ICESat-2数据辅助的AW3D30 DEM精度评价和修正

Accuracy Validation and Improvement of AW3D30 DEM Aided by ICESat-2 Data

AW3D30 DEM数据是应用最为广泛的基础地理信息数据之一,其精度直接影响一系列衍生产品的可靠性和严谨性。因此,AW3D30 DEM数据的精度评价与修正一直是研究热点。然而,常规高精度验证数据获取困难且成本较高,难以应用在大范围研究区域。ICESat-2数据全球覆盖、高程精度达亚米级,可为AW3D30 DEM数据精度评价和修正提供可靠的参考数据源。为此,以河南省为研究区域,利用ICESat-2数据从坡度、坡向、地貌类型、土地利用类型角度评估AW3D30 DEM高程精度,并提出一种随机森林-长短期记忆网络混合模型修正AW3D30 DEM。实验表明:AW3D30 DEM高程精度随坡度、海拔和地形起伏度的增大而降低;坡向对高程精度的影响较小,误差分布无明显规律性;在裸地和耕地土地利用类型精度更高,在林地土地利用类型精度较差。随机森林—长短期记忆网络混合模型能够显著降低AW3D30 DEM的平均绝对误差和均方根误差,提升AW3D30 DEM精度,可为其他DEM数据修正模型的建立提供参考。

AW3D30 DEM data is one of the most widely used basic geographic information data,and its accura⁃cy directly affects the reliability and rigor of a series of derivative products.Therefore,the accuracy validation and improvement of AW3D30 DEM data has always been a research hotspot..However,conventional highprecision verification data are difficult to obtain and expensive to apply in a wide range of research areas.With global coverage and sub-meter elevation accuracy,ICESat-2 data can provide reliable reference data source for AW3D30 DEM data accuracy validation and improvement.Therefore,this paper takes Henan Province as the study area,and uses ICESat-2 data to validate the elevation accuracy of AW3D30 DEM from the perspective of slope,aspect,geomorphic type and land use type and proposes the Random Forest-Long Short Term Mem⁃ory Network(RF-LSTM)hybrid model to improve AW3D30 DEM.The results show that the elevation accu⁃racy of AW3D30 DEM decreases with the increase of slope,elevation and topographic relief.The slope direc⁃tion has less influence on AW3D30 DEM’s elevation accuracy,and the error distribution has no obvious regu⁃larity.The accuracy is higher in bare land and cultivated land,and worse in woodland land.The RF-LSTM hy⁃brid model can significantly reduce the mean absolute error and root mean square error of AW3D30 DEM,im⁃prove the accuracy of AW3D30 DEM,and provide a reference for the establishment of other DEM data im⁃provement models.