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New Automatic Accuracy Evaluation of Altimetry Data: DTM 5G Compared with ZABAGED® Altimetry

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Surface Models for Geosciences

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

The paper tackles the issue of accuracy of digital terrain models, which is a long term research area at the University of West Bohemia in Pilsen. In 2014, a new generation of digital terrain models were completed in the Czech Republic. This fact initiated an impulse for new measures and tests in this field. The accuracy tests have been realized by comparing the Digital Terrain Models (DTM) of the Czech Republic—the 5th Generation (DTM 5G) and the previous generation of altimetry data from ZABAGED®. The test have been performed in two selected test fields in the Pilsen Region. This comparison was done already in previous research, but it was built on pre-released laser scanning data before the final filtration and gross error clearing. In order to confirm the results from the previous testing, the comparison has been repeated using the final dataset. The robust method of DTM accuracy evaluation developed at the University of West Bohemia in Pilsen and a highly automated implementation of the comparative method on 250 local test sites (total area of 85 km2) have been applied in this project. The algorithm’s implementation is based on ArcPy libraries provided by Esri. The key parts of the Python source code are described in detail and the whole algorithm is published as open-source. The tests proved that the pre-release dataset was good enough for accuracy testing. The results are similar with the previous research. It underlines the value of the new generation of altimetry data in the Czech Republic. Their accuracy is significantly higher than the previous generation in ZABAGED®.

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Correspondence to Jakub Šilhavý .

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Šilhavý, J., Čada, V. (2015). New Automatic Accuracy Evaluation of Altimetry Data: DTM 5G Compared with ZABAGED® Altimetry. In: Růžičková, K., Inspektor, T. (eds) Surface Models for Geosciences. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-18407-4_19

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