基于网格面积比例加权聚合(grid area ratio weighting lumped method,GARWLM)的空间尺度转换方法。通过在网格(1km×1km)内部基于各种地表覆盖类型所占面积比例,分别赋予相应权重,建立高分辨率遥感数据向低分辨率遥感数据的尺度转换模型,实现了由高分辨率数据估算的ET向低分辨率数据估算的ET的空间尺度转换,并通过回归对低分辨率数据估算的ET进行了尺度效应纠正。在伊洛河流域的试验结果表明,估算的ET与地面实测数据的平均相对误差由纠正前的23.5%减小到纠正后的12%,与高分辨率估算结果的相关性分别由纠正前的0.339提高到纠正后的0.604,经过尺度纠正后的ET精度有了很大程度的提高。更多还原

【Abstract】 As a result of the existence of spatial heterogeneity and mixed pixels,there are salient spatial scaling effects in the evapotranspiration(ET)estimated from low resolution remote sensing data.A spatial scaling transformation method is proposed based on GARWLM(grid area ratio weighting lumped method).The new method gives the corresponding weights according to the area ratio of various land cover types and makes the scaling model from the fine resolution(HJ1B)to the coarse resolution(MODIS)in a grid(1km);spatial scaling transformation from ET estimated from HJ-1B data to ET estimated from MODIS images is performed by the above steps.Finally,the correction of scale effect to ET estimated from coarse resolution data or MODIS is accomplished by regression.The studies in Yiluo River basin show that the average relative error between the estimated ET and ground measured data decreases from 23.5%to 12%.The correlation of the fine resolution increases from 0.339 to 0.604.The accuracy of ET corrected for scale effect has been greatly improved.更多还原