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