Uncertainty Assessment and Weight Map Generation for Efficient Fusion of Tandem-X and Cartosat-1 Dems

Abstract

ABSTRACT:Recently, with InSAR data provided by the German TanDEM-X mission, a new global, high-resolution Digital Elevation Model (DEM) has been produced by the German Aerospace Center (DLR) with unprecedented height accuracy. However, due to SAR-inherent sensor specifics, its quality decreases over urban areas, making additional improvement necessary. On the other hand, DEMs derived from optical remote sensing imagery, such as Cartosat-1 data, have an apparently greater resolution in urban areas, making their fusion with TanDEM-X elevation data a promising perspective. The objective of this paper is two-fold: First, the height accuracies of TanDEM-X and Cartosat-1 elevation data over different land types are empirically evaluated in order to analyze the potential of TanDEM-XCartosat-1 DEM data fusion. After the quality assessment, urban DEM fusion using weighted averaging is investigated. In this experiment, both weight maps derived from the height error maps delivered with the DEM data, as well as more sophisticated weight maps predicted by a procedure based on artificial neural networks (ANNs) are compared. The ANN framework employs several features that can describe the height residual performance to predict the weights used in the subsequent fusion step. The results demonstrate that especially the ANN-based framework is able to improve the quality of the final DEM through data fusion.

Fusion of Multi-Sensor-Derived Heights and OSM-Derived Building Footprints for Urban 3D Reconstruction

“…The evaluation illustrates that the absolute vertical accuracy of Cartosat-1 DEM increased more than 2 m. The evaluations were performed with respect to a LiDAR DSM created from the LiDAR point cloud by reducing and interpolating the 3D points into a 2.5D grid with a pixel spacing of 5 m. It should be noted that the TanDEM-X raw DEM is also converted into a 5 m pixel spacing DEM by interpolation. As we were able to show in [24], this fusion improves the final DEM quality; quantitative results for the test scene are repeated in Table 4. Table 4.…”

“…In parallel, the TanDEM-X mission is a recent endeavour for producing a global DEM through an interferometric SAR processing chain. Evaluation with respect to LiDAR reference data illustrates that the TanDEM-X DEM has a better absolute accuracy than the Cartosat-1 DEM, while its precision drops out in urban areas because of intrinsic properties of InSAR-based height construction [24]. Figure 2b shows the performance of both DEMs in a subset selected for height precision evaluation over an urban scene.…”

Urban TanDEM-X Raw DEM Fusion Based ON TV-L1 and Huber Models

“…Different methods have been implemented for fusing DEMs with different properties [4], [5], [6] as an application of data fusion in remote sensing [7] . In this paper, three approaches are carried out for TanDEM-X raw DEM fusion.…”

Fusion of TanDEM-X and Cartosat-1 DEMS using TV-norm regularization and ANN-predicted weights

“…An uncertainty assessment of the TanDEM-X and Cartosat-1 DEMs [2] illustrates that the Cartosat-1 DEM is more accurate than the TanDEM-X DEM in urban areas while the accuracy of both DEMs is nearly same over non-urban areas. The results of this assessment of the relative accuracies in different land types over urban and non-urban areas are briefly summarized in Table 1 for sake of completeness.…”

“…Cartosat-1 is an Indian satellite equipped with a dual-optics 2-line along-track stereoscopic push broom scanner with a stereo angle of 31 • and a resolution of 2.5 m. It is specifically designed for high-resolution DEM generation with relatively large areal coverage. An initial evaluation quantified the quality differences between the Cartosat-1 DEM and the TanDEM-X DEM in urban areas [2]. This paper first quickly evaluates the raw TanDEM-X and Cartosat-1 DEMs over urban areas and then will focus on the fusion of both DEMs to achieve a final global DEM with higher accuracy in urban areas.…”